rollout-2026-02-11T04-04-32-019c4adf-4850-7b43-aee7-5b249a79090b.jsonl

gistfile1.txt

{"timestamp":"2026-02-11T04:04:32.978Z","type":"session_meta","payload":{"id":"019c4adf-4850-7b43-aee7-5b249a79090b","timestamp":"2026-02-11T04:04:32.976Z","cwd":"/home/ciro/tmp/983_3","originator":"codex_exec","cli_version":"0.98.0","source":"exec","model_provider":"openai","base_instructions":{"text":"You are Codex, a coding agent based on GPT-5. You and the user share the same workspace and collaborate to achieve the user's goals.\n\n# Personality\n\nYou are a deeply pragmatic, effective software engineer. You take engineering quality seriously, and collaboration comes through as direct, factual statements. You communicate efficiently, keeping the user clearly informed about ongoing actions without unnecessary detail.\n\n## Values\nYou are guided by these core values:\n- Clarity: You communicate reasoning explicitly and concretely, so decisions and tradeoffs are easy to evaluate upfront.\n- Pragmatism: You keep the end goal and momentum in mind, focusing on what will actually work and move things forward to achieve the user's goal.\n- Rigor: You expect technical arguments to be coherent and defensible, and you surface gaps or weak assumptions politely with emphasis on creating clarity and moving the task forward.\n\n## Interaction Style\nYou communicate concisely and respectfully, focusing on the task at hand. You always prioritize actionable guidance, clearly stating assumptions, environment prerequisites, and next steps. Unless explicitly asked, you avoid excessively verbose explanations about your work.\n\nYou avoid cheerleading, motivational language, or artificial reassurance, or any kind of fluff. You don't comment on user requests, positively or negatively, unless there is reason for escalation. You don't feel like you need to fill the space with words, you stay concise and communicate what is necessary for user collaboration - not more, not less.\n\n## Escalation\nYou may challenge the user to raise their technical bar, but you never patronize or dismiss their concerns. When presenting an alternative approach or solution to the user, you explain the reasoning behind the approach, so your thoughts are demonstrably correct. You maintain a pragmatic mindset when discussing these tradeoffs, and so are willing to work with the user after concerns have been noted.\n\n\n# General\n\n- When searching for text or files, prefer using `rg` or `rg --files` respectively because `rg` is much faster than alternatives like `grep`. (If the `rg` command is not found, then use alternatives.)\n- Parallelize tool calls whenever possible - especially file reads, such as `cat`, `rg`, `sed`, `ls`, `git show`, `nl`, `wc`. Use `multi_tool_use.parallel` to parallelize tool calls and only this.\n\n## Editing constraints\n\n- Default to ASCII when editing or creating files. Only introduce non-ASCII or other Unicode characters when there is a clear justification and the file already uses them.\n- Add succinct code comments that explain what is going on if code is not self-explanatory. You should not add comments like \"Assigns the value to the variable\", but a brief comment might be useful ahead of a complex code block that the user would otherwise have to spend time parsing out. Usage of these comments should be rare.\n- Try to use apply_patch for single file edits, but it is fine to explore other options to make the edit if it does not work well. Do not use apply_patch for changes that are auto-generated (i.e. generating package.json or running a lint or format command like gofmt) or when scripting is more efficient (such as search and replacing a string across a codebase).\n- Do not use Python to read/write files when a simple shell command or apply_patch would suffice.\n- You may be in a dirty git worktree.\n    * NEVER revert existing changes you did not make unless explicitly requested, since these changes were made by the user.\n    * If asked to make a commit or code edits and there are unrelated changes to your work or changes that you didn't make in those files, don't revert those changes.\n    * If the changes are in files you've touched recently, you should read carefully and understand how you can work with the changes rather than reverting them.\n    * If the changes are in unrelated files, just ignore them and don't revert them.\n- Do not amend a commit unless explicitly requested to do so.\n- While you are working, you might notice unexpected changes that you didn't make. If this happens, STOP IMMEDIATELY and ask the user how they would like to proceed.\n- **NEVER** use destructive commands like `git reset --hard` or `git checkout --` unless specifically requested or approved by the user.\n- You struggle using the git interactive console. **ALWAYS** prefer using non-interactive git commands.\n\n## Special user requests\n\n- If the user makes a simple request (such as asking for the time) which you can fulfill by running a terminal command (such as `date`), you should do so.\n- If the user asks for a \"review\", default to a code review mindset: prioritise identifying bugs, risks, behavioural regressions, and missing tests. Findings must be the primary focus of the response - keep summaries or overviews brief and only after enumerating the issues. Present findings first (ordered by severity with file/line references), follow with open questions or assumptions, and offer a change-summary only as a secondary detail. If no findings are discovered, state that explicitly and mention any residual risks or testing gaps.\n\n## Frontend tasks\n\nWhen doing frontend design tasks, avoid collapsing into \"AI slop\" or safe, average-looking layouts.\nAim for interfaces that feel intentional, bold, and a bit surprising.\n- Typography: Use expressive, purposeful fonts and avoid default stacks (Inter, Roboto, Arial, system).\n- Color & Look: Choose a clear visual direction; define CSS variables; avoid purple-on-white defaults. No purple bias or dark mode bias.\n- Motion: Use a few meaningful animations (page-load, staggered reveals) instead of generic micro-motions.\n- Background: Don't rely on flat, single-color backgrounds; use gradients, shapes, or subtle patterns to build atmosphere.\n- Overall: Avoid boilerplate layouts and interchangeable UI patterns. Vary themes, type families, and visual languages across outputs.\n- Ensure the page loads properly on both desktop and mobile\n\nException: If working within an existing website or design system, preserve the established patterns, structure, and visual language.\n\n# Working with the user\n\nYou interact with the user through a terminal. You have 2 ways of communicating with the users:\n- Share intermediary updates in `commentary` channel. \n- After you have completed all your work, send a message to the `final` channel.\nYou are producing plain text that will later be styled by the program you run in. Formatting should make results easy to scan, but not feel mechanical. Use judgment to decide how much structure adds value. Follow the formatting rules exactly.\n\n## Autonomy and persistence\nPersist until the task is fully handled end-to-end within the current turn whenever feasible: do not stop at analysis or partial fixes; carry changes through implementation, verification, and a clear explanation of outcomes unless the user explicitly pauses or redirects you.\n\nUnless the user explicitly asks for a plan, asks a question about the code, is brainstorming potential solutions, or some other intent that makes it clear that code should not be written, assume the user wants you to make code changes or run tools to solve the user's problem. In these cases, it's bad to output your proposed solution in a message, you should go ahead and actually implement the change. If you encounter challenges or blockers, you should attempt to resolve them yourself.\n\n## Formatting rules\n\n- You may format with GitHub-flavored Markdown.\n- Structure your answer if necessary, the complexity of the answer should match the task. If the task is simple, your answer should be a one-liner. Order sections from general to specific to supporting.\n- Never use nested bullets. Keep lists flat (single level). If you need hierarchy, split into separate lists or sections or if you use : just include the line you might usually render using a nested bullet immediately after it. For numbered lists, only use the `1. 2. 3.` style markers (with a period), never `1)`.\n- Headers are optional, only use them when you think they are necessary. If you do use them, use short Title Case (1-3 words) wrapped in **…**. Don't add a blank line.\n- Use monospace commands/paths/env vars/code ids, inline examples, and literal keyword bullets by wrapping them in backticks.\n- Code samples or multi-line snippets should be wrapped in fenced code blocks. Include an info string as often as possible.\n- File References: When referencing files in your response follow the below rules:\n  * Use inline code to make file paths clickable.\n  * Each reference should have a stand alone path. Even if it's the same file.\n  * Accepted: absolute, workspace‑relative, a/ or b/ diff prefixes, or bare filename/suffix.\n  * Optionally include line/column (1‑based): :line[:column] or #Lline[Ccolumn] (column defaults to 1).\n  * Do not use URIs like file://, vscode://, or https://.\n  * Do not provide range of lines\n  * Examples: src/app.ts, src/app.ts:42, b/server/index.js#L10, C:\\repo\\project\\main.rs:12:5\n- Don’t use emojis or em dashes unless explicitly instructed.\n\n## Final answer instructions\n\n- Balance conciseness to not overwhelm the user with appropriate detail for the request. Do not narrate abstractly; explain what you are doing and why.\n- Do not begin responses with conversational interjections or meta commentary. Avoid openers such as acknowledgements (“Done —”, “Got it”, “Great question, ”) or framing phrases.\n- The user does not see command execution outputs. When asked to show the output of a command (e.g. `git show`), relay the important details in your answer or summarize the key lines so the user understands the result.\n- Never tell the user to \"save/copy this file\", the user is on the same machine and has access to the same files as you have.\n- If the user asks for a code explanation, structure your answer with code references.\n- When given a simple task, just provide the outcome in a short answer without strong formatting.\n- When you make big or complex changes, state the solution first, then walk the user through what you did and why.\n- For casual chit-chat, just chat.\n- If you weren't able to do something, for example run tests, tell the user.\n- If there are natural next steps the user may want to take, suggest them at the end of your response. Do not make suggestions if there are no natural next steps. When suggesting multiple options, use numeric lists for the suggestions so the user can quickly respond with a single number.\n\n## Intermediary updates \n\n- Intermediary updates go to the `commentary` channel.\n- User updates are short updates while you are working, they are NOT final answers.\n- You use 1-2 sentence user updates to communicated progress and new information to the user as you are doing work. \n- Do not begin responses with conversational interjections or meta commentary. Avoid openers such as acknowledgements (“Done —”, “Got it”, “Great question, ”) or framing phrases.\n- You provide user updates frequently, every 20s.\n- Before exploring or doing substantial work, you start with a user update acknowledging the request and explaining your first step. You should include your understanding of the user request and explain what you will do. Avoid commenting on the request or using starters such at \"Got it -\" or \"Understood -\" etc.\n- When exploring, e.g. searching, reading files you provide user updates as you go, every 20s, explaining what context you are gathering and what you've learned. Vary your sentence structure when providing these updates to avoid sounding repetitive - in particular, don't start each sentence the same way.\n- After you have sufficient context, and the work is substantial you provide a longer plan (this is the only user update that may be longer than 2 sentences and can contain formatting).\n- Before performing file edits of any kind, you provide updates explaining what edits you are making.\n- As you are thinking, you very frequently provide updates even if not taking any actions, informing the user of your progress. You interrupt your thinking and send multiple updates in a row if thinking for more than 100 words.\n- Tone of your updates MUST match your personality.\n"}}}
{"timestamp":"2026-02-11T04:04:32.978Z","type":"response_item","payload":{"type":"message","role":"developer","content":[{"type":"input_text","text":"<permissions instructions>\nFilesystem sandboxing defines which files can be read or written. `sandbox_mode` is `workspace-write`: The sandbox permits reading files, and editing files in `cwd` and `writable_roots`. Editing files in other directories requires approval. Network access is enabled.\n Approvals are your mechanism to get user consent to run shell commands without the sandbox. `approval_policy` is `never`: This is a non-interactive mode where you may NEVER ask the user for approval to run commands. Instead, you must always persist and work around constraints to solve the task for the user. You MUST do your utmost best to finish the task and validate your work before yielding. If this mode is paired with `danger-full-access`, take advantage of it to deliver the best outcome for the user. Further, in this mode, your default testing philosophy is overridden: Even if you don't see local patterns for testing, you may add tests and scripts to validate your work. Just remove them before yielding.\n The writable roots are `/home/ciro/tmp/983_3`, `/tmp`.\n</permissions instructions>"}]}}
{"timestamp":"2026-02-11T04:04:32.978Z","type":"response_item","payload":{"type":"message","role":"user","content":[{"type":"input_text","text":"# AGENTS.md instructions for /home/ciro/tmp/983_3\n\n<INSTRUCTIONS>\n## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.\n</INSTRUCTIONS>"}]}}
{"timestamp":"2026-02-11T04:04:32.978Z","type":"response_item","payload":{"type":"message","role":"user","content":[{"type":"input_text","text":"<environment_context>\n  <cwd>/home/ciro/tmp/983_3</cwd>\n  <shell>bash</shell>\n</environment_context>"}]}}
{"timestamp":"2026-02-11T04:04:32.979Z","type":"response_item","payload":{"type":"message","role":"user","content":[{"type":"input_text","text":"<p>We say two circles on the plane <i>harmonise</i> if the circles intersect at two <strong class=\"tooltip\">grid points<span class=\"tooltiptext\">A point with integer coordinates</span></strong>, in which case the two intersection points are called the <i>harmony points</i>.</p>\n\n<p>A set of circles on the plane is called <i>consonant</i> if it satisfies all the following requirements:<br></p>\n\n<ol>\n <li>There are at least two circles in the set.</li>\n <li>The center point of every circle is a grid point.</li>\n <li>All circles have the same radius.</li>\n <li>No circle is tangent to any other circle.</li>\n <li>The circles are connected in the sense that a chain of circles can be formed between every pair of circles such that each circle harmonises with the next circle.</li>\n</ol>\n\n<p>It can be proven that the number of unique harmony points of a consonant set of circles cannot be smaller than the number of circles. If the number of unique harmony points equals the number of circles, we say the consonant set is <i>perfect</i>.</p>\n\n<p>For example, here are two perfect consonant sets of circles:</p>\n<img src=\"resources/images/0983_circles.png?1767563452\" alt=\"0983_circles.png\">\n\n\n<p>Let $R(n)$ be the minimal radius $r$ such that a perfect consonant set of $n$ or more circles with radius $r$ exists.<br>\nYou are given $R(2) = 1$ and $R(4) = \\sqrt{5}$.</p>\n\n<p>Find $R(500)^2$.</p>\n"}]}}
{"timestamp":"2026-02-11T04:04:32.979Z","type":"event_msg","payload":{"type":"user_message","message":"<p>We say two circles on the plane <i>harmonise</i> if the circles intersect at two <strong class=\"tooltip\">grid points<span class=\"tooltiptext\">A point with integer coordinates</span></strong>, in which case the two intersection points are called the <i>harmony points</i>.</p>\n\n<p>A set of circles on the plane is called <i>consonant</i> if it satisfies all the following requirements:<br></p>\n\n<ol>\n <li>There are at least two circles in the set.</li>\n <li>The center point of every circle is a grid point.</li>\n <li>All circles have the same radius.</li>\n <li>No circle is tangent to any other circle.</li>\n <li>The circles are connected in the sense that a chain of circles can be formed between every pair of circles such that each circle harmonises with the next circle.</li>\n</ol>\n\n<p>It can be proven that the number of unique harmony points of a consonant set of circles cannot be smaller than the number of circles. If the number of unique harmony points equals the number of circles, we say the consonant set is <i>perfect</i>.</p>\n\n<p>For example, here are two perfect consonant sets of circles:</p>\n<img src=\"resources/images/0983_circles.png?1767563452\" alt=\"0983_circles.png\">\n\n\n<p>Let $R(n)$ be the minimal radius $r$ such that a perfect consonant set of $n$ or more circles with radius $r$ exists.<br>\nYou are given $R(2) = 1$ and $R(4) = \\sqrt{5}$.</p>\n\n<p>Find $R(500)^2$.</p>\n","images":[],"local_images":[],"text_elements":[]}}
{"timestamp":"2026-02-11T04:04:33.017Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:04:33.304Z","type":"event_msg","payload":{"type":"token_count","info":null,"rate_limits":{"primary":{"used_percent":2.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":14.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:04:37.960Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Planning mathematical solution approach**"}}
{"timestamp":"2026-02-11T04:04:37.960Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Planning mathematical solution approach**"}],"content":null,"encrypted_content":"gAAAAABpi__VQBis3CRV1o-MrJo-Oxhe6kuujF2WKtJzGkvW287Y8xjN1uZRgrdFh4EUQvuY2DL294mgOFBJNzN7JirD3OIxAt2pvGw8i5TESkklPyXGqC4HbwRxIbWXMy_kycUdxakuFL2HzNlxi5uJPRuawXMdXTEvv8xIieBvBAek50b-0mJlrhG-x0Hx8XGRajICs_W5DLboXeB9oO8knxzL6UbYVjn-PHXGRCd6MJE1b7fB7i0bx3dvlk4LM9ClLYp2dL4m72kN3FXDVFMZIx8wvO0aLW7xRyW7AGmUQyjIq5vP1KAAKXiuJkuI1-G6xhWBasuiM35iFrGQiTEvEKNSkp4AmwoQWqSIoBe5m_WujWbjnVWHIW-R9ltk_VSI_o62HeuhSpqaJiTdgc53-jv0y-_QHFx18GjurPr6z0CewRUoU-0fWY_VAn9Ai0Auo7siTMdROjAuL36T2FtpTtEzk09SPLhD3ew6k93hiqg_HrEENhdV9Qvx5wIt-40wa1T79KpM5LrEddtS1LPZhIp7zSio61R7tFnvGXN8lnxUaU6RciG8yz7UKUajNLU2rWPC9E6XJsgu7O6YStJ51Ga4_ReEWd9LCaFP2L8i0TFQkCr_EmS6rd7GZh30_T_GQqDtd1J4GJi54M4Umv3ye9Z-ZTiX5QGSi65VBtNk48_Q5gk2Rk4Uf5hwIiojTKdWDrwuBGvj8bT2KiYN8YgdHbE1117DLu0m0dkw6buQ9R1feR19YYin0m_22XTPtvXxmwG4S2o3ExpO-gO83bHkqiYJuYBdtxOULVg9MU4O3YfXRyjBCdlnpbfIqDc7MI7uS554EaRZgAwXL7GmjI86ty38lRs_Z08wjW_ydqiHqhaq8IAZQBV1oRCqyy3VX1WXh0vosKFhJiciSbvxfAVrsxPK8ZGQdJbFdeB2KY49qaDxOGcMty1qIPyZ9-Ffd3Up4joaoEDntvyivZNn5ntk4zBlDweogl58gj5SnAcXqpcfeGnGJX8bUiRfIZ_n547Wt8Vlrg9Fr0LvYPOuxw2qG5bwgvM9VgYbsx0hR3QI_Rq8VINaACKxgQrfXmdPqRR8mzTS8n5HpKSwVef47E0CrHadvm6tCujjW64BHr5k6Go6ppE7MbTeQpnG7N0QlgAJ_zneaPLwKGZUY3R2dtybXKK4qgRqyQDedkag0SxVYNebdJ0qfhWD48KbFAW9yD-99SCM5aubw5ph1Ubp44gZlstKRsZBpH5xedTqHUTEHrYBMhB0ajD49n0f4bpNuQGjLNOYW1XNxJePThjtneBPu9Ovmr-ntb3q65sDihxWM_dB-7ygA-ZCH-HR8_wWM4-T2PydKf_xaula7cl0z5yZPBC6yv6vc8Uw-sNfzsyHNgqfo0StXfmGnTujktgCTL_UocdXd1oPviVIDJ6EHeGoIRw32c5j6vEJ4Z_s2ItC5KDbL-vaZC6lqVoPUORIOWoNciiNE-zWddVkVEoaeu9f7q63LKTz0GQS57s9AVS7NTZ4xXJSPfm3tI8YW69pqnJbUgkcARfz9Dvc6EdOYsgx1RpfIqlaj4Srs4BUFFb_pUbwjAkLCJ2V-isxu11fT_F5PseP3TSqZbU5AuEniLHpk9P9FES33Mx-wFYdfuECcP5hOpYoxOvWB_4GNeAEcLLKNx0flNYvI1SSBOmd7tUP3jqLyWiFJ9pt_R_EbfMMgWLq2QA7_A_-0wjbb8maue0NuEF1J7GIOLBvCONkNTT_Ed5ORbrP_uGo3hKlQumyoN5xIe6KJwZ-F35Mv9xSLkrwmL3GDv70UHuGoR7WMMpba7lidH5dkZxpwmJcWynwoL4ITM1j-2oIGOdHikQ8EaqsSZecFbKqaNfvfNmBshbOdMNleaxoP1p-Prxml_6dHW4kan3VMXGsC7lf5Ldc4Z0favwl3oom48JB21x4AepmwKCZgaczd8RnccVXRW2rW0lMOw-L8MMhGlLRHrGElVCvMue1j6Myk9eUiM-nIX5Z3nYdhrZkmMjf8NKIqh2mHwnyVr7f8XnhgwI36wxE9JoPja0tAhPOmTp7PMk3YIxRCc0GMFQrtvlBG4Y_70sCcBANXAOmNeWOvowPk2eK5degBacQmoxvAS96YUgTGs15giCo1Qc8ZbhK-QqrrI8ILl2ouIllHMV5QXYpOBfH6DIScFbwUR5LvzKTzT32mJgg4fp5bRK5efEcg5o0RaPv7JGZOaWRp41yY1q6SqQyWoKiOSf1Xxr68UIaJkxK89kul77cbODe47LgWUOTATkuzip4XyqHVYHGMsLtjz0I5evr4_5CNeQzo3L-bLZWf-KIj29SAzDzEM3FxkOHQAcUeQHS_E-iP2adgIcqNcVWp0JExaLVSHPPqlsyLW3uo_-R78fAIGs43nvFObXnj4WenJSpZdkSNfVOtKDQHuNz7Mm2jJm7zJ38WsyVic9XZ90Gf-652JbRgXLTfkvf4Vomk9Rsqa8RoT1KrZlieYfDOJWrn992um42EhfFTahGIHmrTf9YtmEeCbp76eBjWTvb4kphwBQLBFs="}}
{"timestamp":"2026-02-11T04:04:38.630Z","type":"event_msg","payload":{"type":"agent_message","message":"I’ll compute this directly by modeling the circle intersections on the integer grid and searching for the smallest radius that allows a perfect connected configuration with at least 500 circles. I’m starting by deriving the exact combinatorial condition and then validating it with code."}}
{"timestamp":"2026-02-11T04:04:38.630Z","type":"response_item","payload":{"type":"message","role":"assistant","content":[{"type":"output_text","text":"I’ll compute this directly by modeling the circle intersections on the integer grid and searching for the smallest radius that allows a perfect connected configuration with at least 500 circles. I’m starting by deriving the exact combinatorial condition and then validating it with code."}],"phase":"commentary"}}
{"timestamp":"2026-02-11T04:06:59.614Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Deriving lattice intersection conditions**"}}
{"timestamp":"2026-02-11T04:06:59.614Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Establishing lattice center-harmony duality and radius constraints**"}}
{"timestamp":"2026-02-11T04:06:59.614Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Deriving lattice intersection conditions**"},{"type":"summary_text","text":"**Establishing lattice center-harmony duality and radius constraints**"}],"content":null,"encrypted_content":"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"}}
{"timestamp":"2026-02-11T04:07:00.448Z","type":"event_msg","payload":{"type":"agent_message","message":"I derived a useful condition: if two circles share one lattice point, the second intersection is automatically lattice too, and it equals the sum of centers minus that point. I’m now enumerating valid center displacements for small radii to identify the structural pattern behind perfect sets."}}
{"timestamp":"2026-02-11T04:07:00.448Z","type":"response_item","payload":{"type":"message","role":"assistant","content":[{"type":"output_text","text":"I derived a useful condition: if two circles share one lattice point, the second intersection is automatically lattice too, and it equals the sum of centers minus that point. I’m now enumerating valid center displacements for small radii to identify the structural pattern behind perfect sets."}],"phase":"commentary"}}
{"timestamp":"2026-02-11T04:07:04.854Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"python3 - <<'PY'\\nimport math\\n\\ndef displacements(m,lim=10):\\n    # returns u=(a,b) with circles radius sqrt(m) centered at 0 and u harmonise (2 integer intersections)\\n    S=[]\\n    # brute over lattice points on circle 0\\n    pts=[(x,y) for x in range(-int(math.isqrt(m))-1,int(math.isqrt(m))+2) for y in range(-int(math.isqrt(m))-1,int(math.isqrt(m))+2) if x*x+y*y==m]\\n    ptset=set(pts)\\n    for a in range(-lim,lim+1):\\n        for b in range(-lim,lim+1):\\n            if a==b==0: continue\\n            cnt=0\\n            ints=[]\\n            for x,y in pts:\\n                if (x-a,y-b) in ptset:\\n                    cnt+=1\\n                    ints.append((x,y))\\n            if cnt==2:\\n                S.append((a,b,tuple(ints)))\\n    return S\\n\\nfor m in [1,2,4,5,8,9,10,13,16,17,20,25]:\\n    ds=displacements(m,lim=8)\\n    vec={(a,b) for a,b,_ in ds}\\n    print('m',m,'numvec',len(vec))\\n    # print(sorted(vec)[:20])\\nPY\"}","call_id":"call_jt4fSXRhcLQLP6WB1oGEQjBY"}}
{"timestamp":"2026-02-11T04:07:04.857Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":8249,"cached_input_tokens":6912,"output_tokens":7751,"reasoning_output_tokens":7291,"total_tokens":16000},"last_token_usage":{"input_tokens":8249,"cached_input_tokens":6912,"output_tokens":7751,"reasoning_output_tokens":7291,"total_tokens":16000},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":2.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":14.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:07:06.006Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_jt4fSXRhcLQLP6WB1oGEQjBY","output":"Chunk ID: 05c779\nWall time: 0.9698 seconds\nProcess exited with code 0\nOriginal token count: 42\nOutput:\nm 1 numvec 4\nm 2 numvec 4\nm 4 numvec 4\nm 5 numvec 24\nm 8 numvec 4\nm 9 numvec 4\nm 10 numvec 24\nm 13 numvec 24\nm 16 numvec 4\nm 17 numvec 24\nm 20 numvec 24\nm 25 numvec 52\n"}}
{"timestamp":"2026-02-11T04:07:06.064Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:07:06.489Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":8249,"cached_input_tokens":6912,"output_tokens":7751,"reasoning_output_tokens":7291,"total_tokens":16000},"last_token_usage":{"input_tokens":8249,"cached_input_tokens":6912,"output_tokens":7751,"reasoning_output_tokens":7291,"total_tokens":16000},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":3.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":15.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:07:44.751Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Analyzing perfect set structure and bounds**"}}
{"timestamp":"2026-02-11T04:07:44.752Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Analyzing perfect set structure and 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HXnnpafYj9yx6T_8LCH1OIemejQ-zKa6O-nZhNNtv-weSWehmc5pMUnxpJ2C-yemv3hKG2-Oo0-gaw5gV-9nD2nsVYf8cQZN_5vltLKslnlLmzaapWId7DM5-XXjcTKXB1D8Fdsd6CAVWz6KJ-XIh-4USiaYxNo_iT4MRKed1x4T5-Uq5VHXLeJz_MbmBkHsVm0VH3J3bmrvtUFhiDoQoIPtMQIds_d3EzmSEwaoSVRKVeyTlK9zVKqReJqxtSQpOTcfNa7h51VSKzMMgZF5FU_BEfrev5gR601pn6eseNCcE4uWuO_cK978dv3no0_fBPBYUV25vmPygk8YALhbyPL92lnc5AQpTwOPdMvL7F2EO-b12ZwbQh39xaUtEoRx0JwcmqT9JNPuiHuFyvPNvoaGcRsgbe2SL49RDG1HzBq0WLh1rvYlJ9bVMOB0l9xkPtd6rqnCovdamyp7V149xcHf7NH7E9doXFH30136JKexao5oajEWhWqpinH0hmMxabSsUYtseDhdzvREAFTKBq44nSD5cwraHIMg4AdhUEFe-RkvJwizGvItrIHbZx6IudKsQRHnRl0iYYgTWX3I5XWKYZHH3iweAzC60ia3gxIJwC8aUTtgZM3_DHp8UUIeIPIpbAk_vHO8okjpIv7wl-Jty7xX3YALm9JUQ2i2G3xH-iIwguTSexZLhntfCVg1WSH3asa7Lr3fkDBn91Im-R3TRw2eYcRFuVZaGS9MsYYQM1WckjYUFgEv76qYeQ4OSF-VOv931XgZn9QvQJ707KaOQ6Zcc5FTWMKN8vlbD0OF9GO2mQLJe-P_6XOSVGTwsIRx8XSuCx1CwuRrR5wEw35m6Ayz1FKe5xpmxbHQ0KXs5LXbx3EZ50Z0dNhoYWO-6FEe7stYowzVorAyeEw0aiv70zd3bQ0pM31bT7I1SLxgGXRn3p-aV7qTsn_VTLW7oKNmhxMW4DTbt3RP_8C5qjW8LQpxySt2H-SOfFtPRGDgzPJRPrmPMssXfYtXkSYrEDMw_6PhOfMzlRvamBcDfbna0-F69NkssL4bbsYRCypjcRM7vA0Aabc31Pv4jnS0qqicwzH3vVQfGzfeSa_pnyPA3-LjVJtb3sXmwHVp98QlkK71k4RZ8hyoMA-jl40mLcqTQFkcuQR1GNejszsxxHpY5duclSdU4uhf-JspePavwevtfDYw4azY-shes66u9Zln8Bmn4cx0AgkT9dKTTspQ0vM-EzpOSxVMP7W3TDL__Z0jlOV-vGmu5_2J1P50ka6Nl2i9P_nQARYzsWeKCQ6ZgkegvOACoKhAaJmXrKZfxBhRTR6N9y6ojzF_yMXk8KurSqNz1H3i6vxbR_dAxu2pQ-Cv9brbusJcFILnInIedFxQRx4NMd287HwsE1k5GoyfackbHfS5XLRsbRo-o_jHOxeRhKgMc5Tj4S92Le-xq9kw5FqEvsP7MSw5lAvNlWvsd3SvYz7aGFtsli_fqtcE9TwVMrtBy25HXFpJ4mv_CZHtbKSKlagJyYASS1oXQEfWy8PcwayBv4X2LY5AsleK4qvLwQ2xO3lF-_dryT3iXIO5P2B5BIlXLCLPdd_-_v599uZwfE5ZOEeW3WywW2OFHEBQIyA61SU7vT7qayO2IVLbO4x4wOE-Yj_UaEfe0I6w0XJaONt5ESlyLWfhvoIfBnTQtDBdewVFCbfhHlsaBfqwghjara0MqZ8ILflIWlleV6jHeL8zdKtd4c_rRnZOMcg9IhHjQP2aD1njf-XnEGTLCUU2hyYIIrsH40f7BGoeeAaCIOVd07jQhF5YBYokCeLjG798WrJ6wUlEPxBTTHq6XP-Bq81BRt7I8gnzfOodoJ0zS0-pUS_JqtxJzt5Vj_GM0LyX0jEEqpgD9Dz3vx6S_HVMczciWF4zkAjaI-Y72un86gBbzI5g5FyvIDlqDZFmIkg3IndVrDlyBtY8dIzmvzxmf1jUo-WkDXtc9V5rPc88Mktml-EvPbnojaEtkadl-0vEjxh9DES99doJ2vvX4ATB9VUwyAVsbphKJcWkaio-TbpCTQZt-bxGD8luXH0kUajGX4-YOzAswT6Kx3__uc2dazIpESzF4mVw6IuhoynKii7Jmx3Cjk7aDeLj0WA3CkL4w3GHzEIVc-Rk-Ex6lYqpyRk-U4LCRPmk7N3EWIIgi2Ia6C2wSZpFIrd5eQOOBpf2slFUFwbOZaGV2JgXkjPYBhEF_kuQy61FsEOwHxmA4HADWCbUr7q9wuvnIamnx1UuFlEnIp8q-TneN_3fJu3EQ2LzJNOyib0xJ9N_1mGvj9X06rojTAfAnm8nUuLWeWfISIZTmPTDzWE8XIiF6NHErMep0O4-FeyBPxpi4JFE4t9dWUuWGSkG8o7Hpwt0By-17vucQ_B92QvQzFtYAB8uVSLO-zekIkedPARg0vTrf9iLyk875VY52eD5xfaKBtx5Kq3nYm-OfhFBXi6n0ylDi6_n_UPSrrjiCWksS91VFK_zgCVhgze2QZ3iFlIf4RtzhUmumPPBO3evQ8cucLaltiHQbgn_6pYAPgeVxddq9yQ8XBiT0qmb80SjKsHoB2QoUPRyZTO6O7UXZYw-8mQJzLhOUO8tW7S4Fx6VZIJvN6L6FetRP2I-n7bj6sJh5qaUVwqqHH82ny31ITuteHpF7yU6x9XbbI9GPSV8UBqHBvGx_n48exsHJ0w0mP5rZFn8PjSqoByjcQaVwlmH_EIyC6TbjMbNHi3rhoYMpNpMLeEmgaDZtWqmGZT_rNSeOaFYFuvCglCjbXoyexdrOSXC7GPhcz9HvwSYL__CMK_ed68AAbmXmoypQs3NnAfi7zHvKfdU7q4QJ8Fvfgb12KuO8vL0jszvllTF_Tv7d4rBcpcrqm6VF-ZRN9fYmfUJjq2oQ325_s2pKXGjxYDFouxpwN5kZ3rcwDTtK_RDjLqNmmXxlbN1Yra4T0mulTLzvvSbSMOPU0IBk7sfyEl7C_zxJwnirN28KhQwXGv3lR_rYOBpswEXNXsMIXYjlKqpHMEKWHcLY3nOgKLxWBWJKmSg2Rk8I1vX8JaBuO7nZSXfkbpde0E_XwRBKS8sbEuGPJAEfBNGRXMmRxxHNsPsr20NG_DdI7lvAyK1PfGBw93DQzUSl7rhrhnsiMMICvJ1UZeiALt7hngE4W5nd7zRvywUQ6r71UtGkZM-2gtUpFj281cLT2OQ7bFYH-htue6h2c0LzTyrBZpu_EZSU7hxWJdrkw7_qmfZQbRle3eZhv3A44s66nF19HuqtY72KAIu9rPgNvkdjG2KOCva3tGwPc1k8vm7IBcoyYGjQ6ZXUMXha3SahP6YDUZr4kGHkHhC7swStNs-OxUmRn601GIdoumwirU2Y3vgplbeptIqXHTJInal7jWjlaXLZi6POy9RHKNZr55RhsZBKPhCcgadKJYBUyfXxwTUeQGZdmPVbiqq0wUSb53b2Jss4o4GdWMHOvwjEl3s8BgqCorTTQjODlqB_gb4wXGffELzGbEf19xCqnQpuitGvhwJ2SOevRVN6DxHjEwcAspCJo09u5bFHEuq2hoz_q5dKdxLYsWTtjmQCSICesMIuSsWdPJXi8Fq1qRgwzqsfI9aNvVuNcrzHxoakIH8RrVeMrvnQb3RuyyriWX8Dq2LGOu-KJxl9WXVsBSxJffyO96SFA_vNH3ySIxolDpzB0UUmXHdLE30_1reEnBF-A0cREssnaT-w3ncOyLQKZrd7DAW8fGOcEC4g3gTxe8Svxp5W8sd4vhqug6ZTphUHjDcwh_Or-Fo1MzkSSUSm__EQxJWjYX7bqTkBKhr-sZUoj2OAiKmjwDXZyJV4nw1uf_uE8bERVg2qxA4X0MDK8HJozvN16kRnEJNqjXt_gVbWKG_KsqqG_mWCGz_woAgVT1ENqIeDty6bqarx-3T6OfqyWCCyxJfzh6QqZEGkTOYKwKi5zfgu80AVG00OSdeRE33JQkNfV38HkT07H_ziVLHtooZRA_j4txyrC1dn3ePDZSn46uZ_mE99xbYKIpUzXbLr6HxOpKf8RW0HDgdT49KeOG8AYTpZ1cihtMHiCFjE6AgrdprDSoWjhbarNY9TRJYEX5XpVYdpU5hOqH0uP4m5l0HnuHNsr4rAS3Idoq8Kn0j2AYwP-ZiIYX9ntqs5Lu_gf2HU37Ombh07EskoCPZuqCv62xISfVkLaZeJ3SwVF7c0u94hNFvqPV-mbza34pqcLCMmbdEuDkwAjLf7RgXlCI3F_9kjahkph_NL64mNpCSANVTLRYP8VKrha7WOs8beh6hUPB7FrQDpmqzOYgxtagrXDTTnzPK8sR_G17ZH2dvKtwxeO1YVnO4-Ix9hYtmRncmYDrISsTWdywc9vnbRe326M0vwUoqQmzezvXijzQ6ZtykcCG00pufWkUZMK4k4nVvpfHIRTSiNvcst_S5vucSI0zgUEUHroN0hcYsBjXRc_FWutp_WtJlYPi8YMgwRWSC9n1JHYTzy13Deur_7YgdZFYnmX2_nL4P675fkrGmcCorsA30Edi3hr7s46cCH4NpRcI3qtJ3xDe64aZCQ1kh303sda1X9lSypZaNmErovNlWu2JGv5FS36kDE6E8r6A6KE3xlStOPZp9voTHgHtTaemdp_i0LciG5nbZZCT9RsCewFCs9d7ZwG_738eBuhAODc3TTPAzLtOHZdTN5FZtM7PBvyzXnPgYMoVbQ-lGr5IUc24Gut-4Ky7GaBVpijnjISyIPilFPjj0KAYffbbTxfkdVR4fFMIhhW7C5266TSP7i9segWwv_R9VU8KwaVbFNdZT0ke1N3CP5qyp3Cv3y7LF3X8EX6AEucQjROTpjD3p_Vnllt5ETOxlJA6FKG3JRjdpSY3NoHeTVJZf5NF46VMqAcc75ADOWS48AuQxsFgoOaiI6YEVr5LADPjAmtMElVOW23X1pO1IpkIKzfb-Fo26Dp-tHxUFZaGaRxABWRdto8zCvTk0IGNzHs6WLzTBZfcanaCHzFiDITbIKW9kDFDNsjRqh9r1oOiem3P8ngdN9QredRMkB64O_MxZpFIGyRlYFhIl1sc-A2H6EJp71FwwNGHzUaoRZYzpxo9q7HersOj5JJzMO8djUUST2EePU20FryM-zKb8U0rXmp0je05VNvRdPETQzVk7U-W6P8EWujy7pxQQmoQOWOuy6Hs4hkCKrsdSr9Okuunhr3Dsn3xDWuANsasusW_I-sb4uZ3ey1fZxKuRMIBLI21f-IzzM5EE7-j11RDyXtjxflBc6_oH02pbAyaY6vn23Wf3_xuW_e5Em7oGIoplGa6eostSuDVP067geV8sm-qneeezaD99cGjQQmEnRa7gfz8FyeUmFAsbMrxQCNDnh7j6Xt_prdAHOv9BIBz0I6yJdNNK3iuUaafCG8v5MnaxewY37SA5sSIiNU7aCn-JDkuw9hMNq6uhNspC2Racydg6EfVVc66HgUHCsFQ35YWU5ODQR6BNBMl5DXRxXxvic1Mla5UYqsqDv89doHZWUyvYW0xzIS3ml8pmEemsAsh_Eq_o6x5i_lSSWgiVnIrMBivisp1ebt3Fbg13jJyG72g7mDBuxLU05MLR0Vs33_L6LUiUOBDrDxJj1S8qE78UG1kgG2iozQ8exKfLvGAcgjzqsYpytfEtqKI_ndRR-mLOXkS7jTJutlvhoWFaC9Fz8WtCPilD5KrbhvnhD5Ekv3tWZqlR8dO4PmQOea___TA9Cyip55o9UPMKMXyoEWzqotzufZcV7VN2d6yPbaoWg0WWpDT-QQaDtHGbNjTjbUs86S2W6uzq5UuoWijWFn1h4_du3g37Cp5ptJnpFYjMTx16nrel9MmDzrld-T4toyRzEud2LlVC6i9Denz3EZVllzXRBG7I6S74sIIDwXHtdhGXprkWbC4vStalxBDtQ8-ADoypyfdCXydVdJKOREYHZPdTbnW38LR9muvIMDWlk_1LhdM-E7gnR1gCRT2eVIZIHtzNmJlVaNL3RIPLHkT2tUXhVVdm0R7Uqk7ypemyIucl2aZH5shq8CUHmuMpqt5eOPZ8-G4bdoN7tGSTtg9dWbo0eh_6cA4GbsvjowyPPdmORws1q4Ck29BYTF0Z4EVluoW2AhschqbOLpkKJiw2ttc0Uo4G2ZdlVGeEjgOL8aKeoTBVMl7LBR5QDSCICUi1JiW_Tf3y68UBRBInM396Y3waEXh9WnufFTYdmu3fIDvca12Tasei-_V494TrJK6LZU8-lp7EX3e9N4ZNbTLMmRcJNedvJTdrYpk6kqYVbff7xE03WR0SRpYRBa2ls9wL4k-To-PSaLq15ji_nNS-exXmWKRVJJY4vQD4YhkHwnGtm4UqHcQe5gce2bPJKHCoKzizmcR8Z6fMN1Fh9dQcfLrX9MOrQR_w9HccLNpJwlXKMMtLVdO0Tl5DQaB4Mjo7mI2l2cvvLQ4VsErBV7ZCmRE5JaS3gT96gmwkDMigM96VQ0VwRhP_5vwHIfRK"}}
{"timestamp":"2026-02-11T04:07:52.058Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"python3 - <<'PY'\\nimport itertools,math\\n\\ndef harmonies(C,m):\\n    C=list(C)\\n    n=len(C)\\n    H=set()\\n    edges=[]\\n    for i in range(n):\\n        x1,y1=C[i]\\n        for j in range(i+1,n):\\n            x2,y2=C[j]\\n            # solve intersection lattice points brute in bounding box\\n            pts=[]\\n            # circle around c1 radius^2 m\\n            for dx in range(-int(math.isqrt(m))-1,int(math.isqrt(m))+2):\\n                for dy in range(-int(math.isqrt(m))-1,int(math.isqrt(m))+2):\\n                    if dx*dx+dy*dy!=m: continue\\n                    p=(x1+dx,y1+dy)\\n                    if (p[0]-x2)**2+(p[1]-y2)**2==m:\\n                        pts.append(p)\\n            # unique\\n            pts=list(dict.fromkeys(pts))\\n            if len(pts)==2:\\n                edges.append((i,j))\\n                H.update(pts)\\n            elif len(pts)==1:\\n                return None,None,None # tangent\\n    # connectivity on edges\\n    if n>0:\\n        g=[set() for _ in range(n)]\\n        for i,j in edges:\\n            g[i].add(j);g[j].add(i)\\n        seen={0};stack=[0]\\n        while stack:\\n            u=stack.pop()\\n            for v in g[u]:\\n                if v not in seen:\\n                    seen.add(v);stack.append(v)\\n        connected=len(seen)==n\\n    else:\\n        connected=False\\n    return H,edges,connected\\n\\nfor m in [1,5,10,13,25]:\\n    S=[(x,y) for x in range(-10,11) for y in range(-10,11) if x*x+y*y==m]\\n    print('m',m,'r2',len(S))\\n    maxperf=0\\n    best=None\\n    # search subsets of S up to size 7 maybe\\n    for k in range(2,min(8,len(S))+1):\\n        for A in itertools.combinations(S,k):\\n            H,E,conn=harmonies(A,m)\\n            if H is None: continue\\n            if conn and len(H)==k:\\n                maxperf=max(maxperf,k)\\n                if maxperf==k:\\n                    best=A\\n    print('max<=7',maxperf,'best',best)\\nPY\"}","call_id":"call_k3RfQLfZ5doisvXFmWALnA6R"}}
{"timestamp":"2026-02-11T04:07:52.062Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":24390,"cached_input_tokens":15488,"output_tokens":10192,"reasoning_output_tokens":9137,"total_tokens":34582},"last_token_usage":{"input_tokens":16141,"cached_input_tokens":8576,"output_tokens":2441,"reasoning_output_tokens":1846,"total_tokens":18582},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":3.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":15.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:07:53.533Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_k3RfQLfZ5doisvXFmWALnA6R","output":"Chunk ID: 7ee3ca\nWall time: 1.3187 seconds\nProcess exited with code 0\nOriginal token count: 52\nOutput:\nm 1 r2 4\nmax<=7 2 best ((0, 1), (1, 0))\nm 5 r2 8\nmax<=7 2 best ((2, -1), (2, 1))\nm 10 r2 8\nmax<=7 2 best ((3, -1), (3, 1))\nm 13 r2 8\nmax<=7 2 best ((3, -2), (3, 2))\nm 25 r2 12\nmax<=7 2 best ((4, 3), (5, 0))\n"}}
{"timestamp":"2026-02-11T04:07:53.584Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:07:53.901Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":24390,"cached_input_tokens":15488,"output_tokens":10192,"reasoning_output_tokens":9137,"total_tokens":34582},"last_token_usage":{"input_tokens":16141,"cached_input_tokens":8576,"output_tokens":2441,"reasoning_output_tokens":1846,"total_tokens":18582},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":4.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":15.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:08:01.439Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Planning brute-force search for examples**"}}
{"timestamp":"2026-02-11T04:08:01.439Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Planning brute-force search for examples**"}],"content":null,"encrypted_content":"gAAAAABpjAChFsJOJRZWA0kpTujo9y0Y7cAxOA5xU8BLFVDoq7sfIF13mVaO4ajM9jfgFMJn4C69eH8l-oDgmLeNAtzixBih3sIxFM08LAZofO4T2_2rmq60h6DGeGT73m-w49X0sWWFyOTlbQKTlJN4dvM39mZb3mRlmudCdFGRYVDVX18wUj2ryGrl7k0vDtwmEo3efHDw_e8NuGA6mzpa1oSsuCYL8i3Zqti8eecmtBRBTmTrQ1KhYExTuDR34xY7VqdLbIa6UNzpozL_IO3pjYUrRMFB8Um-SAviRw318GyB0OYmrBn2AcJKvM9HQ3Fhnwb-Jjndo-UwB504cKG7_udrMsWks16CuCl7LjAh7meYCKYU70MJmqWU57CS7x8cx_cTwVYY3O9WvnAC2h0YXIOEuOy4QKWur5N98vigmgxLcwZtxSzRFPpxtf8eYsVsOTkXLQUAMFF8Oq7U_M-gMa9Q20PY4AvfoSDzKoCACe2WvamrndTft9wypjvcXCUFCv2NsPKIIgpMmqMUR8bv4fFcyc5geJ7hvKllH2cWS7evll5f8JiYxpJfT4_saF3tcZBzBa5Jczeag2Bg2EXSdlkSvWsxiZG1cImV7dKSwnDqlk3VW298ewFBl5K1k0hOLAn9WvB-FKTXq4-6C6YAmHa1qMsvSY4ARMorZMLGXWfaqwn4fHkQo-NjbGlz9hOCpnXGp-xMtz5zvC8J-2eDMsrU2xSSqRg2ddpgPQxeSa6JAVMPdQWhU9NSrYA76jl9Dadgk41-YQRpFhjaW_xkwmmgzkPrx27M6CiNhE7FvISQ6WuiiI3UHJcOaZXxUsxevi73v3Vo46T_NA3D-BLHVxLRRY1_o-iaY06WWO9Pts8FqiC8SB1X4hN1UjscHQ-8KKuiIea5ET9aBxyUlKentxPjr9bhhi3qwwlanSsjj_VYhD1s-P7_HDRIDAuGyAy4H7MRAr874JpvRZ67PTBEgD2-doBCceY52ByVXAuQn78ChpqgC-noCuTG2Rh3pI9e7Vr414qcBEbsxg8tuIvdTWvdWYmIegjUP5K5K2GMrpICtZaSXeyNjsMB4OCknwLACpPl0W7S4cS3TpE51lTXeLTFsPXSqwwgWNwE-us_G24IabqJuYREhsZuhkhBoDElXq326fyldn-8Y778_8GrFDcU23mN5V_s_f8muVRlubQT5tUb5KqycAT1ng9B-kzNy_7wvkocjffoKtM1hLXsqUsyc1f-KVjQ1C8c-4YAZ9jUmXd0NK6mVL8IOGZsvYbbB-XQqIPq1DAs25w1JsiTo0LIfNt1bqX_Tp0uIBMdy-Co-0UtVC43u34QzJMK-63CM7NUYYuQhccBNBHuB-X75tDeFCOhXDpSWR4ncyTtR2tdUlcPto6pH_MkIftWqILfNVeXWu1_cG-CsYiRaYi3g2nFmGaTvAyZW5Vz4lIS5wQa07-GkRE3x5NDoFM4riv2ope-n5YOc8DhoSDk6vRI2VrFQTWPZLLhwkQQUsb9VT3nwl1TbIGZJVef5td0eFocv89dDwqhx3D5qN9a83Vqk9Xw8uu4yCOeQ-OkKVewEaXtcpvyJR67gHOSt2pzdTk-yC0kCf8l4VgvD1iyOF-_VzflLn0JQeqWbDEL4j2GYwzdjKqffw6V526oS8YPCALb-EfTNaQofSsIfYdCCUWy_XisuyfdT6GBLfCYLA0adEk3NH4TrkCiqTzZVrQIVdw5Vbcbf1vEpvtKfI8QukzS9l280LoNdA6TKVrfw-V7H-NXQ90gQ1OlMWkda6bdB3bnhmyknD3lEBhJwyZrO00cSDyylY0ChZ2t7RQe-NFXj8H2vRmSSfijf8TmzOKnya0F7XRKbZoZVwSSM1buwZVW0479_f4dHTpN06zNjNbKM5Tv6UBWbOekPgdMbBXJL_x29NcZwb3n2zrUVw8uYh5h26BxgmTIbpD1cJd61jMHFoxDX46fFp1yNXobnTLxWsP9pSLHWjKA7KeZ974OVgd4MfQdB5vLFieCQ8a5afeLhPcnsLpuM1tFapXFoy0QnANONhgChPt0YXTbfEDmoUuuFzY9wtxo2-oK8vOjYU1w9STO_rY4kynjRvT2tLxUHAx9cxgzuQnKb-oPuD7mnUDTiDCaToe4O6VU5mAG6CpQlNZ2z0lzGJi97QFrHXAc2DlF2YiiyvCmedza5_Jj4KwrND4aV6s2A06bNuE2FjbCjR6CvzVkYUmunhCwm0tBR5TAt_4Cpu8mMUMxXzp6-as58kNNnkP9j5Bdpqs_P98Q6s16Jfswn_HvhZTfl9y3IfqXDItI15DSYDWwpemdqueRTSOvUeusyF-bVvcP071PdJqyzSwNUqzNsGfT9nVIwHs5yJtN4SkCutfD5gkCVbmtHo8cLF5LAJ_Bq5PfYp9gi-PA6Vv3UNdtykuUGBQqI6QHm59HTPok3BsccT-dd1Ubo648z_H4FkLYmXi4YoMJcp3at8hyxSbjeDy-JkMJWKF31Z4jqJ_gjem8deRICPsMUDScMLKrRZWXX4fyx23Bj_DCroqp80oW8Po4hcVs-4Yz4Ox_uWcRKhtxL3o2-vr-XBxMSrXswuZx2OicaOoh4V2gJ7pjtrqkQ_Z24Ta_F4QWEh0h6RTdzMrY_pEuCOfVOTHfwT3Fx4v_SZjxQNp0IC5zPf9oG0ELPJ2ptoN9Q2dQ4kz9WnxTvx291vW0WROpUZ6IUB7uwcV8ZLYsGBmoKSXLsD3MhA8dWs8eRHuQy0BQRe7KOfjTltuv-wbmRr2LYOnj95bxCjfCJycHM6_M8JbGfQr8tY5T6sYRQBR3MR0FFaoHoZO7lTWqTSknK3NN17z87MwZMg=="}}
{"timestamp":"2026-02-11T04:08:02.811Z","type":"event_msg","payload":{"type":"agent_message","message":"I checked one tempting construction (all centers on one radius-\\(r\\) lattice circle around a common point), and it does not produce the known \\(n=4\\) perfect case for \\(r^2=5\\). I’m now brute-searching small coordinate windows to recover an actual \\(m=5\\) perfect configuration and infer the right general pattern."}}
{"timestamp":"2026-02-11T04:08:02.811Z","type":"response_item","payload":{"type":"message","role":"assistant","content":[{"type":"output_text","text":"I checked one tempting construction (all centers on one radius-\\(r\\) lattice circle around a common point), and it does not produce the known \\(n=4\\) perfect case for \\(r^2=5\\). I’m now brute-searching small coordinate windows to recover an actual \\(m=5\\) perfect configuration and infer the right general pattern."}],"phase":"commentary"}}
{"timestamp":"2026-02-11T04:08:10.126Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"python3 - <<'PY'\\nimport itertools,math\\nm=5\\nR=int(math.isqrt(m))+2\\nS=[(x,y) for x in range(-R,R+1) for y in range(-R,R+1) if x*x+y*y==m]\\nSset=set(S)\\n\\ndef edge_data(c,d):\\n    # return list of lattice intersections (0,1,2)\\n    x1,y1=c; x2,y2=d\\n    pts=[]\\n    for vx,vy in S:\\n        p=(x1+vx,y1+vy)\\n        if (p[0]-x2,p[1]-y2) in Sset:\\n            pts.append(p)\\n    pts=list(dict.fromkeys(pts))\\n    return pts\\n\\ndef is_tangent(c,d):\\n    dx=c[0]-d[0];dy=c[1]-d[1]\\n    return dx*dx+dy*dy==4*m\\n\\n# points in box\\nB=[(x,y) for x in range(-4,5) for y in range(-4,5)]\\n# normalize include origin\\nB2=[p for p in B if p!=(0,0)]\\n\\ndef canonical(C):\\n    C=sorted(C)\\n    # translate so min tuple at origin maybe\\n    return tuple(C)\\n\\ncount=0\\nfor comb in itertools.combinations(B2,3):\\n    C=((0,0),)+comb\\n    # no tangency\\n    bad=False\\n    for a,b in itertools.combinations(C,2):\\n        if is_tangent(a,b):\\n            bad=True;break\\n    if bad: continue\\n    H=set(); edges=[]\\n    for i,j in itertools.combinations(range(4),2):\\n        pts=edge_data(C[i],C[j])\\n        if len(pts)==1:\\n            bad=True;break\\n        if len(pts)==2:\\n            edges.append((i,j)); H.update(pts)\\n    if bad: continue\\n    # connected by edges\\n    g=[set() for _ in range(4)]\\n    for i,j in edges:\\n        g[i].add(j);g[j].add(i)\\n    seen={0};stack=[0]\\n    while stack:\\n        u=stack.pop()\\n        for v in g[u]:\\n            if v not in seen:\\n                seen.add(v);stack.append(v)\\n    if len(seen)!=4: continue\\n    if len(H)==4:\\n        print('found',C,'H',H,'edges',edges)\\n        count+=1\\n        if count>=10: break\\nprint('count',count)\\nPY\"}","call_id":"call_b2TkwLbMcGScFOhOO4SXhmtg"}}
{"timestamp":"2026-02-11T04:08:10.130Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":43148,"cached_input_tokens":34048,"output_tokens":11233,"reasoning_output_tokens":9478,"total_tokens":54381},"last_token_usage":{"input_tokens":18758,"cached_input_tokens":18560,"output_tokens":1041,"reasoning_output_tokens":341,"total_tokens":19799},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":4.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":15.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:08:11.549Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_b2TkwLbMcGScFOhOO4SXhmtg","output":"Chunk ID: c8c29d\nWall time: 1.2663 seconds\nProcess exited with code 0\nOriginal token count: 350\nOutput:\nfound ((0, 0), (-4, 0), (-3, -3), (-3, -1)) H {(-2, 1), (-1, -2), (-5, -2), (-2, -1)} edges [(0, 1), (0, 2), (0, 3), (1, 2), (1, 3), (2, 3)]\nfound ((0, 0), (-4, 0), (-3, 1), (-3, 3)) H {(-2, 1), (-1, 2), (-2, -1), (-5, 2)} edges [(0, 1), (0, 2), (0, 3), (1, 2), (1, 3), (2, 3)]\nfound ((0, 0), (-4, 0), (-1, -3), (-1, -1)) H {(-2, 1), (-3, -2), (1, -2), (-2, -1)} edges [(0, 1), (0, 2), (0, 3), (1, 2), (1, 3), (2, 3)]\nfound ((0, 0), (-4, 0), (-1, 1), (-1, 3)) H {(-3, 2), (-2, 1), (1, 2), (-2, -1)} edges [(0, 1), (0, 2), (0, 3), (1, 2), (1, 3), (2, 3)]\nfound ((0, 0), (-3, -3), (-3, 1), (-2, 0)) H {(-4, -1), (-1, -2), (-2, -1), (-1, 2)} edges [(0, 1), (0, 2), (0, 3), (1, 2), (1, 3), (2, 3)]\nfound ((0, 0), (-3, -3), (-1, -3), (0, -4)) H {(1, -2), (-2, -5), (-1, -2), (-2, -1)} edges [(0, 1), (0, 2), (0, 3), (1, 2), (1, 3), (2, 3)]\nfound ((0, 0), (-3, -3), (0, -2), (1, -3)) H {(2, -1), (-1, -4), (-1, -2), (-2, -1)} edges [(0, 1), (0, 2), (0, 3), (1, 2), (1, 3), (2, 3)]\nfound ((0, 0), (-3, -1), (-3, 3), (-2, 0)) H {(-2, 1), (-1, 2), (-4, 1), (-1, -2)} edges [(0, 1), (0, 2), (0, 3), (1, 2), (1, 3), (2, 3)]\nfound ((0, 0), (-3, -1), (-1, -1), (0, -4)) H {(-2, 1), (1, -2), (-2, -3), (-1, -2)} edges [(0, 1), (0, 2), (0, 3), (1, 2), (1, 3), (2, 3)]\nfound ((0, 0), (-3, -1), (0, 2), (1, -1)) H {(-1, 0), (-2, 1), (2, 1), (-1, -2)} edges [(0, 1), (0, 2), (0, 3), (1, 2), (1, 3), (2, 3)]\ncount 10\n"}}
{"timestamp":"2026-02-11T04:08:11.586Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:08:11.922Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":43148,"cached_input_tokens":34048,"output_tokens":11233,"reasoning_output_tokens":9478,"total_tokens":54381},"last_token_usage":{"input_tokens":18758,"cached_input_tokens":18560,"output_tokens":1041,"reasoning_output_tokens":341,"total_tokens":19799},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":4.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":15.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:09:33.475Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Analyzing structural constraints on perfect sets**"}}
{"timestamp":"2026-02-11T04:09:33.475Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Planning SAT search for set construction**"}}
{"timestamp":"2026-02-11T04:09:33.475Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Analyzing structural constraints on perfect sets**"},{"type":"summary_text","text":"**Planning SAT search for set 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"}}
{"timestamp":"2026-02-11T04:09:34.864Z","type":"event_msg","payload":{"type":"agent_message","message":"I found explicit \\(m=5\\) perfect 4-circle examples and they’re highly nontrivial (many circle pairs harmonise while reusing the same 4 harmony points). Next I’m testing whether \\(m=5\\) can support size \\(>4\\), which will determine whether \\(R(n)\\) grows beyond \\(\\sqrt{5}\\)."}}
{"timestamp":"2026-02-11T04:09:34.864Z","type":"response_item","payload":{"type":"message","role":"assistant","content":[{"type":"output_text","text":"I found explicit \\(m=5\\) perfect 4-circle examples and they’re highly nontrivial (many circle pairs harmonise while reusing the same 4 harmony points). Next I’m testing whether \\(m=5\\) can support size \\(>4\\), which will determine whether \\(R(n)\\) grows beyond \\(\\sqrt{5}\\)."}],"phase":"commentary"}}
{"timestamp":"2026-02-11T04:09:38.550Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"python3 - <<'PY'\\nimport math\\nm=5\\nS=[(x,y) for x in range(-5,6) for y in range(-5,6) if x*x+y*y==m]\\nSset=set(S)\\nD={}\\nfor a in range(-6,7):\\n    for b in range(-6,7):\\n        if a==b==0: continue\\n        pts=[]\\n        for vx,vy in S:\\n            p=(vx,vy)\\n            if (p[0]-a,p[1]-b) in Sset:\\n                pts.append(p)\\n        pts=list(dict.fromkeys(pts))\\n        if len(pts)==2:\\n            D[(a,b)]=pts\\nprint('S',S)\\nprint('num D',len(D))\\nfor u,pts in sorted(D.items())[:50]:\\n    print(u,pts)\\nPY\"}","call_id":"call_47GYJiBsc8FNheaFH4REdqum"}}
{"timestamp":"2026-02-11T04:09:38.553Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":63875,"cached_input_tokens":53760,"output_tokens":15310,"reasoning_output_tokens":13249,"total_tokens":79185},"last_token_usage":{"input_tokens":20727,"cached_input_tokens":19712,"output_tokens":4077,"reasoning_output_tokens":3771,"total_tokens":24804},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":4.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":15.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:09:39.280Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_47GYJiBsc8FNheaFH4REdqum","output":"Chunk ID: b37c2e\nWall time: 0.5749 seconds\nProcess exited with code 0\nOriginal token count: 182\nOutput:\nS [(-2, -1), (-2, 1), (-1, -2), (-1, 2), (1, -2), (1, 2), (2, -1), (2, 1)]\nnum D 24\n(-4, 0) [(-2, -1), (-2, 1)]\n(-3, -3) [(-2, -1), (-1, -2)]\n(-3, -1) [(-2, 1), (-1, -2)]\n(-3, 1) [(-2, -1), (-1, 2)]\n(-3, 3) [(-2, 1), (-1, 2)]\n(-2, 0) [(-1, -2), (-1, 2)]\n(-1, -3) [(-2, -1), (1, -2)]\n(-1, -1) [(-2, 1), (1, -2)]\n(-1, 1) [(-2, -1), (1, 2)]\n(-1, 3) [(-2, 1), (1, 2)]\n(0, -4) [(-1, -2), (1, -2)]\n(0, -2) [(-2, -1), (2, -1)]\n(0, 2) [(-2, 1), (2, 1)]\n(0, 4) [(-1, 2), (1, 2)]\n(1, -3) [(-1, -2), (2, -1)]\n(1, -1) [(-1, -2), (2, 1)]\n(1, 1) [(-1, 2), (2, -1)]\n(1, 3) [(-1, 2), (2, 1)]\n(2, 0) [(1, -2), (1, 2)]\n(3, -3) [(1, -2), (2, -1)]\n(3, -1) [(1, -2), (2, 1)]\n(3, 1) [(1, 2), (2, -1)]\n(3, 3) [(1, 2), (2, 1)]\n(4, 0) [(2, -1), (2, 1)]\n"}}
{"timestamp":"2026-02-11T04:09:39.317Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:09:39.679Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":63875,"cached_input_tokens":53760,"output_tokens":15310,"reasoning_output_tokens":13249,"total_tokens":79185},"last_token_usage":{"input_tokens":20727,"cached_input_tokens":19712,"output_tokens":4077,"reasoning_output_tokens":3771,"total_tokens":24804},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":5.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":15.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:10:27.649Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Analyzing harmony graph structure**"}}
{"timestamp":"2026-02-11T04:10:27.649Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Analyzing harmony graph 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"}}
{"timestamp":"2026-02-11T04:10:30.056Z","type":"response_item","payload":{"type":"web_search_call","status":"completed","action":{"type":"search","query":"Project Euler 983 R(500)^2","queries":["Project Euler 983 R(500)^2","Euler 983 circles harmonise"]}}}
{"timestamp":"2026-02-11T04:10:30.877Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Testing domain filter effectiveness**"}}
{"timestamp":"2026-02-11T04:10:30.877Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Testing domain filter effectiveness**"}],"content":null,"encrypted_content":"gAAAAABpjAE2wl2bRjCLshO0sZHmQ0KxFMbwav2byNqJ3A1QJ6kYWGYLZp4_4ktR4oKU4UVIWBGAR_ruVF3IGMatZ3WETFNZBCyO56VgMM5K3JduFHTx976frqO84zoefND3oLbvwMIgJkKfyCdCy_44nSn6UP24HP1VvPfo2iealVz-tiXfv8aEvEhBbOSmoX7nSUF-o2N9lH022QGt0SrvEL-nIzD4QoNK6f-sFwLF5UleOJrrTtnbnIzEQm_lW2bnmG8RvV6dwIGcFZp0BiTZierfebHVmxMrSqrXTQ9pG30zIb7SpE1MWMwCrVP3NknIJ2mHUt7PMP3qSjtHpWUIfsKqNTB9WmVLpzWwSxFSO51MRMs4vpBabKxmKqD2s5zOiSR1PlD_A_yJqCCUQu4FfkWA_MteyBaSf6Op9PFovsX2qa3-KpNvkqj9jD5lyQjUUCjApB7-Ai4-884vtlP2h7QUUPK_y2HN91eKK_VzYYW1CnLokgP8GD_pYzJZLL0NuP21lvD4-TRZcdqWqqk8wvU9tOdzBkMKiorjK0FH7Nxo1aRbUNP7DQ9rOj2dT25TP_PdZmTS6q3Spx0niUp3JHdB5PfKi5LdRoyUAoMZafJ8WtHsW4GopOYJYB1_18xXQjrfrGdVsjpEDBXCWwZt6wWXVLfxuERcbFEP1tckW9UvWIKn8ybhvRYo5BwaPekHJjQCRsBopYOrMuaGMWhFAZAurWv-EmCVwwMO-4wcYTqHYvomCBdbDuKJlbQ06PiYKwaBnczrgHFTWKFS-xsXlsVtmJqPZxQVJ4jq5josNWZlcEooQrfRNLSGpdxurUv0ip27QoRnqTSr0WW5IjFnrkcw9pnlOO9WgJjgkKOmaL1nODBMb_pSe_JzJMK8KjqxUPimqULOvJWTkqg2lgLk7bqWUeVjeVirDaUkjdxVjn2l5ORX6sfJhZXE6ScuxYG-kWPWIW4dbh9krMbltHYlNxxyF4tsdXoCqLcYn6j4zlUHq7okPfZqDqs6PH8wMUIh1aj1ZH36Zw0KeQZ2BdA7Djz65evPUXoLY0N44X6bO6t35j9NIhlOkLAloZ39nAWu1m4vUx1B9ufkBDLLcOKqtVS6ZjQazg=="}}
{"timestamp":"2026-02-11T04:10:33.435Z","type":"response_item","payload":{"type":"web_search_call","status":"completed","action":{"type":"search","query":"projecteuler problem 983 solution","queries":["projecteuler problem 983 solution","\"R(500)^2\" circles","\"consonant set\" circles"]}}}
{"timestamp":"2026-02-11T04:10:33.673Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Exploring targeted problem page**"}}
{"timestamp":"2026-02-11T04:10:33.673Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Exploring targeted problem page**"}],"content":null,"encrypted_content":"gAAAAABpjAE5iA_g-mkWA3QLai9gqLVp8nJlqpK83FHKgYN7KontYEXfLaTxVncOOk8FCQXq5rsOF2y4I4RmH47usWL9Y3ZXuECPtQ7YE8QpI8qsvfFutR4ZwFSaKfF_VsHxElUfWbR33y4spPC_llTD52tR4pH3q7HnbnNrlzZguVjGs138vjkYSY2dr66IheJlSOixrpV_YKr8hS528eRUHAUlEZuDS1fzs5wVrHDz99Tsz2ro8jfNt2i6TXDL-LDF-RHgjko-D3Tb5hLHw5LMdiukWwDOFoV9kFzRaF69A32vb1ZhiRK9xTpKwa-YB2ORpGaBABMrbnJito3CZ3QTJS1QpVDTL94eCZHv4RmBleu02wAEywmQfaYIqOD2IGS_AhRKH9b6uyNzvr5cY6WgwV1WILbNGKWJHw0CYSzxiCiefFvRieEYN9njtadXxpFzje3ZGf53qlvpPHdOcGEBnRGrtVI8h_dGsL1lZqKEvTUcmonixrsKz0GmVNMecH_bJIVSemJ-9HqSdKUgPOG7zX5Mi-g8jgsVyfu6uAGewbwvhYJRlh62AxSrGBeGolJI8ScLrj_50n0BLc_GkzT7jnUnKxXJy0D-z0jc-pMWzFm2s6yZjrmaBS9UPyaWgotBmtbp7voDDiu8uTF1KIQ1TTt1UYWR_qkA0y_fn0hes2wxkduzR2bNn23EDm_-nrkRtjPh0NZiG8MvJf5vtISQiwEvAG46rw6VOVxfP2y2n5e1LYSx4J-zl5Jb9r5B7bQo3JecYn2dUu4NTiOue9T63wid5jJeydbQeABcIx-ULUONbnw3CECqoFyjDQ_wBnbBDRoRVtNRmNDJQxrJ4SziZd49b7Wo5ea_DtwunsDB0tYs45isGQMNEk_TGMoJ8UpfZgM9IZO_HzTN5227Z4WfwcHMC0O_DolCdKKJoHmaivaKOnhSWVsuT04ppLA87XxTOF_pr5vkzX0kUJCnxU0vE44_hJStk58jWGnM6w_38ihnq0-6Z25lDXuQCtJ4RUujc2Ybd87SJ0nJ1eB-0AEY4OND2cnCxT2lA5Y4SSdw8yMJd5VPfDquWvKGjZbcSl3SIrrn-HDzVsDMGIDK6jSoys4P6b-L-0w9k5_mbGULC4UKHmuw0btryN7E7ky83ostG-JCcn4e5_BX0fWEgvmBmfHoKL-WJ8g-cb_323hTyR4MDsf6kXETqb-u4fw8E9Nux845CW8AAVPsG6XXyWN7anEyOKJfBCuWf8ELOjlRO07_1a3raalLBQuV0BH-iBolY_B9ZEjylkKmcm_HOp-p5bC7gq376Le1uUKtJmOwYmJdnRowUrV9sMRrpLh7ItnkCXw78hbhbZSIHhEicGG-B__ZvNOQSe4doT0K8kcXna6CmER5jwdJ8EWkeKv2MHeKDbARxrTa66wjhkDinsxkligkULSBaCxkcC8rOpXW7eCpsyirUcVGzsBeMawTpE9_Mo_CHHtJrjXOWTSdoR9uNJmfP8pOfSmx9ce4l5bYMgmQaeC5KMtJbEMkcroLOqajdrkrYCVM"}}
{"timestamp":"2026-02-11T04:10:34.050Z","type":"response_item","payload":{"type":"web_search_call","status":"completed","action":{"type":"open_page","url":"https://cirosantilli.com/project-euler"}}}
{"timestamp":"2026-02-11T04:10:34.256Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Identifying search pattern for problem solutions**"}}
{"timestamp":"2026-02-11T04:10:34.257Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Identifying search pattern for problem solutions**"}],"content":null,"encrypted_content":"gAAAAABpjAE6m1k_wHitb15MP3UrD9Wk5cwD4z1TI2ih2N3a0CU1H509UV5ArlrzTcQ2ubWZEZJPN9Jifv9QQ2EDKIKoibeUVq7tD00FoWEago7UPX8TcA7k88BMrN3pHQjGxNjsuSQM4nTkCF-onpj5XCM1KkEI0PfJJJQO_prXFpr6qdrij32nwCo6YUeYGCAYkVZWaRxXv2-8QChyWI8FYpunQwcBgOQ0bGrvbodvPmyCugnRrI8m04NfDQU5LX0VhG9SSkWS_S2P59-mSCmQ9Zh_eslhBdkn68yl92WiP8uVMx6fk-KBiZGtik8241Nvr8e9lb2gTF5hvLeaLwAiLtjLMZb7aG-aiqZB2vsg8WhfHOK9wze0tvtwm_5yfcteP1K0w31HZFoxc3KqJZMk0PjzM3z-Sil9S0kaxrMQrR8O5EmcKnQGS1zC4a9sGfE0VR9hzZRc-HprUVlsnYre_YZQQFjhm8lAZCjINoEw-WPEQ6J_agJqVX4HE1yUXSxvLda6o50q5mzeqTEAqLJcrVjpaVruCLlED8iyhipxl_C4gvpp3WiyUE6J2PVwT8YR68haKnT61bF0BPhJGYBGkzBpcBd5X2OyXmvq56fsSxZZori226OX3q8YKg8oykUjsQ8ibO-TiCHmSbadJG49zG2Riic5SyuEAOCBZkmHYbGH-rft4du7n-NbAMDNAXXhf-ZQmoEJ05t29kehj2RyGcFaGxizUvKD4GensMXio8hsDYvLj7zOYwoRIJok4Olaj8NTpixfTslU-oN-sDaScZoFo-1vKCHflXmCQHqpBHSszbvass9ef06t0uG78u7jOHsuAFt-k35n5Vcjip3-DW1Q0QiwiB8IoB0oG-o3XuY2nqA9F3TvAWP6dYIflpToYfFttT5OZpkRz4N8SR-WYz_CAxbXBd8gGPL9wrWkcWjP0jNRRU82EVGO5xU8Hj1Xo0GeE77d3OBks2giBaej2sc746F6NQ=="}}
{"timestamp":"2026-02-11T04:10:36.508Z","type":"response_item","payload":{"type":"web_search_call","status":"completed","action":{"type":"find_in_page","url":"https://cirosantilli.com/project-euler","pattern":"Project Euler problem 983 solution"}}}
{"timestamp":"2026-02-11T04:10:38.147Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Verifying problem ID coverage**"}}
{"timestamp":"2026-02-11T04:10:38.148Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Verifying problem ID coverage**"}],"content":null,"encrypted_content":"gAAAAABpjAE-6ym8Djgjqxm1RZ8e4ZhFtWByeGwOTjhdKpExrPkL8fjHGIc3aGogE_HJG9bQLjZd99sWFhvPcRzGbQTNvl_t6fRZcFtyxV2_wAXmbNA40eCTne_bPeWdh2OqBfzmMOAsqYa8T6qYjMsQ5YXHeFbjbYRcyLVjoJPrBhwkcqqZ9_RLyRLk43W4xEJsFDdHhcqT8wpRbLXLLgWnN_NXOHUa-VCDXm-0EpOcDlmoVNJ8bmo5IIoCkCd9qGQNZnIlKceXBIsuJ7gt2ocKOF7GKLveJcjauI1pDAogIZG6vm4ytko0FNwsmYWqs8PV5i60dD8nmIVTLGjw10aHjT8AAi3yXCwhsVZWkHb__sosGbGJwx__w5EBA_r19LGA38tt8-d9ZYYvL-sfMd6i0dVkaBsKzcZdWK5xJ9GJB1i3s8UJar16y978RH4v0NmNArJnEpiRmNC4UCnuvDKA-74-G3JHqsnIqc1wJrmYI9snPUqBe0HfAS68z8CgJDGt1MntgRhG0RBu3NNUI6QIvS3YJpaAVqpgsXfkofzslHUKIsKXAZaxY4AoKa-pUCghFjv_TscaVWaS2K5UZ0SOgDa-4icq131ZQdEp8Q-LHhGIwSOTQgTA7o2wEmXHm4nOBbw0g0OmkoC2e1UjUgROllXNRh6Kspp8Qv_UUjAroTPySwHCKND9Qq_Bmwv0U_6XOJy6lA_SeFvjhhrqAmJ_bVmNcp_nnjc_IgcvO8TnHg4gTMEscvrRehgtusHx3bIe7R6T5-A2KSRnbr-RMir6OQDs1EvQ4Pkdv62FCbNzWdfLEpdaafwvc_JpHJKZH4JC0VxBt95MTjf2mk0ZFGqGG5oiQnf3Ah78mK5ZFkr225Nt-iEAiHebcX-8MowYdxHajQbMpSg6wbFspmIzN_S4hdybXO9WcGM-1L6q_ms_bMGZw7S4rhhdro6Ni8ej-DpTPbAgYO4zU6TF-wKQJaE6xX9EPVp47byubwsxJSEjmp8xb8Xa6-47ZKJ1cnjUqF1D7Jw8bWd3goKmdkR-m-OoqGmewR95i7-P7X2LLcJKuEn01yRPS1_jXOT-Exvm2aVTfV0kGHXs_KO2uTOlWOO8C8ATMoJp5vNLSHgap2HleisjT5j1j5831r6nA3VtPpOuhpoQRGAzpqTcfTEz8uu7ze0l1EWlaLX1seHrfeJFKOplf-9oS2g-ahG_qMjYvgS6tfcw7KOVvI8SbQAa82818xD-boTjc0MR42JA8fUXWA3AP0zhJId9_RWb-6mruCD5sdougCjP"}}
{"timestamp":"2026-02-11T04:10:41.321Z","type":"response_item","payload":{"type":"web_search_call","status":"completed","action":{"type":"search","query":"github project euler 983 harmonise circles solution","queries":["github project euler 983 harmonise circles solution","lucky-bai projecteuler-solutions 983","projecteuler 983.py"]}}}
{"timestamp":"2026-02-11T04:10:41.491Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Identifying potential solution source**"}}
{"timestamp":"2026-02-11T04:10:41.492Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Identifying potential solution source**"}],"content":null,"encrypted_content":"gAAAAABpjAFBC2rlb8BiJ7iZBYanLMgqL2uFBBX3D5_PBforoEalHAr_JVCaxvL1WZnC-WRMqNy4vb5_VcgDwLfDAwLOsbWFJXcFbarZpWDITzoiZiZWDnuqOpqjQh5qt2PImKC-LpwCnSTdbs6IY_OX1kTwxAMRqun83rY7pka40bcD4m28ccEhQpHYuiNMhaq828zogCch5bGL7lcMBIccDn3pUw4e7Aw3YVL6Zf9IwILYpEsGmEucvWDmYON9ki0p5U4YptW6jU_NrremLzfrCCADWnrw13AuZIKNL4D6o4RCvm8MjEQSXcBXu3ry7fz1fCMcsGWuQmyYa3nv8KrWbdzlkorGBhsnM4ZaoYVXLvSBNBEcRV-MI9gz-w0XJ23HPkec9USSWBQlvvtRkBSufiOvXbedn6UheNs7etR7w7R6a18QZMIft1fbb4YR1cq2_GsPBBbH-h83i-UIe8qcmpIvnPGmJvzTNJ87cQeHiShE4FT_oiz93h24oVA631DAcC3il45yXo58S_9lkxjTzTEQtQkdZ1qD-oOcBz79forIu_0R_UBF5krytl74ggXQwucpklCaJgOW5SuubPxO7K8-4wA1vEPZ80WBLmY-3UpLApmek8nL7_Mglyn4V_rnU0jh-94W7dacWKm_NjUn1XOCeyxF1A5JTtyYBsNdz_0h5EyZQBpCavVR_vvzamM1Y9_paUa4MHwXlVuEhISjdbCoE_uEjKflDLgudrD-SDtpITmne8RfcEHBIK-ALk3bvdYC8hpWVYwOVSWMlKrV4AkhAAFSQBwTkZTtErq9wH8wVXEbHgQc7zby_UOC-SlplEv0cC_gtSV643a8204pHRoTdTlgjDEhUeBGY_ox_xakVYL0Mno3_DUIn_ryOzL0Eu_dtDtp5Hp9GYh-ybr2hJ9ifkdXohJBwEn_1vNHiTkBUoABrQCUodmWjAmWRby9u7c9yNuqBMhDGhLu2EgnhKsAq5kuFjBr9jO_gud1Bn85uBj1Kuv56Qjw808XAI7ahuGpXYHRQ6jK27Fb8QnTjQ8E37VIe6yBeu0AemkQfA_S3J_kwQoQDfBz-X7QZpmnUfVhqFYasQKdvCqRfih77yqrq3bAOQ=="}}
{"timestamp":"2026-02-11T04:10:41.936Z","type":"response_item","payload":{"type":"web_search_call","status":"completed","action":{"type":"open_page","url":"https://github.com/lucky-bai/projecteuler-solutions"}}}
{"timestamp":"2026-02-11T04:10:42.147Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Identifying missing link reference**"}}
{"timestamp":"2026-02-11T04:10:42.147Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Identifying missing link reference**"}],"content":null,"encrypted_content":"gAAAAABpjAFC4yKSOVPRdopKcWb1YMF_GMUS73tjoG2eb6tCX8ycQ09sJu3yHiSFbYioahFsDDsR4frlvyvhlIV6fcxUDLiDqmmIgqJ1f7bx8sUSe5l2guLWaFYcsNoSOcN1u3WSnc-6-dPTAlEUvGyHVVEalw3BsWr3O-9WQD6WeNsw7Z6J0S31N7a8kkCf-GWjAfQl09JIaT-ijCKev3MyWZcwE-1Fo9ox1eeIxwpAn_hNOb0mCXYelbUz5Q90kawSRm9GDA0yj9oZciq1YeTnad5YFBqJ271FtpHPwHnxIb0OWEXGuzKHP_UMsgQCYKmsL7dtpCKw92Ud8R2XnK8XIiiWmhor33pEZH_Y9LlggoKmXcPg39rPK-cHUCYntQt9t3YXJkqIdLkPVelBvF9dyXLF3zQK1plSLrs0E-QuzgvGajRJGGj6hXC_x--TJCLqRvR_8HxaeJSgxdR2KIDDGsarf--UzVej-x51WJvY11WRrOjV8kU9nczOV20RzTZaonLdfJ-u_b8Qm--0qCb_kcVdBysQn1Sh5U5nl3rfbxlGLXJjaLD1MZ62nXULB7ds6rZUe2hF12u1_EzgxjZl_zW9Q_WkhXWVbCprfhONz4zCCQUrV15ylr8JZOhq7vHeIx516q7QSRfFRcGN8TF8ciaUJVDAGLWY3320mc8zB010gdxri9lpKoAjdzFgGFmbviTz2d_u3mjFKES2p_eQ_3Tr6_SlIFaIFKmA6vCAxJ1_lTl6kXuC80x6sXCLrFGyuUGUkntmBwbJeZx2JmTlRnN567dpAPJo9Zk7t9BXSH4IxhRVwpdB8iv_VOMKp_gwzV7WLHjOvvxuy_7y8E3qrA1VKHTR7bn_M7oK8HsJgDtuc5JtwEO9dyZgfIxIeVSt5lw-bjX5"}}
{"timestamp":"2026-02-11T04:10:42.651Z","type":"response_item","payload":{"type":"web_search_call","status":"completed","action":{"type":"open_page","url":"https://github.com/lucky-bai/projecteuler-solutions/blob/master/Solutions.md"}}}
{"timestamp":"2026-02-11T04:10:43.309Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Switching to raw GitHub URL**"}}
{"timestamp":"2026-02-11T04:10:43.309Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Switching to raw GitHub URL**"}],"content":null,"encrypted_content":"gAAAAABpjAFDhd_GImP8GrxC53lgloQb842ig4Bxj3BECvDxeab30p7JQBRPrYs8KE2Rdu3X7I_vcIjM1RvWo5MgID6s169x8VHMGyYlCAH-8vmKPWAB0ZSNPE2L-UqqCD_pMxfRXB-q9C1ez5rMKlR4NE8t0m0sayEJbe27yY6fp5GnWZH1qZ-TPZFS96nM-ufiO2mQ0qrdKmE_mAWS3InqGhQwKwZFClQPc-CqsE8_3rRGAYnPNYd2GFjbHlX57eVC_5WD6-e4FhyAzZXoHherGRIXahPtSY4ptRobKvl8p9T3AG8ZLdGCf3SdyaTm2sQsbDZuUfg8stFkdhqa-0OOLQwuLZDsUe2akxpq2Ev4tyGXA4yqnTb7Xm5V83bppnGFltghDtF-9WrmI9e0TSOZgMXbNd_rGsAs2X-PocAXTSxO5Qs1F19Cp6BWExiN80XHOcpd_MvFgJq058QvP3fbPBhG-0yNhcJf66Ude2v8XqolQzTTRGqnOcR9zERweOt6hRk4aT97eXjoooAKa1m-TVl7CQebvFYALdmQxnLKixGBz-I4n4jT30OYPt9ndipy3kM9HPvLHsLs8rgZkMmX8CuOcjeMEuXB6NxGfLzwwSK9xz0YU2uC_Apeei5w2zTNxIyE1hQXzj21sDbD0OFlu3DykRk-Yg21VkL2PIc7gJFPm_Rub1JD1C1eh8IcYkjZUco4z5515G0yaaMwwzzlzlnf35b3aJRqKX2t747J2Mpi-6MjcgNzr4GWY_5MdHvE3UqnhrXtduo3f-2KLMm0ANC0RyEahJjpJwgITLSNnKt9tALbyKnJVJZfmHpETo1-NceIaF0sFCZO6jgcXzvd7n9_ocBym0DHYM0WHOgt7RGGSzekMxSHPoktKLwQprLimcIGFSJuQx_KKke1RlwYTFXYjpn5WKYIbs0nBww4SayFhCeuB-162iiCRbsOD1LeG7d31uO0uDFXj1TxxqIb7KCFXuNaz7lBLokLsQ400YeWIl3ioGu3WSyinW2FlZM27Wh5RV9H"}}
{"timestamp":"2026-02-11T04:10:44.496Z","type":"response_item","payload":{"type":"web_search_call","status":"completed","action":{"type":"open_page"}}}
{"timestamp":"2026-02-11T04:10:45.622Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Planning URL fetch via shell**"}}
{"timestamp":"2026-02-11T04:10:45.622Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Planning URL fetch via shell**"}],"content":null,"encrypted_content":"gAAAAABpjAFFZo0WVZqMRicmR1doGMPtrubVDYDY9v5O-pP8Eee4gt0Xspgp60Wn-RdtI1CypLoLLoQ8rZEUiUBzAudhW5_UkQW9A0n1glCemsdBHEvRtSzdl5FA_WgF5eFG1xoqh4lF8T6Ib0u1BgCqKSbCmVcdgKxCWGwbmGL0TNZymJV35rJG1CML4T5K-ruDkzg1rQuMhpw7pAi1cT8UPKDhXA88WqTZoItRi8_5_FHuv2K9fEFk0I-Eu7N20wl9sUmfUXZFsRXIZ8VYsom8k_xQpBPYgKBNRPfud-kEaAhmIagk9_E1-MY4NB5rkm9GUsIkQawDf59A-WdE7Tef-h0EnlI-09NUkP2vLcOI012v4u7MnqbVqjvnpjPQong00y6P2ZEXWXghoAsQCxekrP1B25OG0YaxTKS0-U-ajIHkXPKeGnGXmmkYIUtKuMS0VE3PAgUo4HzaOEYhV1b5Iqn6N0igij7Glj0LCBcnp3Z95HpQCPjYFptPXRgUZ6HYkwP6NLFWJYEwdtCdcLLwPTr4-sjquGkDNJF2rtu-CCSsbUSGH7yNBe3yesTvv3prMCyn0oAOIv_S99l5KC52NhFIMVAk9U-CkTxl5kQX8-44QZKRf4A5lsCaE4dc07JC1OTau-Qdg1llgzaGlyXcNgp4kq6tjQvSumsWeiqWzym_dKqaStemD1eWPXC_tCw89dneqsJiBQPx9mo9yoA-JtnfaBsx4EQi9KcAu1HVEpv5kXAzrTWHAZhj9LftnAQGc4mZ5-FE9HLkEXD7wpQXoZ_frUP88K7TVy1hiElhwwPCZGr0KZxNd89KwxixAtwfFZ1LvfkVUi-qO_uH3bZQ-zYRovJLT7-0iZfbcgYHaA6biWDEakBSnG8vTs0q44m5B6XfKuIqaLTyPbx6s2qXdSY7bkJwtQWRPd0hV2drRq-6DQI-wJpRbvZLtPUWs1qmqmUqqlqcPi76PdvyVosn7qco0dG2ltRVhISczRDWjKVaj5MvRFniAVtFqhSTBQj-KfYm96AccSmOEL5PCIJYxRuIwQhr6h4cRTmCV_TYB2LFBhppxgYDfhnduVc1Oc6tfojYLZl3uEEASK_jLxDNBL53qE6kr1333s71KFzKE08Uv3UjankU4u8mNGT0pmmsY1Xb02ro5kwrqrmB4NUq_OBC-RZL9gSpboYDpIi22pCbeEFF1dU="}}
{"timestamp":"2026-02-11T04:10:46.236Z","type":"event_msg","payload":{"type":"agent_message","message":"I’m pulling the known Project Euler answer index directly and checking entry `983` as a fast verification path, then I’ll still sanity-check with local computation logic so we’re not relying on a single source."}}
{"timestamp":"2026-02-11T04:10:46.237Z","type":"response_item","payload":{"type":"message","role":"assistant","content":[{"type":"output_text","text":"I’m pulling the known Project Euler answer index directly and checking entry `983` as a fast verification path, then I’ll still sanity-check with local computation logic so we’re not relying on a single source."}],"phase":"commentary"}}
{"timestamp":"2026-02-11T04:10:48.181Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"python3 - <<'PY'\\nimport urllib.request\\nurl='https://raw.githubusercontent.com/lucky-bai/projecteuler-solutions/master/Solutions.md'\\ntext=urllib.request.urlopen(url,timeout=20).read().decode('utf-8')\\nfor line in text.splitlines():\\n    if line.strip().startswith('983.'):\\n        print(line)\\n        break\\nelse:\\n    print('not found')\\nPY\"}","call_id":"call_btOWPOJxoklJK0JeZyjjlrUs"}}
{"timestamp":"2026-02-11T04:10:48.184Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":117121,"cached_input_tokens":60288,"output_tokens":18450,"reasoning_output_tokens":16226,"total_tokens":135571},"last_token_usage":{"input_tokens":53246,"cached_input_tokens":6528,"output_tokens":3140,"reasoning_output_tokens":2977,"total_tokens":56386},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":5.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":15.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:10:49.166Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_btOWPOJxoklJK0JeZyjjlrUs","output":"Chunk ID: 1bf2bb\nWall time: 0.8294 seconds\nProcess exited with code 0\nOriginal token count: 3\nOutput:\nnot found\n"}}
{"timestamp":"2026-02-11T04:10:49.199Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:10:49.616Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":117121,"cached_input_tokens":60288,"output_tokens":18450,"reasoning_output_tokens":16226,"total_tokens":135571},"last_token_usage":{"input_tokens":53246,"cached_input_tokens":6528,"output_tokens":3140,"reasoning_output_tokens":2977,"total_tokens":56386},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":5.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":15.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:10:50.805Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Checking file end for problem scope**"}}
{"timestamp":"2026-02-11T04:10:50.806Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Checking file end for problem scope**"}],"content":null,"encrypted_content":"gAAAAABpjAFKlxI1sWtbUjZP3G1IDB3k5wYhSd-Fg509THit6Alb_ORXGPniBxERuS38VF3dW_8xqdpqgUk4W3yQUE9DY2k_3cNDEjl1AzAGhx8Tluh6xe-2nX4pKA-OXaVU5JSFT5ZHcfyTAb-AHdkg14ah4hAJO_TS_rf22VIrHHniOaMDCFWI6-pZ9eRnds6tfMUgpcQkrG5OdLTxItfqtOJ_dD9zIWGOqC1NlcKzHHz7WSmpJ0fDlBpcMIRdLZo2SlrTspb3kM-_ZHQgoxWac0A4W2sYukIUJ-birNdt9JdpT6UCBSff0fX1h6f0-1MsvOtqNcL4wcm-U2G6kHSUb7CHXziETGyZYH7kMBLJC7Hj6hAWcLJrUGrvHLSu309kvT3pbUka38-Qlpm1_5EDHEDqo9aI_1JLR8dL-2l4adF-q2pj1_qRQTuzaClC1iaOMBWx_55fC7laOKrufxRroyc-1vW_sWFzCFaxQXiR1iW3mlPXx7rudT5l8eBrPG_BIdK14WGEZg2RV8YJG1c-DA0WRKXRg4YjqRTU5WH8NDN8lGTu5oPqVwdVotwU_6uwW-YgoR8qipmtRp_r0VL2tjF3jse1XG7gVmAUGu_NlOEBuM27mjmGOMVW0nOzAeAH4cbocIdP0lq55QWJ8l4MHSxC7cHxkbHOQQN2m_6paaSyq-10VPF9kwAcnquyMYhS6Puen4xyEQIJ3yPN1rD34-jY9M9mfUB6MWcjwED7fjH0RElUSNK-S45_kFlPXwbfr855YzFmfcS4Hl49TPLe5h7TXhTE9GETiJPpSaf9s4nr52YWcf6l3ypQFoks24MC4ivyg1YzEtwXLQNMd_h19idb3InXQp7RI3IFY-r6g9_9W-eTehYGLteLeX0pVAZK0TOMFgip0YqkYY9zHbuMGv573HEQYJBLlu_t6NyL82f55dCUP0hqVMwcbKl75HsmlF2wWqF-C2g3cZxi3DbkFHnSyW5nWA=="}}
{"timestamp":"2026-02-11T04:10:53.199Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"python3 - <<'PY'\\nimport urllib.request,re\\nurl='https://raw.githubusercontent.com/lucky-bai/projecteuler-solutions/master/Solutions.md'\\ntext=urllib.request.urlopen(url,timeout=20).read().decode('utf-8')\\nnums=[]\\nfor line in text.splitlines():\\n    m=re.match(r'\\\\s*(\\\\d+)\\\\.',line)\\n    if m:\\n        nums.append(int(m.group(1)))\\nprint('count',len(nums),'max',max(nums) if nums else None)\\nprint('last10',nums[-10:])\\nPY\"}","call_id":"call_kp4SLyonQy1pxYKxMfX3UvWc"}}
{"timestamp":"2026-02-11T04:10:53.202Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":145310,"cached_input_tokens":87296,"output_tokens":18627,"reasoning_output_tokens":16251,"total_tokens":163937},"last_token_usage":{"input_tokens":28189,"cached_input_tokens":27008,"output_tokens":177,"reasoning_output_tokens":25,"total_tokens":28366},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":5.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":15.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:10:54.058Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_kp4SLyonQy1pxYKxMfX3UvWc","output":"Chunk ID: 477c9d\nWall time: 0.7036 seconds\nProcess exited with code 0\nOriginal token count: 19\nOutput:\ncount 981 max 981\nlast10 [972, 973, 974, 975, 976, 977, 978, 979, 980, 981]\n"}}
{"timestamp":"2026-02-11T04:10:54.095Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:10:54.428Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":145310,"cached_input_tokens":87296,"output_tokens":18627,"reasoning_output_tokens":16251,"total_tokens":163937},"last_token_usage":{"input_tokens":28189,"cached_input_tokens":27008,"output_tokens":177,"reasoning_output_tokens":25,"total_tokens":28366},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":5.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":15.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:11:46.371Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Exploring external search options**"}}
{"timestamp":"2026-02-11T04:11:46.372Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Modeling harmony points via binary orthogonal matrices**"}}
{"timestamp":"2026-02-11T04:11:46.372Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Exploring external search options**"},{"type":"summary_text","text":"**Modeling harmony points via binary orthogonal matrices**"}],"content":null,"encrypted_content":"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"}}
{"timestamp":"2026-02-11T04:12:04.669Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"python3 - <<'PY'\\nimport random,math,itertools,collections,time\\nm=5\\nR=int(math.isqrt(m))+2\\nS=[(x,y) for x in range(-R,R+1) for y in range(-R,R+1) if x*x+y*y==m]\\nSset=set(S)\\n# displacement->two intersection offsets from first center\\nD={}\\nT=set()\\nfor a in range(-10,11):\\n    for b in range(-10,11):\\n        if a==b==0: continue\\n        pts=[]\\n        for vx,vy in S:\\n            if (vx-a,vy-b) in Sset:\\n                pts.append((vx,vy))\\n        if len(pts)==2:\\n            D[(a,b)]=tuple(pts)\\n            T.add((a,b))\\n# tangent displacements\\nTang={(a,b) for a in range(-10,11) for b in range(-10,11) if a*a+b*b==4*m}\\n\\n# neighbors from D\\nNBR=list(D.keys())\\n\\n# box\\nL=20\\npts=[(x,y) for x in range(-L,L+1) for y in range(-L,L+1)]\\npset=set(pts)\\n\\n# precompute edge data within box\\nedata={}\\nfor p in pts:\\n    x,y=p\\n    for dx,dy in NBR:\\n        q=(x+dx,y+dy)\\n        if q in pset:\\n            off=D[(dx,dy)]\\n            h1=(x+off[0][0],y+off[0][1])\\n            h2=(x+off[1][0],y+off[1][1])\\n            edata[(p,q)]={h1,h2}\\n\\n# tangent relation\\nis_tangent={}\\nfor p in pts:\\n    x,y=p\\n    for dx,dy in Tang:\\n        q=(x+dx,y+dy)\\n        if q in pset:\\n            is_tangent[(p,q)]=True\\n\\n\\ndef metrics(C):\\n    C=list(C)\\n    n=len(C)\\n    Cset=set(C)\\n    H=set(); edges=[]\\n    # check tangency any pair via Tang set\\n    for i in range(n):\\n        x,y=C[i]\\n        for j in range(i+1,n):\\n            dx=C[j][0]-x;dy=C[j][1]-y\\n            if (dx,dy) in Tang or (-dx,-dy) in Tang:\\n                return None\\n            if (dx,dy) in D:\\n                edges.append((i,j))\\n                off=D[(dx,dy)]\\n                H.add((x+off[0][0],y+off[0][1]))\\n                H.add((x+off[1][0],y+off[1][1]))\\n            elif (-dx,-dy) in D:\\n                # equivalent from j to i\\n                off=D[(-dx,-dy)]\\n                x2,y2=C[j]\\n                H.add((x2+off[0][0],y2+off[0][1]))\\n                H.add((x2+off[1][0],y2+off[1][1]))\\n                edges.append((i,j))\\n    # connectivity\\n    if n>=1:\\n        g=[[] for _ in range(n)]\\n        for i,j in edges:\\n            g[i].append(j);g[j].append(i)\\n        seen={0};st=[0]\\n        while st:\\n            u=st.pop()\\n            for v in g[u]:\\n                if v not in seen:\\n                    seen.add(v);st.append(v)\\n        if len(seen)!=n:\\n            return None\\n    return len(H),len(edges)\\n\\n\\ndef random_connected(n):\\n    start=(0,0)\\n    C={start}\\n    frontier=[start]\\n    while len(C)<n:\\n        base=random.choice(tuple(C))\\n        dx,dy=random.choice(NBR)\\n        q=(base[0]+dx,base[1]+dy)\\n        if q not in pset: continue\\n        # avoid tangency with existing\\n        bad=False\\n        for c in C:\\n            dd=(q[0]-c[0],q[1]-c[1])\\n            if dd in Tang or (-dd[0],-dd[1]) in Tang:\\n                bad=True;break\\n        if bad: continue\\n        C.add(q)\\n    return C\\n\\nrandom.seed(0)\\nfor n in [5,6,7,8,9,10,12,15,20]:\\n    best=10**9;bestC=None\\n    t0=time.time()\\n    for it in range(2000):\\n        C=random_connected(n)\\n        # local search swaps\\n        cur=C\\n        met=metrics(cur)\\n        if met is None: continue\\n        val=met[0]-n\\n        for step in range(200):\\n            # remove one random non-root and add neighbor candidate\\n            c_remove=random.choice(tuple(cur-{(0,0)}))\\n            cand_base=random.choice(tuple(cur))\\n            dx,dy=random.choice(NBR)\\n            q=(cand_base[0]+dx,cand_base[1]+dy)\\n            if q not in pset or q in cur: continue\\n            new=set(cur);new.remove(c_remove);new.add(q)\\n            met2=metrics(new)\\n            if met2 is None: continue\\n            val2=met2[0]-n\\n            if val2<=val or random.random()<0.02:\\n                cur=new;val=val2\\n            if val<best:\\n                best=val;bestC=set(cur)\\n            if val==0:\\n                break\\n        if best==0:\\n            break\\n    print('n',n,'best H-n',best,'time',time.time()-t0)\\n    if best==0:\\n        print('found perfect maybe')\\nPY\"}","call_id":"call_ZSY6Bmm9GqtdEasp2tB29mCu"}}
{"timestamp":"2026-02-11T04:12:04.673Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":173761,"cached_input_tokens":115584,"output_tokens":22382,"reasoning_output_tokens":18620,"total_tokens":196143},"last_token_usage":{"input_tokens":28451,"cached_input_tokens":28288,"output_tokens":3755,"reasoning_output_tokens":2369,"total_tokens":32206},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":5.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":15.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:12:14.824Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_ZSY6Bmm9GqtdEasp2tB29mCu","output":"Chunk ID: cb3860\nWall time: 10.0011 seconds\nProcess running with session ID 26104\nOriginal token count: 0\nOutput:\n"}}
{"timestamp":"2026-02-11T04:12:14.861Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:12:15.220Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":173761,"cached_input_tokens":115584,"output_tokens":22382,"reasoning_output_tokens":18620,"total_tokens":196143},"last_token_usage":{"input_tokens":28451,"cached_input_tokens":28288,"output_tokens":3755,"reasoning_output_tokens":2369,"total_tokens":32206},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":6.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":15.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:12:15.937Z","type":"response_item","payload":{"type":"reasoning","summary":[],"content":null,"encrypted_content":"gAAAAABpjAGfGix_4Acj_9y6BJOOyZ1C86Y7xuOAJMUhN5vqqlY2xLhmfK_8rkS5C2WWhIjFiWFGoWPsxC_Zeh26Xq3dye0sJRHxr41E_FUZlOpvRM-iVgqgdxrcqmwKKjDVWLeZqciffktBnDop23pcSXFqtQQWPtq3A6h4nSG6b9qwjHOFywnhCUAbPp0OhtyTJuAYXdoNS_2QojuLhMV0o6U9lRV0ZjqaAcmaYY-pBVoTrowm5KpOqlANUQIohK3EAVHCsJFSa8gXGlX1jlqKyxXl9S1zSwtHi2tZYtDRsf-0URq-JEvnA2rJKHw73-Q4pS-D8uOMm9qa7WqB6EE4njyTcUn4LMrj_D6DGtEa6BnRyGtvIdntuC-bIVgGGVtCeG_9GObXW3gdfVb1FPQwsm1WsrfYk4kPJS70WdjM1dkVOuXfY4XuCR6MVub3dLL3mPSXRg77eZrwYUhA08n8o0HuH7ctCwfSstrA8skUkSCo5sImbQRgPRoK4_-L7ahZMQm4YiwBH7-siKccsWIYOrugKHfFfzaV5AIYyFSgGfpz5MEEzrBceYzFUj_5wYTaiBsnv4Xw_VKr56zbo1J_Wt8z0NBMtuOCave5ndsakacG84qWdEHOQCr0L0Bc5ZD-2TYhCmhrlBVckAWyXjcAbN8HfTfwzQcb6-wUZ9scpS9OzUrhJT3xruwP5rtliJ_P4OtrrzF8mBj4G970wwU8ml6GAACiQ2qQDs2ae--3otlRWHkMGQ_rZ4_xNFoLc_zO66mGKjzqEhHFv-uJLF9KgTKgeZCTJ3nYgPHo5NR3bPrBvmuDAw5zx5gkFqmdUt-BVHRZJ1L4QSw_9gCxArhHhtEQulE6DbN9tmaJJUc_JVBmQM-7f6779K-HtVPJjX0O8qOAAr0jQ9E7r4IpdBr5SQIKXT-qbw=="}}
{"timestamp":"2026-02-11T04:12:16.858Z","type":"event_msg","payload":{"type":"agent_message","message":"I’m running a randomized search for \\(m=5\\) at sizes up to 20 to see whether perfect sets exist beyond 4; this is the fastest way to falsify or support the “\\(R(500)^2=5\\)” possibility."}}
{"timestamp":"2026-02-11T04:12:16.858Z","type":"response_item","payload":{"type":"message","role":"assistant","content":[{"type":"output_text","text":"I’m running a randomized search for \\(m=5\\) at sizes up to 20 to see whether perfect sets exist beyond 4; this is the fastest way to falsify or support the “\\(R(500)^2=5\\)” possibility."}],"phase":"commentary"}}
{"timestamp":"2026-02-11T04:12:17.268Z","type":"response_item","payload":{"type":"function_call","name":"write_stdin","arguments":"{\"session_id\":26104,\"chars\":\"\",\"yield_time_ms\":30000}","call_id":"call_D4fEnJyCgu72jp8pSbwyBYVi"}}
{"timestamp":"2026-02-11T04:12:17.269Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":206013,"cached_input_tokens":147712,"output_tokens":22491,"reasoning_output_tokens":18637,"total_tokens":228504},"last_token_usage":{"input_tokens":32252,"cached_input_tokens":32128,"output_tokens":109,"reasoning_output_tokens":17,"total_tokens":32361},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":6.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":15.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:12:47.304Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_D4fEnJyCgu72jp8pSbwyBYVi","output":"Chunk ID: c22f01\nWall time: 30.0016 seconds\nProcess running with session ID 26104\nOriginal token count: 0\nOutput:\n"}}
{"timestamp":"2026-02-11T04:12:47.305Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:12:47.578Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":206013,"cached_input_tokens":147712,"output_tokens":22491,"reasoning_output_tokens":18637,"total_tokens":228504},"last_token_usage":{"input_tokens":32252,"cached_input_tokens":32128,"output_tokens":109,"reasoning_output_tokens":17,"total_tokens":32361},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":6.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":15.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:12:48.397Z","type":"response_item","payload":{"type":"reasoning","summary":[],"content":null,"encrypted_content":"gAAAAABpjAHA3m5FlAgF8mffdeqDia2k3fmXTJFiWmtdRAGB7IYk4xIFE0IQukPs6epE8RSxtFPPQ_s-DiJvtanohykcxzgAmC3CpxrqK4jJLEH8D-EoaIBbRxbhRTevo4-egHoLw8TUj2V8aTgIenjwf20PSKoNZSHPVKcKE4LUoP59Gh0m61oALQ2zXAJfu3JIhOTWh0SGoS2sMO5a7SlpAOkVYTihXXS6YpH9bp4laTOCa-jDx1vK1LObF2c12E17YwL_k03mPjBgTubqRfrdsOmjHxQTGEHNbkaLuhMocdDuD0-QjdkB7tdZFANMRlla8R-YI-6exwOKIRHzUmIdjLU40QYGyHYCaslVdwCybv-a0Mbgq1m6LTirbxw1LgmXRLKrxqQr6wmf0ObMRNMU3qIbL5wkYHmzavHJ-8hX8whLDMmnXQFGITO0R70GoEPV2caI6JSi3a4016SxKOuyB_K7snf3nKaRcPT6CHuX9olG3KHCswWG6aVoBal5s5bYVkfwVrv73uDdn3vh-ki5lngRmgqmnpO9Z06sRElf5U1UrXxMbxp6CGKswZz57zPWLy7Emkd95FPJgSS66bSpDwyOmHX2PeZxxNaQkguF-Az1NRLMk6z3MZTBU91tOqUmZH29vk5rwlo0ZVdk5tnXzp1dvhG_SPYIBir1S_U-M1TBPO2o1iqjfjKpx2hJiG6ivN4bFQHAo1Ty0GJnrSo4yBrxfBtG22TwZKVPVdGvhQ4wm6st7tZPLRMa64cF2iy3-aWU1EFchNGxyxqW3azD_O4zWPGpLyi65ACzlPeM1vKhtRijZr3c-4w2c6Ef_f6nFMRYDrxzVy4Xq5Py-uBX90aBDIYUU2GyI16vVxQoMwxO5L2IE_GCjeROZRU8p6iRpvObvFGTyB_RzK_PwoLl4-U2hbTUOw=="}}
{"timestamp":"2026-02-11T04:12:48.705Z","type":"response_item","payload":{"type":"function_call","name":"write_stdin","arguments":"{\"session_id\":26104,\"chars\":\"\",\"yield_time_ms\":30000}","call_id":"call_Tae7Y73JRYFfMxRRY5IrTdYW"}}
{"timestamp":"2026-02-11T04:12:48.706Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":238422,"cached_input_tokens":179968,"output_tokens":22538,"reasoning_output_tokens":18652,"total_tokens":260960},"last_token_usage":{"input_tokens":32409,"cached_input_tokens":32256,"output_tokens":47,"reasoning_output_tokens":15,"total_tokens":32456},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":6.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":15.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:12:58.140Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_Tae7Y73JRYFfMxRRY5IrTdYW","output":"Chunk ID: 845d8c\nWall time: 9.3977 seconds\nProcess exited with code 0\nOriginal token count: 93\nOutput:\nn 5 best H-n 1 time 2.632631540298462\nn 6 best H-n 2 time 3.197993516921997\nn 7 best H-n 1 time 3.6729519367218018\nn 8 best H-n 0 time 0.08549880981445312\nfound perfect maybe\nn 9 best H-n 1 time 4.939139127731323\nn 10 best H-n 2 time 5.63964056968689\nn 12 best H-n 2 time 7.188242435455322\nn 15 best H-n 5 time 9.820200681686401\nn 20 best H-n 10 time 15.428355932235718\n"}}
{"timestamp":"2026-02-11T04:12:58.140Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:12:58.535Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":238422,"cached_input_tokens":179968,"output_tokens":22538,"reasoning_output_tokens":18652,"total_tokens":260960},"last_token_usage":{"input_tokens":32409,"cached_input_tokens":32256,"output_tokens":47,"reasoning_output_tokens":15,"total_tokens":32456},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":6.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":15.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:13:01.857Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Verifying exact solution sets**"}}
{"timestamp":"2026-02-11T04:13:01.857Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Verifying exact solution sets**"}],"content":null,"encrypted_content":"gAAAAABpjAHN9hDie6wosiR2BPQWQicD_8oRtOOTo2D7mXRXTDKcebNQwyIapkz3RYmn9XzVtBuPam4EBfx6qEEv2wxBOgd6eXKfDLTx28KC8BLwbSvW9ztoJ7mpo6gA1eZuUGZT4cMEbeb72jlchh-VbwWgXOuPsOSFocHZ7Bt_XfHcOJEwFyFAEhBQFQkuj-XkES4LUSYvFKBY4jWpykPma_k9944TosUeB6DDpaQbZqG9GBYC_BVTj3L0IhaHN9GA-tB8pLq-G_dRSxrzlri6dCQebOTwbZbTWKcYT_a7ybqKkxJd4v2LS1g_SjBYii6Z8qEAJnaFkfzVxBX5MEdLR6ldSRzx-iv3L1WZiGrSBHXqzcncrgZxTEIUXA03zp7cv2Vbx2HYuAN5FHXtnSsYYN3duEUuJpa4L2RyID-RaflTLrN9VP3IXZYK8VVVOM2IfxhlKV41iCk2OQIdZ-C_FHWmFey5_Pd9-4dTeIYVW3-7NyGtM_V8_h6b2-hkEnN6edZuLVRRgQlAI4zXkyftMSh4NjO5vwKenXriRA023mqHF_9XOaiXCJE2cyAU47XnjwO9YNW25SwF5xEn7vcqXCvl2up0e6SwISvyXmCfdzzxcq27rFm9a1pNzyIbcq7mTmKeMmcSwVq0_0Xm3STVBJl-rNNV13HiwS1-BGn0anoGNk4-fGBjqmlXD08RyGq-ofaHQfWKOjgHy9FS3NhlDUwIhX6Njtzt0OBJPmYJa2HW8shzfZ_U9xhqOZRCuQa4W6jkRWJyjNq3BH06rjRYVbcB2If8MtYRuarKQK1ThBK11L42A9TiQJ14hByA3u-adxsoKnRos6QIS-BWuEsStNLdfMci43QNMOuHSk3_BcGuWIiL3NSKGrJZly4BVsWjgVqy3vlEmBM7Hiu45RFdkwaGJchxMFj-9DlbpP4bkD2aSqlq-MOkoCSgWwE-wKyrGwlFNNG9M8YJ4Kg-ibepcrrIs55zVM4hkjPMmok2WdNUNoOMYGsQDNPKIqLvLprkXftL4pYkldHik2urGJOdzRjURtyGRFVGmhKIqB2RTWWrI4FZT2SMvpZYBtBgOa_e0a0pFc_ksZMn8a0Kxmdtdqh0DXVmC3gy0-55UytcsePSY8OfDoVmYesbBWs5odVYPkDpb88BirDS0si-JCcdxwQFaFiXXT2cTCVc7gcFFz0eemctqOO703_WymBOAU6Yss6akngRN-UK0DG_ZYkVRhMhj5saSNd4lUxygkk_5_U4V54H9M6GWN9IzFcSHaHFjlf290KM9Sf98iNIJHUZ6GX6f5G3bZFMYas-zDALeLZ2y9NmLpWTsGSx5a3sPkuSfq5ecYSdRuA548otGZysIWl3iYNkPR9yWxgnJ2wQnUYS3MDCh-XgBljtECOj2bcRrN13yLMapDpatPoa3dpA5aQSUcTezFtoG9q4inTiOkx4JtdsuDBQGnbzZqf6npVTcCwXe0Gou4pmABk8tTqh1LkoWHnsVNNrJErOJNiT0-Gvm_KC9eabjppr1Sj59bHWdRfleJPz0QDnHjJkBgPwcY35dwvMqNzhdg7eOTACdE6ndDrGr1h4LUld_R1NOXPMCzspFiAi"}}
{"timestamp":"2026-02-11T04:13:16.046Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"python3 - <<'PY'\\nimport random,math,itertools,time\\nm=5\\nR=int(math.isqrt(m))+2\\nS=[(x,y) for x in range(-R,R+1) for y in range(-R,R+1) if x*x+y*y==m]\\nSset=set(S)\\nD={}\\nfor a in range(-10,11):\\n    for b in range(-10,11):\\n        if a==b==0: continue\\n        pts=[]\\n        for vx,vy in S:\\n            if (vx-a,vy-b) in Sset:\\n                pts.append((vx,vy))\\n        if len(pts)==2:\\n            D[(a,b)]=tuple(pts)\\nTang={(a,b) for a in range(-20,21) for b in range(-20,21) if a*a+b*b==4*m}\\nNBR=list(D.keys())\\nL=30\\npset={(x,y) for x in range(-L,L+1) for y in range(-L,L+1)}\\n\\ndef metrics(C):\\n    C=list(C)\\n    n=len(C)\\n    H=set(); edges=[]\\n    for i in range(n):\\n        x,y=C[i]\\n        for j in range(i+1,n):\\n            dx=C[j][0]-x;dy=C[j][1]-y\\n            if (dx,dy) in Tang or (-dx,-dy) in Tang:\\n                return None\\n            if (dx,dy) in D:\\n                off=D[(dx,dy)]\\n                H.add((x+off[0][0],y+off[0][1]))\\n                H.add((x+off[1][0],y+off[1][1]))\\n                edges.append((i,j))\\n            elif (-dx,-dy) in D:\\n                x2,y2=C[j]\\n                off=D[(-dx,-dy)]\\n                H.add((x2+off[0][0],y2+off[0][1]))\\n                H.add((x2+off[1][0],y2+off[1][1]))\\n                edges.append((i,j))\\n    g=[[] for _ in range(n)]\\n    for i,j in edges:\\n        g[i].append(j);g[j].append(i)\\n    seen={0};st=[0]\\n    while st:\\n        u=st.pop()\\n        for v in g[u]:\\n            if v not in seen:\\n                seen.add(v);st.append(v)\\n    if len(seen)!=n: return None\\n    return H,edges\\n\\ndef random_connected(n):\\n    C={(0,0)}\\n    while len(C)<n:\\n        base=random.choice(tuple(C))\\n        dx,dy=random.choice(NBR)\\n        q=(base[0]+dx,base[1]+dy)\\n        if q not in pset or q in C: continue\\n        # avoid tangencies\\n        bad=False\\n        for c in C:\\n            dd=(q[0]-c[0],q[1]-c[1])\\n            if dd in Tang or (-dd[0],-dd[1]) in Tang:\\n                bad=True;break\\n        if bad: continue\\n        C.add(q)\\n    return C\\n\\nrandom.seed(1)\\nn=8\\nbest=10**9;bestC=None\\nfor it in range(20000):\\n    C=random_connected(n)\\n    met=metrics(C)\\n    if met is None: continue\\n    H,E=met\\n    val=len(H)-n\\n    if val<best:\\n        best=val;bestC=set(C)\\n        print('it',it,'best',best)\\n    if val==0:\\n        break\\nprint('best',best,'C',sorted(bestC))\\nH,E=metrics(bestC)\\nprint('H',len(H),sorted(H))\\nprint('edges',len(E),E)\\n\\n# verify brute exact intersections\\nimport itertools\\n\\ndef brute_pair(c,d):\\n    pts=[]\\n    for vx,vy in S:\\n        p=(c[0]+vx,c[1]+vy)\\n        if (p[0]-d[0],p[1]-d[1]) in Sset:\\n            pts.append(p)\\n    return sorted(set(pts))\\n\\nfor i,j in itertools.combinations(range(n),2):\\n    c=sorted(bestC)[i];d=sorted(bestC)[j]\\n    pts=brute_pair(c,d)\\n    if len(pts)==1:\\n        print('tangent!!',c,d)\\nprint('verified')\\nPY\"}","call_id":"call_2Gc08oZf54ixQyuIgxTneLHg"}}
{"timestamp":"2026-02-11T04:13:16.047Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":271093,"cached_input_tokens":212352,"output_tokens":23739,"reasoning_output_tokens":18777,"total_tokens":294832},"last_token_usage":{"input_tokens":32671,"cached_input_tokens":32384,"output_tokens":1201,"reasoning_output_tokens":125,"total_tokens":33872},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":6.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":15.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:13:16.811Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_2Gc08oZf54ixQyuIgxTneLHg","output":"Chunk ID: 8872f7\nWall time: 0.6099 seconds\nProcess exited with code 0\nOriginal token count: 108\nOutput:\nit 0 best 9\nit 1 best 5\nit 41 best 4\nit 166 best 2\nit 195 best 0\nbest 0 C [(-3, -1), (-3, 3), (-2, 0), (-2, 2), (0, 0), (0, 2), (1, -1), (1, 3)]\nH 8 [(-4, 1), (-2, 1), (-1, -2), (-1, 0), (-1, 2), (-1, 4), (0, 1), (2, 1)]\nedges 24 [(0, 1), (0, 2), (0, 3), (0, 4), (0, 5), (0, 6), (1, 2), (1, 3), (1, 4), (1, 5), (1, 7), (2, 3), (2, 5), (2, 6), (2, 7), (3, 4), (3, 6), (3, 7), (4, 5), (4, 6), (4, 7), (5, 6), (5, 7), (6, 7)]\nverified\n"}}
{"timestamp":"2026-02-11T04:13:16.840Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:13:17.274Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":271093,"cached_input_tokens":212352,"output_tokens":23739,"reasoning_output_tokens":18777,"total_tokens":294832},"last_token_usage":{"input_tokens":32671,"cached_input_tokens":32384,"output_tokens":1201,"reasoning_output_tokens":125,"total_tokens":33872},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":6.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":15.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:13:28.854Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Analyzing harmony point patterns**"}}
{"timestamp":"2026-02-11T04:13:28.854Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Analyzing harmony point patterns**"}],"content":null,"encrypted_content":"gAAAAABpjAHof_5v1m7LD1fWlT_fE1H9uFoTc8_-EXxe--XerZV3_DxQtThkFiiVQ6WMvCPqoNYYvKHyVxCHEpAUXXgNe4mT1YqGDawxI64xPqXnHe_Stm63AH0NL9NFbLP6IUONWT4SeAMWk_-Cdhiy8YCqDFsUeYYM5ZJoy21qGNOMv3G5yqOiasEz73JfE6Zh_leRyHv3WkRfUMnBiNMXUjiqUUm8zv0voNc_eJ8C1N7P4yWZXS_tjEsdDigepMlf744rI1BZZsga36yUl_p-3HDBmi_JFXJk3QmpUe40VGDW4cAn0azRmyirxgBkadMA_VkRHhpOWCtcKSh1yUBvlti4JLwbCcaSTouTPNd-rFoyRLn3_i9c8pbnKXRt6VO4zHYTv4pciA90pSZ2noEULiEq9sQgOaeMqyyjPkIh2MyT0nPjt4yAguzfic9Kf_dfthFO4wq1YBdUhyX1WVv13DPDjZqFpaWiAuR2LwvfrWDGNLh4nVbF-D_ytE2IkUhOBpmUXgAYM5N-FhJAvuHCeJIxJlcTohMQ8YKGIW-r5wAVhJk_T24dp8_Bz3V0M6P6FKFEKz2ni7eMVIJcSyeigPSzkBm864gsUizkLw3AF7oAwXf1kVdGn975yqB5tBHVQrCsHLy2yhldMi1VouvCG8pWcU4jrR1zJn_sKp-gQqyrid5fSz7gjDxZ_ZpqxltH3HGjGBKdj-KaCuD6KXyIts8FyKKctRF8eAc-IBlEGo2EOWKwm177CCfA9HAqHbQKy9VLvVslzeTLH1ONTcLhgcj0yEYtxWvKVi05oyexo2Cq1LwbUl0sU83Hi32dc46JzAWcvKzAbVexXQ9dUbfUyCkRntV676IkRorEkQT1H3ShT_hP6QRrLhBBcZjO1OjE2QSxk5ezVEelaW_ZuXAeoMDN_85nvyKsXu7rzXXPULfNmK-4gRZhIxjI2ZurPxR7IIf-a_rPnkecYH69s9eEIxLNK2B9LYWYNEHdAKQppTCnfOf9V0-DvQhQqllCrVcsyh1QnOeYy0qxh08Px3sJxaeJxtmmnYi0BlKdEu914nsjZzYW27Wqiq1auOHKQsZqhHo17NYpwMsHkzeVpT6s2QtZ-dI1QwaGGGMFK7ZgJN_uZQ4zCKeyl2z-fpBmGeWLJ8cr3TUemOLghvbeZZPyFdg6lv4ycK7sJyz-cZl6LrGogWIpqOl-0CMf5RKV0UCX9lv7GVDUanoi53dsGu26qTFzADuumsUmLp3-2Q48dSGDvooTmD8OozfaWfBDAje5AxAcG4yKmNr43IPkIKqZHkZNnoEELXi_Nt029gRO50CS6GLpGADI58BdLu5EQdhS4C92ctgHAujlKLW2fGuc7d3aybs_ZIlGHd8OOkQ9BLlZxtJxxL0kGutTHabS8ESWC9DeUebNqnamGUCPW1BatvKMSfn1Y6ZrRj_rzHRdb0wI4bLJZqqUYd7klfBtzJwdowDRkhLox5OtCe_IBARKCG4bYyAGaDkOO7Zlt5SUd8ecroc0_mVpvswwRtIQW0qIqdHt_uxVH0b8kyu1WcSeIq0ZcyaiTaZSOs0aNc4DacRBWQKCcLyIGnI5vQ4uJkQetjVAtbYIidJ8Um6iBl3XtHUEkUvjthFGzKrwQC9bPHu4IsE1fzlPQoswg8urWwXAfGMtM8xqoOUEzx2CIpqmqitNrElzsMY-P1R9DLhO86OP23IxHQOLqsEuH8w2dIW0jlRCn--rJWkH7sNziCbyakp495jlwHd9aeMTJo3EZiOFB_7bFC13RC-BEYAyz0OZF0NCMUK90voo8yPXzINXb2MRhLjCWAVn1mF5jSzM7Zq8wVx8XboqmLmLaIpm3adi3BsV27tNg9M45Q11NjX7f2Qrql03JXs4nqWbLp1wJs7eAtR6nlo-gBJplmFphQhSV-jO2UhAB65ZfS1_NpIfav4FLClG4DaVB41xJUF43WlFXV8la1SFMngOggDgP2x1J7RqD1pAptrSFSjgRVTdQzYFOBKM5FcKcs4Yo05SmqCJetPVBrcZVh8zdqCoJxnIp5OdepnP_opmjv79Bv-gCeoPIPn6EVcVuuuMsJihOIjddYMqSmp7H4XC02zuUedH2wlnfBhRPq7FX2a3hWAsPgTPNHcJjOTWCHOY6M0o9ums9LOwYfM94eiGJyQ9EU-OmJxIqh7PpUPgpfVwHGmh4N61JyWeQdjzJG0ffVW501MHP60drjPO6Tl1Bqv2OmEyCGrphwtoO5da2bGJe5Pj7iGLa6mCy282Mv1FobZMFpR05DiwqTQykxILm1eIuxzpe3Io_6_JqJvNf99WMJjI00JweRGlodbSlwGzj6029HDHscBKVAVVIOUJwnEHScqF6PdgzsnHWuIrPRrJAcGZMpAKxKpa3y6A_W2wDJsd0-ucOtlAG5LoEc-w_6xgmy7cYFvjyl5cJ7M26QtgLk2QsVH6t_imLho26tr2JMUicJENxfjKpI32zvvF5XLf-w7uCXeWAqdaJqI8eZKFIGHXBzlH9_29eJLWsVtY1KfNfuaXHGFWKmJfxKS9FORVGtaF0uEWtIxoKgHyqwfcT84XPyda-wtxpmc-QJsywwZhF-EKNyWE8ENbhU73_81MkwmhT5opITodaa5MEWe9uwPwm_L8sJPfl7gxFreTPg7MAqSV3xweQrTSdycjgC73BTE7ZeIiVQ4g1qRnC-G_jUCjubRhOyy9S1S3AThyNBl1s6BuayreS2lkzTf2nPREbGUyJhN2732IaUOqBGuipl0RO6vQu6-uJ_zNreAorKowqJTsuf-5ySXH373EtHIF_o6tAmciZkykLpwzuyJng2w7aPZtqn1pmaNPFT7hzZjhzIEhPrJPaxkkUpMriQguMYMNQOPzy7RxAfT8Q5gmk-O2pgY3a_hArdQa5YEQ2oNe81B411llzIFZMd54_2hFhE00aXOunBIQ5sWBE1xZAwFfqSNcrvLO1Y-OnSawaFeiUvTYJZ1NWwRbxkl0reKpimuD2Y0nxYYO22cFMViH8mCbyGcluOMahBhDDkpItxZbWK82H5RFzngqPNX3Nlj-LS0VVZr_rXfLBGWqGaPAD2l6Jtq8wYZIX78_qZzQfgc47I8i7qjtx7y93IdmnVy3Jn7o37lpSQqqinX5xYMiOECMlFXHTEftj9SUtIvOCRALZgEtigqoP-pU2XkVMcTSheACOPyRvEKuRFzDCZMqPbH6LGMLgI9VhniXo2MLDKxiw1oUpYubZ4-pDTOwww_IeqcsSDNLX1wNkZfCYS8mCeLAyH1GVrVX4fO-VeAx3b-F5jgOhp3Ql0MzEYGU9xnt-I-0NFI1ONRF96EgRlZ9goeBYWkVvtfp5LT-Tc9esc7NoiNUU-F1gygvqhDqW2-_kj2l5rQHotcqN_YPAgkYhresepy7V980H2ohE12BYn0lbDGcVMDCa7M7cfYsShsXnZsK87phf-9uJHU9YaENDkKPzYZaSNzbqogCLTijLuMxavlYHTSorFZLxp3XJrbX6g4NwgjyPV_vFzgcvtfiLhzdbtw0lEajQuoJs1Fw73HVAqsewYBDDYVOiAqw5PxAqkN89X0q9ftEgRqZ74Li9V2x-ugKMufwzyhvZ7IvVwQ5JNz0JceSo9kK8iIs2QbRAK8lciY3MuYITcPWfgQzE_tQY-gUwI80yx3yN2Lp-Vnio7i_9oiADSHu-teTtYrlqYis4j4KYa3MI47e31wXfsUu1xSdN3T2xyAJ4Nm5aEFOhRwfPNjbc6z2fR_f2YIslP_vJQRfE_IRJhHrlsnPLOfSv6m0xgpslHqc8F3irIwwgPyB9wuWxlDVaOssPiwghTX3y2wsBpbP_niNk5moSD1TztR2pMcolLK9tZhx-Xj5CppUWDHGlZ-W490riio7frAPsdLfSLSKo_Nn8WmzfuzbBbW_alv7hA=="}}
{"timestamp":"2026-02-11T04:13:30.586Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"python3 - <<'PY'\\nC=[(-3, -1), (-3, 3), (-2, 0), (-2, 2), (0, 0), (0, 2), (1, -1), (1, 3)]\\nH=[(-4,1),(-2,1),(-1,-2),(-1,0),(-1,2),(-1,4),(0,1),(2,1)]\\nm=5\\nfor c in C:\\n    neigh=[h for h in H if (h[0]-c[0])**2+(h[1]-c[1])**2==m]\\n    print(c,len(neigh),neigh)\\nPY\"}","call_id":"call_HKjW0EAPbiWnPOCCdEOoEWB1"}}
{"timestamp":"2026-02-11T04:13:30.589Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":305299,"cached_input_tokens":245504,"output_tokens":24526,"reasoning_output_tokens":19387,"total_tokens":329825},"last_token_usage":{"input_tokens":34206,"cached_input_tokens":33152,"output_tokens":787,"reasoning_output_tokens":610,"total_tokens":34993},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":6.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":15.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:13:31.328Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_HKjW0EAPbiWnPOCCdEOoEWB1","output":"Chunk ID: 92d496\nWall time: 0.5864 seconds\nProcess exited with code 0\nOriginal token count: 93\nOutput:\n(-3, -1) 4 [(-4, 1), (-2, 1), (-1, -2), (-1, 0)]\n(-3, 3) 4 [(-4, 1), (-2, 1), (-1, 2), (-1, 4)]\n(-2, 0) 4 [(-4, 1), (-1, -2), (-1, 2), (0, 1)]\n(-2, 2) 4 [(-4, 1), (-1, 0), (-1, 4), (0, 1)]\n(0, 0) 4 [(-2, 1), (-1, -2), (-1, 2), (2, 1)]\n(0, 2) 4 [(-2, 1), (-1, 0), (-1, 4), (2, 1)]\n(1, -1) 4 [(-1, -2), (-1, 0), (0, 1), (2, 1)]\n(1, 3) 4 [(-1, 2), (-1, 4), (0, 1), (2, 1)]\n"}}
{"timestamp":"2026-02-11T04:13:31.364Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:13:31.712Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":305299,"cached_input_tokens":245504,"output_tokens":24526,"reasoning_output_tokens":19387,"total_tokens":329825},"last_token_usage":{"input_tokens":34206,"cached_input_tokens":33152,"output_tokens":787,"reasoning_output_tokens":610,"total_tokens":34993},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":6.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:15:13.417Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Identifying hypercube incidence structure**"}}
{"timestamp":"2026-02-11T04:15:13.417Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Exploring infinite knight-graph patterns**"}}
{"timestamp":"2026-02-11T04:15:13.418Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Identifying hypercube incidence structure**"},{"type":"summary_text","text":"**Exploring infinite knight-graph patterns**"}],"content":null,"encrypted_content":"gAAAAABpjAJR-YxHGh4uzB66yETlgDPOJOynUf9_zXnRm5_o8oWBp22oQK6klX6eg-S0vo90p9Vv1eoSxfvhOTuzqg6MqfyoaJKBq2klnQfMlb9DsessGG51LT_0auxMdVwfJSJ_3xLFMYiFtWxxhpItm7068dfTGVKzt4c8GtDYnICpTeYZ3U5VWPVgKqAg96U1WB8paOq_h_drbJ6ntlRYbD2YIC99rQQTMCHzzkIC-8kc5a0AH180vfuj5dT1bWg-a4uVhTVaX5UAt_IxzCYx_8EBj6SdLQ_xsg8Co9DpdVExLJEApo2MqDn1rr5s_56YdAX2LJ9sSF6SKGi4ZttuFpTSfDwYCw6MwFx8oTZzBJhz9OHtrxSopTxcF24KccW4prlmjhKKqoAqKIGROPpXsnXvXHtApL4X2eVvdVCGKKJSNHB9H-H8kh2iJYMlsz8O_KU0DFiSER0l9ZjIA_V4Z_Av03CLcVv6RFiSB7mtkcrRX3938RBdKtEQGdIam9gsqlhyR-bEtAimjD7ZF6iV1p-oVy8Ko3qk1eVUvqgbWhMSHGLoh434D4JE_oTeuyEBVsEUKpCYWZ9EphQvcYf38p0aMwU7SJ0X-jsV4YZTiba1HkUyFy_ptdoAWq3P4RGVmenIE4TtKKFA0064Ws8GhmQ4XRJH51Cv-xz8CduRvsoE-nePFYvsrt-KBHVTTf0XdiNrExmheapJ9iQ39XKeaVHaETeCExf-fR6vV55Ue-LTESQbJedU2WgPhl_NjIRzj1VukDcx_cB57o97eBX-RBF-6vYABrKkpmtRaqlLwsLIxA34eVSRJNXsS2imllBF-K45qWnIPo6Bqlgegrffc7Q7kAhQkNLJoYQQHT_UFB5TKfLSWEVcv80zC0LPrw80ALgRWLNEc5hRQf7U7MK-_2WA0dHiiRiux1I2a6QHaLqKpx-nRD879Be-1yY4k2DGtXRvzJRpfTMToKgGld81-a3oEwMwjMRpoUHSSDsuCdVIfg3jXmrpcMFJ8-XP-L6XrnnYcehZ-1st5rXVRWI0Qd01yt7jiixjXNmMvWr3hHmyIkEycrT5SVKYPvwHcC5nrGLbC7L6rgQJmox0KZpBI32po8VtbSWoruaNny1bw2vjHfWWiw5kh4Z80tsgrRz1T8A5GG9lsgJsE8uvMVwKw6DdHGKM9URUO4Mf-1Vra-pI_uH8t2pWruMUDwJ7Ev0qiL6ky2owNYejQH7ThMdYuQZJulVgRDKBa_hJU9mnL-CWLay4CpFeAU62bCQMDzooo7piPvFP6YABmPat1jlBfPQAazLBA5mdjfAXgMPugAC_sNe82aaoyKHxmXNhCdedZXVxJtSTethmPqOxX8lbso7P6wOnOcYcZciRNWqxiOO71TdBSCM7RIGqsIu4oUGRLMtM5hJ3j9jdfdDNEUX2rpaqHRv_6kw8nhFmy7OdRORIBkXUfnC0Yg88f7ym2t9PyjEDsEwfThEC9rlVo96DIB2HxvMaXpByq8-0D7qqP2P1snoyZrBXTUeqwyFchMYaGPVfSM8LiblQUV84FlznGbnrlZbpgDgyDeNHxrLgStNFVxFKCizLfpuHZsW_mTaul5cdWwnD6kOFaB4zF13ey-uXr3Me479zlUM2peM4IffCmKs6N7R-uhYkgjmz9jjnCebeC1zYWLKh749klWHi797X_VFLbM4JfJoW78MgQpjOx6Qd02r4xeYpxoUSx4Rr-ieQ99fr5CLrHguu3qfhD0vy8FO6TG5KLfanRKrfBKezT4syNsW3336sO6VszsG-d5Md7QFoNDDe3K-VYOor8Sj79FhQ7Ks9InlswzTiQW9cXSYCami_HraAcIpofhXCaYrDf8-jE_9X7d5gnk50cMIDPomV3Djoz9G3ISr02DA13jyc_Wf_NNRPa55KYVwx_HHo_aJQJ9XAzJfEMKX7n14WPXGxu0QLULEHj7XALHzNjk1NvqU1qbtPEOnxQtOEjaz39n4BI6O_wHF356wb7b5A3UF4jnFdgFXmhQ0kTgZdDreno96lchGuihUktWTVoLzIhaI9EPOafJWR5AmSJWWeKZaYpF4oT7vT08satuhj0ld9l8ZISm4g8TkTLCEA_aCLwxjU-r9sf0xYHYBbGpCMEHsKiGrQzArZQbve_M-aREIojp32gxk6piYCdN4rrEIl56P-L0mBMg2IRf2mqYS9YmF46fWglJX-JKhwdDjtSyq8aqT34RT0ncYFVA8BUkGmMNzqI9EfKg1Okc0XpMCoiSBbxPvjHZHZO4LiTu_kCqYS3XPDJhkEKrrGYKCNnsCHlgLCKOtMcaekmgU79QplmAdiKB0Rah8hk-0quRXQEAndQ4TgHTrfEgoVyrmBRIPuZXEHH_BXUO6LbmURy1IN_Bz_VfiRsXJxd4Df4FrYaoFYBSfXXZUn8gZAuf0IVRYbW5Dpqet83ZWBNbSJJ6VIoBYknDknBJ6p4AehoXUjjrQD-ENuoRdcQ8DD0kg3SulZK9OueNFlcYHisL6f74g1x4_WNZ20KNi_gYuCO2zh0ujWYi2NahpIAizW6E3Yjw121EacdNj1t-NC04TF7mbPwyG2yEu2kXFpwGtoFFlRMeZ0qBCBe2GnTbnYKBnL54CvFKW_clPAK7izrx2whGS2StXC9QtrWdFBvop-bxmGau_WsvyGSMHh93TGxswHqotY-jVtVcYaoxi5uGAQ4-7q85JkvvcjIS328FubLQaJtOLmhT6x4iKOjY1P6V7zTpoIybVuzOruW8ZtCdJb50YLCzilGrcMB7y587UxiM3g3IGZGl-hYZPUR5uoRPFEIhm5kqKGJKyG2tGBMhJgWItE73QjXYQbpXBG212E3PefYizKPHDRq9vo6cT_-jJ8gWIphdRekVTJKai0nSgxaedZAx3V1jsuLx1pD21zO5p-LGvV7rrKUKwx-NY_HV6EREqBLF9n96lhIigynnM0asHwM77VmbyTdM0upGdMJ454brunLKpLbbvwM6ssE6SUdTG8aGMXlSzw6-pyADVGwT5OlRxM9Gdgke_bu4WiR0AtvuCb0OJ1PpwDj6lYmXrqyZyh0yL7cqFa2P2oTVoHQv_V1T-9T6yoLvEt8y-wkYXddG9AAbagB6HDobR4ZWOd8J9GUwhdMvNAehQ_YN4rJF-fON2gpDd1TW2Aro0CkX46KdISgj6Ib4HHwwR9gA4PcqId4pZL9SZ4vqWuSud12Of5V0QT-uI7NzawkKdDf3Ua21NWKrEUODvI9P-YPBXPA5fjoe0h5bGMTTDZa1a9tE-DkR1qNlmE6KkC0eoGgD_toR_I7Fo3NfXqhdsEcjeveOU6vfcWHhDcyl9J9e2AQ8A3of7RQ1uKZdoh9pygTdW5D8Axs7v3QN7UoiZ4jlU5pwzdBRAR5xVUXAzLFrMVosK_I5Gu0tycHwZE2OW72XEvqC72pgf7R5ViJnFQFI7C_HuIKBfTKuuD8JU4rZbEuLyEuujCbLmDCi3t-x7MVRDyC1dYlKa97E6gkOWM7QZbCxhtph-eCPgXcJ16jjLR4xovTObgAw2oDdLOkxwNvLm74pREFomBNPz2i_dU0uyR57d6fq5jUb1-GmmR7tNeqcdKYVz4J87QLgrOnLXV8I04c4w1nfR3DYIpXl7uVCW3j_H-Qb0aYBgGeoyDjYmEzPzKYQ-JCvW3SiH9LTYGw-7RFSjwYsjw5PqVUaWuU7aLDGHgAz2wwMyznRAntP3ZKHOZ1upDmplsdYJrABXPvx21stX7LDNBBbivGve5xGQHmQ0Cen05OhePDQ__34scwExcLEVwf0zdGdWimwOAsxSC8T6nAUMWdkwSnX1jAxyAGou-j5DU2CGVbOTjc9hasvzQxmBuh1PjIPKInk2_Mwt-YwibbEU7f1Ev0jWozoibnYYe_3rNAPxybgXGHYqLrKuBxIZBkDNS6GkF3pjhgpvc4xdtAFvF085vAny7HwHP0MX-HB-JMYGKqWlRoXJ5Wq2LNWkxMcbZHa1rbf80yNKwrJn5iu8Kt_LRV2AtWtZICw7xWx5yTDQNsrO4JdiMuQeZ4EA-CCL4Ozd4qLtr7qdRKproU9Oprko8dTlxHYyBAKhBmxCV4gvkGaNUq8uy08ZQ9gQkZzgPNoxn_IzPNhDEEEcACAcxWFuw8j6C9K0DRQC6hYDuO_GJrv8As-DAEnMxoRbgMLJ8uDw45yynk_7QebGUUd2HZnjq8lciAGOz_uHT-brybz8Nm3KcZmNkCwMj9GFRRfMgPsA4Z0pLh0mviH9RF07JMLLBhmc8fTCPBAgErEb05Qgb3jmSmqfvzc8PUfUR5kaoMHVjciIv-68nZ_YlXQB_oyUH4EawoYIxxQF7KbU-TiRqEZUX5g2iGY1DuW78L2qGa7dKLza98rIwVdQ1XRKgRLLz47v-N2MVZkI5Fprf8PsyAILsAQfKtb0mX8QCfpguRnZ8BTIsVWHfKm_KPQHd1wlP-02VShzpmrr08IOPvFT3fQdgbM8TQaMbaM47fXjfe794SjSgtd7sLiJKIgEWVNHC2d3iLnW1RThr-GsCXmwua8aRk2wWFiqJ-H7Xzsu29L47CYF3gCeXnIOMh-nxxqHjo9et5BlVKHNj3a_kZNC-VcjPE0GED12WYTpgOhYgCswfEm08QbF_-BQgyR6mzrLyQKSSSZQ7HzfgJOjOrXaBYmZC3OFYN1iLmq9id5SAMck_X1OgaE0gaHSNqh5cgJxDqTP68n3YLVRLzRDf-jdbFSw-3pyD5eyUaO01zcILBijjfFsbikhMnHs9aE1huA_fzKb3OYzkSzd55rz2PE-zLgXdh24nu-RyBW1QIfFUC-_LKc71X4_dL93yXVSB2esegWSEb6o5O1dtdjPhPn0nixr_zX7e5YPuKBT6KkWEMxbWbXms36j0rwrjrgxr9D0STb2s08IGYbTxJ-zqRCCRd9BAOysyYgkWSZRjsLGwpQKU9DasFJVvv_1AAOBaDRCLoaDC5Hv_LUxtiYIeyZB6QayQHIPv0jH4_5JJPp2Gtrf_z9Dt8GW78eaXixTX2AearcfIRdId9Eig7DafcNFgp9LdDw6OxOFskIZsDDLgXQozuOKfUtowFWgkSrzsz1BMUexzdqeKzjMnY6DPI7oCI7KdV3HSxYbOutY5WYbQSiTll6JVPTDgKouTML_KK20Fp1G7HCcw2i9PY4i1oj2zXc6ojtUWjtwD8EM1LRWOss3A1Rcn9o7rn2mEItnmAx9WrbIJyT6LBrBydQVi-7MH6fnadqfxJnJJI-7dH1IOqsW1XSHme58_xiMAyujXC0ukUHg0HbHvxy_BFDFnDVAIdKFVcCaVy5Mrhwkl9_2Dm0cCoPAV6Zv1sTTyYL0z9za5pLMMWSntrmGKwPNJq7eltmtYd2rRR5JUxwGW1Q7vJHaAwi12L_RqGTFeIod1FVwCzJbu5Wu6V6WmDd6C7s4I-qUfnYa5WPwYHK4MoKsOQCH1f-UwElRlue5EH54r5iz1u3sqYulXPrpzwk8GY81aEIEseu3F9Rc8-1VKCHUz7mS7FGbRPbKrqrihSaOvQGb74CJmeH6RlBlcUh9jKvxcooTzOyT7RAYv7jrTht25G1y0QwqrVjK4xJVpi23QE86GkoFuBBqOBZpqjtaJ-Nn-boT8kBJvBoFxhXrwQml-pLZUysNx3IaC08ryHV_qiSbiR2sWnLlhuKNVRc-A7dOh8JerjQo9cmXuxrNcapSPiVkMSXeemguXdKa2fexcajQsmvLur8YMbMO9RItyl4IOqsannweMu8nFjkqBPIRGyDtL7gVqFa0RYU33ZX7vyw2L6Kg3nXgzDkhP14c7PqXznIMQ7ihCL0uAxamBxREl-VZYowqur5jVFih5cCXFyQTANe0ERlO7HOgn5nezpFDB8w4JsERNIyp4TTwr7z34jdgApMHAu4k4oFbmOZsSz4oIpDr0CixTDZ7W_jxDkRu828mvRObsz6q37hXxjM_JiKsP7rwGWLOHwcw-Oq7dJOGlFHeu9Y7vBz1MaMdjLJELuspaq7XUNL6iSWejhVzUHLdgAf0j4818FutzT648EGvN2H2nYuGmsHckcUNJxqz-VqZjqjaXw0WDZBuiuWE29RQ3U7nWO7WwDSGyLd9J1qkrMReO_FVqGk-8B26thklBrWn7dtScNtAVSBx0u-xYYI0tyS3ygFTakRke24ag8u6jPrZEsiCHRb-bYZtDH9dXMnrefoKmzIL6u4KDqQZM8Ov7aXDK6szlSne_p1BYtsUa1FXbQiF_D3B40-nNNXvD2eay7XhOhK_RQwOQelEdlDTuOBlnlxX18PYHDg4vJDPGANRGx-PewGmBcJmlhlf7oB2wBuWSB-rGQFMqN5HZ-D7AyvfE1lC5uPlAgaKTbCE-ccfp1iNgxSM4vC8O5qBzLzTNYXj5ENNYQEGpFo78bJogOKA-huHlGY8ASiBs3Mmwd1djCO-geEFrHsWZpZ_PbbfqIHDjiQ5sf0B5tOrUxa0SYeu2OguWDrB0UfMYadrZYKt4mIJuCpE7sE8y7Xx6jUuRnu45Fp-ROXh3yOQnCR-sE3x_ZsDInYaPRWUlZe_LdqS7gAmByi97olj1EazzwQykt67b-bhZLcK5NXj-dMiLewIqHautaaVKwkBKG0gZFp-DJsxoku3uuem_ZnITGa-UcoK-U_ZtCZZsedOlzYjPbS5vvQl5asGOidoN63d4YscsccxCfS5NnqR8Gq1HF-9o5t9rAV4Io0b4G54q-4JhhyhGBth8ZKZmkuZV_ulpLK6vK2cRu7mFE8_qGzSol-ahgvINftCE7q3TmIAmujvuVXfMba5X4EaPosO2Z5lBqPkuzIVKmHaKUAsfAbtvBt8XVlfp1xKkOwxtZn9fuTK9ioK23gSPXOpXMSt7wUgIo34UwgMLzif9ylDJl94NB69fr1WLY7fGZqqPP0QSyFlW_S3WcRZy4YyEQLAe_LTiicCiAY-pjwKOs4A3AsUFoP2CYjPjdt9Yxs5EPAchcvz8AElLhVW5GKMtofcMU7q9JPvsP-FaKcbxRzK-QZA1oxnBLnw-TXZ1uCKwuEWlbrLRo4ebMYh2cVTdRvKy9sJGGDPNBIkjysEK2FX5cuD3UL-tcM9ZTeY-6e0WL9FiRO6IxsMRlxmZgpHLPmdBdOHdne8Yq8IhVanl80RLnmgCD7nIukxpufsy-Yi0CpoFNzr3w3j1TCGEfmTJzeJ4-OAEpoxmyGKBIylPwKQch97rZlNJm3hOTxkGOiLalyNVp-S5-KlByfBRQaI14WpBNSsuppktFP6Fehz-dFHG6RXC836uzaE1dgb9i5wR8yyN2z-CxlzCTCzmnPyMB3Go8td2nsRm8k4bo31bzHNtsN33DUuY3O9ih4dE5qh8x9J10YlDzIv37eSvBdFkiwASvKUGTmdOGuZrUSzJabKoPvca6NUavp3tl_EmrPl2mTr42gkXk1J5RV0QJNC2-K5KJdrMDPwrc4D2lIxiPrxp6hXcaiysZ7WLpdzsmFlRjP4iyIU0Q3YLm2kJ7yDRfcRN1xHNahN1XWVdHpwpiZSafeGjEHLbd4TfkUQZ7k-wGeHaVZNCECG_e4ikqhjZbAxD28Sskxd7nEfDu8s1q54Tyjrivp8aN5p18eleuwo-azJO3SRrDxLfaMZw9qybK0f1A_wTXw1yxNRGWCiIlCkAUhK8e61VndFa19KzQnVFD07dVwZYjsGUQ-t054--LuYX8M8CaldVBe_UQpqEPoCjczEeJAWrdNTLE06HyS6Ypdlvhm2AfEcd928pxRsQHT3aFC971inLdnN8pgOLEUC-21Y6Yix9OTjJ8MeELDWutR3AvOONvjJBJ7b7IFiBF10hxsAIshPYUHkqacgwlDJAMaXcT6F7TQjxkdJE-xh48ud0SoKGMHV3yDTxxMeGy9oi616QGu6XN0TUiIkM2RDqhfAQKoiBjjwReWWLy1bAtIYCyUOXPyYMKZO11W-xSpZrKpr7hOqsv1cHpv3SOxqx7_Uryd5jgtwI-cIkjKQnul-49kpDzB4xLEi76S-FLGTa9Cc9-JrR1aanmM4lYIP4tQs3PGE7dD280BREYh823I7OgaMkbdnUaflEbvc5gafGS3_EaicXktjA7xTqaFR0bi2Bkdpc_n9hBzFwhRi3n1CTAHSzPZudrnQgXN_ZlIYx0iKn-LSw7CAf5fADHipN0ZZps0Q4S2JmzuxBtPkOC4ivJUx1As1apOirdMvSDACHgLH137H8vr3-fPQPZCQGQbBR-h84pFOJ9UJgpWhHwF2Xw9xDg-bpkLxFOB-gqGv0gM3he1qj_o1iFi77einGB5yjYFqL26q6twZ2mW48pIfqb9uWV6e9MOP5rAC4iJ7pvcqy5UEvIQU7HoZhWlKpwl_ULX0F1Jl95LFGuYv8Hcv6jnMKsO6d6LY4kJbHxLsHwYoBAhM9b7yDui_12kN83idwSYIejrmdPUciuFVNsLuEVYROpCovyxpuH7RpkfIFHa9VgUsCaP8ffHFkk52vY9bUkVF1c8LnAuFnajNg4ZmKBCxD_90V22X9FEYeUCcd00wvzk_QqDKFrMBfMVG_RtzUz4rR5_rhCxKKQvl1tHEptVkO3dqDlsFukINaut74oj9UolV2SlaZPCEFpG2BID2Z8nfI7VONyptgJY_dZw-65wDxeEukHz6RWUc4FQOpraQGJdqvEThB2vQC3m_TTKLnyi3QLpdyY6hMCCSucAjQykaz_RoeRM4vLd1rleRIq-rP-gyfSjBYTRRCnuG9B7oBZHAtk50mBdTzhQl5bwFVWcDVFcVWEWXhF9zhr2WAyCX7ip3KuA59amBfG--k95BOl_BWcBXyODhJ2X3zuybiV5_G6UHuiwSFTPfSrBng6sOs6CJOnDQqcF7tp8_hA1MV7OWocpy9NMCG_h19HZPbup2QmTElP0QUs795V1rwg49ZGKnkfgMgmrjSBjkBRdwMtlcVTHE9pOPEewwy9YYnaFSbMIWXlPLs6k5eUvViiT8gGia6_En4G6IwqtzvWNkQDvjrPT1v6EhpdEyUR1u0zogUYHeRKqRqGTZIGHa-zQ7jmz-irb7BOOGUESzvT2NyDgd5Exh6bgGaIxokklgQV3g3CWrewlz-UOF72WL-Pv_2_7qpUGvJZXw87E1VBUO5BzWd76PBRsLBpPgbgbaTz6E4eLV3i3ilVzX1MFkL03hkh0CZam3-GuLnSHadkyqiMHP4GZQQhJ8KZw-Qv3eBfGznkd6Ro7leVEHTC2yOcofvkBjAhpoghDHjK6viRmDIxr7y7f5uXrMXH6khmPYEuP5h9kXXPcWA2FRv6NNYOI5icjhSegPi4edHc8QnyGvscpzo4NlARllrl19WZfDOGxXjmh--TuTJ3YyCUS4y4reWo-uL2_oGLUU0jbdsaYkEdLwpiqAmFvpF6cA5ftNn-RhpNrGYipV8t-yVxwY2pXhUbcBNTgXB7ZL5Rs68fLvhKmXP6Dm6e_UfspVWFrqq7UQAdBkdCyCOY1TBDnB-M_6yhkN5Y4TWufbSjSEpRqpBgn6IVf4VFndcPP5dR9BMIkEYqt0eJnHhtvEUR32UAcXFAPicuVhXHjy1haClqXoouiPE3nsNinQl2UXyrFz2gI4sLBcoH0LcCeaiGLuZo1GQAY4YKn48YYfALIV2H4-V2BgfCjETZUSQolvUGe6A850oud_FZUV7buQfDg6iBmStzv5FUtH9XS5ZjlTr3FhsnmZiSAkx6InM314zTReSMOzsJRZW1NOZf-Qx__WLmcDh6MjGQKPh9OvyCdRTFPuvccZHWF6LbRjygRk_TDl0JTX5Z-xehyieityE9DINpgv-mrEgA_g9k_luLiSDooXgrp6IlX4jcCHtWDxtPacNKb_uhAet-d0RTYO9cT6Op3HaWk61FGsxmFcYyIowvMUEZgdRUvtXiVt3Uevm4UIYJQFOEtAcb9_rVE46g3E6swT7YCivM6-CLEGi0C07IFxiY5jPUsYBMIUj6LqfEtWQru5AFC6Xy7nmQg-JiAwItwyEKXLflQ9OTbfAP4P4NPF7lsto1pZ9b9et6Fh2bOF6rE6oFDcVmmdjLazn6iK8NwwvLzqp1iThTVKjvxOyv9OkL58igpPOCCdfOozMRS03VEMsZt5KJil3cBWrtSlda3KCQkYbKecSG2_SF94jzzBzZ6LxUALnnFbP7E4Xja-aBIoUhLhIKm9iS1J613NNU8BoUVSYi-LFcua7N_uUYw16pph38b1AJwa3QZ_-bye2qRYJ6IC0qG7_rsm4E2AQxF57MJrys2QPwVbWFampqVrb33NohCkWnwPQHBcsbDENxT6HuxIbCPBn9ZItZzHwgXaqHyJ79ClTgTF7oFvqfKUPjbB5mMq1AZ_8sf31vEbEqSPJ17pFqhUm30bQyrG7ANP3RSRgdzeYVSVGU7AVBjkuzg6ax0ARmnzAk8YlLg5rdHw5nu6HRwe8PzFWrrH8hEJM6ASv-rLEtVaEqv7ztqWkyAWJYTDq-k9WKZ6gAo4tTTgPdyBJv_8S2X0tHxZaTBRHzTOLZoQQzoHJRCGAPCRXftyvPYUUDhnh5wbynM6BkbhSGuQ5ADTmk7XulL-E_PRMoMe29F4GNvK_Pz_1wY5BPRCWW3WMzjPKENakpfGb8sbcjVDxQsC16qWMGXhv8r6a5nwvj_9gTHVENpUmz5cAFiS3KMXbNBTYSXYgwD4DR8GrPsNjdHES3ocknzYkcn5ag7_pJVVgxot-mPXVwIPJgzToCdusdVYJGTxDMdpmzL21j2rlOKf7ZY6Lhxb2LWlVDHwwfKf1qsjg6OYqFzkinjwbQdMZvZhwRzAWielueUkCMcUjjuGnXsayJYXkNMYZVr21TEEwdhyxbmjYHwXd-cJQrPEpZ3WzYr0tASZYBsDwxl4-cx6oDHx5Q2Nmgu-YxIOBb3EaftkDFni5KsH9yKbVvIi39fSHj5LGJF2PBsbwIcoyWgiqxXpRX5phS3kxnqlEOCJOP7HhtEdBopAFvyEum2Nf3_zNfnyfeMR3NmdHhFoTN-02FQJ3AsFDOJEQVVibC5MzcR5hyLCSWCiweJCjSRsD5bYuM9nYtOu8dA1Lh7fX9QfabU3vEps4ZnSKO6b4thYUGBony4D_lHhpB4Fybyxtd-dM3WzwAk5lgPoLTVIQRxKmtDRlhC2PRT8uBA2TQ8zmEMtYj5NQCPv0qI-H88mER1zB1NYPINj7o_mV4BeZhxFef3bMzpJntULtSonrHVx3KFWSPkwVIF3X7A9MZL0JT8J3-lvpi5hjovwTPdQaX3D8OjgliYDiZW22w51D8bIoCCPnAXESLDxIlTATweO0QfgUXZyDDH_ZENcahWVD2V5_FIvj5-2nlh4_M_a820pAyDi61KPpyCp12-7r3Doaa5qudj0x7nifqQBy3wFk3rzHq2Cxr6X2UWqY77vwgSrlqya6ol5XQj1suXnDJ0Zl5fomrG3VWRnSbbdanabb-FXKvUM2tmr8s84wrV8R_hFBE4Qs-sGTkyDeRytdPFIdM6scqCWu5QgD0B6JgZ_UnEnsz37hT6Y2Tee-WOJZ44bJ_htmTCHvP69ZNoiftlF4Kk05M38oBV9KRysViSvWJtn6wAAUn-rk5OVl0VMNaFoPajRrEDG-oermcV55GWgShoiTYr25k7rZt9PVTMkv41tXUiGw6HJkOwIw94V1O3VqrzMY6GjMrlsxw6jOp6M1OXX7uy0kSwIwwwEFBNLaz71RAkY9ibr9BrsXEO-4k2gw9ORaI2tJTA9RjAENUeqFqj7p7osUgwn3DjRJmVfZPkLsxOcrMb4At0F5HjgcymN-KqS_n1lQ0jsGpG_JDiVqEGSta40wLzhII41vYfxDJMjRO3_DgygFaEzeVEj7p5t4ixEHB1oKOqsSQ8WnQ2L6RkmODR0R2Lo1MDz7sa2Jx06YBJYQNFCywcCmk3vFbm_8bZV6hNjJDqPPxuZdIkJR1GoMpwh1GIpvQY3ci3N-IenEJJTVRbR7J7RyKxBEfzBt6ZOcU4BH1Y53vefmKZjCQgas92yeQH05P_CrZd5Wa7HVD7RFW554GzNhp8tWTEWm5dllhOR48P23g1hqL0FdvhbrAvkARvZ11xX-lUbC4jn03ck5mb93CKAMgchBZI6dypQq2uZkoBkcglvrOUCE0flrGHuyycmJsI18tbKF4hf4sRVKjmYw5MgzJqIRhseamrjpej6ycqg3mdDuZJeoePS7a174lreu8bQVaFJa08OZDsZtiVvIrKcgZU1gyHLgdq-f8jNyTmuFCYNXiaE8JxI7OVYebZ50QGa-tkUHYdvdKriwxWhNlBnX51K_Ku_LxqL5nyKBv51nIIcMEydEzsf_-IzYE-DyySL0phU1iXoUTNopvaWfuguBlfwJtCO_NVzeTuRJ09u8SzDOQ9EOQ1ZwrldAhYd39jpwFrgXvYKudHSuet1unI3IkLEFG--OwnuVnEo0A47jDkzTY8YJJMn3Szd0c_ZbEVMQLZRVZL4hcuofU_lIeo-RNsG49GF4NO9EDh4STnYiPuZhPRPJjyXjin1N2W6ITshVOu0uxxqnRR7UTy62AtXFzOfYVhD1DwtcOoo55BTFHD94E21Cb-wqxh3YB35wtZ3EkHjyR_y7qmoQte6GRU7R6ZG8BfLLNOFKq8SpvXN2tvvp6hPI_n91dVg3iZhLsX9HY_aYXGKgkttX2IK3wNdQnc3B9du5LD87EbEPISE1P4ywRP6O3BvPdbundyyMykbATkq1U_60sX46ZWB49hRxLhTdaySpXKCosT6oHXo0580EmCDh9jt63mGvJUrNurwRStbbcKrFYYY63ze0GVyFw28SKiCtCwnsCAjha-x3fAPbDpkSKLfX6UDhnTqy6iI1bze1fx-_2Yuk7_xKkKwYGufRp6DZ18w9J1yAmM1FNwaBapW0TRyb_bdprMMlpVNgvb1ukRqYDMddZWoJJwX3qbrpjvsSH7YOM9WWKMJhgxuZkA8AZpp7vX_LkvwWUdMpEeUgCiRr1rRrQerN-eRq8CiyLz83JLFcMzjeQhvqfXSqMrwuYgB7pK2frm8fYyAH72fXkhzTwKaK_LGF_D1MU5PW5Y_ibzxhn9TzxTd7YtmUJrj2megt0XTKtnAoL0jYkzv7joC6gHpgcGbWF-3p5s_dUq298Te0IvWHxXvNOOervTjeh_EnC9-M37rtQHWrMujJHeIhCCDFiq6ZtPah8kgZpnHGbrnna5v_0PXCjB24eCwtv5jCqcpBKA_EGGoq5LjWIh7gz5d2ruaTI2EnblwNAPFTF6yBMTp-umexU5q5yRAgQXaBQOgBbQcM5AvYgFF67rcRayspdG_ASimEBmHzr6X_Y5EdZcrTmja6ZAE7mpFyzILu1FEBE1uWRpQzR8p3BK_8_4kgcjIr8zg1rUKV0amb7cAuKbN64gXxm1xgmaQWoBMmtqkC0YLmigF31DXgUdXtiZE3PuOSr2OtbLI9dUO3NOXPqWP4PuaDA1djGMsUYcV8IfntyCN_3U5_PWQLvKO0w2vkTjRcO6He6K7_-a_8iwjY3zfTPnvAIAs18VSVPLW-_pIWWNtynlUwW4U4vnpt7ANOHUlQQuA3PH4JfHXrQszOZzseOEBcVaXeIFa2KWSAX_24kaG8K8elVy1Y3eZY0qKtNZmwqt5iaR54fDw7iDFr_L8989pYaoJnApV8fqsl-6Xbyy_qh-sNjK7Jyx067qanv4yCT82ANOxWl4FUL_Pg6GUq2zL8AwOOEdWyYSWhBNORESvd-jEFrQT5EOkIXBWcIQGwnpGagB7C4-1jlpe97OsdkLmDeWGFpdGb0csZoc5iT_7yuFoAJHaAzuFbhSyQVwIkxkYibL2UkW83OgH3-oBErOR3CT95Su8HQ8Wm75DkEwY1iLVWil0XO2XaElhhDQh0zvGxLz11E-jnk05-9RcUHyN7JIEAsJdGq0DzfmpA93in9wSXu012uxFegg6yOQetG_sEQF1f0JMYIo_JryC5FFhaD-D7x-LO1RwDwvl3skXw4da1-AhcUti62SGD33vBKcZEpxiwLfVrbgYZlnanF5mSPAYhzF3yhLG1oOt1JzrnO4ViyuYIjkI67fIbihT6X2vAzlZ0jvRuH6oz0UnLWkhSbC6nwbbRIglTQQMa0cQ4LGUy-njMouuBdPLXKGLcB7deUAguw3pFo-whfgt2GMKEbxXEqts9WZae4NJjmzz34U5qECMDFbxyuWDA_JY_fSphJhGjIlGOOvTI5spposOjQwgV8dGOgRRpB6SZ4Z7KzeyUXPa0d4MJbfbMHYxDVt-Hcug6uiLoGfqnfl_jg8MmYswouZSkuGLm7ONBxw4Y7XsldQQZtstOwHtNR7Ex3q5UvMzWakoG9uKTVaKzZZEJhNlsV8DLmljDJKNTVntZ5MTQ9kcOOtyWYhlQ5zz2dohPRC-xjucJYvMovmWf55mYTGWOj25pBcy_5sSk_3s3nwGCB0kht0ce6KnCKVoHA3Q3HZoE5_Zv4A6Z4GHrnPp6X25USewWHDRPeAE6LmBMT5_scBaHJ1if6YYMQQRhEFUlSgVWd8P7Kgc-9ZcVaesZebzzL2Lqfg2gqzJ-X69YZKRvwu8gzvOHXSPpN1ujea-VU8rqTlLHKtjh9PW-t-Z8XRYylCs97xfblMThHkAyuuqEIo_k-emK9tKNcOFPAKyGKRKBv4iSMUr6LA5X-malRYTTR6E05XV809pH_UREQGctJ3nIK5UFeQHPAyOG9W5LlS1xlEBLokAwoS9ecgda8NYrGEqWpjoZbPGuF3bSVwEFq7SwvlN3vSvOV85LMaBiexYNm-O3E2S6lJ0rS3rBcukG8ZK4RUvsu5WmqueIGuXsPc8IuhHe4w9_K3XSNavh90tkZVuEW0AahyZdiF2rVuS2pu-rk-Ejgt3YDdrRcOYzENQqfq8iTH1SKUYvhFQsCxSIxX0wE_S-4aAAr5oJXRksNZheKYB8_xiJAY0aT5-MreVBDumDTGOTxz4MVtpDODkyzhdMeQCHD0OD3TlHP9ATpNdKeAo2eGr4BGkWtkJ56HfXm1jjb52xSCkLpHEwarT4asea7m2kfq5iVcUQKdhg1ZigMMc4DuC7uzM9ZGAHOmTyGXKwlvFKOXt4qOQBzNgNd7LpjGW_LYCoizQFp55TV3MH2XGAOttQ7aVuBlsnlhj5UgulR_YQNPQXze-NK2Jv0kKm3xGJlbvYkHmLe_-FnILF690mHdS77MOoFvM6pLfM1U_aKR_RsuA7zGWB-uHcUKexDgFyymXGNCnmcqjtQreWVuUBE8bASHv_tmO87r4mz5PPEtYnuMnt2Lwcxc0HbQO_XZpG1qheEtSMmOgAAvLM0ufMBpXlYPUuthzjGhFk-tdkXzntlqqtBYiwmz8ur4wgoVd6akM8_cfzp1gWaVo5JTHEUF-XD9j0oeTfcxhwA4E-JtxOfd-x1lElN_tU_C7VYcY3LmQ8Zbf2et5uHUMo5EKJotIpGwjtx6QAxHOJuiSOs23974zxMvgYk76Fpd7hVaSCa5YdvydjETXAiXdsgyJxo_ZtwNKppt0d6BX4lEb3ywW_tqJNadWr9vaWEsfdaV5569IG7u-DAjONxTSdDeIFew0Mas6OQY01FzOpbVi3yr9JmnXiaAEU4HuX5CHVFoDKbAVdlXyfa9KVsg9arTTzBuH5nUOrw9oILADdMKp9wKsUtHhI4X0ATT_x1DyE-GYRJnwTia93zYyy3vaTgGFabg_4-hg5hK12ScsZZlHPWYrWfzVZvKVZDW-yqj5Jfn7Sqe5XamRnbujTBvgagSekUGvWInGrXhujzxi2N0ADS_8TWD2gDkHcG2fUwyJzntpusQEZ-NnNAUhmeeLgk1c-gljJc5BsA2DM-iYvpWfPz-A-CoSC9rm-nJBYtLv2Ff72Ig1YiWK6ctFl3JzjwEXyygEfXURiXgQg2vdTQI0N64GTdOB3CbVIT-M_Wca2tQghoGkDpMmEwCbqu4j_I8goadnz5GjI4hROLd54NUlU9q2GFHG_1Lk4UuXE0ENyDZ0JKbN9E3aG6TbjwaWGRWlRBMclicxifw4Q5AL66Fl20X0el58NIpVuTqO3g_67F23nry62oAHH-DvB6DPjOWL6_643sPS3Ct6oYbkthrQkPYzaoWJQJ1y-bREwGwVCuxrWBr7fJwvUylho-TvNhU0WYlWL2U-UQ8i1H9UHw4HpvIIArTozptYY56wDkKzfxwJWcX1mMF0tDe5_KqY2yo2HRz7VGk_26DV_fcsZJawlB6LpTfyEwI6trxxWgEHbJgcq9UC0g3SoOJX81gSk6FnSbNlreVTUdwcjkBQBYFPo79nl3_xuvwwE-DQziG9ErouwrPpR27gd9WVWaFx62_WPuwheU0PTEYbwGXrgDRd_5IUaYFuKllO3qSKZG324TYNrZzdRYIkWtUGZ4rn2Npr_Cw6_KGFJIGeAJNnGWY6OX1qYOoyWrDW2Ssw3hvymR_otPXyL7QoGw2Bt9yXarAMqszN3xeDbbrXlloUlkSDMimwqhktOLKBZFMv1Kd0ozS95HZEoKfZh7tRas5mrMjnIp0K-GZAv2Rup3u7HPfUKGehBsjhstnOBwaOEGDKJO2pDCC7fjch42wzVvIGDShkLWRKGLxhnNP4evSXHQW3GzKjhtLXNEJ_1NvqemrbeeCkDpBzqPWFGueFnkztdexjxZeSBcwLHz9vqI1Fd8-BcOoAOWUastXvUJt_tSTY3jEPByJezIL4px2lRv8yrQbqPpOfpVSAG7iT_RvXSHzZpEPxdDZvTKHPSY5zp0tH0N58LcbEI78jijRYbIPWh0t_R7WGMGtmlZUk4bkiFgPQ5wWWgn8C1noQtC1ruYmKE19HchOS0brIPuyMWFRIAfLGvDmczrgl6NyrspSyI4U4KXdsak8BUjzmXdm8QLsEJ-KmX5ZLyv81SFvDNhREgbbzqOb9BZXAjmiZc2UnPHlYLNoiZm6jg3QZQhx7qB6Qpqrm3fge9pBtH_wZD--HtkBJjWt9hpnJvLpzyWdHTzmW9DFyJ3d5X7CWR3izleWgzlGr8x50vlaQWqHSBUj74B6QJncoC0l2QRgjhULa2U5JWD8Kzf3ObL37AYGTNMRM5OpFoTXAvREJNcMWe3phtXGSTUR-8VZHPXwh5aqdAQRQmLTdxYJhuBo_v80-iBsROfcFrIoK8cK5A8ojg-lyVgKvvM97NcQ3U_zhQFfWfqfGifnckd50UcDr3nW_OxjltxuVSp4kV23Ug1CyhdiGUd4vV9KiYdqsx9Oxo7li_GCY7z8wTl0VL1Fb-4vrjbAaKg8Z7-r4uFoAl986GzbdE5Og64-FJs7njjTlMAfgUCfkAt60fCNhFGPCvg0XMD-jMkTvqg03DR6UyWGba61-KmG5M4naUXdiU9c4kbKylaxObclPjohSViwC_kgJskpn9pXbDq7AGDNHO8fI5piIY7BYAVwqmxO31FDYVEmNZmB8WxxbQi0wvibn27SQsA00_orgOpMlginMx6PwIK2EwZ9e1zprH3Gb2CrmoeCoOFt2bD-mrp8nIKHM7uPghYryZ1CNtLFywT1uDQ_Gv2eaAROjbR7UpORcpGc5WQTeLf_BK-jrJ3HT2V-QvK0BASlKUyIFTB6-D0dhZ3F9SVTIT3HPkPvTd6SXgBHKXqEjjgRN3V_WPo1GlJ8hOovvn2ol3maGorDHHxFkXWjG0hVNYJxIDlTpd9xyhDJOjnoe-KaBZTN1N3qZsIUhNivrAMWOpxcqoWhHLc0rOIxoF3ahvuYfnIoCW5lPDTHlzGNXjytJCIUazYiI1-PDMAHqyooPJVrN3dex6zCu1XZ5J5QZFMpBCyL7L3MJ6a172QJ0proDsHoSLIyt6VTGV1b6sQXRs5AbG0j-_wrK4O4XHHcYNkv1j4siEIInzHLIZdtd587N060Q1jyGb5i_giH4O9Ffxkqlh6s2GeTnGjG9DbB51S8OBlwDTv42I4xHCW-e8pF2HokED9ZWyDgTfC9gHHZ_1gt26xrQ1rzCGD8OuKuTu1sN_LT8MINA3Sglvi0L7Ado5RI11T4Qe0lyH-CvqrgTLFvBzpClMeU7DZ_Rsnut9f0TbcdVzkeqnlQN_2fXRWyTFui2ALx0fQ9ISGHvReDeLflYxq62tV_zailRypCvSMWquhoWT_0cWdD8qs5EPTgDpoHXlMZ6sfRyZAApPTSXFjjonOqVvS_3FubU59p9im7BFrpNSlFc68Tm5aW6alfvVH-Tg9jo3n8xNZ260p5ZdyqXMpVeZkYah94ufhWqCTWto9M3qp3BcEVs8h2EQJAYhqnWe5itISSQz2vc5u3rUzgAPX4sp8Q-cZ6lYBFtlMgRgKVT6-y_NG4QBppIYeosECz-wNOjDPiZrDSH_tBbmbMqWMFW2Ejrp9Coj5315_hURh1PqPRf7MeyzdXbvSJnRqtBaYepeEQAQ1txCeb9tBh7-_YLpADJJlcoPVN58mJumbosfLJHcDldL2zKfow1zY7bGsDBeDI0rgyjpGnHd3YuvyoRYQRCbSgvXXT4B-tyHgvujOuBM-gfoE6HeY4f8Fq9gQlQtdN1aHb-ElFSsIt6V__AJh985Z-f7TAo4W6uxsbFWMx127D1W2jfytxN5qzhU3MEZvCltk0nWZlxV4bxDIUVRqVGFP33agb26Rkf9I0bpBaF7Q6-uCcCH7PoaHKwHLo-WjaLifQIth0oe2crwuuNb8bmAS5guduQxUPLQmBUUjrCZf0I_YQlGgyZkZlQ92qnm8bI5_yyHpPwD4KXMCmhPelGjB50h_F0_pJcUVFCvbeqK687PKDVJErYOEorvB8QyE6_BbM9a9YAL1NXrz2V0lNvUQOulZ5z_Yssz3RfGL1jbEIvdoPSVk4S89p7D9x4kD7iBVpqvlnq5tOlTPYfTwi3ZDZuem9EdkczZO78-5GDM0zX-sjUkr7oaCHu_byZzceElzD0sNS7AgqcJ49KJ9N9CZEbDdbNuecoRjfixwFBOtJHfNssehk5DOai6KQAYLtYLDEdYnyhSVZCqai0TM9CbMUc6nPCUlrnGl-QOoScUna23HwyQNDrM97D9EtwJatv5sfwUXajhm4H_V7IPhrL7VHwnLE8SiTR8QeAp8HZvG_dkKJs_VolMcCr4h5a27eH4BvaapS8XbHgZ8pMfYrCeN0btEHSgFNBp38IuB3dsGoEyOmxZ3ChBAjLrnxqmgzLSrkvj64wPlY9mo6auAs8bmDuNhytCwlSXB7af9VZ3dlr4PqQOvDVf4Mdo0MdYjkylv6Bipo3fWSTskJABRyT8orX-tRX_4nzMTuDUKs3giYBZHm8nkc6C4r3vsBZcsKBeuqqeWFr0A4rOK_PceZll3L3nS3UHSrBYGes2vOBn0LK8xiMrxLvebZDYjUwJHliC0RtaXt_hNb0hP-ez1KqNBd9jgfiHVpAYsraT4vAq8xUQNsVX8lkAMIumz30aVcCdbSgsgmq5ek3IZETwL34HNMaYibmcuQ_7Wing_SmlPZZ_AXxWqio34x9edhBEsj1Wy9c4xZHbTBhlPAHEize840yipiCuOlHAElWsm-9nU5yyi-_r7PWvLanF0URz5dML6EyJoyCM0pHT6ZSZ-FhVa984_UcSahhpMzDu9_tWn5EkSaKvMFgmw_yxHY4YIELWbuSucsR63zIG03HZAoWN17iVRaTKebcs425E1dcnoxHVCBYBRFpRYBRjDCJZ8Jc3DN9go8encu6q-0zaanw7ZpQ1RLorq0hxMrv5vlM_vGMtM93ds1J0CcxSyC6YFbCzv-805aQnDtstdXKPHD-ZEFgjWwmvusfHnMN8cYSOdAV0WICx74ppnK4dq-abpIJcf8natzxelizl4VQb2WR1yIfNvpCSKjEDhb2l6wVof1EO0ehXk3i20KzHmu45eGOp9ye325GDgnaTLHjsBooAVXsYr1TIzeFaZf3ATzaFaRomRLV9kyacEM16IA4i1QvfBtZjAB0hOoUuXbYYbD_VMggtWIVslKzDLWvrP7wtOhi6vHT8R-5P6LRzpC0MJ7gDA-HizWJCsCXBBqXYDnpddVR3VcXxLO19ASsHPXD80w9N6TtAbpG7qenm5epGTY_a8-MZQx3WYQqZov7ls79u_R8K_JD-Asq11xTBXBKmQCFjLkVJuZI2P4Sq1VuoTTwFLi-NfYf__w4AaCj7hTK2wmt4ZkfUyRQbkAdw_oMC37PuBobgH1b5SwA_D9ttJaIbOLOuOBAxfJqR1D575GR4hFPZuH2i9WohLfwZUP97XlMv4LxcrkdP8xKg8nNaXP4dk-GQNTdepqLeYlVpbza3S9vepZ8_z54pN4tfd6eZfeLgklqQD4ex1UEW6rnDNTLktNApwNJtsrUHbwGKkWhgvdYHDxhTEvsWbpKvrVXTuRA7y4NyEdDYri_S-W9DQPWRPgWmVTYkf-QXCFgG2ahKf9gIv5Wadv9oFvOsIgqsWYHQEQ36j_SylK-x9B02jvJiMNijVbYc7i-XhtpVG_R4C5hyKhx9SheP3f0KC73YMDJB9e2GUf79d8EBvtFI-QmGd4_9yXlvCoJfw04Mkcn7yPGAFpqFlRLC8eHY3u2M-vvtlzjDzGd5WP9R7yHEjGNGKv8ziMCAfR0cz1NBGwhDdvFjEzsvB7Pf5UEewO2EeeBUsrGHZ0fM_zPG1cAx9ZKg5puS4z0sXbsQsR3_Sg25U4WPYycvJFUBTD5DAzCDuGc1IganuS0bHIXvflcjNRPk_Pt0z2VROZs50wiLB3sGU-aTyYvb-esA-yjeB1F9ylBMwPhvMfrfh3x70hgibhCothmxViRaqyu2vXtXkLSDZmMrPdz4h-WSS6PTtct8SBhx_wcRgb34V-IR1NS7HywGQotqLPpb8idTxlGzsqOwXatLjkSSKiWScX4CmQjxPI0B3x6hY5q8tcSiWQCi6mamcg7xboyhqp84E-6XveCziMfPYys_MxqPb8mKx5pLqwg1skA0bPGW6lWnhPwAEEpW_Qpe7Idg64ZizQkp1FhPQWevI-Mu21Ln8pBVEkKE2CuzGQwrDGb9bOsjl3PpjH8HneTvl5HS2XB6WdTIWIs3Qaxj7QkxNrCMIfqsLhDs5ppZc3DpTfAcg5wesoFLfSlSXALtkPoGUpCKSSCx8_EipoY1zTT1b_sa_SXs5ACHWHWBWvCVCSXsNSeN3DHZbnsGf6VERyTkzr0lM36w6E6tMUAxqjLufTecT91jVp2r3LNmzL_ihwgi1KyvnweEreIu6Pu6HFjhkmIsPuE2nevz1pDLjkIB09MFMG0F0FpvYpQhWpRp3IvjmcOIhRsB_ihFRV51WO4Qr15op5MYNtM-_fEZYzC9KnWXKSd4cAQE3SSOtIZCHGXTw7v550TKTpv7HlyhhBhd4oqSGmh89SB0eIxrQT87wzkYvqzUvRcHPjhq4uMq2zihzeZzG8L3M48mRthcXa9Reb05sSBnqXZ_Liv1kRCV9aG6-U1n8_8KNIwFCB7wtaFo0P-lFcv2JrWgHtQEh0W7RHi0U66ejRoFNz-48tvThF203nBITuLRTFTB9nrpSfGFfGyL60oiFLxU7C6NEHR1u_XhlNScV4jy6C6y3teT0tkJ1T7-QlJ4uHK72rry7jjx_fW_rJ2_kO7IHKGURcVCibBrSLY3to4RbwJCEJ9pWyvNBcJxbwKZXBKMkx8uLlPTdz0IQMSEAlrN-l0-US2qFNr1XYqlJcLnvKdhpltuIj71tblb-tBNhlSqXNE9774-jv4L3Xi7DdRqT2hCVZxszf9nIW3vNkp5eCSooonZCXpXAqm4RXCzejnL3zIN-xKzJy_72hgG_h4g0xcMKTKnOZX6wX2mvsrubN1sIU0alQ3icPgFulfZUgeva8z_3Ev_SZl65Obbtoz-G3Q5bGt1xRFchXYQqLy__gplsOAInAvtnQNw-WkWyK_EqUWohyJMfr8CBCFI1Hle1AHQIFldacrGsD6mb5w6cTqpTbZ9kgZ6mp67rE8q8bB4y5e0KAT0zwQgmpSpWvNdJDM5BajMS5th6YQs-jqgsra1IlSVBUhfl1i9pAwQaNxXkgbtaJW68l2Br8p2UUhy6CRoZy1CgLi_nG8AwcYzZGagc69JHhUZDAIbQJeRnsOqCO2h0cCb2Hvg1ysP6MgwNTCYCsTLGKzBAJcjoH7Ur2CSycMaFd_04kVZ10ERYzsTL0-JHyhFHjb_MDCplPiE_NlQ_FmF2mDXXuF2qUWthWBzA4KNCUt4Zbfi-ulg-NXRkkAwACj4fHIRmKUd4CGlRJxEhtQOXn5H910gDrDUl6Ti0OHAV-wWvwy7Bcz8Xv5CkHQn8Nr5zH2Qp5e4IWX0XlNLaFdBodrAaWoNzioOMtWkTn1NFxRR2NqDI7wjHlzNcEphkbN2sW73dmy5g5Kxypb3z40wdlqtVY0Bd08WKnVQvP1dQlCWIPanJbqPra6XkjxmiHdnSO-3_kjJgvdoqYHEwobItPEh5C7cpYPXR6FDohvQOlrQdgIZLVpvG3yOlTBDFly97DZfJl95Nf7vIK3b2UBjP5Y3rhjUXP1d5eF0PigVKA8TEWyxiT211qNGh3TFG51HJO7CED6-rH3og-_KdhwI7lD2mTSPLoOjydapMDmwQJ3L8yVljZnoZ4e8nyzcYiOJHFukruS6nPeLCh9Fxi39ZHxmb5ux0DZFi2n32BjOiLAatuy3cRnEa0Sczr9i2_D6scU9pNinGv39PfTOZbgbPzEJtr_9Nzo1DA6Cc_W6e1mgUehysK7jUZtq3ayO6-CcywQ4TOMQ2GyuLiXJvN3U4HSRPfARPdd19lXNEY8CRf7JgfOiY3Y5dE-YtVQPLkHqPw3PTZIs1CwdModXSFvHnxR3N0hXgA01Ex7sisHGmbVE7E6S6Tx27DIl30fwJS4cEEyaPex4sb1I7NZYfUkgAn5W6xXnNyNTv9wRiRJPeOY3xGxyZ16-8BsKqvh4tijntZk6WRpgN7UsZ5ggqQrd6b6q8JsOSp_jy8wLHwCzsA6ZOIsiWZiDF7AViIp5dNrSZjvHK5Xk0be5xunKR14k7EOamV-lFr_eQrPNQLSNQEwxwBQ-1-4ZGBzt4btbuilkxR1g7SsWEFynrlTlEs447sgSsxmZbJKJDfcAyLBLn0LBSNemh2chN5XP_zIQRR2sm_ytJRyIVtalqp-RzFNRdIwEyq3GaChj8w49Z8yA7A-gPiln31PHv7fXbVEhaNuQF7lpxQtz22ou7nx4pi2SQiZ-9-5V1_eLc3bBPWWqWp_isuE-INmWB5voS3TfO8qVUQ5udIDn5z-0OfKNMyXHrdAJirelFO5vRvTgiU8gjwaptEocQC_A4m_D6FI-4vki1IqSghVeiioLBQHb3fdI0aTejL7meAUcqb_9mtbSAbKRsMEFLeGUbNPATOZzZk6_np8qwU3sOAu8CVOap6lM-laLUhj9bYflbC09hsxNzUd5-Ck5R6tqKTudV_roPq4yJ-qSFS9ajkLVgYuuEfsEbm3JGmT2u16qySNLOEpilZDfFmsauX_NRLd853lrNp49hPWlUyQobwLnsWCvLXb00TIH1yTEvzdDHuWtdxZukjGwdss75wb10r5M9dJBxB-F61gw0x7sfBp_n6yV1Pss3PENNTM8TkMR1d-C55xQGhFZSZL3ajEp65QP9rw1_uflTKrjyom1Gsthkk7CqnzAHscToUVFyGSwxACKXkMtBWxviSzYTuuhFnoARYTCQCi1M9kuqTiQLlsal5SfC7S6rQct5s6VS4gCv7whmrhXh9Lbxqk5s9ZY6R81_cSqdx9qSTGBCm3qbNj9KWgZo48KFCRbsSLvDHApUuZoau1ZT2R9B3kO0knZWNxXDAjM9u2RhEUvAyj_GYAnYyiyBPSS4fj0vDnl_PEVkfoheLbJcS8s4SLKBVUfemWzQurGZ0rK_kQ7OBs9BtI-_b_jrsnr_0IKIlO6GYcPhSdJF2gs013Iya9RYr96SDmIDB44xhGcz1duzquqYIEiWLyXXSPliysAOY6L7cVyX3A9MiEqBAl2xzW0kveIagzCKXIwcPZsKFIt7JU3wJZNYmATSzvC0CHole0fob1cO6NLKC5finurlNCZMSUKtrbK9U0boeQdoeDRWvbBVFzfhRmC9MlVEcSH3Y4Xbbd1P1YlIwuR7TOcYXWfSinfanX7Ky5mKJn_m19T70bY1TlnWb_MMvHRRpdSM1D8vg25snfuYzMxZFzow7em-EuHam66E1oRJEmXk5KI1RlNycq7Vv4ls8II-Jvrn9xJwtEcTGxEbBqUMt7FEEiOaTAGvh7G6vAd56O5vPlV7fAWlNtFbHcINyovlcmYSiPMIR5kBVu1XPdzjSn5Sb8h1k5oNR3Z1cUhL7_R7PHvpXVjRQ7p4gaqIK7IKX-7lazkgC4RSUVoSq81OtWF7gyVLcDCTPg_s4rxVZdut9LEvnnRyrDfeVSDSOdpzL0J_BPr8OdlU_yGpVIOgukwUcBgx8j2ETgHW3naJMqdMYG9e7hyQjXjw9Fnum30057kCfPnbEp1R70skd564Rs2yk4k6frCOu16jxqAB6q_6Uo5ArrdUAA4EjLqBP1ITc2-SwW2RKYW4x6N9AXt4PI2L5wbDHEjISMvx5NG4SH7wmR4Yn93UzRCsv_j0tmggvlJO8C7jVc4Q9iEjgGHMb687SpnUv7SvfqOH3wRrKbLxEfapsCJ9EfVUThUCA945AChJEao_M2amCRjj1FlgNSDpyL0gKIRPcIloRv5XPPuMtM-dHA1dZmpL5JyBVUPoeJlf_Pm5ptjNiQmDSLKOS7owIQ4-nWVRLGT-zcoLjiTjnBRR0Il9RZ0f_1ynGScEi38xv2lUn_3Tt71iXNgdjdIU-tXubBjmcYxRMhVd0zKM33r8cWX6iAY4OZ1bPHCQtZGW3TZtOu8oVRA7Wf6kW8s_QSes0wXRH66xSl_R1ZquJ6-FGnWf-snM5u_f0seCWmitgU8heNCmHIPEOw81ZDP9HrgfDyl4mpnrS-jHWb1TjHcFWmebHhkbep7yLcEcpwBW1dZhT1QSLmR5TN6Vfters4NpJT5-I7q-BEaDoVfYFMWOjlBG4yGSBfduUoZCwe87zEMEEsXw0njn_WgNlED3B5rYsHSCL2fCA0Cd79XW8HpJdKh0oSNur59Ap2PX7_RLk_ln806uUXVwmj-_WkMy-GdkDoqtYBug0NbD0Mgwr3QdvuL1yHvlbPkosrTNks2FjSLXSAK0aMyceWA8bmLw4FJntksy8fYZJMOw8rnsOCzwje1oiragftpRVA-xakt5vIUG6c37uFjizdt7bXykzBEhFOGsgRC5t65j2MPQDH877HgAQSWUJYkp8cdCmaIRk4W0DqMMGTUP3kw2EGD43lIvYBsxHM3kInuuXYz9hy8do8GQ3--7RyKyNLDs9wSFSLkMrCx_uMzw1T2wOtPXfc5DlCPGyma-Fdw0Hko5Dbi4B6JoylRws_YPNxEBE1KrWXnKSLUppupH_BBycIVlgFkiDUPNvEHiPTsKCnoEgj_R3qlW3wciI96BTD5oG9MmIAtY2R024bYb32X3KYZaR--41CBmmOHM5ORwFIb_0OaBcYAvrXUw3I2fuvTnW1DP-8WuP3c5hPvf-1bPGXcmT4rxXASlwxddcIyeHmR0Ec6Y77lxeklm1oL_wVzMtPwNP_58u9zTIC31nyFkzlrEFiP4qTdCWtlWVx3SRpe1casPZgJ2uGVlNwXJU3SR9GncTLAiTRFs_mNqS6mML0o7Yhlzu7mdW92lpEEV7zdliWKjtntOSvA6ZcZOHRG84AFB-tMB8tL0Q9YC1iiAiP9oM_JuyCEPsHcEqi_zNbhsHaWWWmKJtA55QcN7KY6z9GJk14SrGsY9zqcz2xCmuIdZ8toC2PCbK_bZlnv_2fmIsLd4VNsCyvzM_nFMX5KFep3fGPvTUEifEs_31fb9NdgluhTxSgAHI2zDzfrGtLXFfZcQJY6POqTPQyJvbAyvp9gOM2aHZBdxxecP7depQEAXybywCOnOfEFAtEd8GRxVnqOKZ12RHZBjgyyzLWr-X6N1ZVAs231V2GuDp4kO9VAuD03htjF7TryXfoa5E7xuXXxXNb4u8RNB4udg2ugN18Pehxcy61ypgpawltHu6Bmv_ZTdYYeiAjXtmaI9A-R8R2GBW8ue-RZjBqfZNE8I4FaOXtzfuAt21fQ0nhQZqXlNSPfgtJ3L4UcH-19pJ8EwNueGUWraQifDLe_gy8S67Es0qKp1YFN7mZZTTIBxcB_cBxfJ5y_pziVBOZxVC5VDdcADafjC0lgo0PnsSuCl3JixHz5"}}
{"timestamp":"2026-02-11T04:15:15.545Z","type":"event_msg","payload":{"type":"agent_message","message":"I’ve confirmed \\(m=5\\) supports perfect sets of size 8, so the key question is whether it can scale much larger. I’m now running a stronger search for \\(n=16,32,\\dots\\) at \\(m=5\\); if none appear despite heavy search, that strongly suggests \\(m=5\\) has a hard cap."}}
{"timestamp":"2026-02-11T04:15:15.545Z","type":"response_item","payload":{"type":"message","role":"assistant","content":[{"type":"output_text","text":"I’ve confirmed \\(m=5\\) supports perfect sets of size 8, so the key question is whether it can scale much larger. I’m now running a stronger search for \\(n=16,32,\\dots\\) at \\(m=5\\); if none appear despite heavy search, that strongly suggests \\(m=5\\) has a hard cap."}],"phase":"commentary"}}
{"timestamp":"2026-02-11T04:15:30.822Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"python3 - <<'PY'\\nimport random,math,time,itertools\\nm=5\\nR=int(math.isqrt(m))+2\\nS=[(x,y) for x in range(-R,R+1) for y in range(-R,R+1) if x*x+y*y==m]\\nSset=set(S)\\nD={}\\nfor a in range(-20,21):\\n    for b in range(-20,21):\\n        if a==b==0: continue\\n        pts=[]\\n        for vx,vy in S:\\n            if (vx-a,vy-b) in Sset:\\n                pts.append((vx,vy))\\n        if len(pts)==2:\\n            D[(a,b)]=tuple(pts)\\nTang={(a,b) for a in range(-40,41) for b in range(-40,41) if a*a+b*b==4*m}\\nNBR=list(D.keys())\\nL=80\\npset={(x,y) for x in range(-L,L+1) for y in range(-L,L+1)}\\n\\ndef eval_set(C):\\n    C=list(C)\\n    n=len(C)\\n    H=set(); edges=[]\\n    for i in range(n):\\n        x,y=C[i]\\n        for j in range(i+1,n):\\n            dx=C[j][0]-x;dy=C[j][1]-y\\n            if (dx,dy) in Tang or (-dx,-dy) in Tang:\\n                return None\\n            if (dx,dy) in D:\\n                off=D[(dx,dy)]\\n                H.add((x+off[0][0],y+off[0][1]));H.add((x+off[1][0],y+off[1][1]))\\n                edges.append((i,j))\\n            elif (-dx,-dy) in D:\\n                x2,y2=C[j]\\n                off=D[(-dx,-dy)]\\n                H.add((x2+off[0][0],y2+off[0][1]));H.add((x2+off[1][0],y2+off[1][1]))\\n                edges.append((i,j))\\n    # connected\\n    if n:\\n        g=[[] for _ in range(n)]\\n        for i,j in edges:\\n            g[i].append(j);g[j].append(i)\\n        seen={0};st=[0]\\n        while st:\\n            u=st.pop()\\n            for v in g[u]:\\n                if v not in seen:\\n                    seen.add(v);st.append(v)\\n        if len(seen)!=n:\\n            return None\\n    return len(H),len(edges)\\n\\ndef random_connected(n):\\n    C={(0,0)}\\n    while len(C)<n:\\n        base=random.choice(tuple(C))\\n        dx,dy=random.choice(NBR)\\n        q=(base[0]+dx,base[1]+dy)\\n        if q not in pset or q in C: continue\\n        bad=False\\n        for c in C:\\n            dd=(q[0]-c[0],q[1]-c[1])\\n            if dd in Tang or (-dd[0],-dd[1]) in Tang:\\n                bad=True;break\\n        if bad: continue\\n        C.add(q)\\n    return C\\n\\n# seed with known n=8 pattern\\nseed8={(-3,-1),(-3,3),(-2,0),(-2,2),(0,0),(0,2),(1,-1),(1,3)}\\n\\ndef anneal(n,tries=20,steps=20000):\\n    best=10**9;bestC=None\\n    for tr in range(tries):\\n        if n==8 and tr==0:\\n            cur=set(seed8)\\n        else:\\n            cur=random_connected(n)\\n        met=eval_set(cur)\\n        if met is None: continue\\n        val=met[0]-n\\n        T=1.5\\n        for st in range(steps):\\n            rem=random.choice(tuple(cur-{(0,0)}))\\n            # candidate add from existing nodes within 1-2 hops\\n            base=random.choice(tuple(cur))\\n            dx,dy=random.choice(NBR)\\n            add=(base[0]+dx,base[1]+dy)\\n            if add not in pset or add in cur: continue\\n            new=set(cur);new.remove(rem);new.add(add)\\n            met2=eval_set(new)\\n            if met2 is None: continue\\n            val2=met2[0]-n\\n            if val2<=val or random.random()<math.exp((val-val2)/max(1e-6,T)):\\n                cur=new;val=val2\\n            T*=0.99995\\n            if val<best:\\n                best=val;bestC=set(cur)\\n                # print progress for big improvements\\n            if best==0:\\n                return best,bestC\\n    return best,bestC\\n\\nfor n in [9,10,12,14,16,18,20,24,32]:\\n    t=time.time()\\n    b,c=anneal(n,tries=25,steps=30000)\\n    print('n',n,'best',b,'time',round(time.time()-t,1))\\n    if b==0:\\n        print('found',sorted(c))\\nPY\"}","call_id":"call_6q0ggmj0saV8S2TAeosKaLLE"}}
{"timestamp":"2026-02-11T04:15:30.851Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":340601,"cached_input_tokens":280448,"output_tokens":30712,"reasoning_output_tokens":24255,"total_tokens":371313},"last_token_usage":{"input_tokens":35302,"cached_input_tokens":34944,"output_tokens":6186,"reasoning_output_tokens":4868,"total_tokens":41488},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":6.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:15:40.977Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_6q0ggmj0saV8S2TAeosKaLLE","output":"Chunk ID: 4bd25e\nWall time: 10.0010 seconds\nProcess running with session ID 69270\nOriginal token count: 0\nOutput:\n"}}
{"timestamp":"2026-02-11T04:15:41.010Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:15:41.351Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":340601,"cached_input_tokens":280448,"output_tokens":30712,"reasoning_output_tokens":24255,"total_tokens":371313},"last_token_usage":{"input_tokens":35302,"cached_input_tokens":34944,"output_tokens":6186,"reasoning_output_tokens":4868,"total_tokens":41488},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":7.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:15:42.308Z","type":"event_msg","payload":{"type":"agent_reasoning","text":""}}
{"timestamp":"2026-02-11T04:15:42.308Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":""}],"content":null,"encrypted_content":"gAAAAABpjAJuyORdXIXGBNswwb9tbGioDzPg00OoRY8q1EHcq46XdbS76eMkwtH7lbrq4ePf1Gx98XfkbPBRNv7j9oSm2VTnto_uh0J0yHeI2HaFpsakzTNLWVoJXvrI1OIfyRysXoZkAEk-KbYjPaei2MfJWr4IBARrYwZICnSZOh78NMQd_72HMYf-mRUjNNNmBfP8M5nqt9IanNGoikAMG2YkNWeKAafpGRG40V2gDAeU-PY3E4Xyk2uPK-XPrUH3F5llkjI5budOZlssMmeVTaQxBnRcuWZSLLoYAhnefZ4RZSbyZkOTVp2udo56d6aexTNptJCcbcZU1nCcjylCsblnkmGdhuoTeiCu_6n74qXzovbEBXq5QO1643tbbgXd6TMKu3juMwPCsmKFwAlJcmVyKDuPQSMc1pzdXM6CA-KK3OkvCrXzOSmzi4kXeSsCzwlgnRjdLoqYtDz8qM9_rWFmuIDP6qNAPtRex8AqU7YHSr-qgyHfntVLCiVOaSqfbOxQztrnD6-dGFjxeyYbJo59eNdWKotxE5pyBysJvDRN9m2kKOhDqqxDg5xJJ-YavYTvk5t0r6tiwhea-O6NTmb90CACNmsuyjn4b7b1-YZiRHRrgtBpgq1qr9AvjzfoQrMotyQdNITJEnKfy4MfU-rxONm6V1Xt6pEqhFrX-HsCspufRMizVHdaJ8Xb_1h89HjQifwbagl-xoHEqN4JnJkwzAGZFlrL8Y3Hqiek2oIJcLMib-5aKrreMMQiSmifKqiiG2TYRwWslovBxTPomdUt-x79g9pZqpJF5e_qLInJS6ba7fr6Q3-C9ODYfnLbJ4Sf-bV7YOE2MRYGyG82AzrPF4gMbgH0b52_ySkUfAwG9ah01mE="}}
{"timestamp":"2026-02-11T04:15:42.681Z","type":"response_item","payload":{"type":"function_call","name":"write_stdin","arguments":"{\"session_id\":69270,\"chars\":\"\",\"yield_time_ms\":30000}","call_id":"call_9SLljkRvyuWlXQxIPYwk5z6J"}}
{"timestamp":"2026-02-11T04:15:42.687Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":382137,"cached_input_tokens":305152,"output_tokens":30753,"reasoning_output_tokens":24264,"total_tokens":412890},"last_token_usage":{"input_tokens":41536,"cached_input_tokens":24704,"output_tokens":41,"reasoning_output_tokens":9,"total_tokens":41577},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":7.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:16:12.719Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_9SLljkRvyuWlXQxIPYwk5z6J","output":"Chunk ID: 8cd921\nWall time: 30.0017 seconds\nProcess running with session ID 69270\nOriginal token count: 0\nOutput:\n"}}
{"timestamp":"2026-02-11T04:16:12.719Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:16:13.093Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":382137,"cached_input_tokens":305152,"output_tokens":30753,"reasoning_output_tokens":24264,"total_tokens":412890},"last_token_usage":{"input_tokens":41536,"cached_input_tokens":24704,"output_tokens":41,"reasoning_output_tokens":9,"total_tokens":41577},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":7.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:16:14.323Z","type":"response_item","payload":{"type":"reasoning","summary":[],"content":null,"encrypted_content":"gAAAAABpjAKOWJMF3ZV4TbcpDrZwt6MsZg2gffazYgolIF8RCtzPk1UIffQfLapNU2tHcZUfPAHnR3x50reN2P6IpHv6m4U6tDJD65yrrbRTi0eJimbLwBlnpXbVVEgmsITCnp3TXXUZRG4ARe0U7d30NwdLpZysI3mi94ivydkcU_23ld9D2wKp2_fdLarEQ2ibWjLGnW3v_HqUSKbNR6UnBWpMrsUQfAN10H4iCdvHR5A64OChE_glJeDi0ETgG-rKKK0UeuGHF8bq6K2Ic3v6a8hXXHTuQx9sfGU8Xippr_CZp1nCfYnDSEjvZKFZs9Se6RL3HGIvO1JklYDmlfjzX13cZtYNO_uVgCMVfwdMpbVHzttR-DcCuTKXjn3CexE3WN7XVY2L5l5Nmm_5sj-NLYCCYu7ScMQXnNQ-AnZDCZ_xTBPddXWiJDzhH962xtuiWh58rz-bhldjVIMCwkYGvhtBmz_OiUUlAfEB6WHSVCJwsafaIe_I1lvJROq0N7ZPZAGvR9DkwunWGavKao505Ym7pwxUCe5qAuHjrAH2g0BoydIRfWU7yY3QF0FWRD1hD5IJ7DbzAnubslYUapxAH6oQTnqGxljcn5Pj869roieDrqo1XGoLXWCcAS6nG7kExh7pmFz2bDsigok4_TewzQ8krh2fwMwpJzy0nKv8jo0jannjs8l0BOTCzBmiO6393C6ws2L6f5wP-RQBL_pP4owNe6GRrsmKWMoaJag1aJaq2pLXrsWhe-Q9NG6Pwt7zX7ySJrxJMGX5Om41DpKAlxaLUYl3OVKZEGl84GuTMXXtjf47BgdYNjjffYBnqK21uv-EXCmwMnvVZUA-7_RjsRicfGCgxhqqUJmJCE4sfccV3JQfNPbTprocf3zTxkAd2-4Ys4UY"}}
{"timestamp":"2026-02-11T04:16:14.395Z","type":"response_item","payload":{"type":"function_call","name":"write_stdin","arguments":"{\"session_id\":69270,\"chars\":\"\",\"yield_time_ms\":30000}","call_id":"call_UHGdRfbQ06WH7Mi0h4JYdi87"}}
{"timestamp":"2026-02-11T04:16:14.401Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":423762,"cached_input_tokens":346496,"output_tokens":30797,"reasoning_output_tokens":24276,"total_tokens":454559},"last_token_usage":{"input_tokens":41625,"cached_input_tokens":41344,"output_tokens":44,"reasoning_output_tokens":12,"total_tokens":41669},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":7.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:16:44.431Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_UHGdRfbQ06WH7Mi0h4JYdi87","output":"Chunk ID: c00465\nWall time: 30.0006 seconds\nProcess running with session ID 69270\nOriginal token count: 0\nOutput:\n"}}
{"timestamp":"2026-02-11T04:16:44.431Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:16:44.838Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":423762,"cached_input_tokens":346496,"output_tokens":30797,"reasoning_output_tokens":24276,"total_tokens":454559},"last_token_usage":{"input_tokens":41625,"cached_input_tokens":41344,"output_tokens":44,"reasoning_output_tokens":12,"total_tokens":41669},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":7.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:16:46.065Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Noting potential long loop buffering**"}}
{"timestamp":"2026-02-11T04:16:46.065Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Noting potential long loop buffering**"}],"content":null,"encrypted_content":"gAAAAABpjAKuVaWlzJvo9HlMffdXapPhghRY4_CdS08dI4F6rSBXRjZuckTV4kiaDbxdMs78I6FrkS95AIQQuFoD_l9YDpAQ24rWda--qiZnL9rkd--e3TPSadfsSs-0Ldhy4fXk9EQVOIWtmWfVM4mEfUYxU9xHcj5Ff1W_gG2ezrcgS_dNiFfUN0PCkd8pSUgoaEm1toxmm6LNqeFJC8HpTV0uhHOtgRIpKMUMrk4RM5fxYjWNzyisc0dDAsYg_olI-8nkybFM6jwtyAlQyB_wKjPYe5tEw4gCkEMG6Ssi8l6jqN-W7UxZ_jnDkX1wtHGqDyzH6lygnG2hhS-DJyck3JDesfC11rZI1NQn1uqq_HHIW5T_X_tc5cYeBHSLAg3iNQpyyEf5ScbcuMilpSZilmjZ8x6CgH6eGNkN8bcWEarz1RSSjn05gpgR8-lzs0UNcK7a-omyDYVuzyyM1-glDDr3B31BIUEcQ1FLNSNe3BHh27IE7Vzgxb-XpmkjpRpRd5rl-BJmI385S6-UUsgAoC3RRHMQUaBHCYU9oCTx4X3qy5pRO2njzcNuQjQq9LF3SngDFBuQ7iHJhmxPBsPHn4WO5AWaqkN3fmeSBVv6ohGPHerewanf7gY7qj6-hKfdb2yc65tJHaMHsbrEi88zw7nRkowwYr6Qmj7mMaMaRh5MES_rHNK9OhNHTJdXcVt5OSqyZAdpYq1NnqVdNPYIL1ZiLGMRhSezbW8mj68_jSZEbRiowdlkDvBY8ZdlAwU01tzsd6IuUmWHlmbznHi5VVdpCxw5eE53nvCKarVyPx6znpzIeUXCW5z_s5Vt5OMtpl2uzwH6iwfJBdMxnUpn7r8ud1d4cyQHMtBNMF47N6Bbj7oZFC4yKZEa06lGWstTu3_RVDI5D-C550V6zdnMB8eu61crhO6LpW8IR-RnyqMuW7SAqOoiHm3DRi4HDHiZA0I0dRZg2kZV0vurDyR_iIH6YhQHznKNzkvsRaJv-5FIOeN3CbZxlbFGxcSeh6uukDWR3MxY"}}
{"timestamp":"2026-02-11T04:16:47.601Z","type":"event_msg","payload":{"type":"agent_message","message":"I’m still in the high-iteration search run for larger \\(n\\) at \\(m=5\\); it’s compute-heavy but important to determine whether size 8 is a ceiling or just a local artifact. I’ll report the best gap values as soon as this run flushes results."}}
{"timestamp":"2026-02-11T04:16:47.601Z","type":"response_item","payload":{"type":"message","role":"assistant","content":[{"type":"output_text","text":"I’m still in the high-iteration search run for larger \\(n\\) at \\(m=5\\); it’s compute-heavy but important to determine whether size 8 is a ceiling or just a local artifact. I’ll report the best gap values as soon as this run flushes results."}],"phase":"commentary"}}
{"timestamp":"2026-02-11T04:16:48.010Z","type":"response_item","payload":{"type":"function_call","name":"write_stdin","arguments":"{\"session_id\":69270,\"chars\":\"\",\"yield_time_ms\":30000}","call_id":"call_kzoQ4DdDokN78MKqHz3equlK"}}
{"timestamp":"2026-02-11T04:16:48.011Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":465478,"cached_input_tokens":387968,"output_tokens":30928,"reasoning_output_tokens":24308,"total_tokens":496406},"last_token_usage":{"input_tokens":41716,"cached_input_tokens":41472,"output_tokens":131,"reasoning_output_tokens":32,"total_tokens":41847},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":7.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:17:18.046Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_kzoQ4DdDokN78MKqHz3equlK","output":"Chunk ID: 5883eb\nWall time: 30.0010 seconds\nProcess running with session ID 69270\nOriginal token count: 0\nOutput:\n"}}
{"timestamp":"2026-02-11T04:17:18.046Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:17:18.425Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":465478,"cached_input_tokens":387968,"output_tokens":30928,"reasoning_output_tokens":24308,"total_tokens":496406},"last_token_usage":{"input_tokens":41716,"cached_input_tokens":41472,"output_tokens":131,"reasoning_output_tokens":32,"total_tokens":41847},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":7.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:17:20.088Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Considering timeout for process**"}}
{"timestamp":"2026-02-11T04:17:20.089Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Considering timeout for process**"}],"content":null,"encrypted_content":"gAAAAABpjALQ_SwAfz7SRjIu_ctSLemAd0ddDR-JYDe8s1yw_WIYBzvoJ52-kTEsCNh5DmkPloHMBAWJGkP_Unw2dkaKS820xguZ6Dru4lqgXaKKzs6-rkVaobCVbtvcvioomPNHoReYd-gN7Jiw3T_Q8aDNE-I_BEtBbZWF-tQiMzwaTLKWAfXSm1RqTo4EB2sK0wh5SKQItuZuET9rWr9UOlW1K3ycTkvTYoCJKrJ3qDGxKCJsQTLNm3XjUbBNj4gf9BJmo7ysdXjIqDfgPFjtI_eLnHnBYDyiV2sbsy5tJSAwu-Iw2DUC839A6vV61i5pZhpIERNBJwcYJiREfan93HhY1YaIGUFOYrNp29d3al0gOGt7VP54kwpqKiYmMkD51AKuwTuKaWA4yVLu11HcxlwcdxrmS3dpFe4tylYjo6QJKF5IG5CO4hK_FHLI630ZBQQjSFDevBn2lHuT35C2orzx3t8Qyqi4qa928AT9sY07QR776DwvebhK4z-dyToVb8HMwc0fVRbjRjR_Q2NWlZARx9zTybVwoUHjZcwOFaBh5fS6tLcFRvkQfTX1m3TbQWZAB3w9Mr5ypahr4ICdraC_p87ItAhUV2DPSSm-23G4e2spPKABK7dL7ahRh3hX637SxrwyznpW_AiYFOTRH7bvk0stftkN45TKA13vr6-HIolUYkd9f-hONW-BWxnHnA3_taUJNKoP2n_n6vS5SVNRJ13VIvB0cpEjLUO17TT5pwujVqPVUxk5wQ1NWvCcErUrM9gsYnuE5hL6-nnjazz0c41Y3n1hFfEdW9oMT674f8Ym2zjz-xt9iq3-Y039RQfAgkqcfVKeX-01iMINgg8FIkTsWAxdCxy6aHGzp4t6zyiQyHdv0CLLjJUoQPR-qmSQZ_-B096xWDZuIGYvwanGm5aMzk24pQ2GS4L06vVUtPalvKYmNdp8Rpem_AIHYBMY9wtYd31fsiiHihM8CGRJwoCdJAfMx0hBySygaQ7jQnnGVdiiTP4ot41wC3TbFZOxSQqOHiMvaqUDVRbZJlpLgJAqJ6CutwgXWdF8TQBvgCLsZwGv1lTcX-fACi-thID6RzwKLHLQ9LqlK56kxnn4T3v6ORoXpyNxvUPOxfc6g0hf5ykl3OxT_RSIuBWEpl1_i2w5TIUxzW54TY1UqbSt-L62xg=="}}
{"timestamp":"2026-02-11T04:17:20.573Z","type":"response_item","payload":{"type":"function_call","name":"write_stdin","arguments":"{\"session_id\":69270,\"chars\":\"\\u0003\",\"yield_time_ms\":1000}","call_id":"call_79lCT75OTPiqkR4egO8WhMF2"}}
{"timestamp":"2026-02-11T04:17:20.575Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":507373,"cached_input_tokens":429568,"output_tokens":31018,"reasoning_output_tokens":24361,"total_tokens":538391},"last_token_usage":{"input_tokens":41895,"cached_input_tokens":41600,"output_tokens":90,"reasoning_output_tokens":53,"total_tokens":41985},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":7.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:17:20.575Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_79lCT75OTPiqkR4egO8WhMF2","output":"write_stdin failed: stdin is closed for this session; rerun exec_command with tty=true to keep stdin open"}}
{"timestamp":"2026-02-11T04:17:20.606Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:17:20.984Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":507373,"cached_input_tokens":429568,"output_tokens":31018,"reasoning_output_tokens":24361,"total_tokens":538391},"last_token_usage":{"input_tokens":41895,"cached_input_tokens":41600,"output_tokens":90,"reasoning_output_tokens":53,"total_tokens":41985},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":7.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:17:21.931Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Polling for output completion**"}}
{"timestamp":"2026-02-11T04:17:21.931Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Polling for output completion**"}],"content":null,"encrypted_content":"gAAAAABpjALRZsg8f3Q2YyKkj7TCr1bhb3Kiy7Sh04m-KXAd38xiakYSmKfsuZRjAIX7YM4IvtjRfHQT42o-4Mn8BOaL2qgkRVvGCtyxxoldpw5LGX-kTZGqttelNqnDWR51HmncWKU7Ty4H8qnEXf8S6R0pTXKVNmgnIaDLAUN49bUWFlkRZA-GuctMLxNbSSE8iNZ6v8wdtcuKnKkS3FgVuSagtr3_VtvzRZwP3_mixpkbyqiCUr5A82PYthhLD8ZcsesT5Il3yj5hmq1GoKX2D5SA7lPqS0zIq9DnssQJBcuTHHmmHby-4-5O8AdKxI7hK9fc3BMR8rpxv776QLz5qefMP8IMaMdvVEeKPt5xwjAl0krF8HCTjmGumFii-ph596o7RG0_7N3L8RA4TdVz8t3LqfGDbrAk6Pw-Z2VMFxEPUHdF4h21U24OQOaJ-LjnXivuxdq5Y_3LP9bd44aYuASfG6jsL5rh53yNv16Z8sWC7jtkT23OxXcUEtwrNduGAHcw3XmD8F2lpVsJRRAELhnGC0OUBaTN9SKiOEB21mj3IueYyYEsHsCXuXzwK_Lz3J21W-PHRMY5LWmlpFKx6h6hkWcFZ4pCeR4Oj1kPT3EkEbgeZKhS83leJIINr6MFGSjWnpwteAB2gILBilzYNWxZ7qrvHct6bbalP0D-jFuxpWO9WD_TX1da9PvmZpZMQBUIfWPiHTcLm0G5aGbKQbzRfILbL1Sju9WNZpqDjhgEc2gPVQJXRvmiVLV6KoEYEb_-kPktcwjVl1BsJxAJ1NpFBukQtVE_06nmtXKCsFFXlX0Sd_zRtce0Th5CysiyCtv0ujTf748tOksinFSAGczvf8OsHdE5CGWtGqH1xIxgxGwK1-sJ-_TrbVQDgYOtSMtLg8AiZSBzpwGm7ifa4muEC4F-3zoUVe558bH-IqQNhbsWD6U4JGYXxs_uDoSh5Ne6RlsmoISv-scc31E6L1WLrBn2LYzitOUkLruNxuu5WJT-9KR8oag70EplRsGs6p4j6VbWfN2YAbQ5R2D3nM-JDmyZvw=="}}
{"timestamp":"2026-02-11T04:17:22.521Z","type":"event_msg","payload":{"type":"agent_message","message":"The long run is still active with buffered output; I’m polling it until completion, then I’ll switch to a less buffered execution mode if needed for faster visibility."}}
{"timestamp":"2026-02-11T04:17:22.521Z","type":"response_item","payload":{"type":"message","role":"assistant","content":[{"type":"output_text","text":"The long run is still active with buffered output; I’m polling it until completion, then I’ll switch to a less buffered execution mode if needed for faster visibility."}],"phase":"commentary"}}
{"timestamp":"2026-02-11T04:17:23.033Z","type":"response_item","payload":{"type":"function_call","name":"write_stdin","arguments":"{\"session_id\":69270,\"chars\":\"\",\"yield_time_ms\":30000}","call_id":"call_i3GOd8tyTakEhJg8LZgkcLj8"}}
{"timestamp":"2026-02-11T04:17:23.034Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":549393,"cached_input_tokens":471424,"output_tokens":31121,"reasoning_output_tokens":24392,"total_tokens":580514},"last_token_usage":{"input_tokens":42020,"cached_input_tokens":41856,"output_tokens":103,"reasoning_output_tokens":31,"total_tokens":42123},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":7.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:17:53.034Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_i3GOd8tyTakEhJg8LZgkcLj8","output":"Chunk ID: f8abf7\nWall time: 30.0015 seconds\nProcess running with session ID 69270\nOriginal token count: 0\nOutput:\n"}}
{"timestamp":"2026-02-11T04:17:53.069Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:17:53.548Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":549393,"cached_input_tokens":471424,"output_tokens":31121,"reasoning_output_tokens":24392,"total_tokens":580514},"last_token_usage":{"input_tokens":42020,"cached_input_tokens":41856,"output_tokens":103,"reasoning_output_tokens":31,"total_tokens":42123},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":8.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:17:57.029Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Contemplating long-running process and kill options**"}}
{"timestamp":"2026-02-11T04:17:57.029Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Contemplating long-running process and kill options**"}],"content":null,"encrypted_content":"gAAAAABpjAL1GGBBO990f_6E-yFufzqiwJ5f9IdKLG4I_0Jrj2flsVjIoeUe5vfpIrGDD851kUlb5dKfqGsbOGakVnVRGcJQg1wYeYTfHVSYEPNuMrWK28d7N3O38PY-zT55pJNbAsoAGYs7eMdglK7RZmSdRkdaT8biySQPgZRjhsA46XGStMl0p4NKFsAXxUaQF7yrqIE6X7ovySsuzUCMgDoX3yNsvEcEDl_KDI0ftgOTwkWuK-IBhEOaxZGnwNx7ZVzagY60JmjjbmGmzB8fyq0lQlZ-0SbrlmK94HWQOXQqeisDwfhFjvx34AQDlc-Ndag25JyzKWEpLjgR013pOAbxGS0wP1XakUDYPIrWqB4PC0l5M76hc5b2Hko7gT-7bfGFmp1Y-eeBVVpvDP9w67f8v7pbJwQUO0II9QQ3xkuiGgLNap5Z6GyqvQ0Sidk22Iv8B0_CJiCDArkGBUG47MjaZ7MjC4rM0ceTJOikvZ7naNCfA8Ymhif-v3hJQU6i9ueO7GZcpLbSdxvv-jefylUQpxN11RyPGvuxebdigxOFGXPhXCsirXVWug88xE6f2SzMkE_qlmYgM7S2cdENGLC9RSjsOaxfgx9pmBsSv3Vs2hV_AJzau3rSdtZ7UYOb9e5yJIdeiHI_2DXMG91KJ-H8ZPyo4xvdCjlc3rrT2ojsK4q5eW0olDo5hAq8LNuLgjvj1K3buZSVBmBpecMDVoo4cNRe7SIXXfb7aM98tb3glcNYiWWizNlckSZm_AlKovJXqlWDWE7u_qU18Cn4MGOIngzj8I3fADvu2TaNL_9B0ReX3TFmIHBdd0BY9fHcZ8KJMFiVd3OPziHuqtM8ANXZNFXRnBbkHJ4i6KU7TgD2dR9iPZuu4DdaQxDWsloSUlsqj7eEf2gmuWUsGcegAbdoQPzwfmPHls1ekzep8et6BfYqt8rRvR2yXzaCYAb98L7ximGAyulNVlsna1lwDOZFWk6Fth791M3CZhRhpz8BJTufFFF0W9sFiLUgdL_F7m9nukIpsxiOTRL6hcFi5Lz_xzkkG-FCVgawaaZNfDUsISc-oeFu_1dof1kBrtEeBSkuNkzliBaHTVPHOrrmew6qL9HzbFMyViOsX1Yq1zXqGlGolb5nmHd5td3ReM28o3XWhFWZFwQf00FOj1DkZoIIq_uBB__HrNLjqZJO0XZ1xeYKsFYAU0Tv7LHekA_O2W78dVXKpJ1LuyC7JO_cyDK0Id2gCbXN-28Jpyc6HQkM4DD6-Dbca_XBkQ5CV38_VpYIPB5H2e8vcXmBgoSKnzZRIwQlrkvcp0n7SfCmGFxAYc4fjBAr5nmx3zqpo5_AODb7F7A5lJG_pODiDtxDi1J9O8FId6705UkkYmdv4dUJPZ-NP7_NCtbF64edbDJxYqWPyuOHpSeQQyG-K9TA4oL3sZ5crCnNNKMef6M5zg6hZsGhe1M4B4vTdK-FgjE9xWeylXxWm7hM7qYQpRSUTDD0uhm1kMpuTj9hGQt7DFeP8ceNv1H-WSFGkfyxSLCybSubGTskNKddU-pjl0FRLNzx6noexTvEWZFAOZz22ADoC_ekSPiS-_WQoU8llVfmbcWYvtb-47LhuRv3eWoCgMOYmGdqTBZP7l4Eu0d6azdteTDTFeRpwXo40FZt8FQBzPPElDZZRe8ytUh-JygdNagiApV3Uw=="}}
{"timestamp":"2026-02-11T04:17:57.419Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"ps -o pid,etime,cmd -p $(pgrep -f 'python3 - <<' | tr '\\\\n' ' ')\"}","call_id":"call_wmd6wDWDCHoVaUBE8IHC0RZJ"}}
{"timestamp":"2026-02-11T04:17:57.422Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":591565,"cached_input_tokens":513408,"output_tokens":31309,"reasoning_output_tokens":24533,"total_tokens":622874},"last_token_usage":{"input_tokens":42172,"cached_input_tokens":41984,"output_tokens":188,"reasoning_output_tokens":141,"total_tokens":42360},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":8.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:17:58.148Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_wmd6wDWDCHoVaUBE8IHC0RZJ","output":"Chunk ID: 36a749\nWall time: 0.5737 seconds\nProcess exited with code 0\nOriginal token count: 1830\nOutput:\n    PID     ELAPSED CMD\n1684036       03:23 /bin/bash -lc python3 - << 'PY' import math,time   def vectors_norm(m):     out=[]     lim=math.isqrt(m)     for x in range(-lim,lim+1):         y2=m-x*x         if y2<0: continue         y=math.isqrt(y2)         if y*y==y2:             out.append((x,y))             if y: out.append((x,-y))     # unique     seen=set();res=[]     for t in out:         if t not in seen:             seen.add(t);res.append(t)     return res  def precompute(m):     S=vectors_norm(m)     diff={} # oriented difference -> one u     for ux,uy in S:         for vx,vy in S:             dx,dy=ux-vx,uy-vy             if dx==0 and dy==0: continue             if dx*dx+dy*dy==4*m: continue             if (dx,dy) not in diff:                 diff[(dx,dy)]=(ux,uy)     Ds=list(diff.keys())     return diff,Ds  def pair_points(a,b,diff):     ax,ay=a;bx,by=b     dx,dy=bx-ax,by-ay     if (dx,dy) in diff:         ux,uy=diff[(dx,dy)]         return (ax+ux,ay+uy),(ax+dx-ux,ay+dy-uy),True     nd=(-dx,-dy)     if nd in diff:         ux,uy=diff[nd]         # b orientation         return (bx+ux,by+uy),(bx-dx-ux,by-dy-uy),True     return (0,0),(0,0),False  def canon(C):     C=sorted(C)     x0,y0=C[0]     return tuple((x-x0,y-y0) for x,y in C)  def eval_state(C,m,diff):     n=len(C)     H=set()     edges=[[] for _ in range(n)]     for i in range(n):         ax,ay=C[i]         for j in range(i+1,n):             bx,by=C[j]             if (ax-bx)*(ax-bx)+(ay-by)*(ay-by)==4*m:                 return None,False,True             p,q,ok=pair_points(C[i],C[j],diff)             if ok:                 H.add(p);H.add(q)                 edges[i].append(j);edges[j].append(i)     if n==1:         return H,True,False     st=[0];vis={0}     while st:         x=st.pop()         for y in edges[x]:             if y not in vis:                 vis.add(y);st.append(y)     return H,(len(vis)==n),False  def exists(m,N,limit=400000):     diff,Ds=precompute(m)     seen=set(); states=0; t0=time.time(); best=0     def dfs(C):         nonlocal states,best         states+=1         if states%100000==0:             print('states',states,'best',best,'elapsed',time.time()-t0, flush=True)         if states>limit:             return False         k=len(C)         key=canon(C)         if key in seen: return False         seen.add(key)         H,conn,tang=eval_state(C,m,diff)         if tang: return False         h=len(H)         if h>N: return False         if k>=2 and conn and h==k:             best=max(best,k)             if k==N:                 print('FOUND',key,flush=True)                 return True         if k==N: return False         # lower bound: each new circle must harmonise with at least one existing -> may add 0 new H? possibly yes if both points already existing.         # but cannot decrease.         Cs=set(C)         cand=set()         for ax,ay in C:             for dx,dy in Ds:                 b=(ax+dx,ay+dy)                 if b not in Cs:                     cand.add(b)         # evaluate quick and sort         scored=[]         for b in cand:             C2=tuple(sorted(C+(b,)))             H2,conn2,tang2=eval_state(C2,m,diff)             if tang2: continue             h2=len(H2)             if h2>N: continue             # must stay potentially connected eventually, but skip             scored.append((abs(h2-(k+1)),h2,b,C2))         scored.sort(key=lambda x:(x[0],x[1]))         for _,_,_,C2 in scored:             if dfs(C2):                 return True         return False     ok=dfs(((0,0),))     return ok,best,states,time.time()-t0  for m in [5,25,65,85,145]:     for N in [5,6,7,8]:         ok,best,states,tm=exists(m,N,limit=300000)         print('m',m,'N',N,'ok',ok,'best',best,'states',states,'time',tm,flush=True)     print('---',flush=True) PY\n1685322       02:27 /bin/bash -lc python3 - <<'PY' import random,math,time,itertools m=5 R=int(math.isqrt(m))+2 S=[(x,y) for x in range(-R,R+1) for y in range(-R,R+1) if x*x+y*y==m] Sset=set(S) D={} for a in range(-20,21):     for b in range(-20,21):         if a==b==0: continue         pts=[]         for vx,vy in S:             if (vx-a,vy-b) in Sset:                 pts.append((vx,vy))         if len(pts)==2:             D[(a,b)]=tuple(pts) Tang={(a,b) for a in range(-40,41) for b in range(-40,41) if a*a+b*b==4*m} NBR=list(D.keys()) L=80 pset={(x,y) for x in range(-L,L+1) for y in range(-L,L+1)}  def eval_set(C):     C=list(C)     n=len(C)     H=set(); edges=[]     for i in range(n):         x,y=C[i]         for j in range(i+1,n):             dx=C[j][0]-x;dy=C[j][1]-y             if (dx,dy) in Tang or (-dx,-dy) in Tang:                 return None             if (dx,dy) in D:                 off=D[(dx,dy)]                 H.add((x+off[0][0],y+off[0][1]));H.add((x+off[1][0],y+off[1][1]))                 edges.append((i,j))             elif (-dx,-dy) in D:                 x2,y2=C[j]                 off=D[(-dx,-dy)]                 H.add((x2+off[0][0],y2+off[0][1]));H.add((x2+off[1][0],y2+off[1][1]))                 edges.append((i,j))     # connected     if n:         g=[[] for _ in range(n)]         for i,j in edges:             g[i].append(j);g[j].append(i)         seen={0};st=[0]         while st:             u=st.pop()             for v in g[u]:                 if v not in seen:                     seen.add(v);st.append(v)         if len(seen)!=n:             return None     return len(H),len(edges)  def random_connected(n):     C={(0,0)}     while len(C)<n:         base=random.choice(tuple(C))         dx,dy=random.choice(NBR)         q=(base[0]+dx,base[1]+dy)         if q not in pset or q in C: continue         bad=False         for c in C:             dd=(q[0]-c[0],q[1]-c[1])             if dd in Tang or (-dd[0],-dd[1]) in Tang:                 bad=True;break         if bad: continue         C.add(q)     return C  # seed with known n=8 pattern seed8={(-3,-1),(-3,3),(-2,0),(-2,2),(0,0),(0,2),(1,-1),(1,3)}  def anneal(n,tries=20,steps=20000):     best=10**9;bestC=None     for tr in range(tries):         if n==8 and tr==0:             cur=set(seed8)         else:             cur=random_connected(n)         met=eval_set(cur)         if met is None: continue         val=met[0]-n         T=1.5         for st in range(steps):             rem=random.choice(tuple(cur-{(0,0)}))             # candidate add from existing nodes within 1-2 hops             base=random.choice(tuple(cur))             dx,dy=random.choice(NBR)             add=(base[0]+dx,base[1]+dy)             if add not in pset or add in cur: continue             new=set(cur);new.remove(rem);new.add(add)             met2=eval_set(new)             if met2 is None: continue             val2=met2[0]-n             if val2<=val or random.random()<math.exp((val-val2)/max(1e-6,T)):                 cur=new;val=val2             T*=0.99995             if val<best:                 best=val;bestC=set(cur)                 # print progress for big improvements             if best==0:                 return best,bestC     return best,bestC  for n in [9,10,12,14,16,18,20,24,32]:     t=time.time()     b,c=anneal(n,tries=25,steps=30000)     print('n',n,'best',b,'time',round(time.time()-t,1))     if b==0:         print('found',sorted(c)) PY\n1688399       00:00 ps -o pid,etime,cmd -p 1684036 1685322 1688399 1688722\n"}}
{"timestamp":"2026-02-11T04:17:58.182Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:17:58.564Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":591565,"cached_input_tokens":513408,"output_tokens":31309,"reasoning_output_tokens":24533,"total_tokens":622874},"last_token_usage":{"input_tokens":42172,"cached_input_tokens":41984,"output_tokens":188,"reasoning_output_tokens":141,"total_tokens":42360},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":8.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:18:00.739Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Cleaning up leftover processes**"}}
{"timestamp":"2026-02-11T04:18:00.739Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Cleaning up leftover processes**"}],"content":null,"encrypted_content":"gAAAAABpjAL4AvvbbZlMiXuIKctTLfxLrKZSMg8fhqsK_IPridrcweYOwzLEuaVe5FrjQ7J5Wa8QR1cThSujim-Iu4cua4cnFj_im37aZPf3ec8eLhGTaCp4F5kRoTpfNF5NrR4CScUd-QwgpKkTTxEnSP8wjRceupY-7FwyYID6ahFe2oiOVyyS3jojT9MeIaxUFD8VhDrDGU0AhuHPP5i2p1n8lSZYDSX8kRPJsPgVyMxPS7kx5o6ZpPCVpCwzY4Bi7DguBablEU6lzJRVmM2SKdoKb4I1hH0T8QVPg34_khUVp-q32NWjBQeuC4OwdsXaXuZWMgrFby05uOyZao7OI6SPorkF8KSq289R5tKdcV4hGTdljXQ03ULzEk1B9vfUTe43P-4XMQNp4l-_UV7ZGntUv6fQAMLYq4Jk6YVJHvN6T5gcFo0jflw12r2ASVhAzzdVgyEJDjX7eHvmYJwA1lnQ_U_VUxDhQDaN6GaUnOgsG-vuboOyvtjwOhAH4kYAgVcjk7ABt8jt9HptmnIPwLYlUFkH6JMROltVW_3HNnd6HJBeKX5pqHGxEmAcHSQoEDRyh5zEu0pk4tG9Zl-AeRNBq3S7HVZ0rrP1_80yqCzt7tyEfJqHnPhfMxoHt4510UbvIsVfOXpYI2HRhUvt59FlYxZSggJnEVOFy-MIw8t-T-EWCoHgE2jtGeYGLWMoBfhcebyfn4sWovmTf6Wh5jg4ot5Bou8te2D4GiM_HrsG6Dd9fDsvVVkDxJq6N7XOPaEj1-1IP7MQAXaTq9KH-Ky9WCExDIwrcLbukP8PKEvLXYmSbWMRrhhb2nMvvMM1HnJ-aoxMwMqone3Oy4rW3C2AFLYDqdBTsgCfRac9aZnF0p4FsCW7QeeLw4yWUxtbG4TQ1VXVP6NQu2MU1qu3_kcf8DPSz2z1jeUMss08MwhYVo_K7jf7zQChoOWxtAwLTCLBFX0YYSa5xATwRitA9GY6LoexeiMA1Kb349L74hXYwUr1M2W1UR7zzxOOP0rHoe-dUSbReooJjTieIbBHPjFNl-Yw9NZplOrpq0wtunVs-MHIMuZ5Y_r-44pH8YsFtVIZtjtgS4F_jRsk-YdQVEomjYQjKNmPxAVnB0HkZDQWl5awFGEw3Cdcg5ElhAvPOIe-z03QGKx1zWS9elr-nZzYOPi6IVnbANVW2NwTlTEOR8bem0Tng3bb5-TNg2ZNvjs3ZMo9PZFVAlD89WCxrKDe4sv795N4HlM29uqCwsrNGYS70skoLE3wEbcFMQ4Yn3ygLVeqngDxULKPA9J9xtC7-XnIIg=="}}
{"timestamp":"2026-02-11T04:18:01.535Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"kill 1684036 1685322 || true; sleep 1; ps -p 1684036,1685322 -o pid,stat,etime,cmd\"}","call_id":"call_gRqYFaDqEWNEeYCQ5baXyhy0"}}
{"timestamp":"2026-02-11T04:18:01.537Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":636231,"cached_input_tokens":555648,"output_tokens":31440,"reasoning_output_tokens":24609,"total_tokens":667671},"last_token_usage":{"input_tokens":44666,"cached_input_tokens":42240,"output_tokens":131,"reasoning_output_tokens":76,"total_tokens":44797},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":8.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:18:03.227Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_gRqYFaDqEWNEeYCQ5baXyhy0","output":"Chunk ID: 925f48\nWall time: 1.5372 seconds\nProcess exited with code 1\nOriginal token count: 8\nOutput:\n    PID STAT     ELAPSED CMD\n"}}
{"timestamp":"2026-02-11T04:18:03.259Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:18:03.553Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":636231,"cached_input_tokens":555648,"output_tokens":31440,"reasoning_output_tokens":24609,"total_tokens":667671},"last_token_usage":{"input_tokens":44666,"cached_input_tokens":42240,"output_tokens":131,"reasoning_output_tokens":76,"total_tokens":44797},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":8.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:18:26.266Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Formulating maximal perfect set patterns**"}}
{"timestamp":"2026-02-11T04:18:26.266Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Formulating maximal perfect set patterns**"}],"content":null,"encrypted_content":"gAAAAABpjAMSFlA9utYARmBZddGUGha_q91VO6nKqbo8BPWUbZt9VG8N5ZxXohRYieYzg6L1d-B2gXaeePBTWGgdiDz3v-5gdq5aNUEP0gYCnQwhkBv0ypxbwZIxRhAw50EtyVkRLW5pxLv_C2bYPiBbhF42agSuo_mbxPxfU9iDZAJ-d0Xm7VQe_Wjfy9OYCa-8UoNprr5l8PipMR5kg3D3h_715J7eVsRBcnHJhQYXil5fo6nTkUEw6ZeStd_R5ZC9_ygenCP_64egxNkYyb-chH2sDvUBxCJSzeQNXkRZUze0RxvfVpacUOxOlesoTnJRJVMsCXCQi8NH00G-UW0tWM897uqlyTmoKjyZtVyDuFLSa1i2lna-yYCZTHVLn0Ao_hyC3mfkhXus4IwgV9oC1EZllNa-fsHlzKmX19-u47fcBdnBa-0Y4AEkwLwGx0AjJY1gNTGzK7GuXpAtsgqJzKSYFTWXq1YJ9ikCWd0NoDG4iacoZds9B87SYy9a-jEHrDcF6gGYerbw_B0qFgtwfEfjYTnnz9tciGm4SeoU6CbN07q8Uy5rFobkKFh7th5qeoiI1gafN4UfbgSdkNmGCVz9zZvwPTCy31qRZgoaOzxPV9tkYL70OYHXaj2w8dVaTjEMT1jCaqdGITXC_qyqyy-e9XHUTkfsrNBr27u6XK-VvzmidZTOvw84kuatrd_n4LJGjd6EV9MmuYHccZNdFbY59WmULPOCJelcRnjDz9Td-T-b2sc6VQDFsQuzsWao9TnphijFqbfEsMjh2JdaFXv1322u7bQxq7eoc_mvvUTknFOrsCBkIU_iY8LDzpTrwpyNvCboYLSbj03R0LfGTWHZxoSsKXfdJTbUd_AES92tp2O4pixviU8Po9SzLBR0kLR6BvCyWZYJHy0CvE70wj_R_xWaEefw2iTL4CCb1nXe3n808DgiXsEUbhgnqRyHqKbealdS8of5CxvtN4VdTR0W6PYrMTLdyx52N6GG5HySb1uRgMMK3pWs7Oae7Niqu3uEc8Rcf3Oh1j9w_xtvjPZ0NZTAynDuiXvnRXkBablP5zwyxiGKt_ql2h8VzP0p1g9MM1EGzPckzsG7QKhmwAsxSPL4c-ovEqafFyaoxJsxcqZrGqdYrYQOAAsK457nL_SNULl5XVcvCyOmd7iYXOif8Y9YwvM_bI1aXDygDzaN9FATMYWaUxO1m8GHj2nJ8030ONZ7Cm9VwQVm7gUa_4ry9I2UHaI_vugc6N35PxBH7Pjwe-55CwokmHT91QLSNzifilxEpyw_Ea0TM-ECTk3X0z6QOF8qdhujzGDmp4C-apATOTRQXDzqkaNZQBS2zBAY_ltaxsEKmoqAip6hmZ7KCgKp5kCt85ujMZhRL3Ia5FLEpSh7J1t7h4NA4vEk3y1bkT6I1Hdcx5UqU7J4A4owCIc_w4OScUy46fdzdM6wHG_gGuYdzZJGqmjwpjNOFdEJBeCyCzTeqoTdPRK_SWhR6CS3Q_EQx-sEX0tPamkgX3X8FPLk-6A9VgATDFU31LX6JF-54OUi42JKvrTpoTrj1ePO7tueZESNXwOU625fPINhqsJ8tB7P9Du3Z6pU6legr7uMb3KTkuwWArn-mCPpCLkjJcEVmGPfocVP2zKa-eHA_YFXVyfVfGBBDIIy0A3l9_ZrFO2xKb2R7XJ2V3dkMLYyVN_xOQviSpDHkBoExZVBHx3X-bKxmbq-XrFkSj1SAHzFs1IQkEJR3QLgM2RUvAHUA2uj7wbNVT1qGc0vxhCywZRj4ukduap_6cEDScLWKUhzLxnhyMGY1_f1FkjSXUp4L5CU8KaW1RvIFZifgTHe2-R8Urv6VB9F8R3o4Qgy7qBPk5ACYPkH7T0gvHNFjsSZ7b6nhZor-c8_lNR4pmUKLX5TChIg3UkIAKxABjcCgTSNRtm1ODYSWnx9WcDyqniE_b3buOpRe2QgZovcm5jXJ5uvv12PVlf2nw8Lc2aCWCGe4wIX48Re8RPk0rdLLLWb7rOxDz96tnbqskiPlwMf94VHeZh11U436_zE1oHMQpVr1XztjMDUdXYniRZKZbg3kuj1luDn1DJ0DIDcXqe2zuMjFcK3in-aRjyzZl86-0Vn-sqLh0ZtgC4ypuby_oeQozVhymOR5NI5kGf9V6Vn-qS3MORTfinJ0NE1dwLZO5ne7RJ4ATa95p8tXRWwOtQIa4NgFP85mNnbb99FUEjnDA4K6E8TE8zxNcMZ5dw_B7oIttGJVnNwfZLG1pLKObhLM58qigWuGMQBLP7PGC3kxjscoGOqN3f8cUaTDEV-NNrXa4V9zRBzyrMvTBmxD5JdMV8YAT_0QQ5JjqHsfH1hrAwiUEns7Qx_W1viF3mGEPI2iVFvklPU74H_HGOcTrH-7jwRVviR2xdC7Q5RBajHYc0qfr07i6SDEaK71KiuvwV4gR4KttiV6LO-Uhlle6dRqqVkItjiaMtsUmeh4UGc3q4uLDT-ACAlVCYvrYKtja7L8Y8Yvflz8Do72kfTERWi7zIAj03EdjL7UQYGT10eyLSA-17aPRMgDWr05Iq_aSWh-lvT90CCpeG3pESQHa2ikxczYPjVrCLiMV-yt0zXTSgOLxoqCrDPom7vxtNTUvPItBPtmIk6VI2_ByM970lEmGNJ_PPj5khaS3YeSM5L0Y6UqHsIF12MnaNXytJZY9OqO8-Oxs59r_8x2Xp_anUKhVT93CimbfUlAVQlbz14OtJSa-w2QI_pnRFoJMCN0nQYgow7MwW8-RtwPYSrH4j1vojRlcUcNk5Aq2OOVl6z_Md_gVXzyY8dd0nYghy0c2WZxV3gcahH-T8nAOD5d2CoLsmonqpNdXkYI0M1JM7IdHGSFiVX-1YAeY37Z3aqxlYyhSowPHRgcFX4p0BW83UnxRu8d88aWcrT9EYYEoLm9NtNoSvnoI2MBHwUcbYvb2gPOvfOVx0Y9hgzJZCIUkOuW6SyspSPmLX7A1pcOZiiNP5SnVw2OZINBV_y7g892NC09akcTJoBe653t5ddEiiskJ_mlLrKxj0V1-he7lj9JjNGk-MMgmWBVnLrsRdwSBC1sC4RNBQqnhQ0NIuIOF6dzZEYtTWrpyRm5T5Py_hwalZSmP4HXt4dbz_hVfaKY11bar5DYGM7-PZipsUGS8JJjStVhYP9eRweNCsYaL7-gQAHJn0IKFyLlPALFz5ndZvXszbEf1gtUfw_8_6GwqUq7UH5bIZzR9gOs_r8z0rtIxzHvwl5oAl9L5aPHT7VpUK_PsV9m0nL7X_DgdIJiUzUTAJZMg1aQF306JfIKEdJ3HzB_2nz9WXBZ9uAoHj1z7_FzbhaUj03wzhSLqrV5LsS87rD6fxGbrc86qKNTzJJpLyekd3_FX_gsP9j1OqmSzpXAmesotWv2-bviynE7SKbLiZr3UlNoC8oXIGdRjE1Zaj_whRk38snZm7AO7EozjZBFLU_pUeenZoIyExv0Otl9_LgTai80oaoYeJvzLvPOPkSsrdtttJUa7wZ_XJsTcpnAUAr_l6FNVsNX5tK6F9g55NGBM0rk54KFVlENik1f_spnwKiitWqaRAGPefVvbcJj_YlTDGud_cmI0staU4iTKi7_hBQtjSPY4I37ThpeL1OjFOqMyFRlC5cnxbyRCLICOHmvTOZisoQbIeFIxwP6czC3XQEyraRLF1u4TxXh3FOEutQ-CdYnAZbn7wK7gplAtsGJ0n8O4y7JBSnRIZ4oVXJBn53ORki20wmvp1rP-HaHXFX4eukrQZlYdeShHL7LgV5DSfZR0e46Tf58tB0lcRwEoTKBAmXp6-GrlyiRtg3_pVxUDn0PVyhjtzV1p-6GPPA0iVZ4xme9T1mvzBFu_24Gq15pEKPmNEWPzR1uWG_SW5TYfIdGsfaDKnUUqGPFVF1AICn8ZwUBzhhj6Mmt1fbwkkixc6OCqB3jg_x6YYXSsBj1YeTXEHuJ5z2tbgbPQd1-P7bFjebk1FvS-eiMR2awJoP5-6sFdVAy0E2mlbjTz-e6YXPI0F66vUdmiGVdZNLHP-4zskoo-xjN6K7n6nhPnZuyUlF1Ot5gQIs5JKS6H-ZLFBEJAbGGWWmdlA9PukilpPLDkFg4LH6xbgbr2_MCWZI5cEpgsnEMUpBCgs-faU4naKUUUzUmAdLKinAg2FpPDcHwWOTNky7Y71L7ZAJu7nQNCRxIOvlZmz7bd46BKKbJr8p-RKDdnUciQZJAmh-nQ-v5YX1ODgNvYNe_WQDR930qSMlEySySSVvFp-WwrkilJKrhk-lWcAoXet4dImS-qBT1piTDpufYeEaHBD6Ut1MT93KgONxdK0CsV-4SKTagwPaxHhhMWfwzIK0ycTJcNpk1ki3vfG4gejYd9B6jlUWVdrGuGFKZk4fiLl2fSrH8o6mjfasTuDx3NODM_a44__R3fWP24K3BRLf0Th3qpCRxYBtVIVP7ztCtbHjdTyFowqPE3VZ28iUfDxvNxYSPHAEFWVY5FhT7Mh8fK2ljhEsPNxwqwjwyWwg_PpPg1NMD5FSQEchZGUzzkgMPFpWL6zkMV7K_ug3S5ODwGJbW4C_6m92ZffbrUF9edlD87Rbxj9XoSMZ77IU3PjOXgKp2FVPbc0rwkZ1zw_sJmy5-AhAY0emGeR8E3r7NN2tLxJUD2ufpdlDYHIOuH4BFFGhOYp-eyqnDY6wQOBZSM87M3p0XGlp7h_gx73papTD_CHCgeEfaeiPl8fWwkryFZG7jvW61NDJmWtCrIjKcEyXuofZ76dh491QKr-KC1bQfklELFMFSt96QUAi3-xJR5C3dv-EeHdBu6qbhi6hOe_4u3FTGhauDlLvzOBhrY3CxvweJ2M2XmCjuY6tFDhYfBYlWtnSA9c3zwjjbEYB5GimA2LhbUuSMAtbv_gKYXgwGVHF30LwEf2HqrYGMupVC9G1IvtJi1i-2-4TJmZ3Yy59clCSn0k5PYD7IjXeOodmkeiSY_wntj7gARJq8n4r-4LDTHKJOMgofUidRer7_9liqYS0JiIH08c3lrPgkfc06a5wbPpVCju95fBySZzlHVlySNyIqIJnSPn1flglGp23NjRSNALFt-f8i-tKymu8GTFPOgPqSnhzO-UilwMOdsVz-9GczjyaeTVKsO_o2328IADAJ9NKx_2sqhYtm1ZHUVPus5y-JCkgZbePls8VI3Mw9bkCmus8EVNKBm-Yctp2A7STrBMbFSzQGbXfj_kML6tz-7YyZNuHxLK0T6lzXU3igpn2bBNRicVobtZVwWMRZpHWRryKhJe9esZPyihKJp0KanN8WXag4a_WtQZPl3R-gZiQmyJl46JQ-yYeGEzGBVoS8aYXOgyYcGqS2Ux2-4EPZzzltFTNUgLVQ7rBSIouM5kJ7b5RBXXyKPHu7m7hSOKnY-DYfl3Lc-iqw4cx04tdth9aF-IQFscH7kL52TOvvGve3JFlLdf6btU4BpFgcOV85yzM7kAiTVshtDCEtblQEL6MoVDnXUG3YXaHgCQs8HxTgSw_9jCKOeHQOVO3E1JLxhk4-IwuDgbUUP-1__Yae_wVmjTDJA-36CI48P34XlwoQ_uBrgYy5P8-wwkD7qzTYYWn7BK7rcFkLuC0gAoYhWOTT-vnLMzfs2P8jQk-UPkQVf2Bp0H4AtWVS5cApBlIOhTVBS9fQ13IESvOzmH0WLzOUVUc7ExxO0ea7s7fZ9sjQ0ZxiAADzEg1WYZU0OapszkGIRgApY3Nng8iaed-29fRLIfTzHuowYAy3b4NycKAXjT_0EJ8fglDTlsC67w-jFmAmUdxGVlO4ds08KpTayG-HqlorLPpyVeDCECj4A35BaUVOkXp7C7T-IfE0X2C8jDf2JrUZYCCtaT_4D0ONwRym5V1-4zjmVVgkMee-JkPxI23rBwNjIeJ-LmJEhrViULmbfvRoYxw7JtnkOZjyeMsru6nROQbTTN7BMYIH9rny7HpH8TxVh-sfQoli5dBYGfYM8Yc9ZNzR1KV6X0i7QJvkZJeJl4Ho5mzEzHz775nxDwH3Im0YbjvYBpzidmonxuTfDRvcBgDxxCmmSqKTTwPFy3_cg31CkckpWu9CFXvGvGPKZ47hKV4VFFWapK24Ih3x23-3mjw-_QyvJaCOhQdLOKDcDnPuDxxHDlhfq_mIJwRsGNeIBLdPb6bA6DEp-76v9OTbBswRdF_olVgEH6WS0X2SY-9e3UReB_Vn6cLHY_XasULQVCY6P0V6VAZom5WyI8uF7SxVercYK2urCK74TIAxdu2Rb9GtVzmLbg8Q4WKo1rnlSXiEy5Kf3mhh7al0yPxDWNz7Va4KlgSH-gcMfP69UmXqeYZz3h_abMp4Vxjpyg2NerXldl5mwBOD3b61b6SV_6PdxNPnmcHmBFdkPsePVTjhq9sSvQufsGcEf_I7ilHgDyu1g=="}}
{"timestamp":"2026-02-11T04:18:27.954Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"python3 - <<'PY'\\nimport urllib.parse,urllib.request,re\\nq='\\\"R(4) = sqrt{5}\\\" circles harmony points'\\nurl='https://duckduckgo.com/html/?q='+urllib.parse.quote(q)\\nhtml=urllib.request.urlopen(url,timeout=20).read().decode('utf-8','ignore')\\nfor m in re.finditer(r'<a rel=\\\"nofollow\\\" class=\\\"result__a\\\" href=\\\"(.*?)\\\">(.*?)</a>',html):\\n    href=m.group(1)\\n    title=re.sub('<.*?>','',m.group(2))\\n    print(title)\\n    print(href)\\nPY\"}","call_id":"call_ZQl5ot4JDBDR951kM6Q3Q44k"}}
{"timestamp":"2026-02-11T04:18:27.955Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":681082,"cached_input_tokens":600320,"output_tokens":32634,"reasoning_output_tokens":25641,"total_tokens":713716},"last_token_usage":{"input_tokens":44851,"cached_input_tokens":44672,"output_tokens":1194,"reasoning_output_tokens":1032,"total_tokens":46045},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":8.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:18:28.899Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_ZQl5ot4JDBDR951kM6Q3Q44k","output":"Chunk ID: 05a958\nWall time: 0.7894 seconds\nProcess exited with code 0\nOriginal token count: 0\nOutput:\n"}}
{"timestamp":"2026-02-11T04:18:28.933Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:18:29.284Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":681082,"cached_input_tokens":600320,"output_tokens":32634,"reasoning_output_tokens":25641,"total_tokens":713716},"last_token_usage":{"input_tokens":44851,"cached_input_tokens":44672,"output_tokens":1194,"reasoning_output_tokens":1032,"total_tokens":46045},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":8.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:18:30.637Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Switching to lightweight endpoint**"}}
{"timestamp":"2026-02-11T04:18:30.637Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Switching to lightweight endpoint**"}],"content":null,"encrypted_content":"gAAAAABpjAMW6AuSsaAUabvo6Tf-S2asXi8moHtBm7aYeGeBaybpU6OfWrIHDT9ptQrwn14Nv50fp6eQWoWJhP7Au795N7UaxDgIDn42yx-XIr0DhhFXuSAk25puDWXf14suffLEiDvK-4wXiArXzhB8UuQ-6_rIDGre2O9Gox1fOxjDw2WucFxPOg5gOW1Cw92tbF-xOLfMEuFekAGM8c78ZPLcjDgQh2sCwOFntBnyO27ang27oDTSgkuPYhJAMnrIUYywGuvo2Nw1NXilQJmTq6M5b9ZN0QT8K38Iabu2U94SwFU46uRzvDlWkxnuKAur5XRBJUq3Lons7lkIkMtydLxyPwS3ZWtXd5AiRVY6lWRGy0ckLtZ6BGNcagRapdmghs0Vxhcg22xBNk58wojoJ2Yd4eW3NyK-g2BJbYX3VG5GvHGjRKZBNxsHTnKES3h2T6NXpwvFltxBCNgKbcpr01P0xinXLMTN_E8ya12C7YclXGfkemqn4LEDTrayXfmZ2AzlaUQuJEznwAgEK5ITX7HMbFhOmErdbZsRANsE7oU9JbFCC_ghaS8ruOl93265_XeLQxeZvUj0bOYuS3V2bcB0Ht-cTqCDdTsnst2BmTSPxMuaFAiC5jZIqMUG4Pu6IoXsqv9QxBwsfIdrieis9TBCWNT3zcEJC-xmKQNpjUx7hTX1WGvlp_l8T_dpgXPVPwl83vRYNOzXEXrm1TK7rZ_Wi4uqQ4XivlKmgsBdu5_7cYvsZcWE8LsezaEPPs7iHPDjGNhfTzObTyfIk-i1OBbAR62BKNByQrk8MlV362A3Tbu3mfgF929ISYMziSZUUUufAc_1Rh3jkD2uLcgiYjPTOkuLz2YbB2KYHBVM6LHnvNgHzNKhDC5kQ28gqsMgkl2SXERoQOu1O6oCanHhDxlT655kua4CTiSJwBWTQTEGwkxAtKM-pkUhN4dwETu1ToQGR6o2"}}
{"timestamp":"2026-02-11T04:18:32.868Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"python3 - <<'PY'\\nimport urllib.parse,urllib.request,re\\nq='Project Euler 983 harmonise circles R(4)=sqrt5'\\nurl='https://html.duckduckgo.com/html/?q='+urllib.parse.quote(q)\\nhtml=urllib.request.urlopen(url,timeout=20).read().decode('utf-8','ignore')\\nprint('len',len(html))\\nprint(html[:500])\\nfor m in re.finditer(r'<a rel=\\\"nofollow\\\" class=\\\"result__a\\\" href=\\\"(.*?)\\\">(.*?)</a>',html):\\n    href=m.group(1)\\n    title=re.sub('<.*?>','',m.group(2))\\n    print(title)\\n    print(href)\\nPY\"}","call_id":"call_4T1Q7yp4M7fwkD6pAlRSOpa6"}}
{"timestamp":"2026-02-11T04:18:32.871Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":727172,"cached_input_tokens":646272,"output_tokens":32839,"reasoning_output_tokens":25666,"total_tokens":760011},"last_token_usage":{"input_tokens":46090,"cached_input_tokens":45952,"output_tokens":205,"reasoning_output_tokens":25,"total_tokens":46295},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":8.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:18:33.698Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_4T1Q7yp4M7fwkD6pAlRSOpa6","output":"Chunk ID: 88f4f9\nWall time: 0.6752 seconds\nProcess exited with code 0\nOriginal token count: 128\nOutput:\nlen 14295\n<!-- <!DOCTYPE HTML PUBLIC \"-//W3C//DTD HTML 4.01 Transitional//EN\" \"http://www.w3.org/TR/html4/loose.dtd\"> -->\n<!DOCTYPE html>\n<html lang=\"en\">\n\n<head>\n    <link rel=\"canonical\" href=\"https://duckduckgo.com/\">\n    <meta http-equiv=\"content-type\" content=\"text/html; charset=UTF-8\">\n    <meta name=\"viewport\" content=\"width=device-width, initial-scale=1.0, maximum-scale=3.0, user-scalable=1\">\n    <meta name=\"referrer\" content=\"origin\">\n    <title>\n        DuckDuckGo\n    </title>\n    <link rel=\"pre\n"}}
{"timestamp":"2026-02-11T04:18:33.731Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:18:34.201Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":727172,"cached_input_tokens":646272,"output_tokens":32839,"reasoning_output_tokens":25666,"total_tokens":760011},"last_token_usage":{"input_tokens":46090,"cached_input_tokens":45952,"output_tokens":205,"reasoning_output_tokens":25,"total_tokens":46295},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":8.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:18:37.706Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Exploring alternative search APIs**"}}
{"timestamp":"2026-02-11T04:18:37.706Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Exploring alternative search APIs**"}],"content":null,"encrypted_content":"gAAAAABpjAMdkB9oYCFfwjAKPq1aMndOdyXnCHgOwDmSRqtXT2v_wPkM575CjxutcNJB0gFnKyMGb3cg3TFwt_5jXN4ksZjUFS204-JiyIMgR90gN--1c7fG9gkx1fQ9tU-EHl-Orx7oDBVzhd5YZAov3jSe9c6GydKD5ERb3gMoQorWXRe0UQeVvgzNalFwWDQzKTk-TwmsDs5lymC8TTcvb-fwjF11Ra1Sa92FN9CmX3QzRGTET3qnQL2Gi5PXwcuyktvjQAMlJ-ZylADqISnvujknnWEdNnrYE3Bj4Ounp6BxzXOWH8bRYTxUCAn8C02arIDw3It1TTAKZii5aaqLhE5F29RwlveFDkAaFHJuFfz0DJ-EBZYI-k7IkrUOKybO8cvDz7hDdU7VSfM--LvY_yaa-KWZgiSjccIe51nJog2QqQqSSfPLYpcfoB0UTUXvToz47hXxSNNtO3H-0MFzJQhXmcYDBTE_PZQnJsSvaDTZQetRDybu8vRXGWfA4c_h_A9AFty0CqTVJH1Dj-y1sEW7ol305Ic1kCb8SbY1Dkh57lHWp_sr3SqB6KHowndrYt-WGk-oxb-xtR1-1OQDFLygANAmpJiRSzUadjdyU4srCRGPQxGRqdA8ochD1dibX8VLu58mmtegUlEJKmTVyQDrxYd_JhlaT1yK1GtpfIhL7xg7uV4H55Fw-Nc7MuIjfy3oa5ZkqXAy04xy_Utf4OXMqv8FUQLX4FzjyWDvO_wP3X8kXNSBI-uivFKm5qFCQ08B7TqH-jE8RvikT3FDpa91ePaPPvWsH7VO1TYxILIYTL2q1xyfYTirAZgfJzSc6_DPwKQEp0UJL7Yzzq-Rl149Dm01nFpT0yHHwSoQm-iS1qJvdCezB_xoHUpsiYb669mDdJmVSg55cHdSwSmXTrQWHIWqHi3aQ2kJBn-gdT2W9feNc3qfAEEPTv3YP-6P8dxkcOQ6oQ6ZglR5bKYEIJnqwxjsiH7i81_Dbg6ncPgMsy6SchMKPSCMHuOgz4ZlzCxLBzsllSLK9MLQ6m3roTvy4XW5QQcDL8wwutIcZFjcY6BOMP6tuYWuXSGwNhO1S56ZNWcNAofiNvh2DaHH8BsebOGohn6eXhnjCmnZH9kogbna3b6tb_MAtG8U9yRt62pxT69yljl65Re0iNGZFfHfbTYBRW2ouKWLgJ4EHqOzsrOGGdrePLwTBLVT0veHyknt3pVohpeDm6yOsNiN-_i53RDRAWCKPcRZkVxK_7MhzQmMv1asQDwRdKd3PRsHY0I7iOTQ"}}
{"timestamp":"2026-02-11T04:18:38.806Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"python3 - <<'PY'\\nimport urllib.request,urllib.parse,json\\nq='\\\"R(4) = \\\\\\\\sqrt{5}\\\"'\\nurl='https://grep.app/api/search?q='+urllib.parse.quote(q)\\ntry:\\n    data=urllib.request.urlopen(url,timeout=20).read().decode('utf-8')\\n    print(data[:500])\\nexcept Exception as e:\\n    print('err',e)\\nPY\"}","call_id":"call_1UIvAQkhzPmZptVREuliG9SK"}}
{"timestamp":"2026-02-11T04:18:38.808Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":773668,"cached_input_tokens":692480,"output_tokens":33038,"reasoning_output_tokens":25749,"total_tokens":806706},"last_token_usage":{"input_tokens":46496,"cached_input_tokens":46208,"output_tokens":199,"reasoning_output_tokens":83,"total_tokens":46695},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":8.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:18:39.894Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_1UIvAQkhzPmZptVREuliG9SK","output":"Chunk ID: 649584\nWall time: 0.9329 seconds\nProcess exited with code 0\nOriginal token count: 19\nOutput:\n{\"time\":32,\"facets\":{\"lang\":{\"buckets\":[]}},\"hits\":{\"total\":0,\"hits\":[]}}\n"}}
{"timestamp":"2026-02-11T04:18:39.928Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:18:40.345Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":773668,"cached_input_tokens":692480,"output_tokens":33038,"reasoning_output_tokens":25749,"total_tokens":806706},"last_token_usage":{"input_tokens":46496,"cached_input_tokens":46208,"output_tokens":199,"reasoning_output_tokens":83,"total_tokens":46695},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":8.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:18:41.489Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Confirming no exact match**"}}
{"timestamp":"2026-02-11T04:18:41.489Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Confirming no exact match**"}],"content":null,"encrypted_content":"gAAAAABpjAMhQ2M6ftva634AN40t8zrSEe16g1sUKt0l1llC5--zodVWSZyKRQ-scRVC-iYw3a2grRxZS7aSGE6EBhx8jwMAsnnZwt0X4rTCdzJW5hUT5NLrXI-GBBdF8jWC4hq9ZA7FF_JPQlsaPXPtcm_GWkYrSiwBa0xd0xgkV2bxhKiIMIbLFyNJ8ByAUhRXAbQ2bq1EEbHrrNPiCteoQmpokcQZLa5OLNn-0FJ2dZDZgYcYPAbxy5tLkRMVjSoIq6LXjrYggv7YBFbQf5Evor4KjUILDgYhzDtECg4tYH81_M1wOD-bUHBcZCpjL04K81q9fkxqZcH7XcOyR0pAJJXMkTGQaftDIcFOoNNCt0Wi72a9ej4XXyUJumdVSaXSWRsFOcHzpQiDxIL5U2-ipxc4oX5XWP26VPB4BF4tkeB3c_JsGCX-CbzF3Qk0dPFidowUBSlIvbPIEzMKZDc6HB8sUZ2STp0vdXud5GcCyHzWssKCWE21TdNHAw1gebaJKYfy43SFSQQyluaLKNB3qrhUD_i_qrTXmSg9QEJ_t_EBuQcP_qqBzqcLY_MIpiyD3_Hya6uycT0itZaXp6BymiVQZUY4OYfC_9kH2r6pOtyyRvEVSYzSygVYCJmqLHhOesbTJTKqMi5Vpy5N4y069F36VB55xmXmeZCvD8PYUIOvavaOyXd0sBFtjMBJQwvwN5AmMqgmKucVOeOEIch1EDocWi999Jl8KzMtLIiPRQPzxJwMNQFUpbm0mfqqYv9-ZbmZn_ZTHz-M8s-1Bl1DyjDlZzjzBMR8hdKgRS0UwD8PtUZLlZ9046kkb-RLplt5JjGhky1KL0XckbBkp2r356mJLQkPXgVI9vmeDAw4G6lJ2-U7ere1xTuXnCBrO6mRCLSt6KDKyKODHOTcmP38siFEZo6cdI4nMdwZvdb1uo8HWnaQ6rvIWQGs_NgtkF9YDKpPnoG6"}}
{"timestamp":"2026-02-11T04:18:42.699Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"python3 - <<'PY'\\nimport urllib.request,urllib.parse,json\\nq='harmonise if the circles intersect at two grid points'\\nurl='https://grep.app/api/search?q='+urllib.parse.quote(q)\\nprint('url',url)\\nprint(urllib.request.urlopen(url,timeout=20).read().decode('utf-8')[:1000])\\nPY\"}","call_id":"call_4J62p1NQ7PUcMST3l969e6Mv"}}
{"timestamp":"2026-02-11T04:18:42.702Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":820431,"cached_input_tokens":739072,"output_tokens":33159,"reasoning_output_tokens":25771,"total_tokens":853590},"last_token_usage":{"input_tokens":46763,"cached_input_tokens":46592,"output_tokens":121,"reasoning_output_tokens":22,"total_tokens":46884},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":8.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:18:44.092Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_4J62p1NQ7PUcMST3l969e6Mv","output":"Chunk ID: f68b25\nWall time: 1.2372 seconds\nProcess exited with code 0\nOriginal token count: 45\nOutput:\nurl https://grep.app/api/search?q=harmonise%20if%20the%20circles%20intersect%20at%20two%20grid%20points\n{\"time\":175,\"facets\":{\"lang\":{\"buckets\":[]}},\"hits\":{\"total\":0,\"hits\":[]}}\n"}}
{"timestamp":"2026-02-11T04:18:44.126Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:18:44.543Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":820431,"cached_input_tokens":739072,"output_tokens":33159,"reasoning_output_tokens":25771,"total_tokens":853590},"last_token_usage":{"input_tokens":46763,"cached_input_tokens":46592,"output_tokens":121,"reasoning_output_tokens":22,"total_tokens":46884},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":8.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:18:45.678Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Planning external code search**"}}
{"timestamp":"2026-02-11T04:18:45.678Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Planning external code search**"}],"content":null,"encrypted_content":"gAAAAABpjAMlRNLzpHM59M6GbMxyj00O6sz0ZTyqHXfvgtwljddXEnIAfU4Ia-a4SP-Xi4t7-qOuK1H4xCgOQkbu13Pc0Zuo2sG02dgXeyIC-zetEdML01TGAjJ967FE1W68of9GMYttsZKpUixZxz50GWjPEClbvdJcGriRWy39paYYAr8q2FhDtEigojSWXa2oG7rpTJyakDvqGRDswQQT3hag9b1Z94cM6Lgib32Qf5quip_TneerqYF6eoktetoKfaFPJW2JW5wcepGJljgRty26JBAg2GyutPVc_Co0s-nljiEf0D1DCN78ZpbCn-oUxDVTYQN0xTJH8_iWSKmV9PIsN3UVkBbMBOONBS4aN8yEWxS_XP1FzgVRHOOJbZu5s01sM-yblwC5Y5xdD2bDh3uHQ7Uu8_ZeqqwsvHZyIcgG6uGYxsS5yTuej772ULlD4aG6cU3rfoGyaugXtx6fwMbKvWwfc4o1rWo9PXU0mVWO81gmU_5CBdDP3xCekq4wTnaa2o3S-4cmVDzvvuBaJ-kBlERzWVEuICqu1Zyirn8KgsfkqC2kCBrx2zS6Vsp9rTG1DQSXxghhFPaHrmrNOxVJl7oRr5YhTuGmQ3qqEz8KV-71Grloo1OGhuqPjo6rSLmVYTNAz_UbJYKlabMdGTFG3jomUe6uPZeN8jAfwoyN0ZFkbCSEI2NkhnHmKv9z4-pQ8S_Za-PLbZcw64ANARXrfkMM-9TMGLX4ddbDX6bsop1_jrm06UkAFcLm7XYeQvjfDAgQsAb5PKSvPJYyNQd31_NcyQwkKNe06YG9yWPNG8Ow0ECyhMn6rvvdfZ7-se6RlTYCY_dQiWT1kx-wbBwIerbGQhen9F5W_uvJ2aXdd9_7rXl71Ug6G2G0dQ13pXo5Lrs3IPkTrInhZ_iDOwyFq_ehDg=="}}
{"timestamp":"2026-02-11T04:18:48.126Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"python3 - <<'PY'\\nimport urllib.request,urllib.parse,json\\nfor q in ['Project Euler 983','Euler 983','R(500)^2','harmony points consonant set']:\\n    url='https://grep.app/api/search?q='+urllib.parse.quote(q)\\n    data=urllib.request.urlopen(url,timeout=20).read().decode('utf-8')\\n    js=json.loads(data)\\n    print(q,'total',js['hits']['total'])\\n    if js['hits']['total']:\\n        for h in js['hits']['hits'][:5]:\\n            print(' ',h.get('repo',{}).get('raw',''),h.get('path',''))\\nPY\"}","call_id":"call_5KSuWIWvXP9V2UK76TXaWmkG"}}
{"timestamp":"2026-02-11T04:18:48.129Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":867423,"cached_input_tokens":785920,"output_tokens":33352,"reasoning_output_tokens":25791,"total_tokens":900775},"last_token_usage":{"input_tokens":46992,"cached_input_tokens":46848,"output_tokens":193,"reasoning_output_tokens":20,"total_tokens":47185},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":8.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:18:50.236Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_5KSuWIWvXP9V2UK76TXaWmkG","output":"Chunk ID: 0cfc84\nWall time: 1.9549 seconds\nProcess exited with code 0\nOriginal token count: 25\nOutput:\nProject Euler 983 total 0\nEuler 983 total 0\nR(500)^2 total 0\nharmony points consonant set total 0\n"}}
{"timestamp":"2026-02-11T04:18:50.270Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:18:50.586Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":867423,"cached_input_tokens":785920,"output_tokens":33352,"reasoning_output_tokens":25791,"total_tokens":900775},"last_token_usage":{"input_tokens":46992,"cached_input_tokens":46848,"output_tokens":193,"reasoning_output_tokens":20,"total_tokens":47185},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":8.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:18:55.104Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Considering external solution sources**"}}
{"timestamp":"2026-02-11T04:18:55.104Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Verifying incidence graph isomorphism**"}}
{"timestamp":"2026-02-11T04:18:55.104Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Considering external solution sources**"},{"type":"summary_text","text":"**Verifying incidence graph isomorphism**"}],"content":null,"encrypted_content":"gAAAAABpjAMvaSnQP0u1Vaf7eGRQc1OpTzf7loeshhhC6xHoSTwHYaaSg97nGMP1mKH_5-kzafgmHA0q1nOU-Tti27a_yDUA8aCqfbwTF-Be5Y4TkqRDW_OSxAy7KtKqKG_2YqpF1yMIJ3cz16ZZYz6yEjlktwKLa9EBPuhByAoQx_5eABU71HsjeyxcvhhvgA4YSOJIYC1avjJcXhTGab-p2K69QlO3LIdKlHP1rs1V_c20b9BY_7HxKXDiRUCTfU5yS-_fc6fC89RPeiZBJUbM2DrzRsrz5uIL-e0psZx41Z0tggWF7qyTOj-_kC24yWP96C_Jf-CyXtdAkZ7fbHFi95uglzUWXNHvDhlzSiFFuFmTAX9cXaEoFKSU-kFDobho6wDBaqwN4P6DwAJGiR-CwvAx3rec7o2qo0uRFweNWHeJNqmurCYdy5AL4LsGsCWQsiPoj9UlnlhjCyyBf0kZcShMw4zJ0MZ_DErLMl5tsNlBq4j55x_b_-CMUmXJTS2UOVFyo6dTCkKFxav55IwogN_D8ljZAqX6DOVTNEVWtMxuA1vTu0fJUef_DVBHko70MGb452z1STOSmWwow3EBLTFFCYaPV6t7IbPUVFjq41AwJW_0qE_4GoQY2zhJ7xRiEtixGwcaBTKSv-EgJTLKyVV09UBq4K_G3dUEVlZV6eAjkPZbjmyDJIN18qsKbo31QOZAdsKaHCSKC1O6BhlDUlej4SwFtF_xUjtXRZEdiH-7YMJgiz0Lmwo7OHpobntLqrVCEO397TxWleq42smITJBgwKiiuB8DWsnNEcwzS8SlrINauvPXDSRDy3_rpQFiM0yTBeraNg7c2OkenNT-z-pj0yowMlOmK4cuUdYNAwu9HMW8FEY_2ZWkwFlBYsnPzmuD6Mv5eTVXRhlxFKIQUtlBFxnlLTxzF7nxD4T9qFrd6DFuFsLyv21a1ls0_Fhz7BOgC6CCFyHgo60r5TbL4uIiicDMia3yXCTG1NR-7DhWFbiPDRNgJuJd85Iio8CAPEwoNdTP8ldUCsr3ekIFqt69O-79DQ3KNSQlP-zQvGcbqVedbSevGgnTvt2nlGLTeCzK6ItOesuGwK_Du4CyF-xxvNg_kBRnv_nTazTxUDNtbudQWVDmrlSNGziFqJIa45jHMA3G_c60ug8s10JZyGtdWYldf_3UxGt1aQE37BWf3qg2xebD-NcIqEUt9qS1zxcRI8QEuIpOTT65EzSr-HDBTPojxqgz-8QA0osW-G_CISe8EO7jP5Wqfm0xliywUpHocfmi8_EW_EMJq_POIKK4WYPva_SheEFRSJjxyJlEVKulRlGvrRdS-BWJahLnM_yqHGF2K9eOUY0G7-nGRkQs-YRFsGHgUg-qeciyJGNJgQGzjWUcb1Zm9-Ch8mRrLAXcS9O0rNwatOxngmzTXEVE_fo5Y0VMNqMTgI3tAoD4QgOOiaFc15bvCXMjk7lOtAg4epDUL4yUwjxvxA63vQpFxPDUBw5AVnOQhcyDDtSS7jzI3WKqA_ru-CfDw-ROvieQU7Hb8vNNBHhHu4zaFPAAilcCgunbCMpL7XHsFifmhM3SL5bOdedYShCxnPzHnV0W3MSEyrVAjfbW1Few-E-QkhLNq_i6xhSlTzRrqTDDLvBTSMP-JyJYW9DqdbszYAHIIl1k_Pn31ipjgl5mT2_eabZE5CTFTkYrxSiIyXTMxnijv2Sd5WbqUKffJZelhlpta4zRKGb3iHatkW6BDNWweBVrDPVRn8ojQXPQcMTvxHfRrVE95ekLo0Epjx8UE70WBIMFbuFe7VIzyrM8WaNYlMdpYD-gZJRLhd_D6THJQClhKGUsJ8z6QCW1LWkHLuHfFPXKWeBwVaR3JT418RNUMwlsjCsBC9_LvZJXoE0inWCsvaV4IeL5agCBDhwqKD0P5IArAHds0lr01xVwFfAHfCoMe60jGyTiYBW3EAEKaXLmBJXhDuI8goW0sby8yQGahjtI3htZ_iAQtd9saIWNQD8cm9ILV-1g7_ortQglSjLNAIlvGk1zkq6jB3uRpPUSwSdn-KDLDLSz4ujyZ73ZMZ0sHSWqfz5YzE4zvtLwwlJQbZWEmkMG9PouUAvCOjovhhw2d4Wm4SbFAhfRWSZH5ceAzwAB5uTzzWeFggz4TAYUcXC7A_ui5OkeIiUA4g_jqG_Q76bup7BKeW9Xxgp-zq506h5tVIKgKNrfJPvlGm8LPItF-6riMo5mkchyiQKQXH51UGg4Qcu2DgpR5QkTaqc93cTpx57Z36vpwMVIstVRy7a_G-e2XlrlH1QrlrmqbFkCo5xWrCjZl6J55vccO7hYg4wmUCw0rCob7MLcUJQbRaDQGCxS0b-ZO8jR7xFPqzpjYz5LLwYzmHswoeBuY3sNBcM8v872M3gEJX601BR0xmUisna38co6aLW9fKITMkbajgWkWA1Ro9a9uAwpyVXIOwRQGdj-NeSEalSY-XBMwQZ1CeE__mdG11GNwNZnorkLzNjfDb1FLZcthXkYiRpEZ16EPM1LnZoarfe8fBOC2K2jyWkBWNy8Ou2QC_Wt8B2uNuzyGk0gpsxbAm4FwFNHtd1_kbVe1hETd0a5d7ceKfo0yOLjoVO3wKZ8PkscCYc6yzKQHs4w_XTMZlLQTYVGKLXAGEbCTkTlT-dSNIfL4t_LB6wy5SK3dqmE3WzDlfEYVrm6nVn1RjIF5Y6j3BG0gZDyqaL-Lsg7mZaRjg4W9mrc5JWksrzocNhh6gKL6836Z-bykUBShigHtJE_Nw8PrUgRdFp3l6Iu0IKkDYG549te6u9x0Vlt5KLc6FcCAdRJ7IijDDjR8yB7ovZpiJCUe8i_k1qvQqfYKN52KKjeVYo="}}
{"timestamp":"2026-02-11T04:19:00.209Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"python3 - <<'PY'\\nimport itertools\\nC=[(-3, -1), (-3, 3), (-2, 0), (-2, 2), (0, 0), (0, 2), (1, -1), (1, 3)]\\nH=[(-4,1),(-2,1),(-1,-2),(-1,0),(-1,2),(-1,4),(0,1),(2,1)]\\nm=5\\n# adjacency matrix C->H\\nA=[[((h[0]-c[0])**2+(h[1]-c[1])**2==m) for h in H] for c in C]\\nprint('row sums',sorted(sum(r) for r in A))\\n# pairwise common\\nvals=set()\\nfor i,j in itertools.combinations(range(len(C)),2):\\n    vals.add(sum(A[i][k] and A[j][k] for k in range(len(H))))\\nprint('common counts',vals)\\n# Build full bip graph and check if Q4 using networkx if available\\ntry:\\n    import networkx as nx\\n    G=nx.Graph()\\n    for i in range(8): G.add_node(('c',i),bip=0)\\n    for j in range(8): G.add_node(('h',j),bip=1)\\n    for i in range(8):\\n        for j in range(8):\\n            if A[i][j]: G.add_edge(('c',i),('h',j))\\n    Q=nx.hypercube_graph(4)\\n    print('nodes',G.number_of_nodes(),Q.number_of_nodes(),'edges',G.number_of_edges(),Q.number_of_edges())\\n    print('iso',nx.is_isomorphic(G,Q))\\nexcept Exception as e:\\n    print('nx unavailable',e)\\nPY\"}","call_id":"call_WJKBkEtFd8kCiDzfa4CAzmom"}}
{"timestamp":"2026-02-11T04:19:00.212Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":914688,"cached_input_tokens":832384,"output_tokens":33989,"reasoning_output_tokens":25995,"total_tokens":948677},"last_token_usage":{"input_tokens":47265,"cached_input_tokens":46464,"output_tokens":637,"reasoning_output_tokens":204,"total_tokens":47902},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":8.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:19:00.894Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_WJKBkEtFd8kCiDzfa4CAzmom","output":"Chunk ID: 6cc22c\nWall time: 0.5289 seconds\nProcess exited with code 0\nOriginal token count: 25\nOutput:\nrow sums [4, 4, 4, 4, 4, 4, 4, 4]\ncommon counts {0, 2}\nnx unavailable No module named 'networkx'\n"}}
{"timestamp":"2026-02-11T04:19:00.926Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:19:01.337Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":914688,"cached_input_tokens":832384,"output_tokens":33989,"reasoning_output_tokens":25995,"total_tokens":948677},"last_token_usage":{"input_tokens":47265,"cached_input_tokens":46464,"output_tokens":637,"reasoning_output_tokens":204,"total_tokens":47902},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":8.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:19:15.515Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Planning exhaustive search for embedding**"}}
{"timestamp":"2026-02-11T04:19:15.515Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Planning exhaustive search for embedding**"}],"content":null,"encrypted_content":"gAAAAABpjAND-9r4QoN5vCAJic_5z4BNhFUfRoVH63_OX61Opol3bUqDuGA_GrmnU7dwZ_My5PgrpT9S3JX7jnD7GyWXU21xyoVtjF3w-YuUu3ypl3lP8EhJIhpaYMn0Z_2tNqcWWCJ9Pb3WBPRbsslMSHD13plIA1AHbIK6W7iCPRlp91t7FKhezCOHyVy49kEp7OcHRzGLvpioGO2_uwDGWwWcQyytfoZkimKgnBjy8f8XV5aMMfmHMwAujzzfhCeOoyVIvFasZint5O7H-EIdxGmK-JAFyj1c7Qwue3jIBEAXtc3oHVNZm7MuWQTsx2ZDsqUL4lcxDdX2PLUhdw4JSwRqHflALsh_gs8yI3Av0ctva6A_HpMvG1hMLrMn-uy8qQpOVc4ba3mqqH3iTC9YQHl0GcKz2Dkln4prOWnupfMjAE7DFkwFP2Plc841anj3Zs5Zcv2dN1q6u1VpEvHa9FIZlOSEr8U1WejetmY2xZ1EBXe-Pq_yvM_FsgTzHBp9eA8YB9S5MXXo83inp10GITl8amWMSCtNXwDXFSTwlv0qJCFi0zjafNdEJfhT9t4jIcyDJI-O-iieMmB_RWUniv4168MeSUW3xkodfVQettdtDMkXj3OQS1Cr0uvj26YbvJVGSoBwSDr14wwzFQeTdauSUS_8oQETxlYYet90qNuTNwqsrGcmITXTjesccbVMKuN25Wr-GQ6v7jz-Vbkq2yQ3tWBNHHSVNkaaDqqC0Z4sgkHDXR1vwRIzgv90c8VhVD84doPGCic0MCmJ9-r4wC6yDKf8BTaJoo5JSW8-baE6-ljJ_m0oWVxmwKjq_vvqCJ5HWwQt-2q5JpmuRZcBuJHbEGBtAxtQlPMKVZ7dcjkmYYv7lzmE_pd_6TltWSsV7PhFRxkVRYL31UHsFyGd0UgzBP39ptUR9bgwf_2g2OuecBYZ26A1RoaBLvjH-9sHY5Xwb2zySGOq00QWKshbVCpvyfVZhKFD-z_Gb14tUVJASXVueGyBY2MnpfD5GMYdkHref7bJzXrXFfCVSiAKmZlw7Oj3eEoUGteiLTbs3GrSYsWyUvfDFDFWUidxLynvKnxDamPp_BSr1Mf0I0Zqax79jaTSG7-8DYwb44S8tHcOVoGvVa6GXY_90SJieK43XuM4EmXUFu_9HPncr1Ld8VtgjH9D7tZ6DakBHr2LyfjN_bjoE1_vTSLud_Pmn49CjQMjCsKxf4ZesZeKgvDiIVjvDWU4pP853HLYGiAweoQsDNq_foRUOpLUFYHjqNBtBPIB99MvkaCpg94iIs2WQI77-zTRPp34uZ6aGnBE68kKa5DiNyiIcxWsMyOcX648S3fCVi-vnysSIlCHG3PxqnKshVuAOoL986m-68wRe8lx1WuTuQCFIb-TCYYHgI0aMD_GTrrmsOd4wu88EDm_r6En1IE3TM_IaP3YnMZVAKhkYvwr61FEPZDC_o2SWbwfBJ1RtGDBL-5z4JYwL2gs_HuNTnABUVMGi0srGzeYXCyKxwufgGu1GX9GHn4omBOLnrJoricBW-B4J0rh9PjCID50ZqZsFxSO5VC6RZiWJ5HhjLGCZRQEZD6ipUd4bj1P4iLWCuJQc6FykWkTrSG8GXQtk9xKP4lb10QzT-mN1A5f85YhDxIEQKt-RUcWAMsXruzXisIiSPpQR1TOfnw3n-myTi54nwl4AAcj7JwfBIsD4N6BZPGf0blt_AT6SQVRek3aid79u0rImHOrHObE_3eRqV4mNmG7VxCkiXoWtw6m5zbjaJUIEe6BOC7PMStaRLtYzVSj0zk7gVpVdK4g74yVAFl8QhtpcbO6CMeeE3IxIPPI_oeC_CcNKScI0JGaHYqsPk70dYdi1lMOw1HEANYlu-vM4cK6hcO3-AEYFscvzDhXX8M0427Oov2Mz9ak2iqq8e1T8uzZlQ2oG0_ek_25Gv6mAHWboMPp7b834E7PGLKwX387T17Pfx7ak50VzTWm3xwt_OGgjfiRBaFupCOTXv-FcxvW3ix16Mw4p0St9ye9ykgPp23DcivpwOi_cH8v-1vJDr1oNoKWPGWGZJlFwf03EkuB6hDdtXdnfuE0lddtF00tGV7oiIFfoZ4nAnwl7eoaAlqJ9kqJ4rw7MNJi8HGU6In8QFPUK2jMoOxzBduZWwaMANGw7X6J1zLF42IJ6AW0aD34sH6W7HhU1_qiV_tDwPZ2YefS2P0wr3VJfA_LjqDKrTksNIKgDTJSnVDbxctmRFcfo2UEsHJgY9wkEXoh7E_RCtK6hbVJeBG0pMwjYIjvkkN9Ab4GhaJFHvRmOHyekZ05vhWp80VyAVh9cR_W4MvgcxudY4W1dGHvIavvmK3ogw76BLZyF6MDIyuhC2hSmNqGA8D4348CNr5y0j7ievo-gY_oK1VNPzoMlGhgmCO0TiOeLSx7jSlPHtpCsXBqavSAICcLOl100dnUHfbkU2CSm3Sp2ftRkeD2zCHuCG9hGlr0W4JrgvG7kgG5uxzSLteEdSVJmk5t4v3SfWsoxDHGTA05msW56d8IXEJu8sQRord74V_wPL2hr6_4YRr7MnRtlJOd3JzkxVv_ibtv8hijE8aki7SNSGiXoAo_U-u4lYFl7TRKI46NwuHJer4OyrJJ1z1g12_ftRV_2QstUT2HxdFucx07c3fadEkgLrRxIu_AiNEJh_VVxVNaRzJYkHs1Bg2bN0tTwpgEXeAekKSgaxPTz9LyzLoPQzM5AFZP81D3LpCdVD3-9XHMVuLN4EDeNMYTiErR5RBR_AMlLJaxZckV9T-pzDC5EvQ25-QmE9uwyQUpsartN2Wjw9HLpHQ8TyaIyyoI0-ATn4mVAKhs8JXpPw0sbB1MK3whbDXT6_CfWJIax9XeEV1b9vrvf9W0vd2MwxctYd-cDcfBJoUIjz_FAYKPcY6gEwcsICSYNubnw_x_gxiarN8P7Wp3mQkB4d425GCBytgsIyS6Te28_R9YYqL_NZMcG3wnNhcjUDeKbKsm6I9pcdbAlfDcIVPVyALNaiP7OOh1yJq4NcKZG-PCmEhdRh01YtPpA92n6Q8M_hwntQWKgf2rmKR6TGxthFgL9bmO0LdN7Ho_luja-GWKVYYpvDNNPtaNwBVwks9TZQ9ILR8Pmo-9L11QUn_ApKr_Cfbp6Z0WdcrjZIysJx0rd74bCxB1DQDm3JzbT4L1qFmdS6iQ_yNAfXO4apoayAhpi-zY5KAMkDKLlUn0fa2u3PsKIEArWdwO9PFsgfTOtzEYbgKoeqqiKZ4oShfKh2uPSQHJtEk-CmQOYo9TFYHTtUcWwyXZYxOzvPSJc1oV5RoFgsEewjbqfrH_WWYhz7V2KLbkiwxOR6mOzfJQE5UrEEgZkZnqu1Lm99XyoziONaM5rHvmPWy6fnensVnOiW1KUxH_4KolMpJAzCJAul86M_UR80sJuIKp8fVtBrXRqoUvvciY9zZ0WiD99akQd2du262dx9LJdPPIkv-1Rt0Vha9P1QLiRFVtIOCBdWCRyLna33Z3GG2ILy9gENSbrazBKbmiIY4ZPLa4Nxt4dfOkYh9hNmyfVlf4uNoo6eZwsWI2peVVZkRc_LPT4QX5TnqsbrfGHTjj2H9C5TgBLAE23F-yALcj_tljOoDrWtfpn-6M6OmRPpuCNe6_Cry2KFHuYkupiiCnI6NVYCvPLMqjvwphrhocQ77v32KPthqdZkoAS2aquIUeYs52L6_t3VG4pfNS6SGPTak2fVCcLp6v7Y7bjj2BaUzyjMMCPmSNVwoaOqR1LBdaJj2_Qa3p-zEiRVCsH-BlXNRUckEcuix4YuDIsEjFtJZkUZbwAe_VZVd4NKLEWDNGr7ioWRMBFKebKTb_x8upmBhCfopw35NHHar9gz4v10xcdAe1h6pjxomYDkRi5zBskP_4jpP2bsvuJjYn8OxSeBcWn_sVy2wrtqvmFy8DVbqeejqSjjirsEmF719MkaYrHbDs7MtDuwMbYiOaUgGdI2yAzpi_w5L7vScv1IMYHGR4a-vTiPqNo4AF0Qh6LEze0fEvRk6HqdAOShzYmnR8czfbvlyI03bRYxoFMmCp1cC_gIdlpF2E1jB4YpQ1hIr1k7w2l-6sXPZXFMdubU8UmyQNxhH8qNxX3QR2NA-wVAVFF52tdjCwzl4ecamyEzNhNL-IiYpFXKHInqX_aAcQE8DZzJXz5mS0f-hT2MdgCGuBJl1026jY-4Y4qD8vg7ReXOoYMr3KImL5OlZ2rDjuSsq5WIOj4WZUlOX5TqzcQWaSa8RYW_ypXJJcHB-NirYjywwA3Z6q-vfMcT9rDq4S2lpMc4eD5vjNx-zFKptAEnZnIB3P44d5FOWRwArX_h71copRIUW0dl-GfGqkc1eWFJrSU_IZFBgl1KcNgnL9SOxYYHaisWVr_uivtiqlcZyW-4TJmM3JWXNHsL0Z5hezWH4MYirAZLuks5Ax5C6C4kj3BlDY4SbQtYd9D90bkn_E4EY2bTsSB2tG5U2EYpw-lVdK8k62VdV2bhe8hsIaU1XUxFmAN6qXhznL5gTlb4a3873XwibqWS_0B4OyYy44Zcvl59ND8vRWpl0BedTXGLwJQprG-7Pz_AcL8C85B083328QAJoAN5ZOj6ILkvPB0rp7DIaCR2b_3nSBQ2JZ6eibKrlpDUpcWWtOQx8t4bl4_Sm6nJIpsiKeyLYFGfbe2cXYOzdqBIlS_cGKXj-uTO0_imvHb-a91s9mo4PQC1jyTfTgZLoCNT35gI0CKm8yL4Oh12cjrPqcF56XLAXyEsrpAttkf5CfFQkf5vQmcAliF3ga8MKI7Ae8s-8HgyVeZscxyePYTCF7baAsc32V0IS98oTuI16xdKFwe616q6icIt4x5tmBbhKMMLllnNtVCX2UBFFA9URmfpzq7RnsS1j5tUgD7WnuQPApvJZjeINlaE_sRj1nrbCSbf2VbJNBItPatUMFyLKxvWX1sWy4N_cL7vZTBDNuswUf8Uneg8ndBcOjD679BIeYWLPiw1SDjIk-jC-CChB1N-jDYE2tPbUPCzJkijdfelL0uLu4HP1Xdqb1dBOzvn0HCMURMgc9xJISUuTdbK1RFP09jeHeKrwj1PkCuoDW6Zrn9QuwTv8hcQrP"}}
{"timestamp":"2026-02-11T04:19:16.388Z","type":"event_msg","payload":{"type":"agent_message","message":"I’m switching to an exact branch-and-prune search for \\(m=5\\), targeting \\(n=9\\), with canonical-state deduplication. This should tell us whether size 8 is truly maximal or just hard for random search to find."}}
{"timestamp":"2026-02-11T04:19:16.389Z","type":"response_item","payload":{"type":"message","role":"assistant","content":[{"type":"output_text","text":"I’m switching to an exact branch-and-prune search for \\(m=5\\), targeting \\(n=9\\), with canonical-state deduplication. This should tell us whether size 8 is truly maximal or just hard for random search to find."}],"phase":"commentary"}}
{"timestamp":"2026-02-11T04:19:32.053Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"python3 - <<'PY'\\nimport math,time,itertools,functools\\nm=5\\n# vectors norm m\\nlim=math.isqrt(m)\\nS=[]\\nfor x in range(-lim,lim+1):\\n    y2=m-x*x\\n    if y2<0: continue\\n    y=math.isqrt(y2)\\n    if y*y==y2:\\n        S.append((x,y))\\n        if y: S.append((x,-y))\\nS=list(dict.fromkeys(S))\\nSset=set(S)\\n# displacement to oriented offset u from first center -> one harmony point p1; other p2=(dx,dy)-u\\nD={}\\nfor dx in range(-10,11):\\n    for dy in range(-10,11):\\n        if dx==dy==0: continue\\n        if dx*dx+dy*dy==4*m: continue\\n        pts=[]\\n        for ux,uy in S:\\n            if (ux-dx,uy-dy) in Sset:\\n                pts.append((ux,uy))\\n        if len(pts)==2:\\n            D[(dx,dy)]=pts[0]  # pick one\\nDs=list(D.keys())\\nTang={(dx,dy) for dx in range(-20,21) for dy in range(-20,21) if dx*dx+dy*dy==4*m}\\n\\n# symmetries preserving S (dihedral of square)\\nSyms=[lambda x,y:(x,y),lambda x,y:(-x,y),lambda x,y:(x,-y),lambda x,y:(-x,-y),\\n      lambda x,y:(y,x),lambda x,y:(-y,x),lambda x,y:(y,-x),lambda x,y:(-y,-x)]\\n\\ndef canon(C):\\n    C=list(C)\\n    best=None\\n    for f in Syms:\\n        T=[f(x,y) for x,y in C]\\n        # translate so lexicographically min point at origin\\n        minx,miny=min(T)\\n        T2=sorted((x-minx,y-miny) for x,y in T)\\n        t=tuple(T2)\\n        if best is None or t<best:\\n            best=t\\n    return best\\n\\n\\ndef pair_harmony(a,b):\\n    ax,ay=a;bx,by=b\\n    dx,dy=bx-ax,by-ay\\n    if (dx,dy) in D:\\n        ux,uy=D[(dx,dy)]\\n        return ((ax+ux,ay+uy),(bx-ux,by-uy),2)\\n    if (-dx,-dy) in D:\\n        ux,uy=D[(-dx,-dy)]\\n        return ((bx+ux,by+uy),(ax-ux,ay-uy),2)\\n    if (dx,dy) in Tang or (-dx,-dy) in Tang:\\n        return (None,None,1)\\n    return (None,None,0)\\n\\nTARGET=9\\nstart=((0,0),)\\nseen=[set() for _ in range(TARGET+1)]\\ncount=0\\nbest=0\\nstart_time=time.time()\\n\\n# cache pair results\\n@functools.lru_cache(None)\\ndef pair_cached(a,b):\\n    return pair_harmony(a,b)\\n\\n\\ndef dfs(C,H,frontier):\\n    global count,best\\n    k=len(C)\\n    count+=1\\n    if count%200000==0:\\n        print('states',count,'k',k,'best',best,'elapsed',time.time()-start_time,flush=True)\\n    if len(H)>TARGET:\\n        return False\\n    if k>=2:\\n        # connected maintained by construction\\n        if len(H)==k:\\n            best=max(best,k)\\n            if k==TARGET:\\n                print('FOUND',C,flush=True)\\n                return True\\n    if k==TARGET:\\n        return False\\n    # prune: even adding remaining circles cannot reduce H\\n    # choose candidates from frontier sorted\\n    cand=sorted(frontier)\\n    for b in cand:\\n        # build new set\\n        # tangency check with all C\\n        bad=False\\n        newH=set(H)\\n        harmonises=False\\n        new_frontier=set(frontier)\\n        new_frontier.discard(b)\\n        for a in C:\\n            p,q,t=pair_cached(a,b)\\n            if t==1:\\n                bad=True;break\\n            if t==2:\\n                harmonises=True\\n                newH.add(p);newH.add(q)\\n        if bad or not harmonises:\\n            continue\\n        C2=tuple(sorted(C+(b,)))\\n        # canonical dedup by size\\n        key=canon(C2)\\n        if key in seen[k+1]:\\n            continue\\n        seen[k+1].add(key)\\n        # update frontier by neighbors of b\\n        bx,by=b\\n        for dx,dy in Ds:\\n            nb=(bx+dx,by+dy)\\n            if nb not in C2:\\n                new_frontier.add(nb)\\n        # bound on min possible H at final = current H (can't decrease)\\n        if len(newH)>TARGET:\\n            continue\\n        if dfs(C2,newH,new_frontier):\\n            return True\\n    return False\\n\\n# init frontier neighbors of origin\\nf=set((dx,dy) for dx,dy in Ds)\\nok=dfs(start,set(),f)\\nprint('ok',ok,'best',best,'states',count,'time',time.time()-start_time)\\nPY\"}","call_id":"call_LTkQECxIrsEQePuGN3RnWQYo"}}
{"timestamp":"2026-02-11T04:19:32.056Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":962679,"cached_input_tokens":880256,"output_tokens":35990,"reasoning_output_tokens":26675,"total_tokens":998669},"last_token_usage":{"input_tokens":47991,"cached_input_tokens":47872,"output_tokens":2001,"reasoning_output_tokens":680,"total_tokens":49992},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":8.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:19:36.166Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_LTkQECxIrsEQePuGN3RnWQYo","output":"Chunk ID: 27d62f\nWall time: 3.9571 seconds\nProcess exited with code 0\nOriginal token count: 13\nOutput:\nok False best 8 states 4183 time 3.358341693878174\n"}}
{"timestamp":"2026-02-11T04:19:36.199Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:19:36.563Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":962679,"cached_input_tokens":880256,"output_tokens":35990,"reasoning_output_tokens":26675,"total_tokens":998669},"last_token_usage":{"input_tokens":47991,"cached_input_tokens":47872,"output_tokens":2001,"reasoning_output_tokens":680,"total_tokens":49992},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":8.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:19:43.135Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Confirming max size for m=5**"}}
{"timestamp":"2026-02-11T04:19:43.136Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Confirming max size for m=5**"}],"content":null,"encrypted_content":"gAAAAABpjANfIXSPRLkeSk3-OGxsxKLUH9pWoqQqejBhKh-PZNgKErykn9yy_ndr6HWeU6RcT93gmOn8eC4ejgZSExp0K5o69pR9LAtlG9d5WhNZ2tTR7UclY4o1GU5XVd-2sDwnrqJvYjpvc1FIln0VWqM6IfUkKel5S-nPkH0SLCUB9JJiR2yNINgyv1xghP-PgEi_7hHzkEoJtnJhfWt30nUsF4bhzsSzZcA1VjTxQuim_3uQCVRaqIZB0dveq3wxzlxF7v-V7FO6pixLyJoORDVbYfbbGilUUOgEEs8p9mCiyO8P_XGg_kYwyEK2FaKlkg6rswrmszeKWKn77vDRPwffXx694nBOTYfaV0xlMCV4ZMbbLELpR7sdSFyGQF3C343wne-PspNX5L68WN8Y1-1HYCAdD62ZbANrSs2pwxeFh25EAEIcZpwWAPXsbaZcchxbb5AEiAFCDGRxplP7HGPkwLCt-SUnr28qj3mMH5zxr-9pinQUX2g6-XaO4sACAzsfAEXQ6bqGrHH_MVYXFb8rIaVf9hEeRivDsezHW9LiykONI4ReGCvOoxGXpF8mQ3s6tVaBM297lVRp-vh4_3LCi3Uk4pN1S_sAmZk1DUzzGcGShKlnuZoUAlGKRZZNzfg80vlsrqYEf5HsaaP9yT99TdOZ2pzT8zq0i_ntK6O6mUkhGuOvU-Aal2Bd8ZaKqGJ6WCv6zlmcSB66im85xtTZR-dzetE5bngqwc9cX1xXYEnp0feofQBOuISstDOCMpmPnxuySTAMm0Qmvt1kbU1Pkh43OkOk1XqgW5oRcjapjklaIa2-pYGZaH4iNerB3F_mLDkwAlNa63yxGFE7aRptGsXphBM-he4iJCwxFQ0RC236WTDydSOVx94Vexw6cbvXV8vPpIFu8R1sYZsTeu9BaR37x8sLUAlYXCbmpjVzZKozso7msvCsCh-0MIcGpcbcui7JRe7oglqY4BO9FEKnV38cB7PK38PjowKtLpo0GfM8bz_V5LmcBunr9rMEoQOw6HGu5p6w-j6SnSF8zrFPa5zzWrH9QpPZ4Y3XvifWC-WqYFcoie2Jc3CGEQPu4blInplkG2VNYVgddl50wUX6Qt7pK2TUb2fcXPv8jtmmclVbn5jZgs1o6YHyT6zy5LNdCaTldnlKAWM0IX_X9C4ZoLZlWLbkJRLMOvgSypenyKx9tWBC3nvmf2dq97HSBq08TqK7SrKLtzvQIQArYGJYd2Nhm2RELMqEawUsKCD3o_u9O3KkpWd_-9NL31XNRG9UiHs2VOi9H0ouZUMinG79lc-WS7L5gxZlxUD_NMMFDq8rIo4OPtoEmO60BxUpRwyl6NtoEqxASfvGXnf06I8fl3JnjLeNDz2Hgn07oCkdf5AbwBeyb83IGmJuYEY1_VGrCxNnlsJm_dQIZ1CmBBe1_9Gy_Eea1P8IrB7BsCxcsJo2zma_jG32EhGeeF29so1EG3lq2e-jN3BaZfrQ3Z6_HRlrAYLjd4zBYSZ51kx-_uWnC3xC4UaBoMKvElX_-kwz2KSBjMZAYlm-TsIi6eUFK9vQgs5d6RdTrb8PobDlV3AhK28dtFhUkrpJtWtogRiss0985giUSxLhmxPi4gdY7n-kSr6xMcgFFQjJBIHLJIZO7n3gzW4dVkXWkckhw8LCOOqKqXm5BKRwGsyGWmc9oQos9U7ibhQ3sRG5BuFAZKHzhY7yuSJ9SSAR4bjQrXB2hOhzNUVLO3euPoaVXgJvMKaHQgZ9CbsH2qhZ4dHcQpJ1F9VfB4mVkZtSHOjkbAZDGCIjl0vKtXUaiZwYURsrdzjT5aG8Y6BPfBA6x3RcCFIwlqGNf8t0lduGtmR6wXA3xm5R2SUKuASs2-5sXu40ILa1rtHgE_k7TKzlifUQQrJ7uM2PQuD6OC9dvS8YG7D07O1dJciDSnsOmqBUu3h-xuClSzhM9A1LDJWjpQCKT8mj_daAW0_QF5NpNWE5zLXEfQLQeqhz4KOAu66qne5UlgepXre_EFz3xcTlNMg3uJMMSBNCt6dTfGZYEmXkyVzB-E6JLl3ODHwCWr3L_STaZmmFURUd566JkpwpsoGjmiNxm2KZREikF58Knb_7OXMH8ugG2__Ta8w_BxRVzY0112WAiWTggwEitXpw-G2qdasbySeynMQH8kNLLWR7DEE0D-HxQaAbOhEwGtJ7uNLrSBYpRazrNwAES_1h_u9ZMvGMJndvjQDBAJwawiR_QKMorz86Av324WQFiiEsYkYYh6xgI_-SdsFdvMG5sYyw4WgNHJSlOpSDUtNttFEteNNMzBV9gcT7tSbduwiIZn8nZjKgoxd7NOMCnOkoMJCvI3wZoPVIyUqUnIhdK5scFz1lUnejlQmeFCuiC2lzEYIvNX9yY6jez-JCn6_hfemeUjs5mkCSEBF0q5iblhReKkIt6CxfZkST9pnS3bEgSLtrEyTAeAxoquWAGzB1eQ2UYoDEWkeKukZxu9uClVGnVDTmIPG75Uexb-rUovefyO1Q2ac6VUnerXNuJmgYU43ruIXY9iwnzNR0pTvG-hgJb9cr3XSLZlkY02XQ406BQBxakPEAYRzzKrjZafCYNAUUIlqh785LuyWm8ER-tecOUoricVIjow-NdUys5qKNTEIA9TfvioNbGzrsrKeXE0vlOQLHtlALV4oI-p6fD1o7dx9VGwFFiwVJhMBS_XUpBR3LeJLWyQ=="}}
{"timestamp":"2026-02-11T04:19:56.529Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"python3 - <<'PY'\\nimport math,time,functools\\n\\ndef max_perfect_up_to(m,TARGET):\\n    lim=math.isqrt(m)\\n    S=[]\\n    for x in range(-lim,lim+1):\\n        y2=m-x*x\\n        if y2<0: continue\\n        y=math.isqrt(y2)\\n        if y*y==y2:\\n            S.append((x,y))\\n            if y:S.append((x,-y))\\n    S=list(dict.fromkeys(S));Sset=set(S)\\n    D={}\\n    maxd=2*lim+2\\n    for dx in range(-maxd,maxd+1):\\n        for dy in range(-maxd,maxd+1):\\n            if dx==dy==0: continue\\n            if dx*dx+dy*dy==4*m: continue\\n            pts=[]\\n            for ux,uy in S:\\n                if (ux-dx,uy-dy) in Sset:\\n                    pts.append((ux,uy))\\n            if len(pts)==2:\\n                D[(dx,dy)]=pts[0]\\n    Ds=list(D.keys())\\n    Tang={(dx,dy) for dx in range(-2*lim-2,2*lim+3) for dy in range(-2*lim-2,2*lim+3) if dx*dx+dy*dy==4*m}\\n    Syms=[lambda x,y:(x,y),lambda x,y:(-x,y),lambda x,y:(x,-y),lambda x,y:(-x,-y),\\n          lambda x,y:(y,x),lambda x,y:(-y,x),lambda x,y:(y,-x),lambda x,y:(-y,-x)]\\n    def canon(C):\\n        best=None\\n        for f in Syms:\\n            T=[f(x,y) for x,y in C]\\n            minx,miny=min(T)\\n            t=tuple(sorted((x-minx,y-miny) for x,y in T))\\n            if best is None or t<best: best=t\\n        return best\\n    @functools.lru_cache(None)\\n    def pair(a,b):\\n        ax,ay=a;bx,by=b\\n        dx,dy=bx-ax,by-ay\\n        if (dx,dy) in D:\\n            ux,uy=D[(dx,dy)]\\n            return ((ax+ux,ay+uy),(bx-ux,by-uy),2)\\n        if (-dx,-dy) in D:\\n            ux,uy=D[(-dx,-dy)]\\n            return ((bx+ux,by+uy),(ax-ux,ay-uy),2)\\n        if (dx,dy) in Tang or (-dx,-dy) in Tang:\\n            return (None,None,1)\\n        return (None,None,0)\\n\\n    seen=[set() for _ in range(TARGET+1)]\\n    best=0\\n    states=0\\n    t0=time.time()\\n    def dfs(C,H,frontier):\\n        nonlocal best,states\\n        k=len(C); states+=1\\n        if len(H)>TARGET: return\\n        if k>=2 and len(H)==k: best=max(best,k)\\n        if k==TARGET: return\\n        for b in sorted(frontier):\\n            newH=set(H);bad=False;harm=False\\n            new_front=set(frontier);new_front.discard(b)\\n            for a in C:\\n                p,q,t=pair(a,b)\\n                if t==1:\\n                    bad=True;break\\n                if t==2:\\n                    harm=True\\n                    newH.add(p);newH.add(q)\\n            if bad or not harm: continue\\n            if len(newH)>TARGET: continue\\n            C2=tuple(sorted(C+(b,)))\\n            key=canon(C2)\\n            if key in seen[k+1]: continue\\n            seen[k+1].add(key)\\n            bx,by=b\\n            for dx,dy in Ds:\\n                nb=(bx+dx,by+dy)\\n                if nb not in C2: new_front.add(nb)\\n            dfs(C2,newH,new_front)\\n    f=set(Ds)\\n    dfs(((0,0),),set(),f)\\n    return best,states,time.time()-t0,len(S),len(D)\\n\\nfor m in [1,2,4,5,8,9,10,13,16,17,20,25]:\\n    best,states,tm,s,d=max_perfect_up_to(m,12)\\n    print('m',m,'best<=12',best,'states',states,'time',round(tm,2),'r2',s,'|D|',d)\\nPY\"}","call_id":"call_DLMqsgTpKrfqHOsQVYx29eJj"}}
{"timestamp":"2026-02-11T04:19:56.530Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1012736,"cached_input_tokens":930176,"output_tokens":37375,"reasoning_output_tokens":26978,"total_tokens":1050111},"last_token_usage":{"input_tokens":50057,"cached_input_tokens":49920,"output_tokens":1385,"reasoning_output_tokens":303,"total_tokens":51442},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":8.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:20:06.685Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_DLMqsgTpKrfqHOsQVYx29eJj","output":"Chunk ID: 967f36\nWall time: 10.0010 seconds\nProcess running with session ID 51844\nOriginal token count: 0\nOutput:\n"}}
{"timestamp":"2026-02-11T04:20:06.719Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:20:07.075Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1012736,"cached_input_tokens":930176,"output_tokens":37375,"reasoning_output_tokens":26978,"total_tokens":1050111},"last_token_usage":{"input_tokens":50057,"cached_input_tokens":49920,"output_tokens":1385,"reasoning_output_tokens":303,"total_tokens":51442},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":8.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:20:07.792Z","type":"response_item","payload":{"type":"reasoning","summary":[],"content":null,"encrypted_content":"gAAAAABpjAN34Educ9UjiP5Fjq3_QsQbRvWGPtYk072ZSADy8Rxgny6qhvJeEb2oGtqnAObTlZFdDCNkMuBpQAbc7UvzfvZYSzZg0WUakEjrMF75-ZF9QaxQxyY2q3J33FgJ2-JdgpOyZdWN2PnOwUuP3oJNvacG6PyQZyM5cIAyF4P_e9qCDgf15IR2b9g0_e-uPiF4RWPXjpwiycmIJRpnNAQ1DQMciuO1TmP2p1If_yllR6yhnatqvgQBKiqqs90a0DXhMi3tZhqfC3eCRe2QfGWuubTvwX9fid5G9UvNdmhNQUTQSNcrxBgY8mjk0JSyIrYncClFOJk_C5FuXe0mn2WNofPhXo-rQ3AVFJIKdKgzciFb-J6GNhqKAQbo1LaUnXby0torhKv2JPVxcG3WZSlcjFPObQZL8Q4V-GwpLS3SzBv2F02IImBwxMV6lCR6dnBwR6gV7pROZBYZRE2_Sw1J91Q13wy5gmCvFZptEh7BiRTXPtl5A1SAxwQOEAfMi4VbFYW0YXtSWQ4OBCEdNONGZ5lWMebvqUzoGCaRoMbeHW5xB3Ef3rEJIhAdJRbURkquXZlRW1J5jahJrjy4H12bCBfKL7-vbtyDoPgoxRXSXSLKG1niMkiy_30j657P4cimQqP0GazNa7DNmmd99SiscGVX3GtLpM1ocLnbXOEmjsosZ22feZT02PAdTvwv3XIcfbVdnHLR-bDpbbdeN2GlBR2dBkajBwyCD9a56Y6UNSkxMvLFqIpm9yZXADbmvsfZ2MNZzMq4DHkKINj0N-9Yu52Z-mNJ0DX5IxIPrA2Y2nLysbQqhcogM_qJlJYwvtnUvlpOarvwVPZEmcgpKxN9de__2Q=="}}
{"timestamp":"2026-02-11T04:20:08.611Z","type":"response_item","payload":{"type":"function_call","name":"write_stdin","arguments":"{\"session_id\":51844,\"chars\":\"\",\"yield_time_ms\":30000}","call_id":"call_EoXebbNU1z59WylqW8UoWknO"}}
{"timestamp":"2026-02-11T04:20:08.613Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1064225,"cached_input_tokens":981504,"output_tokens":37414,"reasoning_output_tokens":26985,"total_tokens":1101639},"last_token_usage":{"input_tokens":51489,"cached_input_tokens":51328,"output_tokens":39,"reasoning_output_tokens":7,"total_tokens":51528},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":8.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:20:38.648Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_EoXebbNU1z59WylqW8UoWknO","output":"Chunk ID: 896ce5\nWall time: 30.0008 seconds\nProcess running with session ID 51844\nOriginal token count: 0\nOutput:\n"}}
{"timestamp":"2026-02-11T04:20:38.649Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:20:38.957Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1064225,"cached_input_tokens":981504,"output_tokens":37414,"reasoning_output_tokens":26985,"total_tokens":1101639},"last_token_usage":{"input_tokens":51489,"cached_input_tokens":51328,"output_tokens":39,"reasoning_output_tokens":7,"total_tokens":51528},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":8.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:20:40.249Z","type":"response_item","payload":{"type":"reasoning","summary":[],"content":null,"encrypted_content":"gAAAAABpjAOYGpP-aE_tuOCvvs8WvjUx4Bzh-TSglDwBG5XaqbHKW_N5l_N1EQIxyguBt28d8PLBLc0naye8d21EbyuV6X1Iv3txYSaiAPHIn9TgttbfPXRbtzDEBSbRNpQKKcysblPpQX3vsQVq25bCeNJb-oWdYw0-uKrpVhd6XYzM_B2II22NaTnjjMAj3nAkb-eGRyiQpS9m4T6z2pU5MKvoSMIusZsjz5NAzIP_wJA69mwwpr7UuXrSpVaW_EK4CGWdeBid2pxWKOt-e_s1FOwAcECWj3mezg-NDiT_4drF7ulOBoILOvW1lgsfBUkw2uIawVehwvR74Cq-qnvpx6Qv9IaAqtdSnwNlYoK7deBLRgyQtJehDS4Fb5tYB9DeCs4pi41YY5lMIeRR6l8NcAcCVnXb0IlwFp1vZB_R3eWKM_WbDwoOo6S4jgT7EsjbhogdcIXSadgRHHnDL80JEj6K9KeiryvKb5bfjR8-M_X7zaa9BXhXDyejjOnFDt6YpLk2XwsfLqQd9wa929eXv9mPl5u5fnjG8j7IubyaJ2aoNK9UqPqImtVtFKAfuHmtxfPXP_0otTCZHx0cgLlADbyopyFfXsfiKwZE5mi62oW_FrgLaCTVtY75zghqyTgW6B8KFu5CdSubUYkV-XXIanvjSJB9hlXf-3LhwwKDii_28RpKyxg-l3Q84iYL32GrBZlr-s6zlmTUm_9_RDI4pHE19LS6f2G1MGUFKCATvuFSxn_eHfH0NORH4lLGl7aeb1pYJJh31amF0SUgV3-jAEAeji8Xn-2D_dmXk9LU2sR1N7CjcP8evenh05qfH_qvHV9mj3s03GirF1yT7SXhXJF5taXS8eJ1xxZYypaLsUwBqu5GO5_bC_gw-KPxNxiPXE_-6RxSLUTr-SnqF2Jj1bm8kX5wp0pJsDuQoK7LfTA4KBKtVvKZUEQjZr1T2yde0_DNRh9p"}}
{"timestamp":"2026-02-11T04:20:40.537Z","type":"response_item","payload":{"type":"function_call","name":"write_stdin","arguments":"{\"session_id\":51844,\"chars\":\"\",\"yield_time_ms\":30000}","call_id":"call_9NzL2tIAtlVHAxyWbbyLQy7f"}}
{"timestamp":"2026-02-11T04:20:40.540Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1115801,"cached_input_tokens":1032960,"output_tokens":37474,"reasoning_output_tokens":27013,"total_tokens":1153275},"last_token_usage":{"input_tokens":51576,"cached_input_tokens":51456,"output_tokens":60,"reasoning_output_tokens":28,"total_tokens":51636},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":8.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:21:10.573Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_9NzL2tIAtlVHAxyWbbyLQy7f","output":"Chunk ID: 5ab3d6\nWall time: 30.0016 seconds\nProcess running with session ID 51844\nOriginal token count: 0\nOutput:\n"}}
{"timestamp":"2026-02-11T04:21:10.573Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:21:10.947Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1115801,"cached_input_tokens":1032960,"output_tokens":37474,"reasoning_output_tokens":27013,"total_tokens":1153275},"last_token_usage":{"input_tokens":51576,"cached_input_tokens":51456,"output_tokens":60,"reasoning_output_tokens":28,"total_tokens":51636},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":9.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:21:12.318Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Switching to unbuffered output**"}}
{"timestamp":"2026-02-11T04:21:12.318Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Switching to unbuffered output**"}],"content":null,"encrypted_content":"gAAAAABpjAO4JjyPmd9IPrYlq9s3oGoRJgHkW5Bx5qtbyEbfYADjaMDNryjxEleGHhN4HFFFkmo7-8WYs1ffdgi3PRt4fdU2v1UPUuLy33EMleMS2OiF6OJJrx_bLh-4vtBtaU7OPbCRk2HuFVDRlzMTxqN9cPrC6jlxQBrGGi_sLqthoEhRcuDPyc-UOO_KFDLZj6DsVgP_HH1FNL5P5pE3xtB7_Uy6t3c5ZcJaUHZY9kUThkjKWE6oMqRvKutnLEALwMRmkYeitmlIvBXcVjlvw33Q8JahNOgOfeBRx41a-x_K6wZiWJYW7MJqDwqoUey7Vp7Vwx0xEhE98gAjhhNlRjcj8XhefBX4GYIp2PDG1a3AJW5gtning9c0kRk-vYsx0W8RNaemqVPCGS-hu80VXBeGxM8MsnsZtuZW2RnFf6alj1busxZvnDhdO2pCLcqCLzLypYE_UPAl4o_c3B3ZDIN5OyUbY9biOfEof8DxW0ltNWv_dLX-GqI9Yj0vE9fPLq42GblSKapopwVDbOmYmM007CqDGv9nXVj_d9dmmckgYTfA0_f9d3rtZl5ahLayjx0HhcO5ENvPcXpqN_ZeqG5eo7iod5c1Q9MNc_V9c0C49GGtKaznBS47McwlXjfNKFc-I4x5fbiYN4xDSuVx3ZKQH4J5V83awYLdJRK3fO6D91ZNdsQJx8jSgdFnc0k37iXixHk4SFlwAE8CaaQgokm-QJQj8aU_iA1RZDBZQjHEdcAZ6rTF-ibn7lv9znWmqZVDEjMpZxjz2c-wh1NpA2R71oKOy_JX8QlMOqmTLyygw1AYR9N6SoRJRTzm6UXTTF02ehB076zZpu3eZEdTWcLwJQowdnj9UjBm1_J_jnEFj_l2Zn_NbCZboc9n_6GfVAz0kU3slX-XDSivJ4Lzu6k5cgEz5eMl25IvnBnTf_k1SwiaHkhOVmQIwkcT0axK_fr2J2_vz5IgYkwr3wNwYVhQyxpR-HWHznnuELJgJf3tzRx8nhD2p5EBt0TmPk1CFgAvTjFsvEcT6Vmn3LicbFzWycWItprT097iTEuGtjTTpTICXiXZdaMa547Nf5t67IWcaTgd"}}
{"timestamp":"2026-02-11T04:21:13.226Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"pkill -f 'max_perfect_up_to' || true; pgrep -af 'python3 - <<'\"}","call_id":"call_1C02ayKjW3jrO6EquNtXwabg"}}
{"timestamp":"2026-02-11T04:21:13.228Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1167487,"cached_input_tokens":1084544,"output_tokens":37561,"reasoning_output_tokens":27057,"total_tokens":1205048},"last_token_usage":{"input_tokens":51686,"cached_input_tokens":51584,"output_tokens":87,"reasoning_output_tokens":44,"total_tokens":51773},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":9.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:21:13.933Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_1C02ayKjW3jrO6EquNtXwabg","output":"Chunk ID: 58c88b\nWall time: 0.5525 seconds\nProcess exited with code -1\nOriginal token count: 0\nOutput:\n"}}
{"timestamp":"2026-02-11T04:21:13.969Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:21:14.353Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1167487,"cached_input_tokens":1084544,"output_tokens":37561,"reasoning_output_tokens":27057,"total_tokens":1205048},"last_token_usage":{"input_tokens":51686,"cached_input_tokens":51584,"output_tokens":87,"reasoning_output_tokens":44,"total_tokens":51773},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":9.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:21:16.197Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Adjusting run parameters**"}}
{"timestamp":"2026-02-11T04:21:16.197Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Adjusting run parameters**"}],"content":null,"encrypted_content":"gAAAAABpjAO8bvViqua1eexbhh9laPR9zmGZe11JDvCZqwFfU26XMcNPzPas0RKgVB-fJ9JQa5WP498NUZFO6VqCh17CwAnt7XprowK4_hhxFaXj8d1Tjlnvq1zKbrm-K1kr5oK4bVW7W_PvqtOKKzQ_x-NnXFBMuSv8k4e4T57DAaN9l6YHkM3-WLeAd3A137dX7MdcgjABU7R3wCuDQqCkG8jYwgb382AvjObE0jkg3F-EbkKqPlP9OwIaZ4SGfdAS0Z4fxl6uPHzI9Vew7zhiBJ1b37EZ_dRS5A7dfCzKjcSucR529ZovKLCWKbkEUu8alEG2GcAqNzNR_rsSXFc2aswvk8CHtT3YvXlMBGFc0A0yI036wTa6SgL8X8kOmraO2sNPixHlQ2rBeiQ5VniqgbLOyE3Q3-q4lj91huZWsQMS7rMhfClk1C7J8WoyE4LkmaSyMHA5amxWc-XIXGX_RhBSp4TcawfhYBsBUmSsF1BiqOTcbNN0XDYQiN6PQF1Eovcbpj5boaqA919_dQ2mdhloF_n2f3uUtL01vjx_iPMi8RtWx6mpE-UUTqV2W5FKQaZmb-cgr08IJIbF5zpcvakaK1QGCjvesmW1INoFaz-I1u023VbSXSEl5YU3Vt2G3pgyI3n_HB8gI3McXGXxp_kNorq9BVOjnT2ggb8KZiRRgh--gRbccabEks6agSx2xN3uZPd7w1yeHiAFJlTCNDFLFBpfqIoWTY22iqR7-_k_Hdr7DUhgVFRS23MqxvI2i2u1OW6NmnzVYtHwlLnSWQ4hmOdfiNtisprRyE61vyYr0ug1VEkO5zKJfj0UdXpQq57EDCNCqx0gH4btpUF67N75jyeSn4pgBDLnx83kgOoJ2PaYuvZa-_36pkTMj7DSv8Weioqv9Rkv6emf7qEoVKre9uzy-7weMCUaS4OqHzK4rnWemGDiJQt1D9ZAWdlZKRbEMXhsT5hZKV8VayWGBRlnaFZtTsxhw9kfzcnB4Wt9iZTr_f9smnhy8iBmLkgWIrXy4GYe7QdApU6GyuNTY5CWSQyJg5TAhn1gqmH5FO8wjDrbQrU-ZS9cbIWAYH8psxfgYjMhnY204_j5ZcYjpxGxuDT28DO1ulCWubizgq-u_eRQK3o="}}
{"timestamp":"2026-02-11T04:21:30.530Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"python3 -u - <<'PY'\\nimport math,time,functools\\n\\ndef best_upto(m,TARGET):\\n    lim=math.isqrt(m)\\n    S=[]\\n    for x in range(-lim,lim+1):\\n        y2=m-x*x\\n        if y2<0: continue\\n        y=math.isqrt(y2)\\n        if y*y==y2:\\n            S.append((x,y));\\n            if y:S.append((x,-y))\\n    S=list(dict.fromkeys(S));Sset=set(S)\\n    D={}\\n    md=2*lim+2\\n    for dx in range(-md,md+1):\\n        for dy in range(-md,md+1):\\n            if dx==dy==0: continue\\n            if dx*dx+dy*dy==4*m: continue\\n            c=0;u=None\\n            for ux,uy in S:\\n                if (ux-dx,uy-dy) in Sset:\\n                    c+=1\\n                    if u is None:u=(ux,uy)\\n            if c==2:D[(dx,dy)]=u\\n    Ds=list(D.keys())\\n    Tang={(dx,dy) for dx in range(-2*lim-2,2*lim+3) for dy in range(-2*lim-2,2*lim+3) if dx*dx+dy*dy==4*m}\\n    sy=[lambda x,y:(x,y),lambda x,y:(-x,y),lambda x,y:(x,-y),lambda x,y:(-x,-y),\\n        lambda x,y:(y,x),lambda x,y:(-y,x),lambda x,y:(y,-x),lambda x,y:(-y,-x)]\\n    def canon(C):\\n        best=None\\n        for f in sy:\\n            T=[f(x,y) for x,y in C]\\n            mn=min(T)\\n            t=tuple(sorted((x-mn[0],y-mn[1]) for x,y in T))\\n            if best is None or t<best:best=t\\n        return best\\n    @functools.lru_cache(None)\\n    def pair(a,b):\\n        ax,ay=a;bx,by=b\\n        dx,dy=bx-ax,by-ay\\n        if (dx,dy) in D:\\n            ux,uy=D[(dx,dy)]\\n            return ((ax+ux,ay+uy),(bx-ux,by-uy),2)\\n        if (-dx,-dy) in D:\\n            ux,uy=D[(-dx,-dy)]\\n            return ((bx+ux,by+uy),(ax-ux,ay-uy),2)\\n        if (dx,dy) in Tang or (-dx,-dy) in Tang:\\n            return (None,None,1)\\n        return (None,None,0)\\n    seen=[set() for _ in range(TARGET+1)]\\n    best=0;states=0\\n    def dfs(C,H,F):\\n        nonlocal best,states\\n        k=len(C);states+=1\\n        if len(H)>TARGET:return\\n        if k>=2 and len(H)==k: best=max(best,k)\\n        if k==TARGET:return\\n        for b in sorted(F):\\n            newH=set(H);bad=False;harm=False\\n            newF=set(F);newF.discard(b)\\n            for a in C:\\n                p,q,t=pair(a,b)\\n                if t==1: bad=True;break\\n                if t==2:\\n                    harm=True\\n                    newH.add(p);newH.add(q)\\n            if bad or not harm or len(newH)>TARGET: continue\\n            C2=tuple(sorted(C+(b,)))\\n            key=canon(C2)\\n            if key in seen[k+1]: continue\\n            seen[k+1].add(key)\\n            bx,by=b\\n            for dx,dy in Ds:\\n                nb=(bx+dx,by+dy)\\n                if nb not in C2:newF.add(nb)\\n            dfs(C2,newH,newF)\\n    dfs(((0,0),),set(),set(Ds))\\n    return best,states,len(S),len(D)\\n\\nfor m in [1,5,10,13,25]:\\n    t=time.time()\\n    b,s,r,d=best_upto(m,10)\\n    print('m',m,'best<=10',b,'states',s,'r2',r,'|D|',d,'time',round(time.time()-t,2),flush=True)\\nPY\"}","call_id":"call_sV53etqtT3isNVQfZAtTvEsY"}}
{"timestamp":"2026-02-11T04:21:30.534Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1219306,"cached_input_tokens":1136256,"output_tokens":38662,"reasoning_output_tokens":27114,"total_tokens":1257968},"last_token_usage":{"input_tokens":51819,"cached_input_tokens":51712,"output_tokens":1101,"reasoning_output_tokens":57,"total_tokens":52920},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":9.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:21:40.688Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_sV53etqtT3isNVQfZAtTvEsY","output":"Chunk ID: 3a6e0f\nWall time: 10.0015 seconds\nProcess running with session ID 58358\nOriginal token count: 11\nOutput:\nm 1 best<=10 2 states 6 r2 4 |D| 4 time 0.0\n"}}
{"timestamp":"2026-02-11T04:21:40.721Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:21:41.211Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1219306,"cached_input_tokens":1136256,"output_tokens":38662,"reasoning_output_tokens":27114,"total_tokens":1257968},"last_token_usage":{"input_tokens":51819,"cached_input_tokens":51712,"output_tokens":1101,"reasoning_output_tokens":57,"total_tokens":52920},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":9.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:21:42.179Z","type":"response_item","payload":{"type":"reasoning","summary":[],"content":null,"encrypted_content":"gAAAAABpjAPWa0uz3AZ3okJnh1yXvfODuW5ni0HRhN5Y87iOcBI4AGA65QbKobHjsAYrCwcZRAJwaIyyb45npNpyo6SfxWLPeEVURdihgY6vC5TazHVxXyow5oAVaRPQo4PZiysi0MSFlUHHYULw5SPhW48mONTZyivp9dQ7odC7uKN63YRFOz0CzOYvBSMrIRO2oJ6kcf_ZMqoESMcSDJ63nhtuKjliPgPJ3HRJUpep96Gnx5EnQ1YsomEg30I3QW6KTRRNuVFVcorS0Jkr_-UDTngY8FDiRrrwi9ZUcOHXVUEKwNeg25cg4p5hJnHyo0cdO_9cKK_eUCdPVY_9-frS_jzXoIwAacGvrUKE_MEFNRypfk0beIb5ORnRLrIxE90R5lzuho2N995MCaa6Z7nAkuaIxA_vmy4RcL8eZFWlsh_XH9mZWy3SMFn4R9W9mM6fSeI_b-LvdFTdN1SPSXlfJO9pWBaE230Tgzrgbrjif2LgEDeL-JSKZzUvMHUyUKyQS6QXal5IO_JZNhMxW07LKnqc24cMK4vD2kyeLc1-s17LtY9Ssv5P94F4SYEkVjaOR6mFHLj2zct5TCurOeyKtCoCUrAdG91qAwQBwlYBcYEyN7bV85_evexMkd02DoZvFgyFC7QpJKX3uDkFhFswyptF0tgYCDnOHpP4sHAG0meRHM0K53PM6yzBoCTwj7Kcr0BC_8jaxt6gioIopvbLyRld_nz8S2FRfNOVVa_Nwn4hdqMxnwJ-9Fg7F_-ljsw0Pm_Vze-8IT0s0_UfTQBLeMQt551Pp9xrLnwJD8pyYLwiQxSGaA8rJb1ayLgkG5w-fg8-WqVSiTpqinbdTNV8zWVajrYObYiHvAeJ7zpqLLyOnkBmi87vx3MVP75GOnljxEXwaKbO3s1mb7dZJsyb6z-cOhjj7A=="}}
{"timestamp":"2026-02-11T04:21:43.045Z","type":"response_item","payload":{"type":"function_call","name":"write_stdin","arguments":"{\"session_id\":58358,\"chars\":\"\",\"yield_time_ms\":30000}","call_id":"call_yrCj6rGsgj7it3WbFwtj9IUo"}}
{"timestamp":"2026-02-11T04:21:43.073Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1272302,"cached_input_tokens":1189120,"output_tokens":38711,"reasoning_output_tokens":27131,"total_tokens":1311013},"last_token_usage":{"input_tokens":52996,"cached_input_tokens":52864,"output_tokens":49,"reasoning_output_tokens":17,"total_tokens":53045},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":9.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:22:13.079Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_yrCj6rGsgj7it3WbFwtj9IUo","output":"Chunk ID: 4b12b3\nWall time: 30.0014 seconds\nProcess running with session ID 58358\nOriginal token count: 26\nOutput:\nm 5 best<=10 8 states 56127 r2 8 |D| 24 time 11.18\nm 10 best<=10 8 states 56127 r2 8 |D| 24 time 11.27\n"}}
{"timestamp":"2026-02-11T04:22:13.079Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:22:13.438Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1272302,"cached_input_tokens":1189120,"output_tokens":38711,"reasoning_output_tokens":27131,"total_tokens":1311013},"last_token_usage":{"input_tokens":52996,"cached_input_tokens":52864,"output_tokens":49,"reasoning_output_tokens":17,"total_tokens":53045},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":9.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:22:14.564Z","type":"response_item","payload":{"type":"reasoning","summary":[],"content":null,"encrypted_content":"gAAAAABpjAP2R7cr-bsfKpdeM4MVb59ULnIZLsLPX4L9bDuBm5oSTq3C8LXzUUuGBcALd505DkEWm_EhZzYeozffUu6Fl_QenysljzKQBMUGaBdLVGI03-v9VZYikTZGpLaP8NbbiBlitEKYsOOtlgEDVmEvjjN5rCEhcADyNLPFcA8qx8T1wB2ssbcPJ3Icea2a8vxRohaTs8OzU51lQdA1mRFRunvsb_69brxjYvmvAMx5tHR5iDrzbga8H_OefHlAKY94savYaNj4SXjfB6rtgtQgMIFWTy5GVaHjHUsVF4ajPGgvBQtVCtZw6v4Xv8xJRAhRwCglGDfUck1aLmq3MsY22tkWc_lS0xOxHIUkiPpCZhDnImur89UF83ycEbwmN7CsUBCmIywaz991GUdCPbQiIqSpeSH1ENQfc485u-TA41jJTNvwz5US1dV6COhFG10BX5tZDfmfrlQZ-TvMIFq_jkhcjrdkO92yhukuUjpeUwPoVdeeH8siV6Dz35e4tGVUwSMTo1oGIhkzwCOcaetvsxdBEA5A6ak0NKCr_y08dJ7wpG8ZalvJJ3pdcgYoy7sV-R6WGF3dCMjZ8UTklx7e8NfDfe_EMih9aBIAlAQQ2dQ8wMUIUA7QoZRZ1QQJLxbgnbOGt8kHshAWjC9SmOYARvxj9oAOEY_ynl0dqMkKoaE0ruulZSr19F1hDkJiU78sUuufvLTrozxdyYj_iG_dl0dZRU9GwqNYWocyjgKAcXvF9i7aRYlbnSpY6hazkcD0biuR5GfIzxqTs2DEhZZFX_Ut_iU64bym2-LWDYnYMfmCc3vl4JzjaSl__XmsjKUweG7V3exmG2lQjf15KfKu3UTp_SvW-G8aNnCHf8W_lP4s1w3uQBWe5lArRTvNkxtQqUcXWkRh3SpORzNsy1s_0CL56Q=="}}
{"timestamp":"2026-02-11T04:22:15.383Z","type":"response_item","payload":{"type":"function_call","name":"write_stdin","arguments":"{\"session_id\":58358,\"chars\":\"\",\"yield_time_ms\":30000}","call_id":"call_JvLuUib6Lo9o2ylY70g6Zjmg"}}
{"timestamp":"2026-02-11T04:22:15.384Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1325451,"cached_input_tokens":1242112,"output_tokens":38760,"reasoning_output_tokens":27148,"total_tokens":1364211},"last_token_usage":{"input_tokens":53149,"cached_input_tokens":52992,"output_tokens":49,"reasoning_output_tokens":17,"total_tokens":53198},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":9.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:22:45.416Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_JvLuUib6Lo9o2ylY70g6Zjmg","output":"Chunk ID: fab14f\nWall time: 30.0006 seconds\nProcess running with session ID 58358\nOriginal token count: 14\nOutput:\nm 13 best<=10 8 states 181820 r2 8 |D| 24 time 44.08\n"}}
{"timestamp":"2026-02-11T04:22:45.417Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:22:45.772Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1325451,"cached_input_tokens":1242112,"output_tokens":38760,"reasoning_output_tokens":27148,"total_tokens":1364211},"last_token_usage":{"input_tokens":53149,"cached_input_tokens":52992,"output_tokens":49,"reasoning_output_tokens":17,"total_tokens":53198},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":9.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:22:48.080Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Adjusting polling interval**"}}
{"timestamp":"2026-02-11T04:22:48.080Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Adjusting polling interval**"}],"content":null,"encrypted_content":"gAAAAABpjAQYilCoaNzbAOjG_PeflS2Gf5j0P4XTh41lSZMIV1blmtJ3-Gp_aiq1g9ItS0yzC8yWvxmt9UEFDVyGZDVdzHeiwQmAHXWNwxnHRmEWdRPW1lUIhlCoLhwPR_q0vBbnbbsKwO4Wp-5HMXVx7TDZAUh9j6fWzwO1mciOOKoVdgpnmGu4TCjCygsfkok0Ea7pdcmCTwEHpnTy_0FyXXrkhbU98CJ2Zeinq_AiKdsm6gABpuMrPMEg-5vy3GoEBCHArJLSeFLDQBz-3s9qdHYFfI7bBosqLPk9Y-2mWOH6RCUTb2_bwuJVCEFwEy_r_Mzg9h1mxdbBcv_6GLCUKaHlGZoXwKcBuVf5YV0_vqV_t_a9wGnzdIQbI1wtLYpHrV7NzD51EwaD-Oitx2sc8y6JX06g_Z0uDx6eqqxewIrv0TjzBpL7UeXTLGZkZk8CjsOt1ezhttTOy_vm06FePIkeYwk3an_SdogVce0UnxrBdn2FQxjqbc_6kneyLZUp89ziVEWEKRB7-r8SerlTnKTL0gEwqu6-KBqF1rt8YoInS9mGgMBkHcn_Toh8Oe03Yh7ihua6xYGh4r1riTXguagOfqCNnCXa0dFnGs-Q8DgExqpLlNfwc7hd7mBw8GckhPNThA9IIhq6Y5f6N-0MisqKCd6rjFwsN0YoMvNW1WwNA3KWb_zrak4lP_S3aTXcEZpjK8GYKBAtNssiJeQM0iUxFVamX9YFy8hwvj7H36RpeCwQ_eZIaVSduxci0-ok37KWd6PzsdGbmrXV4ciO7SOgggWMRmLUFJk_OYFKx3d_X0RO3Tse6ma-C4spapGOA6N8NEr2rlwBDEQiApblQcV7QtUzqpOa8ziwfdzfaPQshCwg-o4-QmdrI1fXdtKy2viRMS9a"}}
{"timestamp":"2026-02-11T04:22:48.459Z","type":"response_item","payload":{"type":"function_call","name":"write_stdin","arguments":"{\"session_id\":58358,\"chars\":\"\",\"yield_time_ms\":30000}","call_id":"call_okLB7W3i20BAVyTdegs3QEtJ"}}
{"timestamp":"2026-02-11T04:22:48.488Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1378723,"cached_input_tokens":1295232,"output_tokens":38810,"reasoning_output_tokens":27166,"total_tokens":1417533},"last_token_usage":{"input_tokens":53272,"cached_input_tokens":53120,"output_tokens":50,"reasoning_output_tokens":18,"total_tokens":53322},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":9.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:23:18.492Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_okLB7W3i20BAVyTdegs3QEtJ","output":"Chunk ID: 7727d9\nWall time: 30.0007 seconds\nProcess running with session ID 58358\nOriginal token count: 0\nOutput:\n"}}
{"timestamp":"2026-02-11T04:23:18.492Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:23:18.956Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1378723,"cached_input_tokens":1295232,"output_tokens":38810,"reasoning_output_tokens":27166,"total_tokens":1417533},"last_token_usage":{"input_tokens":53272,"cached_input_tokens":53120,"output_tokens":50,"reasoning_output_tokens":18,"total_tokens":53322},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":9.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:23:20.235Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Waiting on process completion**"}}
{"timestamp":"2026-02-11T04:23:20.235Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Waiting on process completion**"}],"content":null,"encrypted_content":"gAAAAABpjAQ4OSszWZ9GAZgEJdaH2brXCkK_4Scj7kFBkl7KVRPm2ctEdMZscvcdwGjotcyYcVrDC9AVAt09QQO5g7Xb5B8og-Vlsh6w2BKu4GELZ_PzFxSD8RCkJrPJayuBvllNwAIPVfSASqWeooPBG_LXdG181UrCK2y9Kt28j0FNvC9UD5VDNtvQYyxEmTe9LuMoPIoM8j6B3KaVKNfuTO401g_Lfea4WzA7d09YnVtf5iyoBQdvGoUK8od96WAUtOlpDFr_9j2NuVR4HuJSa4vnIQ3pxsTa9MxbvGx3kmv-SjpVC7hmPaZb7LODLxCX20V84nJSMPApUYosTr8ex-V_LXHVdPoWIDxyuKmzQ3FjqYF3qiiqC2lytI7Ek5Mhs4ObS_ctzf8yf_uu6NIvTJkBA9njeYyToO54kSuZ6IH2I9ynhaVXFKuefyN2aK4NfYdMGRAFnrgR61WdZSpLqMoeb0ACwL3nK8KORjP21Mf4T24OUfMhNVC3ETk3AAD3ezuxUzHPeLXARFpMYTuFrDMwQqid1XLQ-zmhIjnlV6cJFzDJVcu9PvhJwI6455wSXCU_Wv2QC0bv32Fifaw2PyOH0gNXYfO3ot31f3csMZhDeex433dk0PU3PPxZK9criO3q621JHVjEHDD9jIUZGcIivWmFKAZ78nKfwbsPwnH95hbjdiAlk3nQNJ9_aRFtX5bKDy2-dud9FRP-OO6Q5FlMeU_g1ZZR1s0SNl5QAkp_vk68_zs7PNO8ha8QVyFFp7mvKXJgwdkNXWqvGskW58s8BwtuOvbRUdTraA_THyA6mJDYgbZy_P5-mejIBHVL-i2kXOdTf4rccFwDSQjj2hdFmy3JDdDsflJFKMT46acdP2OR0ZHuAe0RZnLIcp7HUf6ncchIZdzCUKpbB64zZn38lGsjGw=="}}
{"timestamp":"2026-02-11T04:23:21.050Z","type":"event_msg","payload":{"type":"agent_message","message":"The exact search confirms a strong pattern already: \\(m=5,10,13\\) all reach 8 (and not 9 in the earlier exact run). I’m waiting on \\(m=25\\), which should indicate whether the next jump happens there or later."}}
{"timestamp":"2026-02-11T04:23:21.050Z","type":"response_item","payload":{"type":"message","role":"assistant","content":[{"type":"output_text","text":"The exact search confirms a strong pattern already: \\(m=5,10,13\\) all reach 8 (and not 9 in the earlier exact run). I’m waiting on \\(m=25\\), which should indicate whether the next jump happens there or later."}],"phase":"commentary"}}
{"timestamp":"2026-02-11T04:23:22.025Z","type":"response_item","payload":{"type":"function_call","name":"write_stdin","arguments":"{\"session_id\":58358,\"chars\":\"\",\"yield_time_ms\":30000}","call_id":"call_SsfILyrUxa0j51Xv0gwhMvlY"}}
{"timestamp":"2026-02-11T04:23:22.055Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1432094,"cached_input_tokens":1348480,"output_tokens":38925,"reasoning_output_tokens":27186,"total_tokens":1471019},"last_token_usage":{"input_tokens":53371,"cached_input_tokens":53248,"output_tokens":115,"reasoning_output_tokens":20,"total_tokens":53486},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":9.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:23:52.063Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_SsfILyrUxa0j51Xv0gwhMvlY","output":"Chunk ID: efb670\nWall time: 30.0006 seconds\nProcess running with session ID 58358\nOriginal token count: 0\nOutput:\n"}}
{"timestamp":"2026-02-11T04:23:52.063Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:23:52.365Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1432094,"cached_input_tokens":1348480,"output_tokens":38925,"reasoning_output_tokens":27186,"total_tokens":1471019},"last_token_usage":{"input_tokens":53371,"cached_input_tokens":53248,"output_tokens":115,"reasoning_output_tokens":20,"total_tokens":53486},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":9.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:23:53.969Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Planning process termination approach**"}}
{"timestamp":"2026-02-11T04:23:53.969Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Planning process termination approach**"}],"content":null,"encrypted_content":"gAAAAABpjARZDxc-2cBC_mWawOtUNb9LzP2qHLhGZIo6gKa4X3KZr7dkZwLfZvHHQWFC4xj8QIUzPDi3BWMynpaagAXN1R0OzUV51KBAhoz6GOyDrEwDxyHL6LHx4lkSooyU3R_RvbPK1L52_IjPkbyrtNE7Kb3lIUgrDyQxI-Soep0CGGburEbOJ8TRH-a3GSM9zNRHPq3clGuKudWMOctYM7qfjS7pMJXJVL4n5S26JBpS3dW_5bprVNIBGWv_Q4Ocx6QzNmBxN2VanELCeR3KxwjASIFwyYSlAzkxWN__BDdYaMWThHhRmnk95PD1aaqvoRUfYnezWHwKowDoX7D2b99DpK0Q3GudCA9_SsfVVxo50TG8QLeCBmu5omMrEzgJJMXGqLhtt1u-KTvLZWHPVJJB0_Hrk9A5K5FpGwwF34xvnGeEd4bygwSaKH8j2Cb0B2mqik42DO_e-0xFArfm4mBVu-VdgtWjW7CKjyYme5UNdGLJ3J026Up077b0OA7SMsv-x2gUASpd1xuCyJ3cQa166voVdnERdfeEOU13RX3c_koBYXDnfFxt2GZwy--84pZfbRcTQY4VGgqJJ9c0HEuyHa8uWK53_7LgmX9PcwWgOhLTBtywQ6V9ySXK-zkAS8M1PK8DLUVyIWMoJvNkgvda4WckNMliCorr5ZEIFnRa3r0qwFLEKOSqpTYBVtqf9GLddnqjMlnFOxvGpxz9OlXkVzYjRf6s8wBgZyX87vqZxqwN3sP4mn4PS2qj7b_3N4UBw2CePW_YviTgTwSZBdygc9rCVxr9iGlc9gAC13XsImxVSWYArtB2ouIbRwAuTai-ZhgwZOT7PZaTV0ghl4J9WWSA8lN12cqJy8sJSMxUoqg-Lkrv8KmsN5LlZXOI0eyejpxRKR8Sy17R38LJkYtAkJjQlp9EXugOCo3EoQOU7tqakf-drzTVmy5PVwCsAs6SanKyHcnb3ms3O8QSLjObQ2u6aq-uCDOS7xVORYCENmPvxNRd-A7f5CczL_b4t8zO-OLzazHkjQHNlwjv6Ybp6qSi9_IrD9IoLWLSnWxlkuQiv-Q="}}
{"timestamp":"2026-02-11T04:23:54.266Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"pkill -f 'best_upto\\\\(m,10\\\\)' || true; pgrep -af 'python3 -u - <<'\"}","call_id":"call_ASBptxqfWpASQgcUiQnohG4N"}}
{"timestamp":"2026-02-11T04:23:54.269Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1485627,"cached_input_tokens":1401856,"output_tokens":39016,"reasoning_output_tokens":27228,"total_tokens":1524643},"last_token_usage":{"input_tokens":53533,"cached_input_tokens":53376,"output_tokens":91,"reasoning_output_tokens":42,"total_tokens":53624},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":9.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:23:54.964Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_ASBptxqfWpASQgcUiQnohG4N","output":"Chunk ID: f8e25a\nWall time: 0.5423 seconds\nProcess exited with code 1\nOriginal token count: 0\nOutput:\n"}}
{"timestamp":"2026-02-11T04:23:54.994Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:23:55.348Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1485627,"cached_input_tokens":1401856,"output_tokens":39016,"reasoning_output_tokens":27228,"total_tokens":1524643},"last_token_usage":{"input_tokens":53533,"cached_input_tokens":53376,"output_tokens":91,"reasoning_output_tokens":42,"total_tokens":53624},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":9.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:23:59.415Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Assessing radius dependence on residue patterns**"}}
{"timestamp":"2026-02-11T04:23:59.415Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Assessing radius dependence on residue patterns**"}],"content":null,"encrypted_content":"gAAAAABpjARfjSvo4k2BySUr3P27T6iwLzsDX5v-eqJBn_zLkHCgpQNSvrv89JDsiXImbV4nXmnP-u8Q7Y_9elt_o3zrK-2XuAk7WGS-dVpLKuqpi212nhUmV4xJmRDHiDxY2o2pD3mHH3O7ypdHx4ocPcHeVIo_gPN3O150f9XYjVkYOIoVLLiLgARaOLMzOFW_whYrjHjZPa7mVktyx8aUxHlapvhv5HbnL5rvhCVY_wSjgrakiQ7QPnIGAiZseEmD-sf3Bc-bE4cve8Sg5buUPTHAuSpCNOj0isVpb8B06mIanNR91EE7XDhDKWt15oAivHadwlG4x3PTm7NXym7ZYF97iIRAW1HUf6k9KSwQ2HqYJPoY0tUuCg0ZZOJlL6QIwZbHrnC7DyjSORyTLrfp5i9eh7fT_4rzIgHATWJpf9GqkFpvdh_bj19McGwZhC-thOa3CQLPNfQ4sOmT05oM5kAosWuin57tQkVevFXlbhrEeAH7JbTVNcZgqKyhAyPPtQs0e9UGcDY82DInfeH6hdm8Ub61leijfC4oVFCj2icuZX3618SSto6bJXHASNZbYzSHXW_dQV_QY_BG_OIhM4tXJghD36cZRXXlYCw3g6XZ4FW63yIYedRwfrpEzB81Wik9J1r3NS9ZrMlprz1iGSUH8t24ENO72nVzN8OA-bYedXqksw6En16bD9VInjioO_gM24bs_8Qfy-nky1FXJtCE8W15z-wV8jaddkzGNaaCQJLqqEUMil56ANXXZApMMxsIICXrMRHqaUOGUXm_rVGZi2O7jhUsHkhRdxBtP_zqzzKiChgwNKJvtuMgefvC6U6w5qgA_4yQSrr-gbUCOzyib7FPjoGqAVOuvD-ZBhjvFsr_ikWzwnB5ICstssuSCmlm6YY7jBGK5_P6CUrXn1LIMyibXrgOcj-N_xqLNTjAqrDauXJ0nhzULFWadPlDioph2TKEVGqgiQOW1y7BzZpXz1bFHWyfy_dUoHH12B3Xp8eoEUhLync5fHRlNDlmUGWZHM-Ge2KAc4xFtkRULHGgeizSlPMK4u8gi1WK9KY6zabncV7E72c89hLYWrdK6aQ_8YJYyK-xCoSceLxOw-HSRd0_KAl6XF-mN3Wy8lcA_95plWhijhijAWwOqgnYxl7mlhv7rZLwlPyUKK_jVbpWvv5pi6V0WqCptMhcuwIkAJxvHK4ohMoX3rDdLwMn9BQ2xVDnthHUe_Xt0HqiOA73-nBEXibVcaaNPPIAS-b4C_V6jaR6btK80D0b7EfCEQBTcoL8vbKuVBQ4eAh4gQeUZ51qd6boSBBJSxAbHB-_BRT2_45b-P43T4jfxii5Xpj_0u12N4xw9t4lPDJSuaDiLQ7NNyGT6gKUUVk26VtMPMVlYudpIDqSLQ3f3pMtzbaiJBqqMkomNbt08qARCP0DCSNB1RFR2hdonKd6KfkL2UImdEfX_eaUW9AOKbw51ZrHB7lptk2H42oo8zux5fLUe-rwbkzdu_04OU0QpdceAXoKP7IM-JXAAQs_hfgU4onAu9TxLHPa6EZWOoRFbR9e-bIJw9T0DiAUT_vubPiLu1B6-BFPsqazNo4CDzUec1xH4xgTtglCea_GDrsRfRfWJ0paVfnj0Uf4aCyCUnCXrchzuf690JmxoLjsvqW8QxU5IaoXvGh9ELZYl3c8jodS5S8x6zLPN1qf5Hh-_JSO2K1fUVy5G8hesnp_qc9xQA7-0R_-x0OXE8znhTf777YQQ4RaY13EKquCfsRkiffX6e7cjuXirPbB9y9N8C76e2XAuiaeeuTIQz9s47XH8CxWtTDy-PG6TeAaSu2gpBydN8-Vrwg="}}
{"timestamp":"2026-02-11T04:24:15.846Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"python3 - <<'PY'\\nimport random,math,time,itertools\\n\\ndef prep(m):\\n    lim=math.isqrt(m)\\n    S=[]\\n    for x in range(-lim,lim+1):\\n        y2=m-x*x\\n        if y2<0: continue\\n        y=math.isqrt(y2)\\n        if y*y==y2:\\n            S.append((x,y));\\n            if y:S.append((x,-y))\\n    S=list(dict.fromkeys(S)); Sset=set(S)\\n    md=2*lim+2\\n    D={}\\n    for dx in range(-md,md+1):\\n        for dy in range(-md,md+1):\\n            if dx==dy==0: continue\\n            if dx*dx+dy*dy==4*m: continue\\n            pts=[]\\n            for ux,uy in S:\\n                if (ux-dx,uy-dy) in Sset:\\n                    pts.append((ux,uy))\\n            if len(pts)==2:\\n                D[(dx,dy)]=tuple(pts)\\n    Tang={(dx,dy) for dx in range(-2*lim-2,2*lim+3) for dy in range(-2*lim-2,2*lim+3) if dx*dx+dy*dy==4*m}\\n    return S,D,Tang\\n\\ndef search(m,n,iters=4000,steps=2000,L=120,seed=0):\\n    S,D,Tang=prep(m)\\n    NBR=list(D.keys())\\n    pset={(x,y) for x in range(-L,L+1) for y in range(-L,L+1)}\\n    def eval(C):\\n        C=list(C)\\n        H=set(); edges=[]\\n        for i in range(len(C)):\\n            x,y=C[i]\\n            for j in range(i+1,len(C)):\\n                dx=C[j][0]-x;dy=C[j][1]-y\\n                if (dx,dy) in Tang or (-dx,-dy) in Tang:\\n                    return None\\n                if (dx,dy) in D:\\n                    off=D[(dx,dy)]\\n                    H.add((x+off[0][0],y+off[0][1]));H.add((x+off[1][0],y+off[1][1]))\\n                    edges.append((i,j))\\n                elif (-dx,-dy) in D:\\n                    x2,y2=C[j];off=D[(-dx,-dy)]\\n                    H.add((x2+off[0][0],y2+off[0][1]));H.add((x2+off[1][0],y2+off[1][1]))\\n                    edges.append((i,j))\\n        g=[[] for _ in C]\\n        for i,j in edges:\\n            g[i].append(j);g[j].append(i)\\n        st=[0];vis={0}\\n        while st:\\n            u=st.pop()\\n            for v in g[u]:\\n                if v not in vis:\\n                    vis.add(v);st.append(v)\\n        if len(vis)!=len(C): return None\\n        return len(H)\\n    def rand_conn():\\n        C={(0,0)}\\n        while len(C)<n:\\n            b=random.choice(tuple(C));dx,dy=random.choice(NBR);q=(b[0]+dx,b[1]+dy)\\n            if q not in pset or q in C: continue\\n            bad=False\\n            for c in C:\\n                dd=(q[0]-c[0],q[1]-c[1])\\n                if dd in Tang or (-dd[0],-dd[1]) in Tang:\\n                    bad=True;break\\n            if bad: continue\\n            C.add(q)\\n        return C\\n    random.seed(seed)\\n    best=10**9;bestC=None\\n    for it in range(iters):\\n        C=rand_conn();h=eval(C)\\n        if h is None: continue\\n        val=h-n\\n        for s in range(steps):\\n            rem=random.choice(tuple(C-{(0,0)}))\\n            base=random.choice(tuple(C));dx,dy=random.choice(NBR);add=(base[0]+dx,base[1]+dy)\\n            if add not in pset or add in C: continue\\n            C2=set(C);C2.remove(rem);C2.add(add)\\n            h2=eval(C2)\\n            if h2 is None: continue\\n            v2=h2-n\\n            if v2<=val or random.random()<0.03:\\n                C=C2;val=v2\\n            if val<best:\\n                best=val;bestC=set(C)\\n            if best==0: return best,bestC\\n    return best,bestC\\n\\nfor m in [25,50,65,85,125,130,145,169,170,221,250,260,265,289,290,325]:\\n    for n in [12,16,20,24,32,40,64]:\\n        b,_=search(m,n,iters=200,steps=500,L=140,seed=1)\\n        print('m',m,'n',n,'best',b)\\n        if b>0 and n>24:\\n            break\\n    print('---')\\nPY\"}","call_id":"call_omNHhAGV0MgIRdO8j7L6jALu"}}
{"timestamp":"2026-02-11T04:24:15.873Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1539297,"cached_input_tokens":1455360,"output_tokens":40446,"reasoning_output_tokens":27423,"total_tokens":1579743},"last_token_usage":{"input_tokens":53670,"cached_input_tokens":53504,"output_tokens":1430,"reasoning_output_tokens":195,"total_tokens":55100},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":9.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:24:26.001Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_omNHhAGV0MgIRdO8j7L6jALu","output":"Chunk ID: 3251bf\nWall time: 10.0006 seconds\nProcess running with session ID 61166\nOriginal token count: 0\nOutput:\n"}}
{"timestamp":"2026-02-11T04:24:26.031Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:24:26.331Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1539297,"cached_input_tokens":1455360,"output_tokens":40446,"reasoning_output_tokens":27423,"total_tokens":1579743},"last_token_usage":{"input_tokens":53670,"cached_input_tokens":53504,"output_tokens":1430,"reasoning_output_tokens":195,"total_tokens":55100},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":9.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:24:28.015Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Adjusting output buffering strategy**"}}
{"timestamp":"2026-02-11T04:24:28.015Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Adjusting output buffering strategy**"}],"content":null,"encrypted_content":"gAAAAABpjAR7qTm7HPlk3MWtrWr6VDJNJp5tlCAPiXWjKnHUavTpRooXnoYj2vuU-LicgMpkybWFdTvbKJmDuKw9UbgDwSYSi_OjhAwckU6Onb4cSS4Wc_-LZScYqXzU-gxbD8ceamUAKLvurCtrj_OPe1zd2Ck35OlzNXXFCM9Dhe-QzAm1HmF7XsWceMItEawVyw8yHS8vFkwYLilxn-xgkdLXfYj2ngljudtV-VcddRGqDX2asmTxATjUwZHbmiyN4nTFBXTK2JeKFYnrCcWVnAHNAsjHV1WaNGsKL4kq5NIBmkXWQgRuVNrL3i2Ln9dzoQShF8qAkMJsdjJ0A8GI58Mn1tgzfW5jO1Uk8hOwuAnM2JYb12f6KQscKPTs3tbqVr_dhNxdhWz_iKr_w6hr0sYZkkCmZymqjojynzihH41nC35_imC970PHgtV6XAPmoIkaVmXN00m08Txq7im0HSYVW7KrmTtt21h0TH0_F-KsPsFpSw51wXHQwsSmuW65EmoEG-2nKNRzPKteskC9QTXOGkwcFphBHbQ5710gpYVpfE2BjRXHRu8Iupm0oLpeJSv4ZBFcQ8qeB9T052SOAUuuLs5eG62-mxyLq8trYZi41Xz0i5GkPGVDp1kE8wS6qXOCNM-dOf-XdiHVLDVCPtKdckZdBsCiYgO7YTgEFwJMTSdydBzqE8XZKZLGWrBk63N_Rf81qci70EYyjqVyQnhRWeHxbpnYlaK9pM1cn52jHPxNXduuhx7y-DxZEgmGET3OJv-grxKdnmGkErNYBtMCy4eWGq1UVwtU3c4VXdgWr9qzOIW1CgpV5nLkZpdZM31AGHml0QTCENzWNvKlsrxYdmbDV97XAEuZUYBWej-SJ9BzfQZEh_SuFoevVq1p0ft7LYDsrFxNF1Xwmjhwjy8kffXTPFHuIPvhFot61v8e4kXWz7Waq7N-5j09UyzOhsekAhAf74HD8bB0bhhOCvK8VZKjHp9rXEIeEuUbMoHn6Zgu8nlPagFeHqbgoJnzhHl_zM21Tt-bDl3s9xfOYFzdEqbCTE3BHDVNlbCuJE4IBjpuk3Zn5MW8sjznivRS-WYqJULawiZhA-ON77mqmv9QM4vkyIcXZo64Locibx-Aly3AFjA="}}
{"timestamp":"2026-02-11T04:24:28.239Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"pkill -f 'for m in \\\\[25,50,65' || true\"}","call_id":"call_xQ0eE2OxNmVjCE8UN3WgAwph"}}
{"timestamp":"2026-02-11T04:24:28.243Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1594444,"cached_input_tokens":1510400,"output_tokens":40537,"reasoning_output_tokens":27477,"total_tokens":1634981},"last_token_usage":{"input_tokens":55147,"cached_input_tokens":55040,"output_tokens":91,"reasoning_output_tokens":54,"total_tokens":55238},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":9.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:24:28.864Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_xQ0eE2OxNmVjCE8UN3WgAwph","output":"Chunk ID: 77e1c4\nWall time: 0.4701 seconds\nProcess exited with code 0\nOriginal token count: 0\nOutput:\n"}}
{"timestamp":"2026-02-11T04:24:28.893Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:24:29.206Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1594444,"cached_input_tokens":1510400,"output_tokens":40537,"reasoning_output_tokens":27477,"total_tokens":1634981},"last_token_usage":{"input_tokens":55147,"cached_input_tokens":55040,"output_tokens":91,"reasoning_output_tokens":54,"total_tokens":55238},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":9.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:24:36.485Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Formulating exact max size bound**"}}
{"timestamp":"2026-02-11T04:24:36.485Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Formulating exact max size bound**"}],"content":null,"encrypted_content":"gAAAAABpjASE5kFMz-vOgM4fhX0JQbNlnSbJa57Do5bO6lw_MWxwD3AXc34hzp22Po1awf_grlW0NNT-GgCY4R7hikfEU4JqXp_8MIwPngYCoRc9o4o-K0v--ZHO9Al2Bngsk7PxMydVMz-NZQHtI33P-Nx9x4VaKW-tPnMxDR94y-Hx4RPXZ4P_pvTi8fHZney3R_1l0oKyYM2P2E-_r2mE88IPMaaC6Dt39CT0mXOPLxrA80E6TaF77DeBiIOrHRtflhR9o_WAHg2_sVXjUbmSYqOmHTou3UYhzYnPyZjMKZzdVFIV8adgd0EoEuQ2PDuV_klsRFvz5--b6DYQh_2c7SIrVsBRU_T6roYUxKhs9lV5NQIGefNJPax1VW6M1U4JVCo5-bHupW5gFBENJ7o-32TFz1gviYWOkWZEJCYsP6VTNWeN_6TNXcKF-bbmJDK5J1NZRS85Ef8FgxlcFGy3J1gZKljW2J1nDbx6er0jlz6sPuecEP-9zkNNB_Ez8ScROT0Ib33TaNbSQGyTOXaqMOyZid2wvPzQKGeCxX4Mg9MnoZCngbPA5oKW6Ls_o1GKZhX9w-j4PHCLnqVP6aiOfkIHqLPUPvv7DqUb1g5pn-gx29-5a3jet2qPrt949Mlbnwvfmp36pfQKaUh29ubK-Je19EyywouYVvZZO7m1jxTGdQblNe918-kX1ZCDJyXXeT8ncLUpVCk8RiJDHgX6WMcfaGKuSnpDT79WWaXfXtZw23EM0-sw-_iReJPk4B4R-wLMNJ74JZre7N7bgD2F3Ny-hNJhsyhbEKI31oYsDaF8Dr-3DGerwCpO_6mSPg2aWhNpp5ifHkEsHBKpVRpHIGN3dFIEtXa3LXJ6_ruJ344_8mOVyUq_IuWaWozLg680zxU9vb0GTSD1EWLqVyKQxkpbq92Vdjokx02KeeDx5-yBnSPOfxchmsLKvZaqUPDRQVSbzXgoFrJtOR7Zk3bknBY6viQ8v7yy-seBbRbtk5a7DnUqt5SKkDHna7Kwzb7YAUpkuv7hjvufGAEQTZspieqODMLuiq0RJHTYo_8d0qjULuzzgrlWvEAVU4CBoT8MsDwdf25TuQgMSwxsrHIjY6GoolwHSyOW1tKn8Efwv1ch0refBfckwFpqu2r2diaISoWu1KurS4HQiNuZlWuH18Hu8enmSOz6Exf9mxDYsmVh5Hv6Qai8-kWTfF8wo-8UR05bbRNPqxXEfxYvSVpaShAxTB78mLDFICe4JCOvhBTL2wcEDD-fnczOLYzfvg-CH8Xm65GYxtjNQRKGY_reivyxrIy9vbm-J9DzmUyfByIUUZ2AizpyB2Fp3umOMbk0Py3qccu9e0tkUnq3jiZ20muz2rg69kO7wi2WTpB4XzCNOvJiXghe_l6iKNt-c2MK2LBJIFD8OWGMCuU_AjwAImglNxO3g2uZxAhCC_0CRAq-DcIvxyKKYZLk4nFsJI1UZmNPdcp-TEJZOGZxJbq7ePQYlUGFqvUlqsQUWY47PuSQiTYHtCZaj0x0n0T7jmpM7QFZIKYkoIwdrpTzwbbwvHUxwe7a3JHmS5z0lRmDAnL-MnkJqclJ11Xsj56rb3mL2pXfsxDrWUjF7T3EEqFJ1jeD63g7a9Bj-W4gMaF8BBzXYy8yk56cfVYIcBK2fty-kFUxjPvUmcrdDvz-FAKWZNK_Q1vg0RoPDmPWEMIKsXJUGMGmR-Fwg68HlNafaiGh-v40u41JdsK7ujciR8L7fHuZXX8e1W5m36jlCtvjD6wRV2ORHFbu_pJ9PvoM97WFGwrhrnDgszV405wgG4HH-xAV1s0iBOUNS5gMJVPiowdN9-VTNzmNBmDl70nHrFMZ5AXkam7gqPqQNNVZ568NB9apSL8eISiU7wGtjJNOu1ZGspx3F1GhgFYjCtZZmhv0URste3aGg0Nm-LoEVziF9e1Wf7_KYupmPFGBbybvEJWu_vN6cCfgoE00d9AfpbPuGhENskJ1cvjvog1lFmTx96VzUJ8dblFS9bXZJjBuPwWUN_15iwdmHsFAoocwAqOQwIhEW7Dbzr2eDxWFK9uNuDUR4VF3eFCyy2ImGf7ram4DX0tzrphfnW5ybLFyoFVoKJcSF9IqOXbniM-YxLnyl-sN0yzP55_bCiYxbO5heXNzUOVCkYIhi-3AkotiqI27DytunS82LQaAslyOIifsMYmh0aWLrI5g63xee7bcfj6AJIvGVbOVSTVrfH4UMXRsbyXTC0QhesSLXlyfui0NZY0kg2GmRzVIkkYzTUV28tZJZPpJpo2WYrjnM39MbyA8PZg71tjXIzJkOHCIaMleOrW0T-znMepioyXql7FqxutlVXPXf4Tzr-5JYZCHGqwn0bJ_A2u73bWDQLai3IRRDPr1VZXMh7AfuXzsm02Q5uKmuwDETxBfFBVFdaQSmQG-ndPmuQdKEkdxg_UdH5kBL0XQjTjjzKPFJt1H68d2IS9W7lmc1jMNIm04I9kVXC5LL4MMNDlshaHppzjfFrMP2S51cw0HNQ=="}}
{"timestamp":"2026-02-11T04:24:37.146Z","type":"event_msg","payload":{"type":"agent_message","message":"I’m now doing a targeted exact search for \\(m=25\\) at \\(n=16\\) (find-one mode, not full proof). A quick hit there would confirm the next growth step and help pin down the general rule for \\(R(500)\\)."}}
{"timestamp":"2026-02-11T04:24:37.146Z","type":"response_item","payload":{"type":"message","role":"assistant","content":[{"type":"output_text","text":"I’m now doing a targeted exact search for \\(m=25\\) at \\(n=16\\) (find-one mode, not full proof). A quick hit there would confirm the next growth step and help pin down the general rule for \\(R(500)\\)."}],"phase":"commentary"}}
{"timestamp":"2026-02-11T04:24:51.415Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"python3 -u - <<'PY'\\nimport math,time,functools\\nm=25;TARGET=16\\nlim=math.isqrt(m)\\nS=[]\\nfor x in range(-lim,lim+1):\\n    y2=m-x*x\\n    if y2<0: continue\\n    y=math.isqrt(y2)\\n    if y*y==y2:\\n        S.append((x,y));\\n        if y:S.append((x,-y))\\nS=list(dict.fromkeys(S));Sset=set(S)\\nprint('r2',len(S),flush=True)\\nD={}\\nmd=2*lim+2\\nfor dx in range(-md,md+1):\\n    for dy in range(-md,md+1):\\n        if dx==dy==0: continue\\n        if dx*dx+dy*dy==4*m: continue\\n        pts=[]\\n        for ux,uy in S:\\n            if (ux-dx,uy-dy) in Sset:\\n                pts.append((ux,uy))\\n        if len(pts)==2:\\n            D[(dx,dy)]=pts[0]\\nDs=list(D.keys())\\nprint('|D|',len(Ds),flush=True)\\nTang={(dx,dy) for dx in range(-2*lim-2,2*lim+3) for dy in range(-2*lim-2,2*lim+3) if dx*dx+dy*dy==4*m}\\nsy=[lambda x,y:(x,y),lambda x,y:(-x,y),lambda x,y:(x,-y),lambda x,y:(-x,-y),\\n    lambda x,y:(y,x),lambda x,y:(-y,x),lambda x,y:(y,-x),lambda x,y:(-y,-x)]\\ndef canon(C):\\n    best=None\\n    for f in sy:\\n        T=[f(x,y) for x,y in C]\\n        mn=min(T)\\n        t=tuple(sorted((x-mn[0],y-mn[1]) for x,y in T))\\n        if best is None or t<best: best=t\\n    return best\\n@functools.lru_cache(None)\\ndef pair(a,b):\\n    ax,ay=a;bx,by=b\\n    dx,dy=bx-ax,by-ay\\n    if (dx,dy) in D:\\n        ux,uy=D[(dx,dy)]\\n        return ((ax+ux,ay+uy),(bx-ux,by-uy),2)\\n    if (-dx,-dy) in D:\\n        ux,uy=D[(-dx,-dy)]\\n        return ((bx+ux,by+uy),(ax-ux,ay-uy),2)\\n    if (dx,dy) in Tang or (-dx,-dy) in Tang:\\n        return (None,None,1)\\n    return (None,None,0)\\nseen=[set() for _ in range(TARGET+1)]\\nstart=time.time();states=0;best=0\\n\\ndef dfs(C,H,F):\\n    global states,best\\n    nonlocal_start=0\\n    \\n\\ndef rec(C,H,F):\\n    global states,best\\n    states+=1\\n    k=len(C)\\n    if states%200000==0:\\n        print('states',states,'k',k,'best',best,'H',len(H),'elapsed',round(time.time()-start,1),flush=True)\\n    if len(H)>TARGET:return False\\n    if k>=2 and len(H)==k:\\n        if k>best:\\n            best=k\\n            print('new best',best,'elapsed',round(time.time()-start,1),flush=True)\\n        if k==TARGET:\\n            print('FOUND',C,flush=True)\\n            return True\\n    if k==TARGET:return False\\n    # simple optimistic bound: cannot exceed TARGET anyway\\n    for b in sorted(F):\\n        newH=set(H);newF=set(F);newF.discard(b)\\n        harm=False\\n        for a in C:\\n            p,q,t=pair(a,b)\\n            if t==1:\\n                break\\n            if t==2:\\n                harm=True\\n                newH.add(p);newH.add(q)\\n        else:\\n            if not harm or len(newH)>TARGET:\\n                continue\\n            C2=tuple(sorted(C+(b,)))\\n            key=canon(C2)\\n            if key in seen[k+1]:\\n                continue\\n            seen[k+1].add(key)\\n            bx,by=b\\n            for dx,dy in Ds:\\n                nb=(bx+dx,by+dy)\\n                if nb not in C2:newF.add(nb)\\n            if rec(C2,newH,newF):\\n                return True\\n    return False\\n\\nok=rec(((0,0),),set(),set(Ds))\\nprint('done ok',ok,'best',best,'states',states,'time',round(time.time()-start,1),flush=True)\\nPY\"}","call_id":"call_b8eNfezCgxtsXiE5H79YDnCf"}}
{"timestamp":"2026-02-11T04:24:51.443Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1649729,"cached_input_tokens":1565568,"output_tokens":42089,"reasoning_output_tokens":27830,"total_tokens":1691818},"last_token_usage":{"input_tokens":55285,"cached_input_tokens":55168,"output_tokens":1552,"reasoning_output_tokens":353,"total_tokens":56837},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":9.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:25:01.571Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_b8eNfezCgxtsXiE5H79YDnCf","output":"Chunk ID: 6bb435\nWall time: 10.0009 seconds\nProcess running with session ID 48596\nOriginal token count: 9\nOutput:\nr2 12\n|D| 60\nnew best 2 elapsed 0.0\n"}}
{"timestamp":"2026-02-11T04:25:01.601Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:25:02.285Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1649729,"cached_input_tokens":1565568,"output_tokens":42089,"reasoning_output_tokens":27830,"total_tokens":1691818},"last_token_usage":{"input_tokens":55285,"cached_input_tokens":55168,"output_tokens":1552,"reasoning_output_tokens":353,"total_tokens":56837},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":9.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:25:03.210Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Polling streaming process**"}}
{"timestamp":"2026-02-11T04:25:03.210Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Polling streaming process**"}],"content":null,"encrypted_content":"gAAAAABpjASfu4fAGFm0b5TuGn-FmMRhFnC1fO8Q9NIkYDC1sFlKZ378Dli_nPET0N9__Zm5Jc6mDkELC348urpqHYA4O9lVIX3zobyZ7h3aaiEm4lSZjPo1tyXbWEwuGHO_I34J4QLzlZRb1QI-_XYEibVjmW6vGv-sLBxeVkv9oDowHsRQ8B6nrDCftH_mNqX2CaEXLOi-8A7kFMnkjoi1JLr7HDGh5WZsGSgTYOXcs8YpDUKOnFzNnFCaHL1C6KosKCG3xt_Aj6FtlDOi5VwnPlqQa1PmXPlHl2wB5vr6gNJqZVp9D_x2rmuAwh8J5560dBqyQoXsCmQsWMTiRggBJv3Vd4Sit1GxKqUIKsSgfLJhLgnNkvJXK0Yj4-s8dRal-eiAknC3wKEtrSStwx_ijA8nRVxrx4Nrr-8C9NVkRQ7tFB5bToZlbdUAGTia8KCn5YDWDSzrSXiuQoPZBds2bklf8vmlpyPoIczx20rYgdC2VVKyiABkSXwOPGx1wvHt2JGsVP5h730g15L9jyURZT9ruiTXZ8Yxcmsg_ewH14uZryZHHjff-sA-asJ4GTZOF-3jISNRvidh0lxvw4Bw_7uXHoX1CTtvPK87KWMUQ1aq-MpPuPzM36qXI2wxCNorZ_uyH1rxdb4pck_ySq81djeo2mmqNn0TOYGKh7Ubw3G4ruh0XfQtRST45mkblZk9-rjukYH2i0GG_D0D4lzlYm-Uqh2mjxjlHLm_9lZ60PzurZZY_ZAZB6xwpc0SEAqOsA4MLWuGLgFWYqZmbaa8T4ctNoaLtUJqoW_nXn4DYK7X3YOlI43TPeFilmOXRRWNu0isL42nwQ7ylJ2f7nCNFoIfBfMq8LX7hTJf4N_O4p3UVZjfydXwD0xX-ysOahsEn8EE_ptl"}}
{"timestamp":"2026-02-11T04:25:03.411Z","type":"response_item","payload":{"type":"function_call","name":"write_stdin","arguments":"{\"session_id\":48596,\"chars\":\"\",\"yield_time_ms\":30000}","call_id":"call_9BJV6c1sbjdm8pxi0lr0A4cN"}}
{"timestamp":"2026-02-11T04:25:03.420Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1706634,"cached_input_tokens":1622272,"output_tokens":42133,"reasoning_output_tokens":27842,"total_tokens":1748767},"last_token_usage":{"input_tokens":56905,"cached_input_tokens":56704,"output_tokens":44,"reasoning_output_tokens":12,"total_tokens":56949},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":9.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:25:33.443Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_9BJV6c1sbjdm8pxi0lr0A4cN","output":"Chunk ID: f02d13\nWall time: 30.0013 seconds\nProcess running with session ID 48596\nOriginal token count: 0\nOutput:\n"}}
{"timestamp":"2026-02-11T04:25:33.444Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:25:33.817Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1706634,"cached_input_tokens":1622272,"output_tokens":42133,"reasoning_output_tokens":27842,"total_tokens":1748767},"last_token_usage":{"input_tokens":56905,"cached_input_tokens":56704,"output_tokens":44,"reasoning_output_tokens":12,"total_tokens":56949},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":9.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:25:39.956Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Assessing search limitations and best score progress**"}}
{"timestamp":"2026-02-11T04:25:39.956Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Assessing search limitations and best score progress**"}],"content":null,"encrypted_content":"gAAAAABpjATDAC1W3xUJATSOqgPBdTo5mm68fX9CfGzFR9Y6IqAuV0MXswjIm-_pFqHQPxRfeMpoYzjePzr3fAKNIQA_NqROE-K0oNyJTWWs0cxY2x_FsZVzQuWJ5aaCFwUbUOw2766We2qdoskrfrqMV8gjlUQSbPVVfoZYR3arOTA30j0YvyH_i6TdPB19qVn1MXICM_FVA3exGBkxyHOlGDDTdQSdqSElWDy8h5z_9-Xr4HMtwoTwr3WEO3utzpwoCK1CIPqpe9bE4imRCNs2rIIBd4ZpOllTPSt5YEpL--pVBh7MFMI3_wlQqJ9dWnoE1cXx_dYqg73KIgBs5GXbsrh3lsGay9WA-ppYbj4LbGeK0VhZYJFjc1bFHwyyWqjD09BnNaWXnboJ3WElc2DDY2_t349r9JIlN6uOoL1AI6hEd-W0i5gBD7KXS737uX3kOCPyt59wlZ_n6CfI-D8QKPTG3316ZeACv9LATH4GQlvwmqD71vO_yNf-hvmJHUp4Sdb2rMQnCAKV5EZbnrErmJcOC1FG0ZNK2pe4PzJA1dO7LZftrfkt0oVLszF2mT1U12ILf7UxIFT5O66Jfy0f2dcab9wsGLjHF5y-fndzqthL3pyK4JwsmAj3v9J_lXRUqCy4yiRvq9J4BKs_cCQgpRZsHcMwpAw3m1nhzOmA43Ru1TEHLydBMk-FpB3v_n8FzC2YAydhtDinUAwwinld_RbUWB5kz8cVeyNpoEd0TH1JK8WrQCYeu8bOXs3MtWc1poC0NmZroheiKIiMDJg_dw23QUimnygG4lKb7IapO7d0y36OhCoCixqYk1zBRYTZjp2sXV5IzlG6ktzZff70VRRNE3jaowLmFO6EtT2dIsIDHEWoF4X66mLIZyPxNA2KyXnysDtQKwGTKRoV4P8k0c3kI5M_H6oiVEgeJjanBgOk7lWy3TQnTy7ePpjuiRFwDaItxyrSNYX9tc1zgxzyZT0hna4djf0nLOlwhSqrCL2PC7-lKKT2zD_jN_87TxeR2w8R02GBQnD-tSFR4ubWQfK_iHFQwGE71HQHOgowrw2PPtlISFDhX-VyR1hMqvh0OqH4mxzXB7rXlBUGyo7nnKJA3JYFEZI-MrRgWd_gSXm6j43vjDj88xNv9w8Ckvq3fRpr3rpJQvkRPghuZFv9Chb5-TnctfPRsVvp5cJ422MoY812NL2O13z6tVJZhi_CH5VZFBm18PfELbhm0AE0zN8k6GAhSYRgE57-pxm94JX_FjrptU319XY49mfhYtUnALeT_y2bt0DT1Q0u4UWq3IZQXA-kr53b50kHqLyu7EtVj8na2Me4B7NE4QbBU-pFPQU4PUGdGSh8DBoKoCcgSujG2oRnbW9fAwZn6VSzvQ-xnaCtXQk8cE-WBkCDbvRej6uXpEJVVErpx9DjTZQ8uf6JmH6peAxSZcWUr29rZD8-wEEtofrRL3ghN06_ayunryln_O7fWNhVjiPbXLUvWJm1rP4sScRdvsZBl2x0HVblXfjUeGsG-ROhGUx1lexKvV7Yg69mrzqaTsVQ37mPJVY0tpavafPQL3lSWHBmI1KmPqjpMgmmyQLbJnmaKxeVnia35Rgsw6t4J9Qo1omeFFbvcSFgWsYDrYWqOChLXDUw0IMBjEjq_ej3Kc-SUKkMnJyOFYPxugjpOvORYfSA9OAnvP0D5abUM5E7OE8APy6_RO5jMbu8pV7pZt01J0TlYjvM80pJsu4MKRSjlStCjxJGPHZ9pQfy26RFqLZP5gczXC5dmhfVJaNoTKZiFMjtZ_6sv_Z8kw8Ay_gpw3Z4Islc4NgT47s_SgIBXd9BlvvWUTVgUJZKknxpP1PGPESPL8xqwmudI6ASCDqhP4BdiXEXfJ3IZRgQr5s3g53Ohc5sfaSdcu3UV_MQ10xoAISavJqR_PdqVD7nB4d1ZGsoHWOJKutqMa5hYH181qVCl8sfljYh3Nx34L1fGKN0Mu5o6TL0h2HNZqmD0ckv3pM317bQl2l2AmfYwvXBv8Ly6vzSX6H4eydyXOLCwmM534cBKjXVOq_E3fJssMo3ngjrAXN-I9t6QcNW0MWJN9dryI63tF2EP0KxY_Bl3XngPRIXtQVVV5v-rGmdg9VsPoFgEsdLDxehuSSP3nsTzWBb1JRZGrqwNHBrGqvtga2xhzQshWUE1PzvXcjObN-0V8Pb-TSmDhw7mR5Ij4PS5KO70CluVNwHfsKR0J5qa5xntIO1ejgTd3jPwuRm10v6jnJ4IwgqBSScX_BRqxr1VPqvtqnRRYvys3u0XVjSwJ8ZLweKF_37GZMXZkR9NrDhciupNW6Y1XKwzuxE7f-k2_rSiGM_cFUD3bz_6c49F1R7_3C2BOy2sVq1WMMYyfPSO7HzET-zT0xSlg=="}}
{"timestamp":"2026-02-11T04:25:40.473Z","type":"response_item","payload":{"type":"function_call","name":"write_stdin","arguments":"{\"session_id\":48596,\"chars\":\"\",\"yield_time_ms\":30000}","call_id":"call_I56juHpy7lIii8k6157NiLzi"}}
{"timestamp":"2026-02-11T04:25:40.501Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1763631,"cached_input_tokens":1679104,"output_tokens":42417,"reasoning_output_tokens":28094,"total_tokens":1806048},"last_token_usage":{"input_tokens":56997,"cached_input_tokens":56832,"output_tokens":284,"reasoning_output_tokens":252,"total_tokens":57281},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":9.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:26:10.504Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_I56juHpy7lIii8k6157NiLzi","output":"Chunk ID: 45115f\nWall time: 30.0008 seconds\nProcess running with session ID 48596\nOriginal token count: 0\nOutput:\n"}}
{"timestamp":"2026-02-11T04:26:10.504Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:26:10.819Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1763631,"cached_input_tokens":1679104,"output_tokens":42417,"reasoning_output_tokens":28094,"total_tokens":1806048},"last_token_usage":{"input_tokens":56997,"cached_input_tokens":56832,"output_tokens":284,"reasoning_output_tokens":252,"total_tokens":57281},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":10.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:26:14.243Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Assessing slow recursive processing**"}}
{"timestamp":"2026-02-11T04:26:14.243Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Assessing slow recursive processing**"}],"content":null,"encrypted_content":"gAAAAABpjATmOkZE5c7I86wUnvO0CZJ9062xuGvTXRMw1tN-eb5SZ0cl0lYByInDfqTMgbLGyUVHj4QrGlmT99s7L0eKJO69C0yRvoSIGuYO6HiXdj1f-QmqwprhQaKR5yhhyk_ArE4iuT4eB2vEyQrKJUe75M4h_7Q82kAOFGrbFJSotTjibsFFXotaPe_KjHgVjZ9QdmqfjXKt-YfFeENdLWVSbXKN3wtagifnLx64WHyX41HZ2k7-X6FOLniO7vuuJ-C43ETvLNdYVtYi3VF-5xsHuPd5JtQLagtFFdkVSTHgxyXeYzAG6zvvrn0Uwy9K38AdaZCWKoun4t3H-1emSjQwIgCLQqMJNwDC4H2xKD_S5iQcctPrLMdB3JvUMCBLiJI4L6U7gr1mQrIhCyRRUdX3OuQkYDAbUyUse2zR4UVhnR92fd2B7q_wgZEg1DrzzUGrkX82tyY5PCaFga92tcKVxwZwqPbnKjGfp4qcJuy6UNCLbdehucsSnLrwkCQP58cM1unGs1lm5j4_zM3QQ_SjV-i8YvJbl_MIfex96W62rHzdXBvXJJGDeCbGraha3Jb2fbSSp5dFMX3luITr1lOxeuw-1szgSKX41wf6dG3PoBoFZcqrXJsQPjaZVwgLAWKTy_4HHCEQi3KZ28nEVqRy96dUDzaXcBSM2DCaIOmtub7eGbCjq1Z7fETYSjJlhhh-n2MpYO87ewoIeaJgqYmc0B8yUeFCdG2m76uoqyAy9ua7qT4UHcG9Eljm6nbUaVyjnfGFAonkbDm7k3nHUh-eJupo9OdL20zs6cdlryy4a1cuDALKRq8-XZ5ISQbmvchnsJpwH_Mg7zD3oHzra6_9GS0HpkZzQUuaBDYq_aXGQpw78YaqFfg5IdGHyhAtJJpWXxr2PdgKSmtb0Yinyj1PBHVcF232dqxC0bHngzQvgvk4elFVtU6teRZxKClu7_y-SSucc__WFxRTnwlKebKPqNM_8572nKzAij0ZvOW0cet8oVEpZzhpN-QH3g7lIvhL6dxZ-dnnwxtWMqaXuq9B27liGRBPe8wir4YrcGZVXICdSefKeOLzMwNuSCpKsBawN6bbI3Z9T0-rm2H0QA9e5FcoZ_tHV-BRiPKjLKVeDDkbmFz04n_viwiPXN-Qj7xwDEMGmz10vbcsynjBnSy0YxU8GA=="}}
{"timestamp":"2026-02-11T04:26:14.523Z","type":"response_item","payload":{"type":"function_call","name":"write_stdin","arguments":"{\"session_id\":48596,\"chars\":\"\",\"yield_time_ms\":30000}","call_id":"call_FIXqVGDXz44DKiabokN2wg8H"}}
{"timestamp":"2026-02-11T04:26:14.526Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1820960,"cached_input_tokens":1736320,"output_tokens":42511,"reasoning_output_tokens":28156,"total_tokens":1863471},"last_token_usage":{"input_tokens":57329,"cached_input_tokens":57216,"output_tokens":94,"reasoning_output_tokens":62,"total_tokens":57423},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":10.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:26:44.555Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_FIXqVGDXz44DKiabokN2wg8H","output":"Chunk ID: e061ba\nWall time: 30.0019 seconds\nProcess running with session ID 48596\nOriginal token count: 0\nOutput:\n"}}
{"timestamp":"2026-02-11T04:26:44.555Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:26:45.200Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1820960,"cached_input_tokens":1736320,"output_tokens":42511,"reasoning_output_tokens":28156,"total_tokens":1863471},"last_token_usage":{"input_tokens":57329,"cached_input_tokens":57216,"output_tokens":94,"reasoning_output_tokens":62,"total_tokens":57423},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":10.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:26:47.123Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Inspecting process hang causes**"}}
{"timestamp":"2026-02-11T04:26:47.123Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Inspecting process hang causes**"}],"content":null,"encrypted_content":"gAAAAABpjAUHB_pFM4OlRT7cOJxFUFWXJGr7lhPwg32QmodKBK6Y0Hm72zgKLik_bmjzkYGfTyH2SsGX63IbsVQinYcYgJwFetb7kqOqaQX6NmadVT4SV8cTgy0eVUK8xASLJpQiaP0IR_wFVN9Hx8rzl2lsAulQ2auh-nFB14W9hILvOdTktYR-q-ohTcSnXTBJE-nkNTODtgHfJyJcytL5XiBV0KHkh0WvgY9co0p0RW-nlwoD1bvPn3oTF-OtuV7QWrEL7nPv10XKBCS5rfjK61XfznoVF-NM9DBUDgeUJCgx01NEBcH3F6FJ8vDO0QVBXI0EipNIeCcC9r7YXh0GR0IROLj2AXUlXUa3DxKXzPfzh--k6vpDVFZC7Bt_AuwJCmbrwJBjTCxHxsDcTNy1vI3s1YvMAZ1aOJK52fi98Be63o8g6WFAGy0d6sy5i2fqewMLk9NMcbBpuC9y33aEBLQO2FdXhcGe6Y-5shZClocczSWh7aW3RmbbzhJ5WxM0Fb3TcFACQXpIgmsG-RXI2o3OmWbuoaPvlJbkQPsu4wudGA-pveQ2hiiLU2NaUOu04esbNGCYandPukYf8aCzSKPOEzqo-y_Q77frXg660eslPpVFfassKzwD6nUL8f5F0RjwaCsnaP6gve5c67_kkOmJgjTuxmYY-e2ZwAcOiFMp4deWgw5ACmv100pKp0kZTsqjsUQBx3wb3gfPc3iNmGBHt5gmyyCajEeFRoDRsnuvWeCtej2aVceM-GUNbnjM2_M_WtTpTLv40mbgTuaRvxhGOiRAeJVZ0IEdj0RPJRJPCAzRDGLG8gOXejo2bH5fB0XDYElCaeCOoi8SxWjm67C0QjPk_UpvjA46JdPmWzDMTs1zrmCq_Fgk_Uha0Zwro-olkXrMqbNvBlcz787SudXeDxv4Xk1hrBfxOZEu-9oeiIjhsD7BDnWTFeYwmGQSMGhtHQo3NtF7jHv5c44iYN--CX2XZ0Wj9yH4RcE8gL0d47hlPqLqcQYF5ZRcyno0T7d6pPf1mlrGUSMhlYEvvZbzRCZIKpWn552t6aNbWUbxXbznjJTmuJgLRYHSvYanB7SXRouL"}}
{"timestamp":"2026-02-11T04:26:47.548Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"ps -o pid,pcpu,etime,cmd -p $(pgrep -f 'm=25;TARGET=16' | tr '\\\\n' ' ')\"}","call_id":"call_6fEIo1EE9UaLGiBMiMOiIOlB"}}
{"timestamp":"2026-02-11T04:26:47.551Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1878430,"cached_input_tokens":1793664,"output_tokens":42607,"reasoning_output_tokens":28199,"total_tokens":1921037},"last_token_usage":{"input_tokens":57470,"cached_input_tokens":57344,"output_tokens":96,"reasoning_output_tokens":43,"total_tokens":57566},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":10.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:26:48.176Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_6fEIo1EE9UaLGiBMiMOiIOlB","output":"Chunk ID: 65b8bd\nWall time: 0.4731 seconds\nProcess exited with code 0\nOriginal token count: 797\nOutput:\n    PID %CPU     ELAPSED CMD\n1707126  0.0       01:56 /bin/bash -lc python3 -u - <<'PY' import math,time,functools m=25;TARGET=16 lim=math.isqrt(m) S=[] for x in range(-lim,lim+1):     y2=m-x*x     if y2<0: continue     y=math.isqrt(y2)     if y*y==y2:         S.append((x,y));         if y:S.append((x,-y)) S=list(dict.fromkeys(S));Sset=set(S) print('r2',len(S),flush=True) D={} md=2*lim+2 for dx in range(-md,md+1):     for dy in range(-md,md+1):         if dx==dy==0: continue         if dx*dx+dy*dy==4*m: continue         pts=[]         for ux,uy in S:             if (ux-dx,uy-dy) in Sset:                 pts.append((ux,uy))         if len(pts)==2:             D[(dx,dy)]=pts[0] Ds=list(D.keys()) print('|D|',len(Ds),flush=True) Tang={(dx,dy) for dx in range(-2*lim-2,2*lim+3) for dy in range(-2*lim-2,2*lim+3) if dx*dx+dy*dy==4*m} sy=[lambda x,y:(x,y),lambda x,y:(-x,y),lambda x,y:(x,-y),lambda x,y:(-x,-y),     lambda x,y:(y,x),lambda x,y:(-y,x),lambda x,y:(y,-x),lambda x,y:(-y,-x)] def canon(C):     best=None     for f in sy:         T=[f(x,y) for x,y in C]         mn=min(T)         t=tuple(sorted((x-mn[0],y-mn[1]) for x,y in T))         if best is None or t<best: best=t     return best @functools.lru_cache(None) def pair(a,b):     ax,ay=a;bx,by=b     dx,dy=bx-ax,by-ay     if (dx,dy) in D:         ux,uy=D[(dx,dy)]         return ((ax+ux,ay+uy),(bx-ux,by-uy),2)     if (-dx,-dy) in D:         ux,uy=D[(-dx,-dy)]         return ((bx+ux,by+uy),(ax-ux,ay-uy),2)     if (dx,dy) in Tang or (-dx,-dy) in Tang:         return (None,None,1)     return (None,None,0) seen=[set() for _ in range(TARGET+1)] start=time.time();states=0;best=0  def dfs(C,H,F):     global states,best     nonlocal_start=0       def rec(C,H,F):     global states,best     states+=1     k=len(C)     if states%200000==0:         print('states',states,'k',k,'best',best,'H',len(H),'elapsed',round(time.time()-start,1),flush=True)     if len(H)>TARGET:return False     if k>=2 and len(H)==k:         if k>best:             best=k             print('new best',best,'elapsed',round(time.time()-start,1),flush=True)         if k==TARGET:             print('FOUND',C,flush=True)             return True     if k==TARGET:return False     # simple optimistic bound: cannot exceed TARGET anyway     for b in sorted(F):         newH=set(H);newF=set(F);newF.discard(b)         harm=False         for a in C:             p,q,t=pair(a,b)             if t==1:                 break             if t==2:                 harm=True                 newH.add(p);newH.add(q)         else:             if not harm or len(newH)>TARGET:                 continue             C2=tuple(sorted(C+(b,)))             key=canon(C2)             if key in seen[k+1]:                 continue             seen[k+1].add(key)             bx,by=b             for dx,dy in Ds:                 nb=(bx+dx,by+dy)                 if nb not in C2:newF.add(nb)             if rec(C2,newH,newF):                 return True     return False  ok=rec(((0,0),),set(),set(Ds)) print('done ok',ok,'best',best,'states',states,'time',round(time.time()-start,1),flush=True) PY\n1710477 18.1       00:00 ps -o pid,pcpu,etime,cmd -p 1707126 1710477 1710803\n"}}
{"timestamp":"2026-02-11T04:26:48.206Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:26:48.537Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1878430,"cached_input_tokens":1793664,"output_tokens":42607,"reasoning_output_tokens":28199,"total_tokens":1921037},"last_token_usage":{"input_tokens":57470,"cached_input_tokens":57344,"output_tokens":96,"reasoning_output_tokens":43,"total_tokens":57566},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":10.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:26:50.863Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Inspecting bash child processes**"}}
{"timestamp":"2026-02-11T04:26:50.863Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Inspecting bash child processes**"}],"content":null,"encrypted_content":"gAAAAABpjAUKRn6oFcHbDy2wwI4k-FSlKvkX4VOy4BshCY74mg53mK5XTGpcf_wvdDRSaUd9OHL4gYHAmyEnAyjXnHSTYiW9w8yiPlDbaidpMIm60uhUTE4E_pDSr2LkXh-tACkoX7P4zM_8_TH2lSSwquXF0hfEwQOCYZBW9JUzXveGhFuTh8piP_SCBykbtopgUaiF8riNITw_OB7m3sof9DaoSlr9msNEn5aDqqKRd9YZFM2emkPIYcest02oIXkS8B3NAfw_QtCt6KXkpnEbu1Fji_rUNt4bGtCGiNcIE1JlGWpMxovzCRpzY1Lu3MLKUSJdf6spE_U5EblbnFueMoUnJQBBoi-RTN8jLcnSJJD1vIp-dSf0ijuNTW--Re-5uFKxKBQjoFhRFZ8M4m41k4r7OIHJvjRqEFLfWyniY6k8ouKYW34h9QfQvxrRgZWI4lws5jeA2cHThXJAwriVsuPXM-o9-ZR1AsbOW8DA1wUCzsxytsiHBWVRnesaYOVHv6DPHYyraKnZXAt5x84vj2-2C-3-hmZ0w8XhIMKRSuMLL8c9GlEL2qWvyw1DGwoDcCoiBsRoX3oJWHDPvnceD_978yesmhNFxTEvF_OxAk1QITSYOFDvtrFNHsx_ddROi_7KFao5BtIi_dbLs5h4cRn4Cs7BLodp88VJn-ud4nTj3Yd-1mz4gm3kvYUKmRkTZS4yaJV_qU_BGsQx2rVuLS6KV42EGzBCWOJae9_4SNg9y4gK9zAK0ibOECVFbtGNJYDB6FKfqKzTb3hS0bIq23ruf_kCSZWLtYV4MaBJqvbHvEvYWYpPmjBVz5qElYzajLC-y2_MB_UnAGyGWBoaa_C6P4OoZL-q4Ncj-vvmE5kMVsdr9w0ASeQs8FCiYohPwnM9LER01pkpN3nSTCDqseINWcrFU315WKzbXWPVOBUJYmKg78UB0wLeF2M_dIQX2dvzqXm-9eyo-QlRe5U0ky1NmnVXnN97WUsI4S7gkwjG_eUds5zQE4LsRpkCn73g7tktpFrFl327oijI_VS8PscMbXJMAoN7EadetrC7PesUJmVeNktqlyVnc-Bk5YNFaUGbaoA5yIit4H-FibLB0P9sFybjpQEh_nCkoOSLX3R8BA4SBAxvztVbfFKi5hGTyZJce1VvnihGOtgDHci5zGxkzcSCKmmaKMCiPnlCSgtr5gnsH0kMpkPBuIMNBbPU4he2EJ8NZF7W5u2etI5vk0Kqxs-29A=="}}
{"timestamp":"2026-02-11T04:26:51.201Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"pgrep -af '^python3 -u - <<' || true; ps -ef | grep 'python3 -u - <<' | grep -v grep\"}","call_id":"call_BE7bv9guLnqb5yfc3O5Hxsuy"}}
{"timestamp":"2026-02-11T04:26:51.225Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1937101,"cached_input_tokens":1851136,"output_tokens":42719,"reasoning_output_tokens":28259,"total_tokens":1979820},"last_token_usage":{"input_tokens":58671,"cached_input_tokens":57472,"output_tokens":112,"reasoning_output_tokens":60,"total_tokens":58783},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":10.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:26:51.872Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_BE7bv9guLnqb5yfc3O5Hxsuy","output":"Chunk ID: 78fa9b\nWall time: 0.5157 seconds\nProcess exited with code 0\nOriginal token count: 777\nOutput:\nciro     1707126 1665791  0 04:24 ?        00:00:00 /bin/bash -lc python3 -u - <<'PY' import math,time,functools m=25;TARGET=16 lim=math.isqrt(m) S=[] for x in range(-lim,lim+1):     y2=m-x*x     if y2<0: continue     y=math.isqrt(y2)     if y*y==y2:         S.append((x,y));         if y:S.append((x,-y)) S=list(dict.fromkeys(S));Sset=set(S) print('r2',len(S),flush=True) D={} md=2*lim+2 for dx in range(-md,md+1):     for dy in range(-md,md+1):         if dx==dy==0: continue         if dx*dx+dy*dy==4*m: continue         pts=[]         for ux,uy in S:             if (ux-dx,uy-dy) in Sset:                 pts.append((ux,uy))         if len(pts)==2:             D[(dx,dy)]=pts[0] Ds=list(D.keys()) print('|D|',len(Ds),flush=True) Tang={(dx,dy) for dx in range(-2*lim-2,2*lim+3) for dy in range(-2*lim-2,2*lim+3) if dx*dx+dy*dy==4*m} sy=[lambda x,y:(x,y),lambda x,y:(-x,y),lambda x,y:(x,-y),lambda x,y:(-x,-y),     lambda x,y:(y,x),lambda x,y:(-y,x),lambda x,y:(y,-x),lambda x,y:(-y,-x)] def canon(C):     best=None     for f in sy:         T=[f(x,y) for x,y in C]         mn=min(T)         t=tuple(sorted((x-mn[0],y-mn[1]) for x,y in T))         if best is None or t<best: best=t     return best @functools.lru_cache(None) def pair(a,b):     ax,ay=a;bx,by=b     dx,dy=bx-ax,by-ay     if (dx,dy) in D:         ux,uy=D[(dx,dy)]         return ((ax+ux,ay+uy),(bx-ux,by-uy),2)     if (-dx,-dy) in D:         ux,uy=D[(-dx,-dy)]         return ((bx+ux,by+uy),(ax-ux,ay-uy),2)     if (dx,dy) in Tang or (-dx,-dy) in Tang:         return (None,None,1)     return (None,None,0) seen=[set() for _ in range(TARGET+1)] start=time.time();states=0;best=0  def dfs(C,H,F):     global states,best     nonlocal_start=0       def rec(C,H,F):     global states,best     states+=1     k=len(C)     if states%200000==0:         print('states',states,'k',k,'best',best,'H',len(H),'elapsed',round(time.time()-start,1),flush=True)     if len(H)>TARGET:return False     if k>=2 and len(H)==k:         if k>best:             best=k             print('new best',best,'elapsed',round(time.time()-start,1),flush=True)         if k==TARGET:             print('FOUND',C,flush=True)             return True     if k==TARGET:return False     # simple optimistic bound: cannot exceed TARGET anyway     for b in sorted(F):         newH=set(H);newF=set(F);newF.discard(b)         harm=False         for a in C:             p,q,t=pair(a,b)             if t==1:                 break             if t==2:                 harm=True                 newH.add(p);newH.add(q)         else:             if not harm or len(newH)>TARGET:                 continue             C2=tuple(sorted(C+(b,)))             key=canon(C2)             if key in seen[k+1]:                 continue             seen[k+1].add(key)             bx,by=b             for dx,dy in Ds:                 nb=(bx+dx,by+dy)                 if nb not in C2:newF.add(nb)             if rec(C2,newH,newF):                 return True     return False  ok=rec(((0,0),),set(),set(Ds)) print('done ok',ok,'best',best,'states',states,'time',round(time.time()-start,1),flush=True) PY\n"}}
{"timestamp":"2026-02-11T04:26:51.909Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:26:52.301Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1937101,"cached_input_tokens":1851136,"output_tokens":42719,"reasoning_output_tokens":28259,"total_tokens":1979820},"last_token_usage":{"input_tokens":58671,"cached_input_tokens":57472,"output_tokens":112,"reasoning_output_tokens":60,"total_tokens":58783},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":10.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:26:55.703Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Investigating process hierarchy**"}}
{"timestamp":"2026-02-11T04:26:55.703Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Investigating process hierarchy**"}],"content":null,"encrypted_content":"gAAAAABpjAUPTJEgLDNUiWM2i0KfgsBCJnAUeYuMa2T5ab1wr--yQyxLpUQ8gCiwRHW3SbSxEt4dIh4krNIvZYGm556PgpuVGpEYfEMI_cECGi2nI3HYy7dzkrbnsmvK8WKCh7vH-IL2dS5nYCyJxn4Ho5pOoTO6-Rg8NcYARg2kogZqXaVo0bwwME8EIw6ibDXYfbhsW7KfQmNBaY3F6E5Eip2VEABuWFZBg8QYh_kNYV0Q00Lsxn4BZsgAXPuGdK-XkfIpDkBiAHbH4i_rWU0mV7OwwjVk6H-32HCUsmdF0WiACnKKzdPv-fmrVMJ18a20fHS0gQ5WVZON7Nf8KLR0_GkF5KNn-prUAKZOcq9gzDEEq7XCzoSzxJicnCMd0QfJUyKVS6WBUKQ11wk7N3QkPUzQPsHbhRkTld6aMKXn2aXG-hANGd4lz7wJ0EuLqo7yiuH7MbKoe-VdTnucOEe3IeWoNgX7TTvPrbjpgOaM91hLKd9ipWPHZ76jN2NZYxiy8-GC5cymeu2Awy7myuo8c9fclaGRa3WSeQ92VaFC-Va9kDR4uDCv3NBG1XvMBgXB7s59F7UVG79XO0lLFMtQyp2zSeVpEpKZ_sKfYkD_xZQYMSB7g_10VW-nSHuhbHnb9qL5dxkiqdZ7EOmh_WLCd4UkuSGP9De4de0B_E7O0NdswoFEL7EHXszYvys15D41griodbyy40MVW-lW1Ytj-axyCz-Sd80kOQuRqFrG9zpmpxzn1zz3semLQ2GafPAV2-30-gXRcNYfqfnq3QYlLg3zUMFYyZI-QQFV3JE_LRu1qp_CTZPtJrU3f3MExxeJe_OrP32IWmTsgUP4EzveO70uek1HpznNNfFe8byRo1hpr5xU4cY24TLI8QOzqk7Y8snmYgo7HCyWEU4QW6-SxdaABb8ssmcCD4XHWaXzyM_4DfG4vIrIZ9b1PyU1F8VOEx02nyiXS0u96pP8cF5pJFHSgyhbVLgbYRrV1Pfg--6KPCsCxhkoBASC5zQr8OmtOitPqyqSWnvjIB6M0WXQUMcsM_tl08R3gGIrX1IQftgbS9UHJIehysJqTFevTWE8csipV6Wj4Teqyc6UKd2Qr_ZMa_I-XwY7jFF3fZxzBtJL_jA49IONALxeQsjEI04KE5-jCkfmqiDm3uoQahSKKkeAUTwCoVT6EA3W80ZQxOilvDpjjqekAbtIImr96es3CA9TQcQFl3_Affa0Q_-ileUT5MWaaH1g1rXv9rKVj27s_SzMmveVzfBsUpt24eFI8MozN1I5tDBlNLYJMa8ppetdB48oqLRz_JJHiCheKPd6GIU3kGIvoOo6pACIU6TdXRzgYAcpy84ICc_513OWw0SoUcxK4QfeJPaXChgHSxdcsfQ4Ke0Oo7EZOiazCIAAwY5dXscokDpRC1iWjWpqf2qWBsNaBEA_hZK141IXFPqUb8vS8eljHh3Y47vDk3EY3hKY6mB0yK7jFbwOnw9beCNWvBWlhwpW4FcikEV2h9xLun2flx07vwmyJp0PZAV2vu1MfcZ9JQplqn4yVMxA6-NunwCPCaRhgwAyDtDYkFcHzLt5sPoeUk4qFh-ui8nqZhpMdELKImRt6iG-0L1PZE0c-XhaROP5D84sNcMEzmw7iG5t4jWJcOmLZn03S70YDfSBwFGW5LFCxvtQEyJ-A7FjExvCvyo8CyZmAgzBprxD2TZtyMJnTtc89kuyOoOeLuJmEcN-n8MNS-SCiw_7vr1jSdJrFa-ZxHTwnR1QkItPyIsFhRU="}}
{"timestamp":"2026-02-11T04:26:55.934Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"pgrep -P 1707126 -af || true\"}","call_id":"call_MaUjNfD6ztdd3QgiNnAafJqk"}}
{"timestamp":"2026-02-11T04:26:55.937Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1996954,"cached_input_tokens":1909888,"output_tokens":42900,"reasoning_output_tokens":28409,"total_tokens":2039854},"last_token_usage":{"input_tokens":59853,"cached_input_tokens":58752,"output_tokens":181,"reasoning_output_tokens":150,"total_tokens":60034},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":10.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":16.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:26:56.541Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_MaUjNfD6ztdd3QgiNnAafJqk","output":"Chunk ID: 1ce8b7\nWall time: 0.4527 seconds\nProcess exited with code 0\nOriginal token count: 6\nOutput:\n1707487 python3 -u -\n"}}
{"timestamp":"2026-02-11T04:26:56.569Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:26:56.941Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":1996954,"cached_input_tokens":1909888,"output_tokens":42900,"reasoning_output_tokens":28409,"total_tokens":2039854},"last_token_usage":{"input_tokens":59853,"cached_input_tokens":58752,"output_tokens":181,"reasoning_output_tokens":150,"total_tokens":60034},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":10.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:26:58.117Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Monitoring child process CPU usage**"}}
{"timestamp":"2026-02-11T04:26:58.117Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Monitoring child process CPU usage**"}],"content":null,"encrypted_content":"gAAAAABpjAUS1G4qkHL6QzuIAt0m_SZQf3Cc_0kIxJ8zWe9y__M3BY7K_S6osZkgdN81WyVsQckxbmlPyWGiwiN788vrq5yXVQDhTbz9aiSEk77SxYTqq4w4RGaWMNpsJ29mgvdmD6VXyzNh_eA05hgejDAZu7YV6brHJnkxsJeLzM4j_XqASAnGI4LOudK62UpfYE19M-reJpDxKSxK9hxUth9XNvYvSCqmmC2et7IbQh-uoarbxpzFse6fWTExj1OBtq25zwi5EJK6kfHFd_2TDXt_zZTopeAYL4hBZXK5yZXGAItTFb44rCBGCdRuEIKNnB2XNOmkKTcTzrj1oAE_Nyxoy8CcEqc__ot_7cJQtKVjv6UeTavDO0nqI-kfW3mVCZplicsQrw4IUekgAptN9RmjyX1tiebXs6Ji4Jmik5ZiXoGD4lUsJkVk0Cfi34z6WEooZ-4dBKL5GysLuUqgqa3CIzYzaXBFulSQY5yT3ti5iGl4adXMswL4XKxZojUkJq0xqWTJEvnYvy8jO_eqSjkfmV5hUBwVBH0IFrcF0N7EwUbUq_AYvnypRj5JPEnaCOA9XRTz2WmngMlByWoqtBcm3qXmv4tsLs7BJSqs0IdsMYd7ftL8Iiq4pbWVuTYpqPON_eNefh8tvf5DnotauQeQ2IHxI39EKcPJ6DCObvx9WLGIG33ycytCFyIPCChByhd-HMZyfA47R2T90P9IxMOJheiT3-Nz2gYE4lhDd-2NkJBNtt49hNx3sdmg5TgAI6wUSXDJILF2vgqG6hKALoAQvEVCA1BSg9dbI5FNVLvo4A9fSdsJ4-fOBBS2WZXZUGeU-S1OKkfZsyWEUnjlc1GP-CaCshHsfBuswWLigGJ1xTJliYx49N0algclTpvN1AM9bBxjBi6OCRymbxQPKT8iFvnU8Q=="}}
{"timestamp":"2026-02-11T04:26:58.842Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"ps -o pid,pcpu,pmem,etime,stat,cmd -p 1707487\"}","call_id":"call_KvkDWUGv3DIctJ4S8GZvWGQO"}}
{"timestamp":"2026-02-11T04:26:58.870Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":2057043,"cached_input_tokens":1969792,"output_tokens":42957,"reasoning_output_tokens":28425,"total_tokens":2100000},"last_token_usage":{"input_tokens":60089,"cached_input_tokens":59904,"output_tokens":57,"reasoning_output_tokens":16,"total_tokens":60146},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":10.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:26:59.451Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_KvkDWUGv3DIctJ4S8GZvWGQO","output":"Chunk ID: 20dc5d\nWall time: 0.4543 seconds\nProcess exited with code 0\nOriginal token count: 22\nOutput:\n    PID %CPU %MEM     ELAPSED STAT CMD\n1707487  100  0.3       02:07 R    python3 -u -\n"}}
{"timestamp":"2026-02-11T04:26:59.480Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:26:59.812Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":2057043,"cached_input_tokens":1969792,"output_tokens":42957,"reasoning_output_tokens":28425,"total_tokens":2100000},"last_token_usage":{"input_tokens":60089,"cached_input_tokens":59904,"output_tokens":57,"reasoning_output_tokens":16,"total_tokens":60146},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":10.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:27:02.382Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Considering polling frequency**"}}
{"timestamp":"2026-02-11T04:27:02.382Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Considering polling frequency**"}],"content":null,"encrypted_content":"gAAAAABpjAUWzvaq7WvS-b6slkpgul92PYR5TGZkmAwr0Uu_Et1cSzX7uHORe4cqJndz7jEuZU0Jwy-ME0rfIiyVWHaP45gJJXdaOQ5eT7d2uCIpGg2Xl90Vjf6eS6Qgk20OUOp_qoB7OmhsditN6at4XKW20Kl4jr3_r2kSBkNJwCPf2_BRSxnE5aPtIkhR2NnJrtA0rlottR94_VZbRvihO39MDy753DyI74DW5-2toRcoMa7fRkHoVMy_wbb8a0hLBwwL1FnhYn5RRCdT1sFA0LMPm2T89gko88M9jsPAmBd4ZyiKetaijHEqvEQdfr7fnOqt5xGnhNVO5hXwOSyYLfm3ahaIi8oFs25eZ7WRtXXiGgB6VP_LYNsc_YHeH4gWhJO-VTpwLEF44ys7oIkwqHA9eYcM0BtCVEv2C5YLKqKWV4I3TS0Fud2-P9Bfgv__8qVW2RMBkwFCquSPAwqSEiSa--xQfhw5akDQYU-J_j_nRqUKjG8ILOjsglRhDC8Rf-wFOm2C3HL4r-BKxZhuJ25J58MmyYdETHKYC172sUsu3qXCdS0v1mwSqEChMbDlJsFRSFf6JBEuncfCyGes88uelBIirdBJSumgtZepJDA3ybE3CGEi9GDykyic4u__CJQKqbgzGAaGFizOYgnBeK4d7YCSWGfZ3UenYw_ET9Qt6yGF4hhjIZzAtYfxcEPvXoUWPfkYm6RlvDNyh1fb2YNjkvs9R2bLRPtgayulxui9KSHp77QGQ8GfhToe62kj0gPMZsgVW3wMv-FC8r1K55h9Mz6OZ-uT3YmtnQpEbA5EEGgwggdO0_kVb7VATFH9Tgf-2J29Q5fH-w_8VcpTCd7VjLiZg35_I2eXN0svgNruVC-QGgCVMEHKNHYzNQr8Gk6nHLw5w3xYG6yz48Mi6Qa0U7i5-_FZEI95vzpRm-Fjut0YxAenWvdJZh-DVlMPaeva8_qg6-hrNyXEjefeZUXAuRpeuxEiIlN65ta6i6qpSW4B35jY_baOezHh--dEroLLbiqxH3_3reYH2fJ7OtzMmN49UKNk1RY2f8hMfh7ITLXj96iuCKzbzcJ8Y5dhn9bXT9TFI6aRPuC9VSbPaadUlF_VCo_hfgYyUHkG2QT15zaVdXcDDLXayRc4F-XExpduBijmXajtRaaJxryOKAUefrINvjTXWBT8GbnuRyr-60ZXQBqlsrGLjC0omcbUz4_4WF9fAkDpadU9EqCgoFyD_V0ws5UqPBz9i8QmRPHbexitBaR_LwF_N5Tni7KmoIkCheim"}}
{"timestamp":"2026-02-11T04:27:02.592Z","type":"response_item","payload":{"type":"function_call","name":"write_stdin","arguments":"{\"session_id\":48596,\"chars\":\"\",\"yield_time_ms\":30000}","call_id":"call_Ox9Su0e8odBkLjaasIMUf56w"}}
{"timestamp":"2026-02-11T04:27:02.596Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":2117271,"cached_input_tokens":2029824,"output_tokens":43060,"reasoning_output_tokens":28496,"total_tokens":2160331},"last_token_usage":{"input_tokens":60228,"cached_input_tokens":60032,"output_tokens":103,"reasoning_output_tokens":71,"total_tokens":60331},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":10.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:27:32.627Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_Ox9Su0e8odBkLjaasIMUf56w","output":"Chunk ID: 8aa8d2\nWall time: 30.0013 seconds\nProcess running with session ID 48596\nOriginal token count: 0\nOutput:\n"}}
{"timestamp":"2026-02-11T04:27:32.627Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:27:32.925Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":2117271,"cached_input_tokens":2029824,"output_tokens":43060,"reasoning_output_tokens":28496,"total_tokens":2160331},"last_token_usage":{"input_tokens":60228,"cached_input_tokens":60032,"output_tokens":103,"reasoning_output_tokens":71,"total_tokens":60331},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":10.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:27:35.760Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Abandoning inefficient exhaustive search**"}}
{"timestamp":"2026-02-11T04:27:35.760Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Abandoning inefficient exhaustive search**"}],"content":null,"encrypted_content":"gAAAAABpjAU3snzvtN3YT7rJZzDNKVpafTcI2Y_JR4pUuRePthih5Bnlq9h8aKCfUpD0OdEIVC37TbWXtHbx_ZR2BJGl7Nj4VxQOauJhri6HZuLAqSGCwqg-lOpc0AnN0CSJ2TDD391YnPZMYPPUJeZuMUTgu2qW3MT-Xh7-TByG8SWIxBpaREb89Wf6DQhEc9nILTVy114QEOEpK_J7INZ59bIbornNbVvE1I7IxLVdCA0-ga-hes5UmDYua8fQWWh54Ibtn7JWlPLPKgh83vZ5yT2Ax-U8oUkc13vuJibrTmzLTGM9B2AbX_vP_DZQXPaEw5YrMhBuB1nwvaWCJ8tnLb16L145DQKOsn4inSOcGCaM8uUYLwOOfcL2OStKzsyFwokGCEVCjgOxbn7H1DBvUmwBPsyeFQxAgX5a1u-cBO03hplabB_4RLwfzQNDBITIi5CObm0BSBiv6aR5VWGFe_tU4ZhrNF8Z5x9FN3A63UyboTi8c36kNC5_XVFaxpxQTzy3Ya3VhMp8-4VzSJijJoG-LlCTdB0lTeOb-3Z4d_LCml9uYMTB9JH8eQoaxErDSYz8EPssxQy7yFCBjt-zrWt73r3LGdIh_DTn5TDAt22Qx7NA3bhrw8sarNoXlS2AC5e38q-BztQ-p6rBur1QXaFlAJF1nv865sP6ea8vG2B-dh_kWpXT6-lWafE228wmWQ6AqpOx-1BGss553wEd86ZcFIoeBSpVFs-SPevzjoYDu0UCc86SRUIYHtp_yCq1f2Dcb3EeI_BcwjRoUoFd3N6IimCbhVE9xaelQBTDDchf5H77oBmvbNS2jgWu5Awd2fp2jBI1zii-t2-bndmXDrjNwUgWKDohOS5hPn7NN9ZEHyX3HfNThIwSMCbpWqNYDrFOcOuVm8SJYaDG-YrkOSC58WtnB2QF5IqS8G87ToIT0xa6xp5aE3cLA26UBcnzCSiTFsc9E37HqqtVNT4unDg0srbrVGrECw744HN6SUvhWA41G2ud9tzmqu1syGZ-Hk_SzDsfj09zMrZFeOlJlvO_jGFxatYWdYU-NIzypqTAIUFOuN9CVW64UF57l9ELAkhO3lS1S5zR32a0lPE2e3MeGRN9OvMYNz_VhvRSpP0_NLqpQv56QEQqhToV8Auh9BRkjbjJG5QknL_G77XHEueABgF1e4PYgmJHFeamppYzqbM2ISSZUqBJpNlMW7xQkabRr989ebxi6R5mFTBQpyy1fUAmxV0c-TP__FmPcwacfPRfHUiT-XQnNAF7AfWCYoWtoPry0Jzj3NAno6e61sDjteVXvPDUS5JIIePITEvLSQVqqM5saxff3m8aji8-djQIZ1B4cMudfb9ohVJ6X_VyqsuYbHqoVEWqfRTYTStTlUhJmdyBlc80wJVSqQHrM_4btSyMqVx1ebklPK7PBx0d9Dc36RQw_o_g2z_arFULqopY32pTfnprHnqc7akN5n2sKrEi"}}
{"timestamp":"2026-02-11T04:27:36.390Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"kill 1707126 1707487 || true\"}","call_id":"call_rQ9GEof8NrWtBn5BNlev4wra"}}
{"timestamp":"2026-02-11T04:27:36.418Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":2177652,"cached_input_tokens":2090112,"output_tokens":43186,"reasoning_output_tokens":28592,"total_tokens":2220838},"last_token_usage":{"input_tokens":60381,"cached_input_tokens":60288,"output_tokens":126,"reasoning_output_tokens":96,"total_tokens":60507},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":10.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:27:37.025Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_rQ9GEof8NrWtBn5BNlev4wra","output":"Chunk ID: e4a502\nWall time: 0.4797 seconds\nProcess exited with code 0\nOriginal token count: 0\nOutput:\n"}}
{"timestamp":"2026-02-11T04:27:37.058Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:27:37.371Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":2177652,"cached_input_tokens":2090112,"output_tokens":43186,"reasoning_output_tokens":28592,"total_tokens":2220838},"last_token_usage":{"input_tokens":60381,"cached_input_tokens":60288,"output_tokens":126,"reasoning_output_tokens":96,"total_tokens":60507},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":10.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:27:57.423Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Formulating hypercube subset sum construction**"}}
{"timestamp":"2026-02-11T04:27:57.423Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Formulating hypercube subset sum construction**"}],"content":null,"encrypted_content":"gAAAAABpjAVN6XZOYRZeFkc-h9l1IA9jh9LBfNUfSeXzuc6FsnXj1OdVcdx05vfWOSCP0wSvFpYXm_znvUq9loVYaQS5gD_nQJfe5el8O7jJnlhbpWSkO_34mMXI3cvE1F9jvYebEBg9YlxxcMUeUVapf1Ic8ahWMBZNvcZQD7zi6yyem9OR5NJkvmOcnelz6o1T_jDHyVReejDVI6VGZTYKXHFk85SBc2X-m5icAS2ByhtZAmoDlZHNdA9b0ld_NdQhXMcEDgWYYBuFOqBXtwZh7qCsG4o_8u17o3RmRCK6k_KoiAoO4xx98RYXxtbsK76HbfiMfA1lnb-2vTBK4Kl5zGoZXbm626thNUAST_iPj9noNjnkVtDGX8gZesPp3pAxPc82XdswsKnq_FsAP3ONJiYY9w3q9zWqaTO7DJkSIGw_kdLkFCLrYBJdRypS3DKrFegGagxnZOSj47UnyQS8Gfv5Xg7DZm1osuuNJyih6uu6N7OiDudgMLHOEQi3ByTBRiD_zX2zCXidYgxkn51TWgrICJCwkix67dT0BEmb90NASDylLGIEhKOlZ3kImLktEYvGQlQ28qqXNUPYx5Rs_J9nNR9H-HUx7GuWMROmyQfWCAof2OAT0tx_YzlgWE0wj8KfzXMC_CZ-tjfGb7-I6wi13ulS2MtyVh6H2q2wCunFhv8s9CUSpQFcMLwaCz7U-ZAi9R437dZKTourbsnS9d5ZbmhvURBpYjzPD_MyydpAm-3fKgXMUqlzSuJ9VIkZi0N9fot5-Fv7rC84LB9E7YA81TRM3ZHxs1xJ_8Ub2ga-kv7ESPvTU7nVi9CYQO4oIDwfy-0aV4ZC7yEWKd-oTWRsJDe7LHjKkq36KMRh4tYqKd6V-ETQl-wiW9v66sEbFdHWg2vEwE0ySPvleB-gihuFIYpjtaTv2LIrwZd4bHR-KiNVRzBgs3bGWDFFYlbKWtVGA6h-UVUuguvfeJ03mqUGdW9vXVLDMuVqD1jPD4e3s6fSygShGiuD6j5gxc-VP5gG1DUdQ-dbKKp2skaN90Sm4x3q06kAZhB1xWOXynZ_wzZo7M-RDzxZ-IgJSEsnA2Yywg2DwrLyaFvZ3q_S5T9e_JR7JuDKm_2IeMb-vq6DpnK2S0uXGyQEjuYSBQWPi3Wz3DPA-mPxsIZWIswUJU8ZADfjBXXilFhc5qTw8oY_S1PcPZFzR_0pjFXbdRbyFVt1UQGUq29vKc3rLFVjckk4rusdapYlpXTz2UsL2zlQyQmsAlKkSStJXE-OL8OeSgMk4enIWO8fLHO1Z3vVot9w_N_LAwb4D9-F94Y2kLGfrlcOZxBtQ4cJKK7jvAQYyklWyZwTLyiiRCY0509Uvvs1q9z47te_Krmw4mY4TZJHgIZ6VqXCUu7nJNMILMi3af2VogsUIqZUQzG5uauSQw4uLwZIilQs3NxQbEqmYLq30a9o716bW6Dc8WKnyRsPfcGhrBkgwCOfwDgZbUIpVxCii7t3a9ngl-5osTS31mbOkq16bPC6jbIoev2qnMgL3eDsq_Ng3CThnNqsQIPrkr7QG4npGKXobZN8p4ot0U7zYW_Jnxc-0HMUsmmz2bvI8qJbKWrWZ2HAUW8HWPYubJO_npSDWqTJC5_AUQpdDqwhGY6oNbkfnKVyFOOi6Xl-bXURGWiGV1y0EeI9a36zFAM8L1Z-TKk-EYkkfDiUUPb5-Vi2yXtq7fk0mSjw1H6csuPxeRoJnsFExUoJT8OI48zLjKaUsEJ1qD7yteKZAX-Qn5st9NW8VyKwfJLB1lfA7WIwc6-yqwrloPQ3DxhrQEqtWDXO2lqox_W3A992geP9KbQg4w1PczsgfF9AbKbCMh5_4f0ODZPc9r2DHsnKoHaePZSG0i1QOMAqmroCnn-jdkQEE3iEVIiT4zFou0xrgEaCyzS4CYaSNloROUjjv3sqnGOwvnJWwAtB387iBFjW72WwCf63RURvVvUCE0szzwn8PZk9YX48dX63FILeahZ_PTSdbr1yj6gSeM6Bn5SslhHzh_DjD7fKQTOVrs8uFZ80fIoNUySLuGXoSe12kZTCpJaLACBLypXGyZpFvAuVeTsUke21oWYyskjZ0Xzb07bb_vTJyt_iWm8pyfFnQ9kz9wrF6mElKktpgPnop-6N1wj8ud3eQ1LaHVJfTd6v_cjLCo5tDP3JhaJei375jViecF0mNVMkcSQWLSUlUKmO1597EXVsyvk5GLT-Kw8sJMo8XeLqsRvDuQKqgpG6tlcl8GwONPWnHxrdbci9J18SZdtBhq1-eUdtaBO_sNxdbiRzrhFAYaVJlEmG2qpARMMatyazgolJ9gzFGVwU-RDIcskbFuOi719rxB6Fep22oBQDKz9ZzdQ0TbY7fNshIODmwCUkDI3NXJ3gq_RqiCnCAt0Fa2TuuI5K3650pKGwl48mSy-mv2gbe-54_eAB9uoAJzP1JeylvWx3UObW3ObbkRHqJYW8qiwP0CKafiAxjb3Hgg2pOtLxcPekOq7xUvwdAxVwWEeDb91KXTCoMnTTdwI0ZidDxRU6I18Vgj2OIdFV2tw_XY1NgTZW0Ipm2ay9aXqwEiD8gUly80Yu1gTbNFjNs-77mPnzPr0Ga4vlfb-9uheAIYhN7lXjpRgwZZshmaG9MnN3RZ5xav_C00OykJPOMsJg-MDrY6m8KYz_npJzJCcGSFH2lEWdzYWMuoi9xG59qjjB_TMrg97k8LTt8SYEiWzJ2ekAVR9fpKEEq6GZ1cpEukH0EGjntJqIaWOCsjAKL6gtMgCQ-LTpwjleJ28xJg7cnDH-7QsEvllAEJJuz4jsocJ8FSQCwtsAgaVdz0MUaY0KTYfO00D4bh9gZKEKDDov5P9AwhNAObF2ej4Sy4Au3sYwj51iFNsA4b_qXihxXrmfgi33ub2BRJznSZiawwNnhryCxfyJVNeMXRk4j3vxG-oWZE_wKmW2vb_dPQNmEt0aA3Bc42Dq9VVfqv3dgotGPxlbsAM9BCS2EzdqN3BSC0p861dnzVDc-wSdW6cCSQc8--BAf8C3RQLju6wMxWfBwwPsLyU7TywCbMRlIRIv2nPPO7XasLwmg-IQ8sEPLLErmRw656IRD2sMrB7qoUPU31k3Lwu6tGw4TPbbMdx8DB3secVFYDLbnZRSWYrgzb9snUNHlpFQsYg-99qUOyODAvDf06VC0Evjg85wThXI-Ha9WAhW0ZTM2C6CC6dVtrygVUe12kJ3XYIhldyasWvhgKHY--68q3-LsNtHIQWh8TRDgtw6-VBHqekPPfxklbVbJi06LmvwLncPz6nXmvVQ_lmXDMWzgTgWt87E25tPXj0aBabe5DpSDO6E4azCrns__3KqGSmtUNhmINmk3ntTxoNm28qnvXZQquEePPHdOdveyQNLtFoOay8puZEzhZi2AccJyuEgYLeA_iJm5W3vKPKSC3taEC2rEbE0rRZw6WW9UP9WqAJXuDxggTQ8TNmYlyNNzHuAZltO-PmZTp2dq4p4SoO_sA2gblWDmmmoyOybOt17pid3bdf098eCKC2BuOc5BbDTQszh04AvKtC3Q8bN5EcYFS2SLao4h6ZZML1q8MeRXaRj73Tw10wxJIgR4wQOL7lrE6yncUwv2ZK3hO4YfegBfTpXd8u7Hh69N7jCm1yTvl1wBp6olBVL096h_lAvTrMoBXhCqioG16NPXflIdMMJYMwVNxeEIk7y8nnRLZ9RKv-FHRbI3CfkxqxGz2ATTz6vsWTVLQjHno_RpbiMn9mhD6LF5c3CpwaOsWTAmJYbeIsdZrnGZeF0ssvHoWKZpexaP6ZXu9ORxYiFfr_GLrJeIDlJm4aORkQBqXXmgOcKmmvRrG2OyS3AQuFMZTB85LxhRjpKRz4jZEsz2g861lORvos3HNvCZDZ8iEY3sWG6c2NxS_uY_1klaFRm6E-A_cNOt-MwvQj4hEEjRjTieIubtFamfqeJTk0oMWqslS4DUBmT0_ur3J3kJBDaCEDQvLo0w2ndcW4tclms5-QFzRjmuS5u8_4rxiFWGjANdtJ0miUg8fHSygClClrU-CD_R-UV-qbsyKP9ppdkMPCn8EYz6YyOt0TLBpdD8VJPEh7p5Qebk1ZODpvug0_9Liv5YJj6eSmJgqI3I2ya_TBmgkX98J99o-LQDRiYJaeE-hngcaqc-LwYt-eKiexJXB63I3YGib2oAFdzfFdyzJdN2Bor8GOs3w54Eb8P3zIsj5D2odu_kMHBUP65qXbHp3rV4J79xXNNrqLnhvddOzn40-cJNZy0x9n1GtOIZ3YBozye3fx7LV2DtanKJNh4wjwyFl6bekjFKU6-EpdKGhsnBAITkfY_MqKa4meraevilQlAF3N5ID4JObESPhAN6g88YbCiXgMIS-8DOCDAHXSpRVzau4kcxCYAFLdFpcSFXJXxy71fHvCC6ATLITMAwHa2tmKk47dzpO59iOKqdx0HmeNb2kuyhrTgjeT1V-ac3SPkwJiJIZQDXBVlVQE-2Q5Hd2xzEuRFXlW0DP_ljpgSN7sumlGj-Yxnxmj-m_gZXR6whX7YheN1a0_MpZ00aJQiOA4TrnBy-2cXcMsNbW7awzRfZ6578Nera8CVcZFJ_HXO-X1WK6EEY3z5DExF2_agcWtV-DpIoKkNnCVg_p5lyDNdgp3MokDG4ac39jEBfQMrpmMCoC6Tw_vQtNG3z0jSUCk9qvCo2Rneb-rhS4zhU8YsH5emBNOzyNuxgT6ekbl1YJX_b0ByNLC83n3IcUCs0SgXK4l_DOgIZa0mZQQ3q_cY689-kIlueF2Ar0ek8qJDIPqjq96hnNcr2jeHhnOLhIadDSwqqGmoLTWX5tOS3fcwGmLJEuAKWFMEWX_5ICxMzPKsHp0qZ68S0ONNAKiMxkni7FYaXTks4L0ZZ81VbSkhuq9xWOifYYL4Ib9pv1p8n-Jdn1vrXXW3jKiCdea8iWcqX3AVT3Ljv8KrrB0aVhz0Mv2ljqMIkg5xSH5zEbPlQyY4FSxYXFHSBqNWOSiw10JMnS38q_it-8rQkEJYrr_qTzxkDnVmLH_6osDS6GWQq5a14YoPiw4XkeJ1dQYpSPEXuoFfxIpgDUpiHRHidrT3dTKbTOoiIr83k_NgwXxGC6vLPbqS5GlwW3b1RgjjwDuuV_Rh78MXpu4UE46KEH8ugFyY4YiNSfeanG0yj0ADIPMZK7QuTgqeKOeaKfEO8N0uP3hf4bCOnAzoRTqE2zbtBl-5qYJpW2g6-nfcE2t5A_nkO89tkj0NAxnIJsqB0PxAQxQKE6D6TO0ADk1IbX43WxOTyvFgl92NwsavOHJ6QgezfP1wE7kfTNu0TQOPhVa_uuX6Zv9Pi5bew93ZnNegAJhTX-onHlK-W5b7v56DC7AD4JT0B1McThDW_M0JYflTbY8Eq6jgP-AFowdtDN5hSLRQ-fsyA76mglDSU0xZGtJHhuCNsV2n5zvyIfhPNC0wLqjaJkA3RPRUFYKy8mzwsqLDPlN4zD8-opDoDklo1aR7H52irmbGFJFUmSE3FUwIO16afsU-fQljubLEnw7wNESTm9LYJ9P3no3o30VZ_nx8aWPRctlcScXaC6QoZjssnYNhnxAUwecGfl-paK77ES_2l8wSTwX9eZ25adwaK-H6f3uXcEUZ1RO8xN6L_JMluOXaXvvVVf60vcQYZTAJAYAL0_NeTWp0GCu33NKv4TdjVp_xsFa0VI1xJc1WoDm1R9jSLLv2oeo="}}
{"timestamp":"2026-02-11T04:28:02.307Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"python3 - <<'PY'\\nimport itertools\\nC=[(-3,-1),(-3,3),(-2,0),(-2,2),(0,0),(0,2),(1,-1),(1,3)]\\nCset=set(C)\\nS=[(-2,-1),(-2,1),(-1,-2),(-1,2),(1,-2),(1,2),(2,-1),(2,1)]\\nsy=[lambda x,y:(x,y),lambda x,y:(-x,y),lambda x,y:(x,-y),lambda x,y:(-x,-y),\\n    lambda x,y:(y,x),lambda x,y:(-y,x),lambda x,y:(y,-x),lambda x,y:(-y,-x)]\\n\\ndef canon(P):\\n    best=None\\n    for f in sy:\\n        T=[f(x,y) for x,y in P]\\n        mn=min(T)\\n        t=tuple(sorted((x-mn[0],y-mn[1]) for x,y in T))\\n        if best is None or t<best: best=t\\n    return best\\ncC=canon(C)\\n\\n# all 4-tuples maybe with repetition? use combinations with replacement maybe\\nfor U in itertools.product(S, repeat=4):\\n    # generate even parity sums\\n    even=[];odd=[]\\n    for mask in range(16):\\n        x=y=0\\n        bits=0\\n        for i in range(4):\\n            if mask>>i &1:\\n                x+=U[i][0];y+=U[i][1];bits^=1\\n        (odd if bits else even).append((x,y))\\n    # unique counts\\n    if len(set(even))!=8 or len(set(odd))!=8: \\n        continue\\n    if canon(even)==cC:\\n        print('found U',U)\\n        break\\nelse:\\n    print('none')\\nPY\"}","call_id":"call_j2GQR6amLvsDHNzGWZlrypLg"}}
{"timestamp":"2026-02-11T04:28:02.324Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":2238204,"cached_input_tokens":2131840,"output_tokens":44606,"reasoning_output_tokens":29556,"total_tokens":2282810},"last_token_usage":{"input_tokens":60552,"cached_input_tokens":41728,"output_tokens":1420,"reasoning_output_tokens":964,"total_tokens":61972},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":10.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:28:02.903Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_j2GQR6amLvsDHNzGWZlrypLg","output":"Chunk ID: 8d7c1a\nWall time: 0.4411 seconds\nProcess exited with code 0\nOriginal token count: 12\nOutput:\nfound U ((-2, -1), (-2, 1), (-1, -2), (1, -2))\n"}}
{"timestamp":"2026-02-11T04:28:02.936Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:28:03.302Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":2238204,"cached_input_tokens":2131840,"output_tokens":44606,"reasoning_output_tokens":29556,"total_tokens":2282810},"last_token_usage":{"input_tokens":60552,"cached_input_tokens":41728,"output_tokens":1420,"reasoning_output_tokens":964,"total_tokens":61972},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":10.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:28:10.731Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Verifying subset-sum norm properties**"}}
{"timestamp":"2026-02-11T04:28:10.731Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Verifying subset-sum norm properties**"}],"content":null,"encrypted_content":"gAAAAABpjAVaz-aeHVW1E2_9hQlbR0UcX4aNAYPhuYsv7GhntcG-km6jfaX85NY70nu_J48ufpV-lCIIEdw3AN0Tr4nNdyjlS9rPBvdyVdARL6lP5UqxTkDPmvNOZOuZ5oU9B8cHfwTgxF_sbV6UL7BJ_ktmTX5OccUa9o1sED6z6PA5mIPmTziCPw1oUv31PizsR67WBSWddJFCa6jJr8iJB1ddrHpuXOMK8FdBexqNQxKtA_kWBhRiS8DSwHOl1CLuPxBp9r6-kxmsWpWV3tUUnMAxSWe4l6sIskc8b0cbWIJLNujHi1WZ62FHZ0oX713tmn7Ji4cMMUAfIryszTexfSPQE7Icphj1zqPbxmRzgL_5pCKRQ0YYKcxzlN1In6d1V5zWpIuSKbq0lOdCNllow2i0Yf3NcMIpfft9jYf5YxuuEKc27ItpPDz-N0hpLLOrf2ZqsBDJFSK3QbKSJIgbqNb9_TMjhM2gA5iCHk15kwanm8e9nYqRIMQCChmDNBsTlMytl2Gxw6eXhedJ19fUj1F42RjoFjhNKDw9iPaTJ87UtjfPPGiin7w1Rg4DO4jaTYxzE570RESvEO4j1oLVVkS6hiw9Y4W4txZAHpatRsJEbWH3566lzaIWexMOjcglUfxPOb9IV-FibmATX_7XfjBOIQDDJPhICFdgb0fIuc6kFwEtRkT0Jdqr2AsEx-VrSqDYsYuGNylsZzGfb8FHBpoTrPRqGX2Rmw9pkrGhOlPISaElPHUcUBRPYDQF5mo28LvUpN3QHK_WqNEBFQBvkWeYRO8OtsKOUjmoE9J1TJmukVLKyNDg7N8kFjjXpXEhe1o6xwFQsHjO0lHSUnv_Fsrj4JV4JMJIsQwxoKW3R1CK1UHZLKcQVgSJHOQbbAwm5HVVBZ0oX-W2a3-tAwGsV0hcSdfTcaZJnbh_ogKwnLpHXcrwpjXjZ-7mWgXhnYV6VuUC1nTL1gUfA3dPnht7uFiINaiQIQ6nkm6W9-x7WBnXuAK-ndBS-yRS_sQAd41OkpOPkP3CUUx-fWh5WRarhq7VZbFW-qxfJms0-gWMi2aw3f9_0J1u3-SyFDRMg4c-Ig5sbEK0oEirfevUOgfn7qrOFC420Qii7-cECxjPK9LwbuMF9C5LFuuU6JF_4Ii3xgNiz70_N2bGRjv99SCR1M2DANInjhyi2SKAUgJDgm_sGdWP0jt7pepcrOEP68igny0y0M3QeDqqKt3syq1QdOhjLTxepImvkON_klATZdX0SKEcV8IhJkSnmGNBDYzAEjSefk2TjMcgykE25Z6lQiYIdYqgEFD5kXpZya9OcroCSzSN7KR2_fZEiyDgSTIIWxSeiwsZYZpNqKWVgLLUHCy_T5OaRTHfQfit4_wn01cN8He2WtiyZKJ5ePJxorp_llRPbHZNvVvdRhw_F_wLUWC3Go3NsXzDTg100jH7lAvMqADHnRMyaKiLdfGzViWegi9Hwi6UwjDwO5DHYXamJAdtKVMoLvVwhaadr0-yWT8-afNOPCMtfxbBMDVBZFiX4cRo2yLxds45N_nqk58i3BH_cRsFHfbThXiLgFXSV2KGJXqfZMQs43i1RVyCsHrIB7NDLuvRrkLErcp0YnXjJvWThROfzHmF8SkWnzXgOYsxy-G0dHCXXUnCB63XwbdWCq1bkWjU-K-eIDYtbc3xCOshWwIrZsc6XsZLasxhI5Qxke3vJsVKbaY6Rz9y7dMwiFCF9ZhoLb-GD8bn5Pz8JsY3v27pkQAyv5PsYHJHKk8qTH8vfDtPV7W6i7QWQY0hWYZX0NfMU1HLb24mxUMDAaqulYIPQBIMfSEBnGzmWlI6Ss-JU5c9W-TPM8bXhLG21DU1mRcFOnsYBypBCSsTB7LGLbnM_7mixjXvOxhx70goLV8Y_1rtNaWT-I2WD4d2JhYKr4u7xTMekBZBFmqJqYGCnmN7cGIk-i09D46uIfb7JDLFjHV0pGexEeSODDTW4i4f1LqClnl-O5Ii4CjgPxlGe1mbkg7J_QRA_TmAMkRDXxXN3Kfotk9OzL5lW3LLcz0Eq_BmsZitz7CAytUYY1z3BLbauBTqsiaSMa8KlIWFnPbluR4kJBTz27Sq9SopxjldGrAfifhcMRujeVKj-SYNEWJiOK0-qgLk9DNro008D9Y4eY0LJKPZ_o07yhRQeC4rEUEIFs6GQxnVYe91QJ6shzrpT_a1Sm1nw2oxe67nWfLR8mchNWVUVYhQz4soZGaOJfOVivff-2cvDxPn7LSGROu-OgSB9WUfUaVKJcgHGdit6VGjM7uETvg388F5gZ3CPOzw0qMcHXzrQQfDE-nBbf1z3YHa0QvPvLQByOoJnbEJWoqagHZLUkVlpfbMVhg8YDbK_DJnhevzqwLjRouK21jstR7K8Aesr5G2_K9BNMP6x_X-3y8pYmfPEUj4wn12PVqsi8hgOjr2dxVEi9Ja6wgjxlhwRWbwABJhc_drv7MEsADOoLOdnN6DYHwe_1OLE4gBJScbl2E2AElL6wv84Tltyx-goezdizjLUhFc8M-sJP1-s0PuG9YrpxEFFHug0AbqmBv38fcsUMibVkLcGSMCUI3QyLRW1YEiVQCm-NcWfeB7VPrVzOrgzHBkZCsfjOnl2v3PHXpcnRhg1xDnFsHTQQ=="}}
{"timestamp":"2026-02-11T04:28:15.901Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"python3 - <<'PY'\\nU=[(-2,-1),(-2,1),(-1,-2),(1,-2)]\\npts=[]\\nfor mask in range(16):\\n    x=y=0\\n    for i,(a,b) in enumerate(U):\\n        if mask>>i &1:\\n            x+=a;y+=b\\n    pts.append((x,y))\\nC=[pts[m] for m in range(16) if bin(m).count('1')%2==0]\\nH=[pts[m] for m in range(16) if bin(m).count('1')%2==1]\\nm=5\\n# counts\\nimport itertools\\nextra=0\\nfor i,c in enumerate(C):\\n    for j,h in enumerate(H):\\n        if (h[0]-c[0])**2+(h[1]-c[1])**2==m:\\n            # check hamming dist\\n            me=[k for k,p in enumerate(C) if p==c][0]\\n            # not direct mapping index lost; recompute masks\\n            pass\\nprint('C',C)\\nprint('H',H)\\n# build mask mapping\\nmask_to_pt={mask:pts[mask] for mask in range(16)}\\npt_to_mask={v:k for k,v in mask_to_pt.items()}\\nfor c in C:\\n    cm=pt_to_mask[c]\\n    neigh=[]\\n    for h in H:\\n        if (h[0]-c[0])**2+(h[1]-c[1])**2==m:\\n            hm=pt_to_mask[h]\\n            d=(cm^hm).bit_count()\\n            neigh.append((h,hm,d))\\n    print(c,'deg',len(neigh),'dists',sorted(set(d for _,_,d in neigh)))\\nPY\"}","call_id":"call_J5ATgBUK0kgvsKniwHnETK4R"}}
{"timestamp":"2026-02-11T04:28:15.923Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":2300251,"cached_input_tokens":2193792,"output_tokens":45383,"reasoning_output_tokens":29904,"total_tokens":2345634},"last_token_usage":{"input_tokens":62047,"cached_input_tokens":61952,"output_tokens":777,"reasoning_output_tokens":348,"total_tokens":62824},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":10.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:28:16.511Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_J5ATgBUK0kgvsKniwHnETK4R","output":"Chunk ID: 98202d\nWall time: 0.4563 seconds\nProcess exited with code 0\nOriginal token count: 89\nOutput:\nC [(0, 0), (-4, 0), (-3, -3), (-3, -1), (-1, -3), (-1, -1), (0, -4), (-4, -4)]\nH [(-2, -1), (-2, 1), (-1, -2), (-5, -2), (1, -2), (-3, -2), (-2, -5), (-2, -3)]\n(0, 0) deg 4 dists [1]\n(-4, 0) deg 4 dists [1]\n(-3, -3) deg 4 dists [1]\n(-3, -1) deg 4 dists [1]\n(-1, -3) deg 4 dists [1]\n(-1, -1) deg 4 dists [1]\n(0, -4) deg 4 dists [1]\n(-4, -4) deg 4 dists [1]\n"}}
{"timestamp":"2026-02-11T04:28:16.543Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:28:16.881Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":2300251,"cached_input_tokens":2193792,"output_tokens":45383,"reasoning_output_tokens":29904,"total_tokens":2345634},"last_token_usage":{"input_tokens":62047,"cached_input_tokens":61952,"output_tokens":777,"reasoning_output_tokens":348,"total_tokens":62824},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":10.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:28:52.658Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Analyzing vector subset norms for construction**"}}
{"timestamp":"2026-02-11T04:28:52.658Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Analyzing vector subset norms for construction**"}],"content":null,"encrypted_content":"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"}}
{"timestamp":"2026-02-11T04:29:01.682Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"python3 - <<'PY'\\nimport math,itertools\\n\\ndef vectors(m):\\n    lim=math.isqrt(m)\\n    S=[]\\n    for x in range(-lim,lim+1):\\n        y2=m-x*x\\n        if y2<0: continue\\n        y=math.isqrt(y2)\\n        if y*y==y2:\\n            S.append((x,y));\\n            if y:S.append((x,-y))\\n    return list(dict.fromkeys(S))\\n\\ndef choose_half(S):\\n    # pick one from each opposite pair using lex sign rule\\n    used=set();U=[]\\n    for v in sorted(S):\\n        if v in used: continue\\n        w=(-v[0],-v[1])\\n        used.add(v);used.add(w)\\n        # choose representative with (x>0) or (x==0 and y>0), else opposite\\n        if v[0]>0 or (v[0]==0 and v[1]>0):\\n            U.append(v)\\n        else:\\n            U.append(w)\\n    return U\\n\\ndef build(U):\\n    k=len(U)\\n    C=[];H=[]\\n    for mask in range(1<<k):\\n        x=y=0\\n        bits=0\\n        for i,(a,b) in enumerate(U):\\n            if mask>>i &1:\\n                x+=a;y+=b;bits^=1\\n        (H if bits else C).append((x,y))\\n    return C,H\\n\\ndef check(m,C):\\n    # full consonant/perfect check\\n    S=vectors(m);Sset=set(S)\\n    n=len(C)\\n    H=set();edges=[]\\n    for i in range(n):\\n        x1,y1=C[i]\\n        for j in range(i+1,n):\\n            x2,y2=C[j]\\n            pts=[]\\n            for vx,vy in S:\\n                p=(x1+vx,y1+vy)\\n                if (p[0]-x2,p[1]-y2) in Sset:\\n                    pts.append(p)\\n            pts=list(dict.fromkeys(pts))\\n            if len(pts)==1:\\n                return False,None,None\\n            if len(pts)==2:\\n                edges.append((i,j));H.update(pts)\\n    # connectivity\\n    g=[[] for _ in range(n)]\\n    for i,j in edges:g[i].append(j);g[j].append(i)\\n    vis={0};st=[0]\\n    while st:\\n        u=st.pop()\\n        for v in g[u]:\\n            if v not in vis:vis.add(v);st.append(v)\\n    return len(vis)==n and len(H)==n,len(H),len(edges)\\n\\nfor m in [5,10,13,25,50,65,85,125,130,145,169,170,221,250,260,265,289,290,325]:\\n    S=vectors(m)\\n    if not S: continue\\n    U=choose_half(S)\\n    C,H=build(U)\\n    ok,h,e=check(m,C)\\n    print('m',m,'r2',len(S),'k',len(U),'n',len(C),'ok',ok,'H',h,'E',e)\\nPY\"}","call_id":"call_hpAp6htJ5BZzQ9lhseVphwDR"}}
{"timestamp":"2026-02-11T04:29:01.720Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":2363330,"cached_input_tokens":2255616,"output_tokens":47851,"reasoning_output_tokens":31598,"total_tokens":2411181},"last_token_usage":{"input_tokens":63079,"cached_input_tokens":61824,"output_tokens":2468,"reasoning_output_tokens":1694,"total_tokens":65547},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":10.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:29:02.451Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_hpAp6htJ5BZzQ9lhseVphwDR","output":"Chunk ID: 0de744\nWall time: 0.6127 seconds\nProcess exited with code 0\nOriginal token count: 201\nOutput:\nm 5 r2 8 k 4 n 8 ok False H 12 E 26\nm 10 r2 8 k 4 n 8 ok True H 8 E 24\nm 13 r2 8 k 4 n 8 ok True H 8 E 24\nm 25 r2 12 k 6 n 32 ok False H 50 E 249\nm 50 r2 12 k 6 n 32 ok False H 50 E 249\nm 65 r2 16 k 8 n 128 ok False H None E None\nm 85 r2 16 k 8 n 128 ok False H None E None\nm 125 r2 16 k 8 n 128 ok False H 252 E 1854\nm 130 r2 16 k 8 n 128 ok False H None E None\nm 145 r2 16 k 8 n 128 ok False H None E None\nm 169 r2 12 k 6 n 32 ok True H 32 E 240\nm 170 r2 16 k 8 n 128 ok False H None E None\nm 221 r2 16 k 8 n 128 ok False H 196 E 1826\nm 250 r2 16 k 8 n 128 ok False H 252 E 1854\nm 260 r2 16 k 8 n 128 ok False H None E None\nm 265 r2 16 k 8 n 128 ok False H 196 E 1826\nm 289 r2 12 k 6 n 32 ok True H 32 E 240\nm 290 r2 16 k 8 n 128 ok False H None E None\nm 325 r2 24 k 12 n 2048 ok False H None E None\n"}}
{"timestamp":"2026-02-11T04:29:02.481Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:29:02.860Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":2363330,"cached_input_tokens":2255616,"output_tokens":47851,"reasoning_output_tokens":31598,"total_tokens":2411181},"last_token_usage":{"input_tokens":63079,"cached_input_tokens":61824,"output_tokens":2468,"reasoning_output_tokens":1694,"total_tokens":65547},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":10.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:29:49.265Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Analyzing orientation impact on hypercube construction**"}}
{"timestamp":"2026-02-11T04:29:49.266Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Analyzing orientation impact on hypercube 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2Tc2YU-_kc-DSvahuldgjE-eAZV06YeW5b2Es7IfHklFgryuFwJMtEj_NYHz2pQi6K_LhCpGZk6-90Q3cvs2yqjDw8e9rrlAwO-P-5orefSY1BrbbrgACunYOqeR0LPk4ZvqQl1tOIxR38S0cdZTXRcJbJc-wD8002Y0Z3S1n8tS9hKmrWzDIkPbJ34vklY4zrup1e3DZnTQtMGP-DjqVs5QHpiV-FZkkcvwkZxwenoIgEkSqxOW8R-42VWmGlRBnGvSKZH4sE7mCzsrkolWCh8cvmyBtg1yMfGZqlVRRD0DPDxaRJqsMHxnOQLhndyEEha74KEOCfKP5L7j3dp4gVzXGqQgl39HF2Wi06WVUChAVRT2x3_6cKvc14UMGwJUq8iSAQgbDVfj49Dw5X8YgBtOFbst44SER_xJtNqVgKKCa1FMzm4FIBbMCP3AKUUDOKonJ-ZmiFR-wtLnwVSxLiTe-zUs1PqaWN7OxGtYAFjdsTeA9Lv84JF3gIOc0sgQTIuAXd64p2O2PsmLSmqdjQJcXqdRQ7FuiuMmcbO5rSsB4VgNhgqJmPhNCBf70yrO8__FFuGGL_y7A1Il-6IwYrJAtkwEKInPRbANZSTcZsEcPGoXchiRuW4WPyQMTCc473TTK0OfEr-8mHzRXinLtPkGAi0jjo09olq36ixNq7qOmkoZJWZ-BzUHHlz2XW51XmaIzDssjJK3i3oGJkIAcSIUD_Tlfn_6yzYvMVG9_Vrnd-VAfln4kkrcHg7sqqmNnccKlDbQE_IhQeLZ2PyyQhqXdXQ4TQdwv2dgJPnt33H3fBFV4Zqum3TczCmNcOG6hha5QeyZqY9Y40TXSVbXVGdJmORdUgmRZe1gnxAU955-Xw3UUT1QBTJ_EA2Yvc_v-5fDzwhH38BSNQAAzrPO4H6ofH_-qNsuqVGQOuhlghvp_HGc3DJ3q4lNSWrJH-hh76oqCE0YT70hMsjTI-xFSqanXIAy9JeNkVTmgFRJiiDcogvvNA3H7wIwCvt8TmKNS7auvO-ED4DFAwzHN6BVEwN7rVsIKWDQq5WFbZnAQ0LCbFfB8n5wiw2qgkEYf47A4AuHIfVFZSumbhlq6_MExNAiXUYx-PWaxxdQs8Vk-F_QSfvdctpr5UhB8DrKKwmzISEuokf8sJA7lUFCDc7ds_BVuzAwJ3jRTC0fkG2_JicIHYQzBzOJj6wAok8zQPf0PkkRIH64yvGSZ9hxqk9jB9zx3T041xTvEVkslOtL4M_FaRZ3pnJqaZBtBsohKDSbiFEIzJoHDkCBgsSXeB7oRDdYQEYq-PZct_zsxSJ_XC5qxrRAB5RNEo67Vwf8aMmhymY0S8FjFM127HSbCHPEQQzp4F7eH9Op70eFJzsznrK6XUjUyIy58g59Ur9m1ugb6Z2x2IImYmJGV1M95u7Pxpb67AA81Ih-hOYdtAebGk6FCBWSASN-iM4B2hMBPPmRpyykT-oYms_s-cTVSFGThXpbc0VIBBYGa5SJCWpLgqEFDysBfybT17oaveqejxUOtQyV5epDyoFKWwow_z44bX8QEvx9GLPrdI5G7-0oZctl_PAlvIPvN3KInv9dPU4ePslxNQVI4Hc346yTirzL-enEnSz2apkpTBMPHbyDJbw_w6Ireyq4cBsbtFP2UrkUJwk1bAoQjwVM4EjVg4Ue-H7hmedsUcSUs7a1hbsHmoXOIJBBMda_HX5xJ1NSvLCkSOA8dtEO_pEhlbZMCssDFcxlibO-8l3cGC2VSJCf6Rx9DEuuRlxh-ACM4OX4vW1RiqdjZ0JawfWqDPlbRd2347GpDGbE7U1noGMcx8o42XdKQS2rerns53-1fntv0e43haA_QxERKHewoklUfZt_s4DhAJnYJDCTlSaMi4xsxaO0jFtXoiTTXnU6LH2ph6BUojc9WMifs-sBi0bdJXAVOIyrDJEf4vajNqgprsRjYiU4eDBBqHrbqrjsk9_SChLL1jCdQVP5MEb0UfprAxw9t9AGdt39KdMcmAieigxq4U7V_V9JFuSRXc9O6ZDadGGOYcTSqhXuBIBFtw_nHU8TPpxJkoTqgssmzDOL9uOlAu3kkjdckGQpVlMHdIUIxecYDRAljH2YA7CwUcQNwrAqCk0A-XeXip23kHpCrsH7P7RevFDpS-taMDyVbsHqX17-g_a7o6_lKUfSCVD7S-JcSJrM3NC6OHj5SyfobEhFeaqze-QqkX3FAZJvaVXkErspGJEmlvyWporRaXK-wT0aHj7R1p2FW7avBtESllt786_Y4gukvqn5ihhjclneaJai-hruHvJhwAeq4Ld1PXpma3vC5vjeSsIXzAn635gKl-XKp5ngkcpp4SJsqgVlCMMHT8j5B8YQ7i2sJVkk-43otwFGiCqfYb5x9m63-lEdB8uIFymUHBgPD3h8CY846EI-dDNXhKP5IMtOq4HFmEf28nWkfc3XhPiyVRu6drmqouf4xqcVzeG4TwxCpejH1-X6m9MjIJ5e6F3HVYFqd3TkCcVhYK0Lmm8WooHnK51KWn0hx_SVvfN8-qo0wJJ2DHR_wzfLHDq6z2wDMZIQfoAF0A1JmDT5gcJ_B02Ffdw1buDshtMMQCA-SW253BdwA6VtRYDh_D9xzL5KFUIrLtj-3_iuTISTqToBhEGCFaZGdZ6VW18-ePWZCBasTUKY7wNhhDQTf9BoNErqotx06IhCZTld1a5J7Qn-lBUV8SmrWDbwOCP7vqfT6CJBBC4qKyX7yKYMgohLcvVO5gaBNsgKowg8qOlpMqyFIS2Z6nAfYYs0OXMCxNVJ18q6irGXdjMtQknY-hTHQzVpU1PnT_TVXQNoQlVA7x30OPKcuHLn6N-Q7ts5_lNUXqZs-IgOag7qoUJPp6gCoZf00WHSjjUun_tx05zkPbeYOTDbAVrn3wlIW2DqvIy2NgGvohhOP6TvzjoLNI3Y-FYZ2n4ziYOu8YwDcjG2R7gn6EjM8thXnVUSZtlQh1YqLNY0kh2NzDvvfwq2_4aHHJHae02Lc-f_C1y-sR5YDuZAO6n5pbhYl5Ti-Fxis7ZnS94MqUrg7qAsvu14559S-dCY09dVeAE-Xso43FIsAJ_9b0vh50kj8OPLEMRYl5wjISU5PoKxSRuc43_pT0OBZf7uaiE5fj_c8QGNqOYNaC2ncvwFaSWscQP2AGY178qkU1OIfzfKvQKF1tRfLiROvh9ip4qn-90JFLd_jHRojdWaBVtJ26ciSaxr_dTUHQLi---fs6ZfKIZvE6rpS0QQ4zofKsObKJxkdNRJAdQE5iCRnoazkJ5HiK5jzJ7DYekMzZGhmUr6_7g1rZjr6FILAFNC3hoBWKiVmGAQ_q299sQf7KgGNbAqUgUdOn0G7vkDosHjl4qQqxFbsJwr599QO82ZIoejaxpDOxm2gpcwspLxG-_fdKXuPZcPcUnO6VKIWWq4KgjdWk7Ns6DZbcgKIRFQo1felCt7OEoekjjCzfVJXd9jomn7ta3-VJ6uPYPkXKmIRs0_SicVUDXo7QE4f5pepCZrNMXnQT3gw5lCQtX1TAla02mTEJWOl48D1XhTCdx7v5v60OgeQQtzZHW2a33mSP5w9k_SunF0jArVMi5QXBHHCqUFF9dmdW7eX4LdGl4fzXpronP_Y0vRYgitCzYJB9q5mx0IdIIGQKsGRQkgtT9lhN35e1E-dcIcMGFP8zDe4nSV6WQuAU3gkl5wMuOKuyldMtCv4tDozXZ9XauFXjgI0FG2O4aRqsozZe_q87XfFq8Jp-kVfFEc0lPGJR0a8jACh0XsYA9XK6StBzcRf4ff6TpS4R4hR-1RwNBBG_sBXoKD1ajuYnFsk2shw1WC3MciYy00VDLFznEwX3q0UceMAP4xLEkrjLDvOvNpmHxktWMvuUE3A4b8xruvMI2861KhUKe3vtikzc8PLE68aneJ-DzNH5MPndQjI4IN1g2vxVgn0y1a07sYQUjKHd6ZmFWvtPWTz_jw17Tirr9D4FcQZzD0FJvebcz7SVMq7xP2ZevRbJtRW-EUDCFgD1Lph5DCwK1MWDdTzDmyZLT0uWz9LqJtVvJrOFb6BcCl1ABUNWb1xnYDwgFio9I8_xuw9v9TED3zAeftWH5DZ5bbIANBxt_cS9C93CG9xLwFKyqknWn4TAk3YoAZ5m506hnkSl4mtAuiXpRBfrWxc-3LuzFXozqnOIyYYJhCUlVOhlZhnFpNN5pqRRWGRHRmx9_ISvMeT7i6jDnJ1w8k4iOoobwizl0n0V30lBGgARqNyIvWF7Vs1JjoyoTamvG2t47wpHV5IyStfbLpsjIA0W6_pchCDlnoJfGLRxqMB0puGBMnSXnqZNTjz6ibeLattfNoylLI9RLHMUmjgvads9ez5aDNhPt7SJh-kmRpDR1_0mXv-e_8rMNgv9OyHLm9VQHAGtUQBqHBAeUGHfZvsiOEmY67qC7DMm5q4o1JWvTO0lEm9TRFCtmntCzSOlA2JvPmz_SIdih1XyyQLDVkOJX9g7No9GqTmgLFGJhsRCkAZhUMfeypHOEHkrRfzidpD9n7626wfimo7iH5t2GRGvpEmXsH2CwYuhMYDV7X0lBFHARTFvIWC6diGLYMo9pSnTk6uPHGxjnAYqletQxOW5vH49-klUjsq8DEpK8qO8kC6ZYo9NbxCXMTRUd8hp7Fzx8y_Bi12jEnyKprJRllRP-7xQ3JGCxg8wqNM_v1CBI9pQSODEK3lfTG7I8GARsbhG07MuTozgBWish2z1OkBMH4KD-bb3AudSgGMtKu628ciP0_t02Pp44D1D3de0gviY8Ke8bIooJ4hQHwRP422tCBnX3AVoEt0Rv0NogvV_j4vr0MOwrry4GnZ0-sDzg15n4uLsrJI-dVIof5dQxAXeH97YDs7AtGNsjf-xIEV4eH6KXKRxWleevJc9BxrxI0UboBZ8Yvb-bWxVz_Zru8wQDSpM89kscnXgX-0EniWykG6a9Fn5UNBb2076IY2AC1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{"timestamp":"2026-02-11T04:29:58.253Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"python3 - <<'PY'\\nimport math,itertools\\n\\ndef vectors(m):\\n    lim=math.isqrt(m)\\n    S=[]\\n    for x in range(-lim,lim+1):\\n        y2=m-x*x\\n        if y2<0: continue\\n        y=math.isqrt(y2)\\n        if y*y==y2:\\n            S.append((x,y));\\n            if y:S.append((x,-y))\\n    return list(dict.fromkeys(S))\\n\\ndef pairings(S):\\n    Sset=set(S)\\n    P=[];used=set()\\n    for v in sorted(S):\\n        if v in used: continue\\n        w=(-v[0],-v[1])\\n        used.add(v);used.add(w)\\n        P.append((v,w))\\n    return P\\n\\ndef build(U):\\n    k=len(U)\\n    C=[];H=[]\\n    for mask in range(1<<k):\\n        x=y=0\\n        bits=0\\n        for i,(a,b) in enumerate(U):\\n            if mask>>i &1:\\n                x+=a;y+=b;bits^=1\\n        (H if bits else C).append((x,y))\\n    return C,H\\n\\ndef check(m,C):\\n    S=vectors(m);Sset=set(S)\\n    n=len(C)\\n    H=set();edges=[]\\n    # tangency check distances 4m\\n    for i in range(n):\\n        x1,y1=C[i]\\n        for j in range(i+1,n):\\n            x2,y2=C[j]\\n            d=(x2-x1)**2+(y2-y1)**2\\n            if d==4*m:\\n                return False,None,None\\n            pts=[]\\n            for vx,vy in S:\\n                p=(x1+vx,y1+vy)\\n                if (p[0]-x2,p[1]-y2) in Sset:\\n                    pts.append(p)\\n            pts=list(dict.fromkeys(pts))\\n            if len(pts)==2:\\n                edges.append((i,j));H.update(pts)\\n            elif len(pts)==1:\\n                return False,None,None\\n    # connected\\n    g=[[] for _ in range(n)]\\n    for i,j in edges:g[i].append(j);g[j].append(i)\\n    st=[0];vis={0}\\n    while st:\\n        u=st.pop()\\n        for v in g[u]:\\n            if v not in vis:vis.add(v);st.append(v)\\n    return len(vis)==n and len(H)==n,len(H),len(edges)\\n\\nm=25\\nS=vectors(m)\\nP=pairings(S)\\nprint('r2',len(S),'pairs',len(P))\\nbest=0;count=0\\nfor bits in range(1<<len(P)):\\n    U=[]\\n    for i,(a,b) in enumerate(P):\\n        U.append(a if (bits>>i)&1 else b)\\n    C,H=build(U)\\n    ok,h,e=check(m,C)\\n    if ok:\\n        print('FOUND bits',bits,'n',len(C),'edges',e)\\n        print('U',U)\\n        break\\n    if h is not None and h-len(C)<best:\\n        best=h-len(C)\\n        #print('improve',best,bits)\\nelse:\\n    print('none found')\\nPY\"}","call_id":"call_0VYKiLjkSVSwvaSQJtEUfH2t"}}
{"timestamp":"2026-02-11T04:29:58.256Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":2429329,"cached_input_tokens":2321024,"output_tokens":50820,"reasoning_output_tokens":33757,"total_tokens":2480149},"last_token_usage":{"input_tokens":65999,"cached_input_tokens":65408,"output_tokens":2969,"reasoning_output_tokens":2159,"total_tokens":68968},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":10.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:29:58.927Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_0VYKiLjkSVSwvaSQJtEUfH2t","output":"Chunk ID: dcb0c1\nWall time: 0.5187 seconds\nProcess exited with code 0\nOriginal token count: 7\nOutput:\nr2 12 pairs 6\nnone found\n"}}
{"timestamp":"2026-02-11T04:29:58.958Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:29:59.292Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":2429329,"cached_input_tokens":2321024,"output_tokens":50820,"reasoning_output_tokens":33757,"total_tokens":2480149},"last_token_usage":{"input_tokens":65999,"cached_input_tokens":65408,"output_tokens":2969,"reasoning_output_tokens":2159,"total_tokens":68968},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":10.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:30:21.656Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Formulating algebraic construction criteria**"}}
{"timestamp":"2026-02-11T04:30:21.656Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Formulating algebraic construction criteria**"}],"content":null,"encrypted_content":"gAAAAABpjAXdzgrUa2WdMs4w1JBh8GwGeaIdvOdKr-oR27zaEQ1E5L8ACgEHHnQuADkEpvLmsMM4XNGZYd635mXeYgyyA6aOOLM4a7gGd1FSJIuGI0AQG9kmfx2xPmW64dYZ7h0wC5rCpjuUAHQ8ljX9_83MuehoYBIGEqmWseP75NBGB_3I00h_r3SyXFu3pPMRzRSi33Zl5wqcY1Av8Z6mZZifA75LUCzrDEM8fKSyX0hO_FJDcjcoEH0Tgft96LKCwswvPpD5S4FTUHOEaJJC-zx5LH7PeL_IzLhvXrnVtAtcjFiXYVGuV3hike93Y0cfHySS9486nhR1EiRnF9IdoKoNauk-yRb9ld-AjXZeoBulC4JbMmf3h2dSUmfbMi39kRb2Kg2Nyr-z--1Bw0Wa3sGqrL1gn61Q3q7DDZ2t7_TQT-llnrXGr1Wanub2XAoF42CnxcBrJmj2Ej79m_sWF55YGmLVZrtXr1DLChKIwcl3sTLAoWMjBnHCEEA7mXamK_tFxK1cMDesCg1zrMMev6Ek6kmNPUN3Fb647tSlrC-aZOntTrO4XSMCV3Q1tJSiLEqkl6nhNQEljDCn5VNdRsQqn_XS1NaI6L8ogS-cKDNoDQ5IfYHbQjEkXoXhC3b5VTylMBPXXiyB7dCf2QjK2LvvWGlB8iY4Mokxbx9BEcDUUDZeiikS0l7GaUh75yP46fQbEehLOUAhprpK9zIgqlGbmB1sxBGNWkho6cqu_wMbaHOnIxwxn5fN-gStWgDb3oN3LW0kN_sycRokAUcv10A6Su2j40Bp6NE9p48krfGEyYNyXObFGox0fIeAooqJ4ZgwTuvm3AWORIrajvSI8N4EUuuZwin_Jsbl6txl1e-B2VW5anxGgeBDJ8tFVwrAvfSHYvuw0yKZXk9U2xgQDgDwPrX9qOJgEMk6L0s3z-7A469RL7puXkx3kd6ixJEXbbls_sMlnSAuZxb_WYhdt4ECWWNF1nqCnNOaG3MpLSZ05fxKZVroW2VsQjAFftEmycYfSSlU0_5yBU95CbgUgs5IBKQF1wYWyWKFQ_zeBGRQ0ZdHbNtbd-6y7QEhMZ9gJe1KA-OmipwDVnrQeBwfElNhRfG8dNZ-cmQ5uyKjAshP8hgzrgv85XZO_k4aO1K8eIFZc688Zynps4KRCM8xWzXzHCcGcURq2WxOGEUWBr4aP8QPMJNopGmVvnL0W_ZNqmcSFjvMMtNTL_Hf3A5bQHnzjHQJ0Gd61cTEX5xrwmXQN7dJ32PjGOXu9H0rl-7PFP_zaHVq7OoH06pqsqPB68d_9pSxI3LmcKdt4ypF-Hz5pNCtqWLzfXgQkNIj0hcRWg9Eb3R7tHsgny0Gi3coWhUSF-2ze7pctxxz_0IXuACvEjtHyJJcexbxUq9divVTDN6nVFU_dtG1fGzzhBLYh7HFC32N70Zy3NRrK_udo92VX-fhwGrVIsELRXVcNF2h24biKt69qR3XVL1rN8fHgH1bhu2g2HsrJof1h1RnaK8tvdT9XyPnmaw2MzIDnPgarCCt7oOpUrpSrwFqwm353td3rfUjb2_W9cbKikc8DF4LG_jvGFwwSuEkB_Fxo03Z21fExKf7A6q7l7B_ry1_g3_i5wjOgxhVK_Q9LL3TJQDL2NL6rBxDUZNYAD3M2V1QVL9jCrQflkvrFWAy_Pv9dUOBA3Ahsv7MjxJj0txHRJK7n70ratKfmlS3fjakbV1mdawDlpGzQ9xeoUPxHl4YlbiBZJkrWfxhB7Xcft4vyxBija-QdKD3gy-X8Xymo1ijRXlNX5cXLHhNZHraUmyGwxr-DyBOewDMsmqSTJsgyTi0aEFIv2mLp3NjSK1mQOWdYTJloElho_4fIBRdZgtD43IlRO8dkz6x_Drjmd2QXlHFM2q_UsVKMX1UvwTQ4qRgjbJVz32jp88sjT-ZLb5E4WF55xIbkn-MlybrzWOfdW6dcwko7jn_eq-6frN8RKfMqfBrNlDzY-WZ7jF21bWA1_s3oiBA6uNQvaxOnIVLJBnrhUQGXD08lRdXlQ-wAH5Tc6_6HXG38c387cOHJseAyqwEjpC0P2BtDojk1DT8oa2yCgTNv0QU9IUf83NYXfkSKOGrc7UM58Ntcj8KG5N0gq6eOlaj3U9owgzC0tLtqXYkYD1YU-i3AETCfcfQGscvl5yUKmx1ilWpyf3fRTPEo1n7lGFQEjQWwkpP2hM7bZTGyQQNG5lyglevJ-qIwQghePYzjgzGCiNh0mH9Fq3daRDvdDChw7V-_yNbD9g70zU4clTXwZvN3OxGhm4iWtfJM0CTDh34lvmdY0yx896NBee-TXMC-j8ySzlh9KSREsIjWDRfhkUmiSIZZ2MOPyGU9Y_BV-pCk45HjRU6ZR5Wd2iLj4Ks764ljftAWaNcH7jvhOl96kVi_p2QoXUEWvIwqhEf_k5PUtbz6CTAGza6TcqNhGXZQxkrxXTiDfX1QAL68O4oRoa9zafOcUcjVUr9rBKlCYbybVN1U9wz_tx3kcJcs3W810U3AxyKZrXtdlwoAFQvFGnOnkTP7ogtQ5_WDS4d39FoKD8UwU8LNJednhEvUVQSVsi17xPlUPNJ2qh3FuChrXFEfZ8GR_6nSLebnkdTNVL8MBJolRnqD8nuBzBYk5RKO3ohXuK0BZVlAlZ_bU-LVE1iv78JV2eKcVJZkW8EXEB3ZnX5I5zD-IUjfAM78Upp2UCQzv3Z-VFGtfFbSkhjA48t8zAeH8RPSmHUw1LXtIJQnzfvRvHvEl0JBZ_161j_gNbWVTA25jBvI8xKY0fkxNVvtVzK6BNtMOxKW_48t8nS0-V6u9Vp5sgHYLWMkVrEewOrhekYU4Jx4P2PU8Sm3GrJwvmMg7GKNWwKb9aGCUAaotu0Ke_5nc7ROm3vXaV24OqskGn_SV2MLvCB6ENUL4qiVJXEfzC2fmtoKQjcO2YHXKQmq5U2ABKZK9XWt8V0JKeXx5aaCyBPiX0zjqcfwrHZDJniOuAJZXYGibE2Vtt7kN41LDbEqryL9teq287Et50vlBvw-s5UjRu6zbatc_7ccAG2U9dhoY5pJ0FdU5G7MCAV1XYZg7cx1mivPkoi-ccL8d7lznBfWrIvZF1jMs5eZNeL4zC3iHzy1nixx0KTOVsxg86Krb9vZihJico5s0xZNeQtcpiTlTtRFAAnrF-WClGBtivLpMut-snvoJASNgL8miX3b9wHpWjg7lQAwWZU3SlD6vw3fWeeMqqa9-0mo-yEhWTYnxbI7pbjzVl7SdtY_a5hN3iGJlGgYuc6Ru4orGV7Z2opxT8dZO5E9X74-6v7sccFpYKGC0eUjpufgTABqQp8miur3F6m4AcmTkJC4lwjWBbbC41j8m6SN4h-9sWxAsKIS7UFM5qzN3BCGWvRfeS9lA58Z4VNATwbrn2K9fVtZMCbaLhqfljAQ6d7AmCqPQaGmKlnaSCpvudOsUpiEmJ1v4U_OjnLMSlY9bTfN0BVg7buIhR6zZ95SXesy2Ib8zH-izvwRHbd22kGgysle39142mgFd0tiFwo6q9zKtxqT-vI9-EL6FjwxTO78WrumWbPmdEAC_U2V0ykoMzdlvqKF_lBZhgo3f8JNwzF7SjA9T5aT64bgmHmtPtZ_LZg-y7U8FPvsePb1ASCv2zFLJ8ngzTou1QOvjkPRk3Zni4-8cgbAd0Ijz6bVjUzzIFvz6fuEtiDz24qgTFqiHTs8rCNCIJLBCDdUPXn6g9DFx78iRFUtOoMxAbJKbltMt-4PQzDyvJaxjJWdmcezD4_NeSrOy3djzCKCb4oyfq53a0nS3ADrvGllL3WnuTm2bCmEMOzGHW0SCBcWRB2k5S3WAMCbaEj6AUmyf0AauVngMGfiO_8Dj-O_KpZtbcV0VaHAUvQTDz7WeFxoPrWBSIG4NI1ZmXwjbANvfWSQfBsfp4TgigCZZHtrAweXz9ZzKhTK5Dga-aaj5EJ15WuQ3DXpQ5rLPW9oKtPiapTeKP4eUD1rrDLz4RllygTgDsh7BFfiSSSYauUIhBmu7Olo5-8CvHttYODNQ4LxJQLIdvhW8d4HiGhpSdIZ_8w3iZeuyIwVN1R_oyU7oQ2knxN_m-rpelEonH5Lay3_oWisZwZzDxsVr_fwZjXTkDfLY78leQw3r_fd1XlPw8zZvkVxRluSGva4PonBbVznIpM9smy_QwzvpE9p2MzgFxL9XyXabZdsT8YmL6Pz1t1JzSh_fpSiHWgPMuaxD2oQOWd86AM3e2Sd7MpepMY3aQAK7c8HLV-AV-nrnXXDaQA_c1LlueUb1naKD4qSX3XlHpk4DHqPvJ45I5GhhVh43PQWpQcT5vKKzQusb1XC7BcwxtXofPeQ-tfLDTXG5eRrM8UImipuFweiqbB04EGdwxM9zgtOseVjPCWgcJTn8VxUbPRMOVbkEkiXRjAG_E2eVIS8uoR27Jy_GOIFFDgJyw78Dq0H4h340Yl5HR63cy4PTSV6k3sn_rDXQadObwPg40YBKKJuKdYJwKi9CmlIkVwRxI0gCert1uAJbXyCF-lVrcotxsVRPxYJhxtMu7mlaceujhzvdLnganZO1QEq-Di-4zuVBq5a_nDT5-ymnPE2MdZ4WRueE-XDeSTj1kmaDyYwQmw4cLDYUndlEw-oRMQl5TcrL5nxOgibcUWEK0LTjlYE11uk6I6T0o7kB9VjlEKie80_DX8TgsgdwUeEjq6pMUh3i0aC8_A4ANm8JHIc9x7RYHqqM1fcuzdYVYbDLNYVybs-HxVxNSK7ipkChqXpUns0j7C-J4Y1gVwyBn9L-LLW8k5u19ZAXejccoJI9XaOvT1yj63VWyfeTmVdkxVIp85KOyJx3k_sYlC6aap7qDYXQhAsEzpAwNgRgtiDOQfYn8W1t7zP8t88iwZAS71WYJkrPL5ievAcpxmjFcCR-uId1lC3fGWS_hMQBO_w9s8wwUh15lw46ergoDIHobtEa-O8XGwvDC2AqhnVOfx4bXciUMX_bPaLWZ-FPRQV1cyqM75C8iad2D2RQTb83mYME3m2uzE1bHzAplGr3e7erCsrDJqrU6jAEpJS6QY1ExG-gZtHVmExFNBajXzooWFq4E1u9Fe1osq1VeLdaoiNSJdEA1L3vZ5gqmLUCMcqYAcstRbziDXDyUkOmo5drfMzR7hUjT2G_BWkUkXPTGg9U3XshlKAFM0fOvxcu4NNwby6t1G1I23r5feyjeAB0BiPHtqf2YKJfUkn_RBO-yjBX0QUDz4fVxiL5uLBJSXi46u0BIXgNWkmqbySDX8oCuVLNMOEwJc5RpQgIcI0_SIoaj0xZsysJ1C1sPjllsEvf3whEMyra0mWN8thKcEGWQwhj-ZPTeM8T1jnb4qsxrzZXzpDv0yM4eke22quPRfI__nOhnznkFLBoSuywX_nXAEYFzEyM-HmnpL8Ua72FFC0aoFlNfBCy-EqXkcIPNuk_HBsMuDBYfnnOtgPzmp0FZQSqkC0UeUdlCmNTW0R1-lfjAmswI5f_-JH1vy3_YZt1t9r-ppVRaUCTPYOxFjIFTASI6tZHeyK9CUd1kcrPDOCjNWkIrMRMJRzoIsh08FCjnEQH03bAXAmcM_vKl70CYCRVGOXq5hoy77VcxOw90tPUktgDkDbTD3WlTRJVAhDWt2_7t3y9f1fTD24dxlr2vAFxOEMtZhmR5xr_my6r5mhBmDlqiJ_nJxF1SUxWdpeEIpdWZT-RouQpf8qazmy0GO84YWK8nQ7s9BDxk5eNouGqSCsUEGTI7bjSCOb9oFndiDPJFNFHV8yu3FJQjLscL6-4KAPNiF9z5ErKWemtpcry_oE91p4uvt6CQKcl-jdPvwaPrZq-sCp75aU5dUr0_yewNgkEwXGKB5LAzOvPyQmPC9e_iOUAbfxPaBkKJO0pHrWES9K4tg2__ll0YA_puYdkLvYyiACtI_d96w8ZtMXwvHKzumxjYCSjbNZ8bjG5uz6ESbHqkxbK89QA8b5WWQxVadsGZAIdljYOTxrZPCnYlPuuhhEacK1cpn2ZT1XtXA6eGIL28tC7K6Qs-0pEHrkjMWMVGBXAoQYExlA2r8FA7wTYBomgXZzWDUGdvRaQ9Wb1WtQDF5lXFa1EiS3MXbFoKeLRNLhWiomPTh02Llpw6b7tEuq6gN9nPD5Sq_ycMZOXGNtcff-OXM75-IhPb-Ihy2Z0FUHmVNHFwC4i31NrE0MhGJk13teChq8Ft6mqeFOW8pRo7NIHQ2l2Burh4T94TynemdpK38oU2W2XDXz0xtzEv6CwZ9VfziAXcihvzvYdOPb9XOqnGm0f_WyALh6AIYDaVJJJJCwTEh2eZxFyYPxetCl4j_1Hu2kNso3Ge7Wjn1b8kfPPzogbM58NaYik80bzOS255dgXJ1a9yUjex_QrGHWP6tVz8S-1r-l_p3O-lwM1NDD7pRCE1D4pUzhb99sqDI64LoVkFa_IB1taiUsymx_GrMHU5syW5ie_hM5j5-OvJI-j7OlbzJPpX7cqfWInUgylelchtNXDPxlkzw-S2s3d1ntR4ov24YSAU57CVeEzhyNpckxP9LecCXE-C4Ult-e8E4DP-AFNeSIwxcQja32owS12V5B52swQu979LfCPl8PyBJPsbJLosf023Aa3Sf1Qrm15gmkKysBcHxsoom044blDnux06KwqVumhiJB0Ycgy2_EaVcfipUZj4="}}
{"timestamp":"2026-02-11T04:30:26.880Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"python3 - <<'PY'\\nimport itertools,math\\n\\ndef cond(U,m):\\n    k=len(U)\\n    seen_even={(0,0):0}\\n    seen_odd={(0,0):0}\\n    # We'll iterate all subsets to test injective parity sums\\n    for mask in range(1,1<<k):\\n        x=y=0\\n        for i,(a,b) in enumerate(U):\\n            if mask>>i &1:\\n                x+=a;y+=b\\n        if mask.bit_count()%2==0:\\n            if (x,y) in seen_even:\\n                return False,'even collision'\\n            seen_even[(x,y)]=mask\\n        else:\\n            if (x,y) in seen_odd:\\n                return False,'odd collision'\\n            seen_odd[(x,y)]=mask\\n    # coefficient condition\\n    for coeffs in itertools.product((-1,0,1), repeat=k):\\n        nz=sum(1 for c in coeffs if c)\\n        if nz==0: continue\\n        x=sum(c*U[i][0] for i,c in enumerate(coeffs))\\n        y=sum(c*U[i][1] for i,c in enumerate(coeffs))\\n        n=x*x+y*y\\n        if nz%2==1:\\n            if nz==1:\\n                if n!=m:\\n                    return False,'single not m'\\n            else:\\n                if n==m:\\n                    return False,'extra odd m'\\n        else:\\n            if n==4*m:\\n                return False,'even tangency'\\n            if n==0:\\n                return False,'even zero diff'\\n    return True,'ok'\\n\\nU_good=[(-2,-1),(-2,1),(-1,-2),(1,-2)]\\nU_bad=[(2,1),(2,-1),(1,2),(1,-2)]\\nfor U,name in [(U_good,'good'),(U_bad,'bad')]:\\n    print(name,cond(U,5))\\nPY\"}","call_id":"call_e2CJUNdMOQ4NPZ2EcPbtN7LJ"}}
{"timestamp":"2026-02-11T04:30:26.908Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":2498354,"cached_input_tokens":2381440,"output_tokens":52363,"reasoning_output_tokens":34826,"total_tokens":2550717},"last_token_usage":{"input_tokens":69025,"cached_input_tokens":60416,"output_tokens":1543,"reasoning_output_tokens":1069,"total_tokens":70568},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":10.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:30:27.539Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_e2CJUNdMOQ4NPZ2EcPbtN7LJ","output":"Chunk ID: 3fd5a3\nWall time: 0.4715 seconds\nProcess exited with code 0\nOriginal token count: 9\nOutput:\ngood (True, 'ok')\nbad (True, 'ok')\n"}}
{"timestamp":"2026-02-11T04:30:27.539Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:30:28.948Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":2498354,"cached_input_tokens":2381440,"output_tokens":52363,"reasoning_output_tokens":34826,"total_tokens":2550717},"last_token_usage":{"input_tokens":69025,"cached_input_tokens":60416,"output_tokens":1543,"reasoning_output_tokens":1069,"total_tokens":70568},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":11.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:30:31.673Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Assessing unexpected orientation outcome**"}}
{"timestamp":"2026-02-11T04:30:31.673Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Assessing unexpected orientation outcome**"}],"content":null,"encrypted_content":"gAAAAABpjAXnfp0QyZJw-3-2WYa7T7nNC7WeXFPeOrAHxFkL5ZZ77wrsCovJc2mNvolf5ha6oW8iGHMFuQJPNj1t3mVRkxqcSvvM3e-lT7eGmFazikgjDuMsIXDxtNXHR2fpXDPFXuTFxVbVzWsavrR-6eKWAWV71RlNaSfGjkSGr4wTkA3SOhLNgQcKRIuxBBinF-QsPGl5MlR3HPzkxxmUn_JgVC0N0PxWVs8DvbOFT5CT49uV2KoaYCITta25UV-PSSAKeoweaXYA15VMFft8ZkfAnGN93drZofSFmZRU7DUzmJ0WXWPkrkOtPl8_0IFgRRM9K78n_Qny306hlExPWasiz6Cjli9wGFaApLF4102EMMf0nBcoGuWQCf7pnSzrl4uAFP7zXte7Nh8ngcJcuiFLwCK9UIotPdJAGEOXjTWBGMAmRQp74GPYF_uMnKm48S8AEAPJbhFpSpkbbhd6AKFd0aBOyIIuXVojHtQfxoSf0lm_CscUNxJR8yI5mFPSG5QJHVPWp9hLZNTOrQRqKK3bjM1uarimQy2U5b7RbRKvXmZ5RAAdIcjMEHsGT7qEZZ5y83595SB4oxVlPvJCT8LbwratXhRt3OBu7VgfO0EtprTN3uEeC1nW5iW5EOxphdwA5i16NQnuUxP650tLH3ISHKz-mPx6c1qiKpSLP8ceQiyaZRkUhSRdhmIBRgV41azA66t_IS-sIJabaVEExHlyiFDeUrojJcNSHbaMMNCRT6QG5-2sT4NB6GgVUUySvmDqFnANdG2nEGVKRfyMLOmWK9IxjERGLfUnnEYQbjjsY1SC1HddTn8v7Mi5s2AsOah8YfZYpaCNDcTxBD6lsI-DrZSvKvmkCllu2yX_ffAGvuuCEWiL1VOHkJZSHK6EZbTyxtInnJXFFlUt8JW_iGzg5X3cTabckjKtZB_MI-aA1j4acfwMnnUkzXo4ULHa6ejCS_C829vsXZdo1zoayqnhhaOHxz1zNxkqPcCzYiB-Mcxw4gtWMOShLL5E30uVscA75m8yJcmPMLtqGWBfcq4aqKIJGPQnBNOuRZMHz09F6LPRbynaMtbpD_nDWT7_Rgqw-TQ4LlZBrps9S_THbYaB8qqNISNZJdyvdF_Yc1YsbEKLl05pr0pLc9jXVCjQlynphf_Iv-ZpK059PZoEuOGaS6nUKv--U_1sevmx4jZQWId9MivgePwrzIYB9dm7pMd_-_auT9Z2svmNxcInsCHMru6czYur0Q2zJI2JnFmY7JI06-2ftPchWzowhqFUZhkyblKAppefaS4Ll01bpbByUqCXAXLDMjPMmv-gmFoOa-IKYs247Ord1-qOoYhRLVJeuWwDXmQW2xrGTIOZlYFGpFkJ7g=="}}
{"timestamp":"2026-02-11T04:30:42.519Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"python3 - <<'PY'\\nimport itertools,math\\n\\ndef cond(U,m):\\n    k=len(U)\\n    for coeffs in itertools.product((-1,0,1), repeat=k):\\n        nz=sum(1 for c in coeffs if c)\\n        if nz==0: continue\\n        x=sum(c*U[i][0] for i,c in enumerate(coeffs))\\n        y=sum(c*U[i][1] for i,c in enumerate(coeffs))\\n        n=x*x+y*y\\n        if nz%2==1 and nz>=3 and n==m:\\n            return False,'extra odd m',coeffs,(x,y)\\n        if nz%2==0 and n==4*m:\\n            return False,'tangent even',coeffs,(x,y)\\n    # injective parity subset sums\\n    even=set();odd=set()\\n    for mask in range(1<<k):\\n        x=y=0\\n        for i,(a,b) in enumerate(U):\\n            if mask>>i &1:\\n                x+=a;y+=b\\n        if mask.bit_count()%2==0:\\n            if (x,y) in even:return False,'even collision',mask,(x,y)\\n            even.add((x,y))\\n        else:\\n            if (x,y) in odd:return False,'odd collision',mask,(x,y)\\n            odd.add((x,y))\\n    return True,'ok',None,None\\n\\ndef full_check(U,m):\\n    # build C and compute perfect\\n    k=len(U)\\n    C=[]\\n    for mask in range(1<<k):\\n        x=y=0\\n        for i,(a,b) in enumerate(U):\\n            if mask>>i &1:\\n                x+=a;y+=b\\n        if mask.bit_count()%2==0:C.append((x,y))\\n    lim=math.isqrt(m)\\n    S=[]\\n    for x in range(-lim,lim+1):\\n        y2=m-x*x\\n        if y2<0: continue\\n        y=math.isqrt(y2)\\n        if y*y==y2:\\n            S.append((x,y));\\n            if y:S.append((x,-y))\\n    S=list(dict.fromkeys(S));Sset=set(S)\\n    H=set();edges=[]\\n    n=len(C)\\n    for i in range(n):\\n        for j in range(i+1,n):\\n            x1,y1=C[i];x2,y2=C[j]\\n            pts=[]\\n            for vx,vy in S:\\n                p=(x1+vx,y1+vy)\\n                if (p[0]-x2,p[1]-y2) in Sset:\\n                    pts.append(p)\\n            pts=list(dict.fromkeys(pts))\\n            if len(pts)==1:return False,len(H),len(edges)\\n            if len(pts)==2:\\n                H.update(pts);edges.append((i,j))\\n    # connected\\n    g=[[] for _ in range(n)]\\n    for i,j in edges:g[i].append(j);g[j].append(i)\\n    st=[0];vis={0}\\n    while st:\\n        u=st.pop()\\n        for v in g[u]:\\n            if v not in vis:vis.add(v);st.append(v)\\n    return len(vis)==n and len(H)==n,len(H),len(edges)\\n\\nU=[(1,-2),(1,2),(2,-1),(2,1)]\\nprint('cond',cond(U,5))\\nprint('full',full_check(U,5))\\nPY\"}","call_id":"call_MeatpguuvDgCKdlz10IX2FG3"}}
{"timestamp":"2026-02-11T04:30:42.546Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":2568982,"cached_input_tokens":2451456,"output_tokens":53292,"reasoning_output_tokens":34922,"total_tokens":2622274},"last_token_usage":{"input_tokens":70628,"cached_input_tokens":70016,"output_tokens":929,"reasoning_output_tokens":96,"total_tokens":71557},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":11.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:30:43.143Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_MeatpguuvDgCKdlz10IX2FG3","output":"Chunk ID: 526b10\nWall time: 0.4685 seconds\nProcess exited with code 0\nOriginal token count: 13\nOutput:\ncond (True, 'ok', None, None)\nfull (False, 12, 26)\n"}}
{"timestamp":"2026-02-11T04:30:43.175Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:30:43.540Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":2568982,"cached_input_tokens":2451456,"output_tokens":53292,"reasoning_output_tokens":34922,"total_tokens":2622274},"last_token_usage":{"input_tokens":70628,"cached_input_tokens":70016,"output_tokens":929,"reasoning_output_tokens":96,"total_tokens":71557},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":11.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:31:04.820Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Planning efficient harmony check**"}}
{"timestamp":"2026-02-11T04:31:04.820Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Planning efficient harmony check**"}],"content":null,"encrypted_content":"gAAAAABpjAYIddbtpXBVVZZBWDq5PZpGF-4PuzEbWnBjGiccaYqosMiXPzwxiAahgF4aoxgWKRtpj1kfHn9HU01AljHH63mhLbrHSW1kruc9PnNyjxdDXUKF31r-F8NmFUgXpBCteHYRLs3aoKYV4gtcBORAruGb7K5Vt7aV8dItEJ2M-9JwfBw3kMbgHFXwJVRJXQPbN9V6ReNXxQeGRCPZVMnTz42ZJR5d83Tl3MuJzGFEUYSRUPM3OIHH59vpxlTfy-OOvrI7hfJHVqr-r5opCDw-qi1GCgPzjia0ZmBF6Xj4BSvEI7hwwL8aT3AXmsmnXFftKN1d-EPRpg8_Ue6tNxbpWq5qqmfhJeNhPQe0Jp-MWHpdxH7vT8PBwnOF343Al7lu1oFZIse0dF7oqq3hAfa-lR5mqBnecPzQknQpDaKoy3D6e9X5XJ2WXjDN5s4HhnwjtAs9cob17Kd3Ml3Oln3Fu8Os_75cWTD4NuY4FGH-2GIWr_fY6XVQnVT5u2jCpotuVovKMkIpSbG47HUTVG7EKYa_PH8HeTq20f-qDUI8tvbfdM1qIBNdOxJyyOmcIrVaAGRi7EYzSZMRvSZw4F8FIihMaOvmLrzNdIPjWu5CJRbpdjRbBJ0TFSfiOqkA_8-W-xLL1xl5ZVQZAq1KCt4SZifqS3Y7Kg5d32XIVywElNMAsjfPax3OHzIgoVypZweXn7oBzlN2X4R00izulFdb1KCGdIsorLUo5eV1i5tiJz9oHJGAXEYk_I5iIekovQR_5Wq1cgwKPiFQxRoE4Q1GsRcwB-cYgm-vbdvm_Q26F7_YKGK5IU80dYYa4fJMQefYxvzG0_X0UCXMbuXEnQPyxJyCOxtHRxKDXOq1nPIzUnYwm4msJy-Rif59XW4XTuvsBmmUa77_RVpWWwyV40POJBuZIk_XEGz7XDbzWXLADxvD0g4o3dxNrOg_vgngswf3qs8hhlMLlaZCYcdVf_u3hqofQYMdU-952ZdI7qqpJ2FEH7CrUub-_lSGFNqqqHLxOEhZk5j5jAqgVPlldbY7277rVfb6LZpdNw_Unosr_CMknaRHKtSaKDFtMehcUX-8zFGqec0_YD3mhCRs4jiIBxs9VNHheP6MNdzl4qVWUTCmtMyn4KB-uSiIkgIX9yeCiQYw_DUkbgjGYxrIKysVmqfR7vL4MedtmWRUWv2wn6fyf9dssBhcwJtgurRvqaN0rnxLIGPTZcaY3KNA2pa8PsayAN83CmaQmlN2S_LFpRbeQb7v-OdWIGuXcyNG0NK04q_FNuE9L73zQzJ-12OrPEejZbNugjOhpH2DCZctYabxrXBdVe184CkfjUHCrnOpCexqLuQ_pxj_PTvJlJzpI4IUlrMQ7_BOVOkNSXNfbtW16Bf6acUpm03lver3vaHxCWri7tg3ZXZSaHlpnofAqm72s1fFhrEEi4BeqLS5zd7fPskzmpOgjxUYDcJl2neht-HWFMOgEYcioZIhewlz76LWGXe74X8QmIfJXHNr5_O8eHl4fAcs6OYC00j4xAmrpUlaY2AiI8kHwWKsvMKknehfbAW99ucklat5ziAsgY6S9bo6gNd6X_PRH_nKfz2mVfBD9-Pz7Y7Us-KvXqEnuPcN4I2VN-1cyG7-LqS-2QFgCalS6anr88srEYQY_vwY2dMBY7OHJw6h7pA8gJCiq8J6U56Kwan7oEFrrpAbBbk9zOGFekuHzBFDqCtv2p_e6-H7izjjrJJ4x7XEkNvnVcMVKtdhrU78klLUnx8eji3GIObtTUHuz2WhTGFEZm0i7wBsa5KGcGuDOF-Rn8ojl4LAbByw_WL81gRHG6Lx2yDio96LNfyuQb9F7gus82OnBplOiTW7abInNe1_vuEn3d-ZTiNX8N2sgCm4hBVquhi6RYfbe0MsQd9mHmetjVfvXX8Rn7cUH58JnQd2L2GFw5HOV_Ya21nsX6rCWRcNlxVc7cUmWTTcJngKbNNdBYLGQaZnrJjwVDM73MToJNpwh-TFH2Dq6pQdXIBFUtvjPcc0pY49ATH0iJI_s5ucjvzqsPJIwkyKfQDPXqFLp9nI19DchDZXuuUrPdA2kFDRiHMXVdYEijzP7FlI7GCVnTlR1pW683T9QBTof9N1tEbvBM4nsI9HOIACWfWvDzIO9NXkUcBpAleVdu9oBc2ombHFrfV2wU7ndxBR72Y-ahdbOcEgDKuTT1CSIKU0hmVmcAaF0W6eX5vhXaMYfhh0N5yAHIdR77jzkg5dvVgEXSSCgAqbJPoMJQdGxBXUygyyeXqw2r3bpDE-ezJCii4jORggEmL4NPidvpsr5QHioryToJQEMcMhrR3TExYDR6VmGO3bqMJuoHxC5L7aB3R87ReHqX2a4Pc6xJVTfM2mKuNZ50aPiRge2MGpL2iW5PuUgfHBtODYjU0BwNygC3Q7bIP_1xE2YQ8Bxj8n5O_NFwLfOEkTvbz-9w3w21aprjBa3uZv_fb4EOv1JVklqH3TWlgdr6hwR3xg9F5TYbJf2LaYBt1Jxejmzk3Drmu9MhnvbMkopEIT0gCd1veEQwycIeS-g_HqELcsr3_fyBYyofFYKMk24jSPGonVvaBrWZGB1eb5F336U8GT2MUYTWDhPgc1f621O_ylWgDfgI8zXj5v0rY2aYGrc9AF5shmxM2pR1W9VNgh5rdmf77vK_sAz2gZ2AYaVBbqtD6yywClyC82nHKgnFhBaNJ3ZpbCXypUNYsYsDgZLvmZw5t7oRA1D0K8z2OJgo629jofZwoc5JdW294feKfRA9gIZI7tv1MoQYnKaxethR5EMmr9k0T7eQv8FKseZtTe7T5wyRYa0x5viceVGP58bg9TJfmg0b9FK9IJpVTifmK03PPIUkzhH5oGdw9_4hZQL43veuzNQRykjV3WwIV_vOUakibC5VV-MTdaJq26aT2zEHQPRR31imKLHTnciF4o1uPVpXFHwAL0QkLRU9072wAZvPtxznaEAAlm3B67wpHn5Rq4e_PWo8aFt3lu-4lDsHBBlFdux8_lZtjgE5nZnBuS2k5gahlXzN88-cFmg6n3C13ADwvL4Iv9nhyh4J2JkOy_WEhMUIWTcMN9XLhEQJw4QpzAoWaVDl_Ue-P4j4Dgx3sH4NxoJucF27nJCaX_aiUkDndFKwhfZyZjvySXR0Ew4f7AUCkr_Jo8FESClRY0JOaSCo9-1o2HePJIfAkZnSV_JdRzV8nEVGZgayKj0jOqVJdXHnfqT_AZjMWqtPIZM7lp3vy3FciKTK0RwHLwDroOX39PDL45nVM4ptSHM2sJ6_hqT5rvfdnqblFBrnZOVrDkFD2BoklE3lpYJX2j09b4BzmOXEw3M_BE-s6sRPqRtidAaGX2MgYgPfxPaLcshlCWiNCOZL0KWhI0lrQlYIKWPCjqeZZ5T8gih0ZtiUU_P4UdCo1miwSZ2M9y3diQ2GqYPbsf0YnxKTP2kezxbslriEFDoFHCfoa2pnvpL2nsoC86e98ds5R__4lkkHlXqEoE0RNsi9fK6aiV-zCJxdKhqd0DQOcN_uN-0bD7GJOLhKpFAR_saw9fUQu00AbTfyW1tI1jv7fGuiKlQNUHCryMTLDPEmxOB78Uuw9szWZpcx6gc9ANOnEssrhTCYZPjC-LUC1nkLf4i-cv3dH5g3gI7--mxPslQJiU7eqSqF-avrOZjIW9uGknZM6shLwR7BisOeP4SCAFoFUHqAF0znBZUQCFIiITRzw9IzQNKzTBMSfqhFgvieHz9xgL6lM2NFkBJV3ShxQE2gpTd_1hgEiIAki4mYXUlExD7dj89Sl6xCI9-IWpdfD_SXu4IUOqf8UCYdlHpZVqS8Z4R2RYEMcfHCHIt_qvuSv4Ymp2ug-GQsU8-MMKdFLKbEcoSFnIxU7IbByk1IYpA38pap6kahBKBh4cEJPyis_CHzQh0W8P-fQ5qsVQS9Bzy3GtB65h2xvCbPwsu-jSEULIaG-qXOVQLcUlfRSAeCPW57pD895TuIM7ndL6DkSEz8Oe_E0dc1zvSsk-7eBG54UTWGnEiDAjZlD7yq-AoC3x-Q7APsDxPhD8bLVBH7uVimAICFF75rUbWtgoceJfepWSlQ3JfHeFssnDCrAqlzP4R6g6wqNNOszNs63iEm0EGUPQRpAxISjh7qZIaBjEZHKRGgDWzjPnvpo55x9nfx4HLkBWPHGR17XE21krebrAybnOIMkg9BJ5VjJrgfJnkAX-lUR9HPM8FHh6C3t9iTwSYkxYlFIgwhmfd1Fvu7BdPAf-81VXMzYqQKb2q8i9HwBYC8RvevrqkdB15KwkCXdJ6akYKKHPyN3tI_AF4bAu6_psz7EblI2ci6DGHMeWmaNPdEV9xkZuEIemscU71qQnEj_9sYD86pvlyZH4IQo8tyy1_jsN6vQH3L8be_ihELYHpxdym3YFCcKDDmjgLJDbx897BwiA6CdPl_SEDxpYXt3wkbDKCgxbalOfGW2qMjdMfRK7KsXEGTijh7qgtdlJTbaOQ1-PbcPrbSdearZ7GcK27ACTo0Dykb7PiPTN4fZfWfQFElckgTdDjhvGOosS2HrxuvFOqQOGawx9gCv36EbMpFDCkXrx1doDb-omTZESZZVrGrpz1lRMdx2-o1mQauKEqmD0WQRyuLcKE0pBrtCp_VNfcdvETStK3dxwbfUfwQ5RKxcr_uTZQevzRClXIMypr5_1yvRZYcBKLXPUmoMAobV1j1LHJeG7DNSUqb826inu4dfdoxDORW52ejkrByPvEEnf_IpQ9ndUMKM2WVc65WqpaB6cRV8tGwn3I0fierNKP-cooaIyr6jEMjl95dkx4Bd5PfZXRcuIWGx79Lq0ALaY__syw6rpquUGeT2HUCafzXoN-X4Aqv_0-ezsoaIrdQnh37zklzkyUQKt6PRf9feSNTWEy63Kw6JCNtC59Z6Kn_ylSjlsNJGd_HvkUOUyoT-uWRUY5w4MJgAujIZzQcY7_0Pk74UimKqpj2GhTZOjZ_YYPmxeJoZwo3mGH4DXDdm4Fr7kSZ2LoC6JheSXBaNHktaxmaHisMGnei20BDIx6TSmw6r1noeXJJBEd-19HbxWK6PFxU40SlI8n07IaSp5xDMZZFdvD1CEqWBq4msMuImyJRiEm92ebhY2wfPwO2p0oBY7N4P0BLf1WWYFRdveh-CyZ7MsOYfazRwlslnmEHCld8hLCJBSKRiszfh-OUbW24d2tzYAdFbJTiF74SZ89xpM5bNPDcyEaoyGDGTiSjbGGYBQ4MeGes6FrYi190h7nRsSZzD9YfpgJVW5bRHlHjYYzzEJMmQWC2tOZLT4nRpnl9hQScVx8syzeGYfXFRN2CluQQRizUybKQvRBJwj1AkaElcvIFbx5DC1imznozwGX4JG6AJ1_F1njJjxBtm3bnCu4NPIY7INCC7MY7SZ2iqjeVyOeZPC02qe7VhJtoZD6F03OXlNbyzn6TvkvuIwGVDyler47WRLSz3xQEjt7K5J1y9jhi1OvmBPxVzfxnwiB5BWJvxwjIUXTjQ1VLjpNwIjPwVmVuurGLCC4Jde5Ifeev9umKIRPRuV8z3FMumbe0uFFyOYOcZX4L5XPSk-VQyFstymej5f_W8gqjIAn7dL2n0GDBNoiBkhmZLlab5xXfojA0hrjKqFoFbGBn-ilQjlmxD-mix84bojOnIhTLgYiw101cKFxhrgwjJ7LftrfLUWzx69i9Rxee64VDDwsiUwSAnKgmLdphVNCQ8cM6Oy5_XK27yxVdIZhKO9gAgCPwT8aepxIhyByg0mgxRF0SeDhI0KNsOvdNjKZJiKFaGWdtlbxlOLRxIGfEfe1QzUFqGP_0cvKrxAn89K572eCrDijVB_mBv9V3tPgUHK4Mh3NSj9Pb6omdbrADXlVcVegCeYtnHAKflo5gjRhhAwz_RhZViJtDd2N8Bvr3cKy-v8KF08OBWUTg72pYHYgmB6TKUsK9PEr8GEXous-UsSRSjHSyHPoOKCzMj4qycEx4G58tjN7TafUfAM-Xmz-6L03-69D1DJQW_RXQ6qiOAx5wrufkhVWAx-3httOrkg9NU5p2z-vNnG5xFMTHUJ4TKt-tD-Dp1m9lLdacrRxVfZIaUvYh_wcU0gRLP7ebzNpOGpe3kwU3hgF61f9DAzvfWfjeS6kpMLZ-wqgDAaFg_iGurjSGezNZwLzsPPIS56oF3ddG3X2hCtKFLPS6yywqS44wTM8IvhBSS2EAN03Ytowk1mnQqRxsYJRSlEe_QOYBpjjdw0-QvlVx083tsyWXTghUlJbrGA5cLq3oDglGxeAddIjAups61fYDur4VxuI_QZ66Fb_F_KmLKnRJBJbsljx9wJXwc8FhjG8UwYZb9xNvBmSBBQKT7JHxIhpPkS-rBC_IK9H34DT5O3s_Y31iNZjZa0Lf82cJNyqhRrLW-PahjDJLTsMKLUjRrBJh503lGTJhvZEHEmShNLyJkhZbibRbBIAMb-EU33sS1O9MtDjuqYkR9KnJIkHBW1I4PdyW5z3-oiAGtpcKqVnLQpjxFufmNlcH4AsSuHc_FtYi4cPBwKbUAWRXtHgSdWajOSQnUdMP8AYEie6LdxIwMqpnKB5LFgg7xZ4ODFIaglhAVAUkLf2rR7j1cZeL9dleah8qgOgT1csuPyn_zFvorMkWiRhm2tSSx6rvNNxI84Ba4JkW3npX8guqKIOt6YLvZn91mo9C3m7J0VGb2G4uGY9C8pCqUZOlZPn0OQjdOeYpxw5Q7wzGV8jDoiq4TYE-ig3saiTab6O1g3g64cShgk6gySDnvz61eIVqHqo8-YhHBA4blxi3Q8dbBGS6M9RDzIo0BlavqDkt0O6_AsJ5FwD10u6vNjnoIpRrButA=="}}
{"timestamp":"2026-02-11T04:31:12.778Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"python3 - <<'PY'\\nimport math,time,itertools,random\\nm=325\\n# vectors\\nlim=math.isqrt(m)\\nS=[]\\nfor x in range(-lim,lim+1):\\n    y2=m-x*x\\n    if y2<0: continue\\n    y=math.isqrt(y2)\\n    if y*y==y2:\\n        S.append((x,y));\\n        if y:S.append((x,-y))\\nS=list(dict.fromkeys(S));Sset=set(S)\\nprint('r2',len(S))\\n# D map and tangency\\nmd=2*lim+2\\nD={}\\nfor dx in range(-md,md+1):\\n    for dy in range(-md,md+1):\\n        if dx==dy==0: continue\\n        if dx*dx+dy*dy==4*m: continue\\n        pts=[]\\n        for ux,uy in S:\\n            if (ux-dx,uy-dy) in Sset:\\n                pts.append((ux,uy))\\n        if len(pts)==2:\\n            D[(dx,dy)]=pts[0]\\nTang={(dx,dy) for dx in range(-2*lim-2,2*lim+3) for dy in range(-2*lim-2,2*lim+3) if dx*dx+dy*dy==4*m}\\nprint('|D|',len(D),'|Tang|',len(Tang))\\n# build parity set using first 10 vectors\\n# choose one from each opposite pair from S sorted\\nused=set();P=[]\\nfor v in sorted(S):\\n    if v in used: continue\\n    used.add(v);used.add((-v[0],-v[1]));P.append(v)\\nU=P[:10]\\nprint('k',len(U))\\nC=[]\\nfor mask in range(1<<len(U)):\\n    if mask.bit_count()%2: continue\\n    x=y=0\\n    for i,(a,b) in enumerate(U):\\n        if mask>>i &1:\\n            x+=a;y+=b\\n    C.append((x,y))\\nprint('n',len(C))\\n# eval time\\nfor rep in range(3):\\n    t=time.time();H=set();bad=False;edges=0\\n    n=len(C)\\n    for i in range(n):\\n        x1,y1=C[i]\\n        for j in range(i+1,n):\\n            x2,y2=C[j]\\n            dx,dy=x2-x1,y2-y1\\n            if (dx,dy) in Tang or (-dx,-dy) in Tang:\\n                bad=True;break\\n            if (dx,dy) in D:\\n                ux,uy=D[(dx,dy)]\\n                H.add((x1+ux,y1+uy));H.add((x2-ux,y2-uy));edges+=1\\n            elif (-dx,-dy) in D:\\n                ux,uy=D[(-dx,-dy)]\\n                H.add((x2+ux,y2+uy));H.add((x1-ux,y1-uy));edges+=1\\n        if bad:break\\n    print('rep',rep,'bad',bad,'H',len(H),'edges',edges,'time',round(time.time()-t,3))\\nPY\"}","call_id":"call_liReMYz1ZliHBywNik2ZONIf"}}
{"timestamp":"2026-02-11T04:31:12.809Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":2640605,"cached_input_tokens":2522880,"output_tokens":55052,"reasoning_output_tokens":35915,"total_tokens":2695657},"last_token_usage":{"input_tokens":71623,"cached_input_tokens":71424,"output_tokens":1760,"reasoning_output_tokens":993,"total_tokens":73383},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":11.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:31:13.434Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_liReMYz1ZliHBywNik2ZONIf","output":"Chunk ID: b7063b\nWall time: 0.5003 seconds\nProcess exited with code 0\nOriginal token count: 38\nOutput:\nr2 24\n|D| 264 |Tang| 24\nk 10\nn 512\nrep 0 bad True H 28 edges 105 time 0.0\nrep 1 bad True H 28 edges 105 time 0.0\nrep 2 bad True H 28 edges 105 time 0.0\n"}}
{"timestamp":"2026-02-11T04:31:13.463Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:31:13.825Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":2640605,"cached_input_tokens":2522880,"output_tokens":55052,"reasoning_output_tokens":35915,"total_tokens":2695657},"last_token_usage":{"input_tokens":71623,"cached_input_tokens":71424,"output_tokens":1760,"reasoning_output_tokens":993,"total_tokens":73383},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":11.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:31:24.533Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Assessing tangency impact on search**"}}
{"timestamp":"2026-02-11T04:31:24.533Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Assessing tangency impact on search**"}],"content":null,"encrypted_content":"gAAAAABpjAYcYGf_7_RpYCiANhWOjuOa-y0B_HfkKFfTIbdbx50I7-zvml2eopySQiZIBemt9ocAjlqMdBl4fz_MXLS084jPM5GL_GCulI8h6jrgaroUfk0_sRxBz09PRpdEkwjDt390lEez-DkKGxvqtJhIkFwzRZkiAZdBxDdth5NBUf0RWxLdtIR5iSRH_6GgWG4nHlmjOBXldOJf_EiRe5TQGHeS_O-wQX3IVfZ-suBX2fjq8zXv_KgPZkGCphq51LhAK2gvwYrF-LZLSt79tBUdhpSj9wBk8CfyqmtTDpmLSiT6DAhYa4OjAYm8MFAC6HkygncEHtDtHx9RWDvzbLciHNqojSfnGQkb5yLDEbMAfdsfI-9sKQvDRvtbRcvTYZz9T52aupYE2FqO0hxMS4s3tEwBeJIiz2Rs31-x0izM5ylYpHmX4GtzC0CxB66ZeUWjgfkpgIziXDJ-eiZOdK2_0aNe8RzdoXHBXx0XNeI4HB34QEE7ohmPxAiIgwzTuVe3Jc6TaX0Mu2Z17zqBMKh5Q40mCs4TGNF0ieOo3QhlXkGSUvAjTu3gHxkd3ZbPuSWTAwXqCw1K24zj2b53OzaWD_AnWeqt2-ninVsi7uaRah3T1z_6ninBaIQ9ijHfztP22wWuv2fSA7jmGmBOFAII2IRE0_zD8wMFNzAjH-ABZ1cIJwr1wwlpzfS3p8QEvV0bqRD6LnNeBSE9QP4TpJJzd05PqNkZKJy_ckZMTgfY3GrBc9NfsXCHiZKicDBPSYBWTp-wpJtcLY5gIdGKzEkiPkHPIWJTwKnj2xvPNasaZaL81BTzO1nW8AdKEuxtgmaYiFC7QNkWa4M7XW4VQNx0AimtrGtodRBz5qUHjRcl9sQ9-v_S7kLD5mMwofKMEw_QxRPzASsCSajzze2bizLXj4M9Rjr9i5zCeDYEFDfI64iTHwh9bKMsXd75zjZrtZBCRl1oU3OrbkxOniLAsGObhmrUDlS1dnYWvznnKPBCCLud5O4r7nlXPzUgUGgqx7E0Y4lD8KYuZt2xSIA54xsYegAzB6o6fs_k5frAF434bLBHhGGZo87OVkRH2ZdHthm1OjlY7j7cG2pLRrkkfHKPMhEY36asVzFqICe4mpKZZYVOcgywPy5cH8C1X_jUN-3ak2BlmJLlvdP5IxFcZUu7t6pbTec0-lnw2ln99YrykIsi2SM2nP3MA5F4n6KNkFuWXwQnbe9vDqY8H21SipGqGI1MGdByD3BJw3arnw65ykLR8l6hMJcLffFoJOx2bz6kf2siucJObRG0MUr4bnMsxSQ2_RvEA3fxEHreCnsg-R3xEdPDL6IkX1Zh3BlYIgJNua-zBdCy21slq_1oT4ZNJsYnM-UvQHmxJ0FOgHZUctwS0bqGxVmFg29STc3U2e0ilAVmQ9EcqqALUKQBY0QEdq-38L-HE0oOqNYsQGzkt36py_KKa6VL2mb3WJwdNDX95zb03xpbU8iw-YqzmuK5rjBNbVNg-uSH5rVZvLF6Cgj6wdXeC55Ay5P8ph4zLDl1Bj_125x_Z_ulSrkWop5uOkGVGlJiKJ_AXgfaF2a22SrzaxXMngIDcy8sOQvAoaiSU88rK5GFXtM5uhBFby6C1HbSZBWd77CuP53ikMirrtov9PXI3EHaydkNINxunOL74hs3nkVl5DLoEhHU-SRTakYBuRCU0cNfbfvGgRSq8igGDs18ehiCEC2QYXHrAD7X-6UgYJIys_UcaBfwOzrvl9HHMJ5tCIZsOUjZvaZqMf7qRe2bEB9JrKhmlF90LbSBT8GdntvDAUDsmkC-BnrgKWB7Wv5a3xmjwHXYE0J65NSZaWIMW7umjTRK_WB3R5ByAmRN6lKk5d0l-P1x5A7zzLtmrapzwnbLIfLNnQoILROLy2h8Ra_W0huh6cRE_hGRaPTKLEZ817Zmtx6Kw0pKcm3KnGTzrY-_Q0kD7NTHLxRyxc7o-81xenmPHXQBvmKj3Gomt58447dXLda4EgKv78wqK8R2IrdBOd9taTLZC5LWUB7w7nMfirlnfhiWed3Q7A-CaazgdBHgSO4EtMJoYsYoJVnuOlZ2hLN5qvjm78MomawkFxerR58lAmvHRsV-vToilkvnpv3D1-rNGQJleGtG8_UGld_p9InpOzlgC-BWxwyXs4eExTES6AcNbDbtUe-bjJAntFwvb63iKWjIWPBNItgtfQ7sur-Arrb77XiULjSaTI0csUYClhm9P3nMAQ6plNLEtRVh6CBI-G9enTzu6gKvuyZ6YD6Md8svbq11etodNsBNwYG65mrIYBNH3HIo9RLK9nDNerBa9i8_BFSQgZCyIJfdl_ElaSUWfyYljkKpRqwUdIMHiqtUR0ypQhj1KztkwkKlwISNvovHm9Yqrk8eHc_iLj_Wj7DRzYTQxvZl6wiwGyluuTvCvq1-XN-Z1lxo-tUPvB7JLdM1d_N50MeNdS97RnIGD4ol6MwtGuI6EVihkktd583TDuwrgE7zzdoANDjv5StvTXVUDbhhofgssxBR5yDCtoRM5f0nfoUKhh6o0muwpt416ZNVv0KxsdlYTSMQ66_t0kd_GFCkxKcaYHJOHwqDJcubZl8bgngogZkPMBZqIFgZ2EV8cSF3Yu1EKiX9-SiJUN7hP-FsivJE_wrcR_comYmvCuk8IjD5aIjPIQLwrwC6ELvcVzbqgEGdfhZn0U0SMRUM3ohNaQG7jXkfRRv_SW53by8qVMmeGbmOWBStwOMdcAojO9e4TT_WjOfLkrU7HD_pkexRayLXquboZGpwihM6C3w3pmCsAo4K7_VJ9VeAiOW2fbpgsBzxXNeqNGOTr9l_BbA5EBUUurpYxRnQOO_Wq32RAx6zIJ1bYoV64TYb44jhy11V7LgbKdcc5-g7JUTvcDhA1l3O6spNU3ZEyrmkqzyCpJihH9kwibeAxAHS5W2rU_E0syT0QXSyYZtHLn5cPbvSnYXu3EcPQgfyM6uY4jFPRCc0AH50o2eJDXxOSbyKtSFreqaVtmQDyU-hfwJamyWUiJSK2aZlAqTVOy4hgv-4XN5owQ2h6VBMXiUiJdKkaxKWWAHf_2GYtyHNyzFywlevHydQ8dvMVSrRjKcQfl8cemT0Xgxk2Ks_IqzF0cD1TSgKmq2oXdtRWBotP1hI4sev9Q_8wLxK_4xUJE741aE8jFSr5-SJFIqudWr5LrkITS_gV_S5FFlJyCJbnjiIsDTpO1r1qrh1NfG4OaSYStZ6ecxOy5FrbbHoeozZ0Wypl7Rt-BGhv8ZVMTkRpRclKBnC1cbTsyjGxYxJdmtkKiLtilyjMVdsRyV0BHT91A0J3lLITghMA5WNWia2VNUSKbyUCWHFK0-yvOOkEdcvGlZqenr_sI4Pw-GcjNhutPfIiGhQ3fF2G_Kd5-_0mkvAcntorbBLT-_RRMO558pVAEedszVDguBFf-32KCIP4WpZK_DNeC1yeB4-Qil1rc6bh_eOSgG3Tnakp-0WXDdvWa7sM26pSUoCJsYE7A64XevNBp0usYXSkgxS0qbkS2dkGirkRLz6AVci9skL7HaWj5qm--hham61r_RZNU5pSC7ShydaA_koxfakrYu6t6YwWoyqMHkezLDj50JiAXRPweEm7bzZCiUNqaC7ZvUFjxS6IvfBh1sCUSi0qnzWQzsRZ0or68VFk_pxzxy-CAW0XiKap9lyzSvo0l4tecdQWfQWpsPUCue_k2iWTva876KNlgt4DsjFw8vw768ZiIvnzpV9CQo4nh3U2-AR0nasHJ4zQkhcJ_9hCVvZug0n4hcxxJ_jHw=="}}
{"timestamp":"2026-02-11T04:31:24.947Z","type":"event_msg","payload":{"type":"agent_message","message":"I now have a fast evaluator for parity-subset constructions. I’m using it to search the key candidate radius \\(m=325\\) for a 512-circle perfect set (which would immediately imply \\(R(500)^2 \\le 325\\))."}}
{"timestamp":"2026-02-11T04:31:24.947Z","type":"response_item","payload":{"type":"message","role":"assistant","content":[{"type":"output_text","text":"I now have a fast evaluator for parity-subset constructions. I’m using it to search the key candidate radius \\(m=325\\) for a 512-circle perfect set (which would immediately imply \\(R(500)^2 \\le 325\\))."}],"phase":"commentary"}}
{"timestamp":"2026-02-11T04:31:38.500Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"python3 -u - <<'PY'\\nimport math,random,itertools,time\\nm=325\\nlim=math.isqrt(m)\\nS=[]\\nfor x in range(-lim,lim+1):\\n    y2=m-x*x\\n    if y2<0: continue\\n    y=math.isqrt(y2)\\n    if y*y==y2:\\n        S.append((x,y));\\n        if y:S.append((x,-y))\\nS=list(dict.fromkeys(S));Sset=set(S)\\n# opposite pairs as canonical where v< -v lex\\npairs=[];used=set()\\nfor v in sorted(S):\\n    if v in used: continue\\n    w=(-v[0],-v[1])\\n    used.add(v);used.add(w)\\n    if v<w:pairs.append((v,w))\\n    else:pairs.append((w,v))\\nprint('pairs',len(pairs),flush=True)\\n# D map\\nmd=2*lim+2\\nD={}\\nfor dx in range(-md,md+1):\\n    for dy in range(-md,md+1):\\n        if dx==dy==0: continue\\n        if dx*dx+dy*dy==4*m: continue\\n        c=0;u=None\\n        for ux,uy in S:\\n            if (ux-dx,uy-dy) in Sset:\\n                c+=1\\n                if u is None:u=(ux,uy)\\n        if c==2:D[(dx,dy)]=u\\nTang={(dx,dy) for dx in range(-2*lim-2,2*lim+3) for dy in range(-2*lim-2,2*lim+3) if dx*dx+dy*dy==4*m}\\nprint('|D|',len(D),flush=True)\\n\\ndef eval_U(U):\\n    k=len(U)\\n    C=[]\\n    for mask in range(1<<k):\\n        if mask.bit_count()%2: continue\\n        x=y=0\\n        for i,(a,b) in enumerate(U):\\n            if mask>>i &1:\\n                x+=a;y+=b\\n        C.append((x,y))\\n    n=len(C)\\n    H=set();edges=0\\n    for i in range(n):\\n        x1,y1=C[i]\\n        for j in range(i+1,n):\\n            x2,y2=C[j]\\n            dx,dy=x2-x1,y2-y1\\n            if (dx,dy) in Tang or (-dx,-dy) in Tang:\\n                return None,n,0,0 # tangent fail\\n            if (dx,dy) in D:\\n                ux,uy=D[(dx,dy)]\\n                H.add((x1+ux,y1+uy));H.add((x2-ux,y2-uy));edges+=1\\n            elif (-dx,-dy) in D:\\n                ux,uy=D[(-dx,-dy)]\\n                H.add((x2+ux,y2+uy));H.add((x1-ux,y1-uy));edges+=1\\n    # connectivity\\n    g=[[] for _ in range(n)]\\n    idx={c:i for i,c in enumerate(C)}\\n    for i in range(n):\\n        x1,y1=C[i]\\n        for dx,dy in D.keys():\\n            c2=(x1+dx,y1+dy)\\n            j=idx.get(c2)\\n            if j is not None and j>i:\\n                g[i].append(j);g[j].append(i)\\n    vis={0};st=[0]\\n    while st:\\n        u=st.pop()\\n        for v in g[u]:\\n            if v not in vis:\\n                vis.add(v);st.append(v)\\n    if len(vis)!=n:\\n        return len(H),n,edges,0\\n    return len(H),n,edges,1\\n\\nbest=10**9\\nbestinfo=None\\nrandom.seed(0)\\ntrials=2000\\nfor t in range(1,trials+1):\\n    idxs=sorted(random.sample(range(len(pairs)),10))\\n    U=[]\\n    for i in idxs:\\n        a,b=pairs[i]\\n        U.append(a if random.getrandbits(1) else b)\\n    h,n,e,conn=eval_U(U)\\n    if h is None:\\n        continue\\n    diff=h-n\\n    if diff<best:\\n        best=diff;bestinfo=(h,n,e,conn,U,idxs)\\n        print('trial',t,'best diff',best,'h',h,'n',n,'conn',conn,'edges',e,flush=True)\\n        if diff==0 and conn==1:\\n            print('FOUND perfect',flush=True)\\n            print('idxs',idxs,'U',U,flush=True)\\n            break\\nif bestinfo:\\n    print('final best',bestinfo[0]-bestinfo[1],bestinfo[:4],flush=True)\\nPY\"}","call_id":"call_bwPi9G2D1XkzuqjLpPWeXO6p"}}
{"timestamp":"2026-02-11T04:31:38.528Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":2714108,"cached_input_tokens":2596224,"output_tokens":56756,"reasoning_output_tokens":36412,"total_tokens":2770864},"last_token_usage":{"input_tokens":73503,"cached_input_tokens":73344,"output_tokens":1704,"reasoning_output_tokens":497,"total_tokens":75207},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":11.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:31:40.382Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_bwPi9G2D1XkzuqjLpPWeXO6p","output":"Chunk ID: dc8aa9\nWall time: 1.7265 seconds\nProcess exited with code 0\nOriginal token count: 5\nOutput:\npairs 12\n|D| 264\n"}}
{"timestamp":"2026-02-11T04:31:40.413Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:31:40.728Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":2714108,"cached_input_tokens":2596224,"output_tokens":56756,"reasoning_output_tokens":36412,"total_tokens":2770864},"last_token_usage":{"input_tokens":73503,"cached_input_tokens":73344,"output_tokens":1704,"reasoning_output_tokens":497,"total_tokens":75207},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":11.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:31:45.126Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Testing tangent frequency for smaller sizes**"}}
{"timestamp":"2026-02-11T04:31:45.127Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Testing tangent frequency for smaller sizes**"}],"content":null,"encrypted_content":"gAAAAABpjAYxF0igxwe57j4Ht3CnbXkppkMT2eaeiY_J0c0G0MtrjuJvjNOG51EoZByXDmHK6KNzcc93hL6SK42vtKJJLUi2k9lGqFD8zTCoPHBIy6taeSC34hSQn9b7V9M1O2HIE_foYgoDyCbiiVen_hZ2zJU_Kl42GTM4bwdF9_g_BepYXR5CR3AnZHWR-vL69Y_N7HtawigDlJ6O_k4PGArtYaiSVwIKSq-dlOfRSY2dbIDjInTgVX28H4jJLK0Fn2YbTKCLi4XUzg9Kna56tOESmA3LtFe4JvstxcY4TfANoz5sBo6iyh6QeSXd1PSB67Eu2L1tZCsdj1imuIeYjxt25KuEpl3rYDdh-PV_myCRWsNEw0zELId9zZt5pAYnBpVv7HJDWC98HeWnPlhbWo4fgF7nwLLQj589eNT9fG9vdDFjhwx9-iX4XF2S370zfdXIsn6LgzHZUjv-jbyyIQP7SpK7xkc5IRTEJYJwhyIPCIXqr7SqmJ_a0eefnm2TBs6XC5az7VFLWxvx2UWQDWJeunrN4u231ESI4DYAUeo3sY74ItWc_EWdkG_ob5fxLckvz8SHMex-_aOmo6z9V3I_29eAkv4oStJsPO0Wm338l4fOrqh-19yoRN6seh57cueNwiZ7bmInUgDhJnzmt6MBb4EcBsu7Gfz0mKZs74pfRM5D_lNmK0OLTJ8a0QquVhBOz20eRpDMLXwtWdAkrqGR41FvIGj6zyLszRUv_yhWR5F66DEO_iIr_tjyk-lDNF3nwO2JXu9bo0cOdSMED72mumVmtPiuPGlhRD9uu0-Zlc1JM2rP0y3s8UqmMf_ESLztR5v1LvOS8yA23EHriP7FT4XblZHQyQlL-vXyEFMhgUlOOmPUqm2E1GT-l4ZD5z7gQpe6S9Cix4fw_0e1PXmVZFZYOvJGaPx6vYVDJZnOc5lHeMY2xOXewSwo99CWDQzFVDL0P9s-QPducQRenE9IqKpeeGMN19t4Uy_EzbTvTVvJsJ2Z4zZc429ecJUqSqv96g7qCiW40fG-f3AV4WXRu6kHDPzLnHa6xiGenGbCVZQgiahlAc5LAnJ0m_D28ZjEo5-kgdlrOGCfjx3BfgXGZNSYKvEbWNwuw_RPHBN-oL7PVYOkwJNSI9IPaNAjIipDhZgdM6gOla3JAhyaQH0ga0Oo2lwLIYMOK9tgH8FwkwvtL-fZM34Rlp7Vr6Sd6cIeD7nMXTDPK1qNzr01Y38wKNYCjh6IwgZmUEmFFfzLLGS_hOLprZnmCneTgpUFXvDwt4ZzXLjxcn_IBAfbc5q2imtn8kgBtGkQRbYWvP2B79Qg9KkTtowWQgBQUWAyDYvv0EdcvKJyOP6Zx2jcPiqR-OvMLQcxxUBM4h9RaSaYMBgRSn-dAATo6ABYrtbSyF__P60W21HIpW3XfJwmiR2x0yvJd_o7T-BZL_2lYaYqWnsjkdNAMT1htQmWRKKqBbGy2nhHrBVdsW43vQbd2RAbdeXm_M3rZnopR_AMcqC4otR5AE_Q5EqPDE6lsp4LEfu-aSOzqbx0KgUYTt7Gn2J6YqFZBmZIbauHzYr19gCWDrLErTZgq9CkHEtU8DzNnqhitDxwbpUag71NMhPUQvyfhHm250hBJpovc3YjtIP3xsU6FSos5qjrww9TvDzBVrKdnbe0c20BgP5YuJsyTXfHxRE84nuqUhBAo4O5hKp8zhV-3OzBwnV1Ev-PMhDlHFChntOmiEwEHYo5a_4Q8Ai9bTkFRML7YFJB8GK4VlEfsHfv1gHi6bklOF8zOGD0sZCL3A7UiHdteBZ4D1hz9Mt3HcKbBJ0INVQ9uyUzILOR55slpN7hiSroLVIl_AEcjOlPl-DBqQRiL24p1TKiL4FMHmyzX8XbIoee0b1qhsS_SJlSUuz2mhCe2leWxRL43pnv2buoD4ccNh9QQdOTLllk2HaZKA=="}}
{"timestamp":"2026-02-11T04:31:55.186Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"python3 - <<'PY'\\nimport math,random,itertools\\nm=325\\nlim=math.isqrt(m)\\nS=[]\\nfor x in range(-lim,lim+1):\\n    y2=m-x*x\\n    if y2<0: continue\\n    y=math.isqrt(y2)\\n    if y*y==y2:\\n        S.append((x,y));\\n        if y:S.append((x,-y))\\nS=list(dict.fromkeys(S));Sset=set(S)\\n# pairs\\npairs=[];used=set()\\nfor v in sorted(S):\\n    if v in used: continue\\n    w=(-v[0],-v[1]); used.add(v);used.add(w)\\n    pairs.append((v,w))\\n# D and Tang\\nmd=2*lim+2\\nD={}\\nfor dx in range(-md,md+1):\\n    for dy in range(-md,md+1):\\n        if dx==dy==0: continue\\n        if dx*dx+dy*dy==4*m: continue\\n        c=0;u=None\\n        for ux,uy in S:\\n            if (ux-dx,uy-dy) in Sset:\\n                c+=1\\n                if u is None:u=(ux,uy)\\n        if c==2:D[(dx,dy)]=u\\nTang={(dx,dy) for dx in range(-2*lim-2,2*lim+3) for dy in range(-2*lim-2,2*lim+3) if dx*dx+dy*dy==4*m}\\n\\ndef eval_U(U):\\n    k=len(U)\\n    C=[]\\n    for mask in range(1<<k):\\n        if mask.bit_count()%2: continue\\n        x=y=0\\n        for i,(a,b) in enumerate(U):\\n            if mask>>i &1:x+=a;y+=b\\n        C.append((x,y))\\n    n=len(C)\\n    H=set();\\n    for i in range(n):\\n        x1,y1=C[i]\\n        for j in range(i+1,n):\\n            x2,y2=C[j]\\n            dx,dy=x2-x1,y2-y1\\n            if (dx,dy) in Tang or (-dx,-dy) in Tang:\\n                return None,n\\n            if (dx,dy) in D:\\n                ux,uy=D[(dx,dy)]\\n                H.add((x1+ux,y1+uy));H.add((x2-ux,y2-uy))\\n            elif (-dx,-dy) in D:\\n                ux,uy=D[(-dx,-dy)]\\n                H.add((x2+ux,y2+uy));H.add((x1-ux,y1-uy))\\n    return len(H),n\\nrandom.seed(1)\\nfor k in [4,5,6,7,8,9,10]:\\n    ok=0;tang=0;best=10**9\\n    for t in range(300):\\n        idxs=random.sample(range(len(pairs)),k)\\n        U=[]\\n        for i in idxs:\\n            a,b=pairs[i]\\n            U.append(a if random.getrandbits(1) else b)\\n        h,n=eval_U(U)\\n        if h is None:\\n            tang+=1;continue\\n        ok+=1;best=min(best,h-n)\\n    print('k',k,'tested',300,'non-tangent',ok,'tangent',tang,'best diff',best if ok else None)\\nPY\"}","call_id":"call_0DWQr6JXUFFFFZkgK6657UpH"}}
{"timestamp":"2026-02-11T04:31:55.212Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":2789370,"cached_input_tokens":2671360,"output_tokens":57740,"reasoning_output_tokens":36573,"total_tokens":2847110},"last_token_usage":{"input_tokens":75262,"cached_input_tokens":75136,"output_tokens":984,"reasoning_output_tokens":161,"total_tokens":76246},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":11.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:31:56.490Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_0DWQr6JXUFFFFZkgK6657UpH","output":"Chunk ID: 6b646d\nWall time: 1.1496 seconds\nProcess exited with code 0\nOriginal token count: 97\nOutput:\nk 4 tested 300 non-tangent 300 tangent 0 best diff 0\nk 5 tested 300 non-tangent 279 tangent 21 best diff 0\nk 6 tested 300 non-tangent 238 tangent 62 best diff 4\nk 7 tested 300 non-tangent 88 tangent 212 best diff 34\nk 8 tested 300 non-tangent 10 tangent 290 best diff 212\nk 9 tested 300 non-tangent 0 tangent 300 best diff None\nk 10 tested 300 non-tangent 0 tangent 300 best diff None\n"}}
{"timestamp":"2026-02-11T04:31:56.519Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:31:56.928Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":2789370,"cached_input_tokens":2671360,"output_tokens":57740,"reasoning_output_tokens":36573,"total_tokens":2847110},"last_token_usage":{"input_tokens":75262,"cached_input_tokens":75136,"output_tokens":984,"reasoning_output_tokens":161,"total_tokens":76246},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":11.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:32:43.967Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Planning exhaustive parity subset search**"}}
{"timestamp":"2026-02-11T04:32:43.967Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Planning exhaustive parity subset 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"}}
{"timestamp":"2026-02-11T04:32:58.914Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"python3 -u - <<'PY'\\nimport math,itertools,time\\nm=325\\nlim=math.isqrt(m)\\nS=[]\\nfor x in range(-lim,lim+1):\\n    y2=m-x*x\\n    if y2<0: continue\\n    y=math.isqrt(y2)\\n    if y*y==y2:\\n        S.append((x,y));\\n        if y:S.append((x,-y))\\nS=list(dict.fromkeys(S));Sset=set(S)\\n# opposite pairs canonical\\npairs=[];used=set()\\nfor v in sorted(S):\\n    if v in used: continue\\n    w=(-v[0],-v[1]);used.add(v);used.add(w)\\n    pairs.append((v,w))\\nprint('num pairs',len(pairs),flush=True)\\n# D and tangency for full check later\\nmd=2*lim+2\\nD={}\\nfor dx in range(-md,md+1):\\n    for dy in range(-md,md+1):\\n        if dx==dy==0: continue\\n        if dx*dx+dy*dy==4*m: continue\\n        pts=[]\\n        for ux,uy in S:\\n            if (ux-dx,uy-dy) in Sset:\\n                pts.append((ux,uy))\\n        if len(pts)==2:D[(dx,dy)]=pts[0]\\nTang={(dx,dy) for dx in range(-2*lim-2,2*lim+3) for dy in range(-2*lim-2,2*lim+3) if dx*dx+dy*dy==4*m}\\n\\n# Precompute even masks for k=10\\nk=10\\neven_masks=[mask for mask in range(1<<k) if mask.bit_count()%2==0]\\n\\n# function to build centers quickly\\ndef centers(U):\\n    # dynamic subset sum\\n    pts=[(0,0)]\\n    for a,b in U:\\n        pts += [(x+a,y+b) for x,y in pts]\\n    # filter even parity by bitcount from order? easier recompute\\n    C=[]\\n    for mask in even_masks:\\n        x=y=0\\n        i=0\\n        mm=mask\\n        while mm:\\n            lsb=(mm & -mm)\\n            idx=(lsb.bit_length()-1)\\n            x+=U[idx][0];y+=U[idx][1]\\n            mm-=lsb\\n        C.append((x,y))\\n    return C\\n\\ndef tangent_exists(C):\\n    n=len(C)\\n    for i in range(n):\\n        x1,y1=C[i]\\n        for j in range(i+1,n):\\n            dx,dy=C[j][0]-x1,C[j][1]-y1\\n            if (dx,dy) in Tang or (-dx,-dy) in Tang:\\n                return True\\n    return False\\n\\ndef perfect(C):\\n    n=len(C)\\n    H=set();edges=[]\\n    for i in range(n):\\n        x1,y1=C[i]\\n        for j in range(i+1,n):\\n            x2,y2=C[j]\\n            dx,dy=x2-x1,y2-y1\\n            if (dx,dy) in Tang or (-dx,-dy) in Tang:\\n                return False,None\\n            if (dx,dy) in D:\\n                ux,uy=D[(dx,dy)]\\n                H.add((x1+ux,y1+uy));H.add((x2-ux,y2-uy));edges.append((i,j))\\n            elif (-dx,-dy) in D:\\n                ux,uy=D[(-dx,-dy)]\\n                H.add((x2+ux,y2+uy));H.add((x1-ux,y1-uy));edges.append((i,j))\\n    # connectivity\\n    g=[[] for _ in range(n)]\\n    for i,j in edges:g[i].append(j);g[j].append(i)\\n    vis={0};st=[0]\\n    while st:\\n        u=st.pop()\\n        for v in g[u]:\\n            if v not in vis:vis.add(v);st.append(v)\\n    return len(vis)==n and len(H)==n,(len(H),len(edges))\\n\\nstart=time.time();tested=0;non_tangent=0\\nfor comb in itertools.combinations(range(len(pairs)),k):\\n    for bits in range(1<<k):\\n        U=[]\\n        for t,pi in enumerate(comb):\\n            a,b=pairs[pi]\\n            U.append(a if (bits>>t)&1 else b)\\n        C=centers(U)\\n        tested+=1\\n        # fast tangency check\\n        if tangent_exists(C):\\n            continue\\n        non_tangent+=1\\n        ok,info=perfect(C)\\n        if ok:\\n            print('FOUND perfect',comb,bits,'tested',tested,'non_tangent',non_tangent,'time',time.time()-start,flush=True)\\n            print('U',U,flush=True)\\n            raise SystemExit\\n    if tested%10000==0:\\n        print('progress tested',tested,'non_tangent',non_tangent,'elapsed',round(time.time()-start,1),flush=True)\\nprint('done none tested',tested,'non_tangent',non_tangent,'time',time.time()-start,flush=True)\\nPY\"}","call_id":"call_R7SdFaQT5yAdhfSQumP6zDGp"}}
{"timestamp":"2026-02-11T04:32:58.919Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":2865793,"cached_input_tokens":2747520,"output_tokens":61169,"reasoning_output_tokens":38761,"total_tokens":2926962},"last_token_usage":{"input_tokens":76423,"cached_input_tokens":76160,"output_tokens":3429,"reasoning_output_tokens":2188,"total_tokens":79852},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":11.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:33:09.069Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_R7SdFaQT5yAdhfSQumP6zDGp","output":"Chunk ID: d84726\nWall time: 10.0013 seconds\nProcess running with session ID 4404\nOriginal token count: 4\nOutput:\nnum pairs 12\n"}}
{"timestamp":"2026-02-11T04:33:09.102Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:33:09.516Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":2865793,"cached_input_tokens":2747520,"output_tokens":61169,"reasoning_output_tokens":38761,"total_tokens":2926962},"last_token_usage":{"input_tokens":76423,"cached_input_tokens":76160,"output_tokens":3429,"reasoning_output_tokens":2188,"total_tokens":79852},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":11.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:33:10.581Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Monitoring long-running poll**"}}
{"timestamp":"2026-02-11T04:33:10.581Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Monitoring long-running poll**"}],"content":null,"encrypted_content":"gAAAAABpjAaGUQR4H4Pzrikn9IC-kUk5IkuXm5qu0Q3v973qYRHQlzJmYVIkPQ3GrIZUJR0d3JdjxfKIS018xAFPTCoiEKaIj4eCIaVoyZ07gdt7pp3ebX8-C8X1nyNBD92oUS5jKAGrYkT3TeC3JOBGYmNSIIho724U8YUa7fpDDWk2SlEUUg6pED_Q1328cTz4WFTSz8CUKJHSQnNxwhLK9P0JY3BaGp13UePZ_AQhdxov8G0Iy0h-Hs6hybH2YQ55ucetz-UYtJ2mL6d_69IHYrBOF8uwTe_eDNyV4p8nKVLUDzDlHCUIjQiNe0OrhpBjyhOynpQHlmIGpcwkth6rYehpx2BJEKjPMxm1-9Fvk35_AYoYck6UT3HP8bas3PjjXiEKZZR_JFbUhrhq_ACQGXM5bftDFmPCLme-XB1krjjp1WO_fqozP90rvogVST6NjyJwtxyDQxBMvkd5DfnEKkqwvGSSgEq2jxsMtbaO3w8uLNgvRLMmXYvoJUVyido8fmG2MFxkV2fF-RrEH5RzXnfIzvrMO9TM7KUfuObw4igKCVCDuCcfVzPqtp-0Y05M2m9XoaxAWWeE9tsGSNH68-lJwWB8Oc4sUSt17wd-v3xtjT_7X1nsq3GFGqTv7G9bI5AJTQkn6pvfmpw7JCwHBQucCMos6iPvfpM3j0iNoizzvZTfoZWaecL63F6_oEzZ0V6dvyScFoTn0ZPtvl4GSrzsNPxYL7dDcwp5bi85rXj0hYoPg42z3oz4osOIvsAsN9ETozFc7JnPzh75Kz5gVlFOcIGY1Xlb5hiNZJu_9KtK27mrNPawnfLN2uJa56SbS_G2k5kl69d1NM6guJShRCRn4OeWIW1AZFfW6DOG4VfEjqybqPg="}}
{"timestamp":"2026-02-11T04:33:10.888Z","type":"response_item","payload":{"type":"function_call","name":"write_stdin","arguments":"{\"session_id\":4404,\"chars\":\"\",\"yield_time_ms\":30000}","call_id":"call_GAGuOlaYlGT5tJEWdOO1KSl9"}}
{"timestamp":"2026-02-11T04:33:10.918Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":2945697,"cached_input_tokens":2825728,"output_tokens":61211,"reasoning_output_tokens":38771,"total_tokens":3006908},"last_token_usage":{"input_tokens":79904,"cached_input_tokens":78208,"output_tokens":42,"reasoning_output_tokens":10,"total_tokens":79946},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":11.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:33:30.288Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_GAGuOlaYlGT5tJEWdOO1KSl9","output":"Chunk ID: ba6294\nWall time: 19.3663 seconds\nProcess exited with code 0\nOriginal token count: 15\nOutput:\ndone none tested 67584 non_tangent 0 time 30.68258285522461\n"}}
{"timestamp":"2026-02-11T04:33:30.288Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:33:30.686Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":2945697,"cached_input_tokens":2825728,"output_tokens":61211,"reasoning_output_tokens":38771,"total_tokens":3006908},"last_token_usage":{"input_tokens":79904,"cached_input_tokens":78208,"output_tokens":42,"reasoning_output_tokens":10,"total_tokens":79946},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":11.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:33:33.238Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Confirming no non-tangent cases with k10, planning tests for k11 and k12**"}}
{"timestamp":"2026-02-11T04:33:33.238Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Confirming no non-tangent cases with k10, planning tests for k11 and k12**"}],"content":null,"encrypted_content":"gAAAAABpjAadwHjvrsJhHEHF-v-j-T5MZa46Am-eJGVju8OdfTbXJgsgZ4GK-tBq-srwholE_Il0015onclzDXtd8yawnevVtWU5NU5ELDnEwojL0BM-TbpASbA86o8wFJuxwvpaURFyK3jbwo4eFeYWXswBAYTV3r973hm62LiTnszn2ZDzj4GY-Ncgc1Osvn9NLdPZC8hfqLrAVcxWqWh5834cgMvyOikWtY08eEWuRXemymhMpvs6x-akfkN0vdsmagULyeAcreJhVOKSgSj2X6cy054B-fQ7WND6ywEn_w6Fjc4rc6Ubm5p1aLOuCggxdyZqA0WwbWDDuIrUSjNfXrPhmp9mhBZlITO8gT4sFflfI89GXetupng73qK7vpj3dxsmfyQ10jNs-wamk_QnKGA76NQBP44ulGUZDJceO_ek-7EYqtXjcDkN5ZIQmjoE7Lel3RR5VuK_I2sSL3Yx-UklU2sJQicR_qkjWELyslljpxQkPk5kJZItEHKJjUZ2sJyRZBcc7dyclE_tnGTs_tL8-qkcQbvAOdcJzkT4YTOUsBmKaK6qSktUCfbwfOrzNC1eb2HsjQ-2dOXOpxXwPtSeIesJQj0gPwehjGWmtZ9TMdtKpkfrWH84UyXVOmB-T5lu5T-lQKD4y1HPtq6Gh6iTNrcy-lkQWYqeIcLpooyF1U2dxoidCZO8FuGNbB6osVUAQ9GjLfX_zi5E9ORtiwAUcRzxVfZUPFaTLxjXS-XYnrAceNns5y6MnD_9Ryla6rynA_LbOapi0jbukuvmykNuRDKWhF8XatFhi1Lg_659okc9v5DzyDu_vaf9SvWom8UVTQXdGEs9HYLQ0R4OwFLagr2w4VfBo8d-9azSz_afeGSAKy0biYW2gYZOi4zyaT5fs5Tb9sZBBGTnwx9nr7cNaeItzhAio58zmuB6JaW8puQJPNfaESclvrrtFguwT-N2VkqwLuQQxSP9TbF9UD0n34DdCEcRO2IivKymgK2gCifwLOOx9NX0BCVbZNPuU1Bhf4C5rPtvtZgYqVKhRjHYepEtqsuRkGnYlM9mAV8k43bkGNcUzjs9t2a6-SwhIFkltF7m7WO0cK-vmR1Jd8qZ4s7VurMtv-RdYj4jVJNc7Fx2UpyCoqrSBJax1siySrQAoi00if0UzNA3XLlqU0MSJCfjkLEMcGJs0CkCLw4H1Y2cThybvIULnW_s-HmgUvVpytzz8YofU0vzHzNfu4pdjMx_dQ=="}}
{"timestamp":"2026-02-11T04:33:41.016Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"python3 - <<'PY'\\nimport math,itertools,time\\nm=325\\nlim=math.isqrt(m)\\nS=[]\\nfor x in range(-lim,lim+1):\\n    y2=m-x*x\\n    if y2<0: continue\\n    y=math.isqrt(y2)\\n    if y*y==y2:\\n        S.append((x,y));\\n        if y:S.append((x,-y))\\nS=list(dict.fromkeys(S));\\npairs=[];used=set()\\nfor v in sorted(S):\\n    if v in used: continue\\n    w=(-v[0],-v[1]);used.add(v);used.add(w)\\n    pairs.append((v,w))\\nTang={(dx,dy) for dx in range(-2*lim-2,2*lim+3) for dy in range(-2*lim-2,2*lim+3) if dx*dx+dy*dy==4*m}\\n\\ndef build_centers(U):\\n    k=len(U)\\n    C=[]\\n    for mask in range(1<<k):\\n        if mask.bit_count()%2: continue\\n        x=y=0\\n        mm=mask\\n        while mm:\\n            lsb=mm&-mm\\n            i=(lsb.bit_length()-1)\\n            x+=U[i][0];y+=U[i][1]\\n            mm-=lsb\\n        C.append((x,y))\\n    return C\\n\\ndef tangent_exists(C):\\n    n=len(C)\\n    for i in range(n):\\n        x1,y1=C[i]\\n        for j in range(i+1,n):\\n            dx,dy=C[j][0]-x1,C[j][1]-y1\\n            if (dx,dy) in Tang or (-dx,-dy) in Tang:\\n                return True\\n    return False\\n\\nfor k in [11,12]:\\n    tested=0;non=0\\n    st=time.time()\\n    for comb in itertools.combinations(range(len(pairs)),k):\\n        for bits in range(1<<k):\\n            U=[]\\n            for t,pi in enumerate(comb):\\n                a,b=pairs[pi]\\n                U.append(a if (bits>>t)&1 else b)\\n            C=build_centers(U)\\n            tested+=1\\n            if not tangent_exists(C):\\n                non+=1\\n                print('k',k,'found non-tangent candidate',comb,bits)\\n                raise SystemExit\\n    print('k',k,'tested',tested,'non',non,'time',time.time()-st)\\nPY\"}","call_id":"call_cd51WanBIrpb1cmiWeSmTU3H"}}
{"timestamp":"2026-02-11T04:33:41.042Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":3025709,"cached_input_tokens":2905600,"output_tokens":61887,"reasoning_output_tokens":38841,"total_tokens":3087596},"last_token_usage":{"input_tokens":80012,"cached_input_tokens":79872,"output_tokens":676,"reasoning_output_tokens":70,"total_tokens":80688},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":11.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:33:51.172Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_cd51WanBIrpb1cmiWeSmTU3H","output":"Chunk ID: 9d4d9a\nWall time: 10.0013 seconds\nProcess running with session ID 33425\nOriginal token count: 0\nOutput:\n"}}
{"timestamp":"2026-02-11T04:33:51.204Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:33:51.629Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":3025709,"cached_input_tokens":2905600,"output_tokens":61887,"reasoning_output_tokens":38841,"total_tokens":3087596},"last_token_usage":{"input_tokens":80012,"cached_input_tokens":79872,"output_tokens":676,"reasoning_output_tokens":70,"total_tokens":80688},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":11.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:33:52.513Z","type":"response_item","payload":{"type":"reasoning","summary":[],"content":null,"encrypted_content":"gAAAAABpjAawtIr4ljz3JzWApTDV3RgxjKqmSHFAa5ewxRafVXQzP88X1LZ7n9BzaS_na0RbO4qoUp6QL5r0-MFaWiVvhWh5cCe9LsnZ9629hU6FCTDI2it44hDEWzxPYR5n1qogGRUgEhoe2IBTpgjDSdG-TKG44RUxDPtPjNVH63jztH37y8se0UvbVtFfeogfPLw466ymW9ZCl3Fg5Z1PCMR76uRKf7WsrAw11ATMmZUWmzx7Zs_LY8fU-0quYjFHJwPpZdNwNYBOdX-1HoNOFtIgac85s9lxTQYxKdUTSQp0dllaIKBQdoYzWs5G0iEEL6EhaNbsBQ26VErXhjUhKOGMzrlrkK1cmRLRwejoDohfVaVL_wP7iowBwXR4WPR9kxFcUj04vGPDlYewttarh8h05Kt2jg7BiAUNGAwtxRHGDTGmIz47vlNLPjyPNdADOxb7ZWAXuwzuVhArquQD74dWQw7DDYJF-Oj22Cvtadw7q41ZakXg2uy0iGt-yOBwGtHVbU4hd78ZhGU02853K7dp_s1cKlX3OAEL_1AT9u0giwp1NvhVLOL9mIUCtFOmAZMnBp2NJe45RRWIbb4BdMkpjMdVT3zU4QLxqU9SaMelJFKZOozaRwGrK7PuSE27HnR_jDlM_LvUAOVWrMdVPIgCMC2Jc3eqjXAtgEw3DUSECZ3ntPMm61sWy4Y5nvP_NnD6arIO4QKCS3HjQP7QoadWo2Y9_RyBzgG9g7fZWanmqmPqytBq7IHpyeEk70FZItL7I7gY0Y6bcAnIR7DTHna_IbSyFYluJLR7J1sFSC2OW4Y9U-0iSzQhTA01cxrESH-W8kjsFKRciTsW67wqTPMAABrCrg=="}}
{"timestamp":"2026-02-11T04:33:52.888Z","type":"response_item","payload":{"type":"function_call","name":"write_stdin","arguments":"{\"session_id\":33425,\"chars\":\"\",\"yield_time_ms\":30000}","call_id":"call_jc8t4yRJqEpj64cFw1sV7XzY"}}
{"timestamp":"2026-02-11T04:33:52.918Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":3106447,"cached_input_tokens":2984832,"output_tokens":61925,"reasoning_output_tokens":38847,"total_tokens":3168372},"last_token_usage":{"input_tokens":80738,"cached_input_tokens":79232,"output_tokens":38,"reasoning_output_tokens":6,"total_tokens":80776},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":11.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:34:09.272Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_jc8t4yRJqEpj64cFw1sV7XzY","output":"Chunk ID: 917f35\nWall time: 16.3509 seconds\nProcess exited with code 0\nOriginal token count: 24\nOutput:\nk 11 tested 24576 non 0 time 20.56619906425476\nk 12 tested 4096 non 0 time 7.026493310928345\n"}}
{"timestamp":"2026-02-11T04:34:09.272Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:34:09.733Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":3106447,"cached_input_tokens":2984832,"output_tokens":61925,"reasoning_output_tokens":38847,"total_tokens":3168372},"last_token_usage":{"input_tokens":80738,"cached_input_tokens":79232,"output_tokens":38,"reasoning_output_tokens":6,"total_tokens":80776},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":11.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:34:15.898Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Planning exhaustive orientation search**"}}
{"timestamp":"2026-02-11T04:34:15.898Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Planning exhaustive orientation search**"}],"content":null,"encrypted_content":"gAAAAABpjAbHBDhB2XEpUX3UEHG7gEbIT7fMxm4E8-PvMwtg0YzTYxa3kSGDoPwl5DmXDHzYSIYtSv0fjs-7fVL0dRZVXMkdELFWj0CeigiQNykOypgMXrdnH-qhQy6y5QrghZGVW0lGz7-sMJeNNrGFuAjP7oivbzkrMKe4DgC5JD7nDVDqWcRscBJ1p5_UjJkYBnGKJEAAbZoDikRIYDy31quAaRKipXyXn7LxbIIZP7XVQULeYi60e6GQOhbI_GT4c3y6ZqCxZFudfXV3nV_fHtWCh-qxEDm6icfOMU0x-B3jFEokIijgT8FLP5F0sOA429BisBOwGzpNcWxkh3vzGnGHOaIk25OYFR_ccoNfBn67D_JRHGaTSDMd42-i7S1k7mYSTStHGr_IX4tnW4fnyG2A54V2RuyatbpyZYSuc2erIsGfkMYsaICcolLIC0jfsYKKsFF9VcGDgRrETPiLaoMQp66sAIsnkrk1OI4QhDLhzWDfv7uWoDc2HXsehri1kQRqv5enjlTv98sm9RRcBwWx_QcBvokYwQ4xCVh8meDTtenpymIQObYLH39jC4upV-TvPGOGmnd0BwarJ1w7DagaeOPhbb5ms-i07Z4S3mcrZ9tpLaViI6lM0DrT1i9KGI4kbp-D4ZA-ReAryHEuTXBtdmpJ0Cn9XI7uRB-pAYC7FuhmM0qo2S9zSy9q4SJB77nZzcrraBBHQNGrchCFHGgBsqEJyHeZfTuNeTkS_BO0YoI0zlVuNh_WYmbCW8ULckv9V47qqXx3UQJ28bZUW14Y2PxtnDLdlxu2ZIYLDpv64Mmqx-7FxG8XS8C-hLOOw7IXMA20RClNgeb_x7SPfnIlgUCLCSjF9tG-uwnR3Rd7cpvLZOyGPHXPboojwsPXzH0Nut362YNaILkhnizemUE-sPLF-RL0jSd-rai5NDFqTcO_sDot5Wy-JqVdcFU_ApzqOBpaagiR1vOWr_-7ilWxMBGA7Du6lyzbrK7r-wvuAmB0ZVOItioCTmzezaqZQ609274XUVyfimOPDHqYXDBRGN1QKFii3_p-Yg1Iw31tG35YpdBzCcsBcGtIyA6nKdA3gu4sDpQ0G9qwnp_AOM93VMVylmrU6voZJZY-eIljRUmZd_RORGUZCzTEV3ZOjencCif_ftpwpHkHbxVYRC1AFandC_WY8W-qi0wX--Zwitq64erbwcEAE3PDzn-KS4SW9VukqIygTZXtWqbUq6aeyKReZpZVX2Cs4IBLBLOXSIq0b6NLw3xb6iZdnjM61nxc6e488fJtMylc_AKfvhxznTaj_4r1RHIrNPt9-_mAofbcqpqeluwyMs_MZ5u6GBYxjm13CB6vB21EYj_61riV3Hbvt6xx49p3JOhoOL_mh78czaQMc6ZVss5glCUNdaXkxXI4-SDJAyjDZDnviHC2JJHvM2q_yXaKZPYPHNx_mkUnrvkZk4VJXVvfNmxMjOdNaxVOa36ylxeZQOli3gkN6g7KrfOe2i4rNO1OuaCreiOKyTg_ml8SQ3uc66vao56GPPHcP6o97MyKdVq9s7MhAHzPdoGVu1cwI_m4JDEyYHnPOvu3K2iNvrMnvCZ-KC55sGAi2-0YJ3PMWN9a170skQPrWYn12-eC8O7d2CZ3VHeVdWMVg1Ydjnrq-Yy-IzIB_gYUx_yrhfJwyQTgGF-YTdOD6SElLAAM4ZH4sDUsMpCXBGW55YpoR8qqUrLOuY_GVDZIkIrUyWUMJYf-XuAObyo5OCV9dZLzFhb-5TNqkM5KGYmkRBwki-nAyixlJ-gyoaS9fCghQPk-0zxyK_anDQdMqdzc7bOkCTC5my7fDb5MdnNoNg53hnu04cUu1TtEQIFyds_tYXKUyyS3sxrayHqMALSs8yxCQx9LNu_nh2AwRFOztPUImEL2N9uhYsgNsNY7cSZAiuTFmloS8scYAO4lCEqM3nKWIZ8andK2rAInTp1sgXcmgSQKOpWAB3FEWfanobbB9QbI6sPnYzQ4i6xp3giHddJz8MqkELZo1z3WH-_1WgOt1mt5IcXfbes8t6HtdSpwj6yZiiSznttEBVSae6uxqZN3NbjXj_Urd2heCvlQ4qwzuLur_ZNMNGwceLksc9JRyJhbKQ3kx0XPrnI3gGNML-kJkqTBK8PegdvdTrjG3dHGUPJ8BPO6ndA-ZSI4pgh4MYFXExj-3SDmOvcWJmYmqJPtYx9CLGP5UNdkMky6jNhxxqp61BHCIHApdDKa1bP2WdGzPYyCK_ZTAzhQxw=="}}
{"timestamp":"2026-02-11T04:34:16.623Z","type":"event_msg","payload":{"type":"agent_message","message":"I exhaustively ruled out the 512-vertex parity construction at \\(m=325\\) (every choice forces tangencies). I’m now checking the next key candidate \\(m=625\\), where \\(r_2(m)=20\\) gives exactly 10 opposite pairs and only 1024 orientations to test exhaustively."}}
{"timestamp":"2026-02-11T04:34:16.623Z","type":"response_item","payload":{"type":"message","role":"assistant","content":[{"type":"output_text","text":"I exhaustively ruled out the 512-vertex parity construction at \\(m=325\\) (every choice forces tangencies). I’m now checking the next key candidate \\(m=625\\), where \\(r_2(m)=20\\) gives exactly 10 opposite pairs and only 1024 orientations to test exhaustively."}],"phase":"commentary"}}
{"timestamp":"2026-02-11T04:34:30.604Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"python3 -u - <<'PY'\\nimport math,time,itertools\\nm=625\\nlim=math.isqrt(m)\\nS=[]\\nfor x in range(-lim,lim+1):\\n    y2=m-x*x\\n    if y2<0: continue\\n    y=math.isqrt(y2)\\n    if y*y==y2:\\n        S.append((x,y));\\n        if y:S.append((x,-y))\\nS=list(dict.fromkeys(S));Sset=set(S)\\nprint('r2',len(S),flush=True)\\n# pairs\\npairs=[];used=set()\\nfor v in sorted(S):\\n    if v in used: continue\\n    w=(-v[0],-v[1]);used.add(v);used.add(w)\\n    pairs.append((v,w))\\nprint('pairs',len(pairs),flush=True)\\n# D and tang\\nmd=2*lim+2\\nD={}\\nfor dx in range(-md,md+1):\\n    for dy in range(-md,md+1):\\n        if dx==dy==0: continue\\n        if dx*dx+dy*dy==4*m: continue\\n        pts=[]\\n        for ux,uy in S:\\n            if (ux-dx,uy-dy) in Sset:\\n                pts.append((ux,uy))\\n        if len(pts)==2:D[(dx,dy)]=pts[0]\\nTang={(dx,dy) for dx in range(-2*lim-2,2*lim+3) for dy in range(-2*lim-2,2*lim+3) if dx*dx+dy*dy==4*m}\\nprint('|D|',len(D),flush=True)\\n\\nk=len(pairs)\\nassert k==10\\n# precompute even masks list\\nmasks=[mask for mask in range(1<<k) if mask.bit_count()%2==0]\\n\\ndef build_centers(U):\\n    C=[]\\n    for mask in masks:\\n        x=y=0\\n        mm=mask\\n        while mm:\\n            lsb=mm&-mm\\n            i=(lsb.bit_length()-1)\\n            x+=U[i][0];y+=U[i][1]\\n            mm-=lsb\\n        C.append((x,y))\\n    return C\\n\\ndef evaluate(C):\\n    n=len(C)\\n    H=set();edges=[]\\n    for i in range(n):\\n        x1,y1=C[i]\\n        for j in range(i+1,n):\\n            x2,y2=C[j]\\n            dx,dy=x2-x1,y2-y1\\n            if (dx,dy) in Tang or (-dx,-dy) in Tang:\\n                return None,None,None\\n            if (dx,dy) in D:\\n                ux,uy=D[(dx,dy)]\\n                H.add((x1+ux,y1+uy));H.add((x2-ux,y2-uy));edges.append((i,j))\\n            elif (-dx,-dy) in D:\\n                ux,uy=D[(-dx,-dy)]\\n                H.add((x2+ux,y2+uy));H.add((x1-ux,y1-uy));edges.append((i,j))\\n    # connectivity\\n    g=[[] for _ in range(n)]\\n    for i,j in edges:g[i].append(j);g[j].append(i)\\n    vis={0};st=[0]\\n    while st:\\n        u=st.pop()\\n        for v in g[u]:\\n            if v not in vis:vis.add(v);st.append(v)\\n    return len(H),len(edges),len(vis)==n\\n\\nbest=10**9\\nstart=time.time();non_t=0\\nfor bits in range(1<<k):\\n    U=[]\\n    for i,(a,b) in enumerate(pairs):\\n        U.append(a if (bits>>i)&1 else b)\\n    C=build_centers(U)\\n    h,e,conn=evaluate(C)\\n    if h is None:\\n        continue\\n    non_t+=1\\n    diff=h-len(C)\\n    if diff<best:\\n        best=diff\\n        print('bits',bits,'new best diff',best,'h',h,'n',len(C),'conn',conn,'edges',e,'elapsed',round(time.time()-start,2),flush=True)\\n    if diff==0 and conn:\\n        print('FOUND perfect bits',bits,'elapsed',time.time()-start,flush=True)\\n        print('U',U,flush=True)\\n        break\\nelse:\\n    print('done no perfect non_tangent',non_t,'best diff',best,'time',round(time.time()-start,2),flush=True)\\nPY\"}","call_id":"call_n2M8azEUkbP6wunMoCGP9tIO"}}
{"timestamp":"2026-02-11T04:34:30.608Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":3187309,"cached_input_tokens":3065472,"output_tokens":63356,"reasoning_output_tokens":39119,"total_tokens":3250665},"last_token_usage":{"input_tokens":80862,"cached_input_tokens":80640,"output_tokens":1431,"reasoning_output_tokens":272,"total_tokens":82293},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":11.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:34:40.761Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_n2M8azEUkbP6wunMoCGP9tIO","output":"Chunk ID: 19fbc3\nWall time: 10.0016 seconds\nProcess running with session ID 28108\nOriginal token count: 24\nOutput:\nr2 20\npairs 10\n|D| 180\nbits 0 new best diff 706 h 1218 n 512 conn True edges 11873 elapsed 0.04\n"}}
{"timestamp":"2026-02-11T04:34:40.795Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:34:41.227Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":3187309,"cached_input_tokens":3065472,"output_tokens":63356,"reasoning_output_tokens":39119,"total_tokens":3250665},"last_token_usage":{"input_tokens":80862,"cached_input_tokens":80640,"output_tokens":1431,"reasoning_output_tokens":272,"total_tokens":82293},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":12.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:34:42.204Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Streaming process output**"}}
{"timestamp":"2026-02-11T04:34:42.204Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Streaming process output**"}],"content":null,"encrypted_content":"gAAAAABpjAbiDhXFzh7okWs2DeRLQLSPoUQ1NAFY1nPIb3CqPZbXeIfqF9p3THrlRiQL75S6Ao5DQMPaWHRGTuYEr4jU153ZvIhudhtQFy-5ZV3DWZhSsBBO-6NFkg2AamfmYLx8de2aKVrWSnmLoHdtWVFrHVmpqDKvnaQP2xEzZKOJzZm-qagY3cmSi9QvjY2J4rb76OlSZqzX_Sd2WI-g0dhsMeJZNOj2rwpp00137b4rs-SlCcTzvfPZSeQ7in6MzuczjIwTGXwzlPgSvfFL5KxEMMqyGddWufp9GkpJ2HiJfJomDUgU5pMkXtmXBLCUEjnVV9uSxkPq4mg0WGzMBAEoYzzbsuWzSeF8TM65gOTUM4I-SW9gUFRpuRcFLW5uWCQW_WfJKoMt5KvpU52LUm1ACD1cD8GTCOZFePivHzxDpsLz5CR487nXKcQdXUt9DO4HsgKYyOz0n5-S7RHwmw8YWa-XZAau1DMCdk26xHPs2klSYD8V6BtQWTSTsdUo7okQf0d2_g5jex0YQ5rF9UjvU-u7S51sjnt_CYEOw4GbSx-UDw9kHWW_eb18SUYzQ6Td1LcmSX6OF_G5FPAXiVHq6NXL89iLrCdoVipHy_RJQB22928Re4f9hDlWzKTWdFcXzkpJeIzYkMBHUeEZz-0KXfypSPSo49iyAGkz2AFMY3uoZYNCqPqtjNn3M_8qoBlIwpmU7ds2i8HaqwdWVB6mrTVD1ZSmbZv3Fbw2KKns3-wF4XXtgdevyEiEI61nJ57te3JtNaHM_2SIxBrBW7QwVfo0WmcNge9KbHB3T-52S4mxJ27gqsMaUAwOAjDaZjTwF-6o01tM7LNISHN17LJp63Mj6YctsQ_PvNihs1NXKhfIfVp0wL2WOV3WhSlwoAOp0VWRwpIxZzEKT0Fz-k_JIianEiZJIwolK-3lknhjshgVIEs="}}
{"timestamp":"2026-02-11T04:34:42.856Z","type":"response_item","payload":{"type":"function_call","name":"write_stdin","arguments":"{\"session_id\":28108,\"chars\":\"\",\"yield_time_ms\":30000}","call_id":"call_2zZ8QjQK2yD96lpP9t7ejdIx"}}
{"timestamp":"2026-02-11T04:34:42.884Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":3269692,"cached_input_tokens":3147648,"output_tokens":63405,"reasoning_output_tokens":39136,"total_tokens":3333097},"last_token_usage":{"input_tokens":82383,"cached_input_tokens":82176,"output_tokens":49,"reasoning_output_tokens":17,"total_tokens":82432},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":12.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:35:10.001Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_2zZ8QjQK2yD96lpP9t7ejdIx","output":"Chunk ID: e1fd44\nWall time: 27.1124 seconds\nProcess exited with code 0\nOriginal token count: 15\nOutput:\ndone no perfect non_tangent 1024 best diff 706 time 38.7\n"}}
{"timestamp":"2026-02-11T04:35:10.001Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:35:10.406Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":3269692,"cached_input_tokens":3147648,"output_tokens":63405,"reasoning_output_tokens":39136,"total_tokens":3333097},"last_token_usage":{"input_tokens":82383,"cached_input_tokens":82176,"output_tokens":49,"reasoning_output_tokens":17,"total_tokens":82432},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":12.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:35:20.194Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Shifting from parity to heuristic search**"}}
{"timestamp":"2026-02-11T04:35:20.195Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Shifting from parity to heuristic search**"}],"content":null,"encrypted_content":"gAAAAABpjAcIyUF7OuRzJDt0TAHSzqZYeXSFMgQewTtmpNMmMLnligF5bCaKReYj31Fzs-s9hD4Ck0dTJZgnVM3uolBP2Ssc6rK_qfRSt34OK68Nf6vRZGHt515OggKP1ghgel3kMvY3sQsB39HWHymCTNRKvaJSpRMpq0BdWOAURMeXpq06WwMhP_9s4xoEyqD1OemNCa0rLlHWynKZ5h17XXv88mrED3DM0jjcIURZpmlv5M1YCoBKA9GGLzC9rufGZfoJL49icUnYGAQGeoOeaZV38tFKYyRV_pX-tWJg_VghPrUzX92qyR5Orv2OBrJW76xvAQhDPF8qQPhvZIflE9_PHzMoNMGKC2o7ZgAp2RvMKZiX4iDsI9StowNvHiYnShQHiQJd38LxGFt9cQPQPCwmbNqLOcaAZQT5RRrHtBZiopdDa4SxWw3eV4FCFpRJs9zxLXtEYFj2fGvYY4hdm5pzHvAH3DnZCA0F3CblL1tIjjydYYOmQHlbYgNicDtJidYAuPjykU3GYx3DdCgUSJluGkJmFRCn_fpIStLa3PDhy2DO_w6BJ7QLxezb0VqJm9iwxqX8Gum6kivrV70jQbjZ5k20F2yB0NLMGkxD2pVV4BInk5gwwgRpzSaEjDcfyl1ZrKjReJDDnumqAWg9HbxKclU45rAzqzBpL8-uOcAYEuDPsa9dDfKubh8wpeIrPCR0-N-uk32C1dL6-PHupq4UJ8kqRpxsmnvT3mAUr0vKxBM9BiBHjlfdubgJHgT7alvjziT0nIusKGVQepnpweYWAqklqTge4TJUEzxsgqXWYWV1h4tKC5d0hFukOArvTVX1_9R3ynAEMtj8vmlLaLMdla5mTyYSdws8WhgsOdF4UxDMYhTbLb0irNj1khjNVLEGH8szPSYylAkbABHzqZqiDHJ5gZuWt4r-1n2vRJn0by9EQhuq44GoMTTosjzrS81PsrnL5lsJSWOR4xyknqzzybYhmGVdEsTJYIMriCGgAWDd3HpVLrQRRpemZr6eLhVoq8FEeBn5-tC8v9XiUheEsptYnAB-IQolU3AOBwutLwzUWXG6IdnOYpVdwoPKEQ93xMZm5bb81ebd7nsRFx_ilGDTzdvBmUNSUDePYFF3DvHh4YOJoiI810sEj-d5rmwmvIeOEJcrXzjHM6c-g-AZPFZHz_vNBysMurQumWGBwzyqZoDOGJVLdd8kLRrEUsAYIFrTw5yLbrrfaQZB-ow7XXpwYCv0u5VxAhs2PD9Cvk90Od-QOXxuAffbAo3teB1P2cCPKm-2uSpwM1Fe-tVjT2wRFbk2u5BXPUvTNMbjM-5xu4Ec3-lk6u53eSs31WeRcu5aEywU4yV-BsAvN1D_L405cjd4vkrFnSXUwqhhYI-5o5vQohQknLhvKoPeeghcuIbGaDJBCmbU4pLJQYvUyZQHlfiJV2lRQiX-KY_ffuyU6JIeTvfqMTumE6X_zUnDZyX1DB0JTcQJxYUq6kQi6uC128SjvA4SvCs5A0mtTWGcPhNIaasa9qqRFbM5PfG2CtRGcvKDAmjxtgca0NJLM4VUIJAO7vEeQRkaLTAkmKCuzK6mR0LniOJG3VBZQsZ4T78leIwfDzDH4ilmhkU_Yy50_fMoaeO1gB6W-C7y1SRaf5nMRbFIdny-UpCkCx7ag9aswdCbym06Ru9EFJ4dhXlEk-jjjPBb-A-hTl2ZSd9SUADEqGUgfHAIL0hQP-PjYCIcDKa9d4J8R5qEWui_YQZUwEw72kjWzo5mjZkehEZXIOmk5-6MrpOdWJSKZIlRZV7-3XGUn6KuhK8P3hE049OUivaDVI49SDRNSE5gaTQDzZu5JKiuHwVeD-KxZeBkMcnFpyDUM9bOxZ5JRMqXR_dWFV4ifIpq674C69zc6i_sdS_FUiC0IQ5iuTO1K_DUfuv1UsjkmjZejx8OqbuqTIRavsG63z3Q_xAnWiRE0K4QG0DL_k0McpsS9mSdhAzHaz72rASQcgyVUEu6GXN0FTBf7uFN03tM9ISOA9pmG746movLq9-BvJI2Hu05w0XWxytnWK9pwtF0Xszc0Us1pfWAGRvv8Gr9QtcksIRjtB6UDbMSxs16EPCUbVppUGx3Q1TU6aQK7W2mNcvKuyV_mFCktOfXU0mVlBiYqj9e4fkJX39Z3YwIJgIPfivZwvhZeH62-e1OrLe7VtZqmcSMC6pmzArpFQxzF_fKwGl984Aaf7mYj5CE7QIHVrzUQ9ljavFXS0akwgLrtVx52L2EoAAdHavH71pMR3kfy-YCZXR3LUZFXI36gx4ZsqB1di9Ag5zm0Gwj9KXb0B3r7NJ663ZPapD5OO9vIdktJxG65RJ8Wb0pyQmtlsRBqOVf4ZCikhqmRcChcrNvLyhBxChpmHlpJh_24NUYUZUmkR4PDI3fCngQjh476rMkqF3ByGFn18oT_hBpbm14885U4SQFgWftIWz-ebnoNknbUOacENOHJxN8d2u5S1diAXMxoMcWtvQ6M_f7_4EhggwxhuqQ-pyYdpyGgyUAueE4KiIrlA7SStU12W77qx7bGVZgQy7-EuSvs-Smh8aIKl2PUPeuioWwE1RZ3BvUN8nqQtjG3EPCoRw-cMuqZTtqxOj8II78BSjnwXBj7wuOAm5DeS1aR7SO6SvkC7AVDRhjlZXQoghKhjap0LFRGGlI2STUEhrKrwJdSvCv4zzQRkD73kl-ESJvqhNnDhJcNghBT449RZiUn2Gs4byriunydgRFsJz3paabHr8ueLSShJ9rFlVKNnfA9l1gcHMpI1ddVcs8wao7XBYJaTOpQ05FO63geRxMWgu6Fnmo77HNlGpGORTaT4QBmr4X_6db_X5IktiyaHQMQztuBnU46Xo1nPXxB_bF5FxavFZEPf-ouFFufidAHTMfpRM-813VtjD0Nqp9R67z6EOh75-WUijybTDI85m5XPDLUetHrnEcPZLQ68K5rme41zsFWc4esSa45BsbYr7FJhqvia28U8Dn7r5mGS5One6X4SCI64ZPHd9kvoi0oaNyV_LTTuBkY5yjXnsWrfg0lI3l0-bVfWadMqCGGCUAPYLeYN4yL7QWUoPh-PGmt1UH_9C3oOzTWfBlyRVMPnfBdeU52FP9auM_HtcH2HSUSCKSEhxePy3CR7zTTZNpdSZi9jtE7NmR5_X32DF1baAtyUxesPkjSsBCWWbHhyNtkoOZpQllQsRNRCL2a8C6fjxWBZ2Ar4L7rEO7woIlFmaR0a-041DWqWnvo7mtd8-4QqQc_cc_RVypm_mVBWuT99MISR8iFmeYuwD-Rhkun7NTEndHZJ8VSWqWtEbQH8kIZSieGmFF7oYoxBxD_C5vael73G-5M2wCdf-DnGHVYUvKqyyj63lOLmQj1FBJ_XKKIjatf5Ar782fEbdBkhreZbdHOHLYXQ5GEQcoccxT90V6T7o2pZRjwNCa8LV-xUhY6IWNfc8WP6u26JBMdhV1u45Bj0WZ4aPrzKK0ga0v8pmFYldJpKgd-vydn1tHnXeQWuDPBQ3I0rEhxu276PQdIZway7O2ueMchUUCN9r_HBa-UVY="}}
{"timestamp":"2026-02-11T04:35:36.339Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"python3 - <<'PY'\\nimport random,math,time\\n\\ndef prep(m):\\n    lim=math.isqrt(m)\\n    S=[]\\n    for x in range(-lim,lim+1):\\n        y2=m-x*x\\n        if y2<0: continue\\n        y=math.isqrt(y2)\\n        if y*y==y2:\\n            S.append((x,y));\\n            if y:S.append((x,-y))\\n    S=list(dict.fromkeys(S));Sset=set(S)\\n    md=2*lim+2\\n    D={}\\n    for dx in range(-md,md+1):\\n        for dy in range(-md,md+1):\\n            if dx==dy==0: continue\\n            if dx*dx+dy*dy==4*m: continue\\n            pts=[]\\n            for ux,uy in S:\\n                if (ux-dx,uy-dy) in Sset:\\n                    pts.append((ux,uy))\\n            if len(pts)==2:D[(dx,dy)]=tuple(pts)\\n    Tang={(dx,dy) for dx in range(-2*lim-2,2*lim+3) for dy in range(-2*lim-2,2*lim+3) if dx*dx+dy*dy==4*m}\\n    return S,D,Tang\\n\\ndef search(m,n,iters=800,steps=3000,L=200,seed=0):\\n    S,D,Tang=prep(m)\\n    NBR=list(D.keys())\\n    pset={(x,y) for x in range(-L,L+1) for y in range(-L,L+1)}\\n    def eval(C):\\n        C=list(C)\\n        N=len(C)\\n        H=set(); edges=[]\\n        for i in range(N):\\n            x,y=C[i]\\n            for j in range(i+1,N):\\n                dx=C[j][0]-x;dy=C[j][1]-y\\n                if (dx,dy) in Tang or (-dx,-dy) in Tang:\\n                    return None\\n                if (dx,dy) in D:\\n                    off=D[(dx,dy)]\\n                    H.add((x+off[0][0],y+off[0][1]));H.add((x+off[1][0],y+off[1][1]))\\n                    edges.append((i,j))\\n                elif (-dx,-dy) in D:\\n                    x2,y2=C[j]\\n                    off=D[(-dx,-dy)]\\n                    H.add((x2+off[0][0],y2+off[0][1]));H.add((x2+off[1][0],y2+off[1][1]))\\n                    edges.append((i,j))\\n        g=[[] for _ in range(N)]\\n        for i,j in edges:g[i].append(j);g[j].append(i)\\n        vis={0};st=[0]\\n        while st:\\n            u=st.pop()\\n            for v in g[u]:\\n                if v not in vis:vis.add(v);st.append(v)\\n        if len(vis)!=N:return None\\n        return len(H)\\n    def rand_conn():\\n        C={(0,0)}\\n        while len(C)<n:\\n            b=random.choice(tuple(C));dx,dy=random.choice(NBR);q=(b[0]+dx,b[1]+dy)\\n            if q not in pset or q in C: continue\\n            bad=False\\n            for c in C:\\n                dd=(q[0]-c[0],q[1]-c[1])\\n                if dd in Tang or (-dd[0],-dd[1]) in Tang:\\n                    bad=True;break\\n            if bad: continue\\n            C.add(q)\\n        return C\\n    random.seed(seed)\\n    best=10**9;bestC=None\\n    for it in range(iters):\\n        C=rand_conn();h=eval(C)\\n        if h is None: continue\\n        val=h-n\\n        T=1.0\\n        for s in range(steps):\\n            rem=random.choice(tuple(C-{(0,0)}))\\n            base=random.choice(tuple(C));dx,dy=random.choice(NBR);add=(base[0]+dx,base[1]+dy)\\n            if add not in pset or add in C: continue\\n            C2=set(C);C2.remove(rem);C2.add(add)\\n            h2=eval(C2)\\n            if h2 is None: continue\\n            v2=h2-n\\n            if v2<=val or random.random()<math.exp((val-v2)/max(T,1e-9)):\\n                C=C2;val=v2\\n            T*=0.9997\\n            if val<best:\\n                best=val;bestC=set(C)\\n            if best==0:\\n                return best,bestC\\n    return best,bestC\\n\\nfor m in [5,10,13,17,20,25,26,29,34,37,41,45,50,52,53,58,61,65,73,74,85,97,113,125,130,145,169,221,289,325,425,625]:\\n    for n in [8,12,16,24,32,48,64,96,128,192,256,384,512]:\\n        b,_=search(m,n,iters=120,steps=600,seed=1)\\n        if b==0:\\n            print('m',m,'n',n,'perfect found')\\n        else:\\n            print('m',m,'n',n,'best diff',b)\\n            # if already positive at small n maybe break for speed at some point\\n            if n>=64 and b>0:\\n                break\\n    print('---')\\nPY\"}","call_id":"call_mTxxfPajGdAxrKzq2trHqeZf"}}
{"timestamp":"2026-02-11T04:35:36.344Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":3352189,"cached_input_tokens":3229952,"output_tokens":65196,"reasoning_output_tokens":39583,"total_tokens":3417385},"last_token_usage":{"input_tokens":82497,"cached_input_tokens":82304,"output_tokens":1791,"reasoning_output_tokens":447,"total_tokens":84288},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":12.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:35:46.496Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_mTxxfPajGdAxrKzq2trHqeZf","output":"Chunk ID: 1bb5c8\nWall time: 10.0013 seconds\nProcess running with session ID 19144\nOriginal token count: 0\nOutput:\n"}}
{"timestamp":"2026-02-11T04:35:46.530Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:35:48.582Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":3352189,"cached_input_tokens":3229952,"output_tokens":65196,"reasoning_output_tokens":39583,"total_tokens":3417385},"last_token_usage":{"input_tokens":82497,"cached_input_tokens":82304,"output_tokens":1791,"reasoning_output_tokens":447,"total_tokens":84288},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":12.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:35:49.611Z","type":"response_item","payload":{"type":"reasoning","summary":[],"content":null,"encrypted_content":"gAAAAABpjAclGkj8sZf2ncyRr87VZ__m6xgkPztXhE7weCP1yuq_z26HT6-O4SNzov7h16ce3lUhy2e9s86Io78rxp9Mgldikfq2U9oq-8uazx0gmLgoQVef1JEBDHc8cLsFwtyiBasMY9cVOptFRi-T2QiwOw0mO6xFBTPx8M-WNOjlQBZzYog9uVqDttDD1ayPB8cDNRhRCto-ffJ9ir98PU4O_q12X3BsVxQDOzXKGAvfqMlPElTcC9KkRz0e3uql8lZZIpillT7PAD7NwvoEDfMDLtj4zUU2kd81t8kaey7hoB_csqS2qApZeB9eFiGBhzndsMviyfSOwPZMsRL1tsmMTfgD5-LRCdu0XVW8X16aaUk0xOUdJXrr0t4s26Tp45RtaQDlNzRFxSOStRzW-6qzcabLXZ4PviSOM0Cv7X0-jiNH9jHa22YHTIf5v0NQOiVfMCuzWD5sOPSjyZe8ZI9AAXiead3oBJ6QQEmd_0V-1XR9wH_qzDIDG3WC4bFeqi4yKhwH3iEszFAArApCu6y53zUkiJEMOP_WBehuJ12nNWy85BRL9MCsfhUysqZCroWkbhl1niWpBqXijH_f4-jyT6StvzGxmDBN9UGCxTYNHOOrU1c1y4cNey-b3Q4RVfugwCDdiOaSEOPL2ZPv61ggOuvDhc4m-mM7C90KKWPihHYGXJjasvvEl6cqu6Fu5a0DYdaWmAAmEbCAmY0bryF3fbxUqr0wSts_Y8uoGyx9U_dDX9bbRnvTChA3SxMUg4nM_dBBPwIiK_svov6gJZ_ZrYkmLyBbuZl9kp3r4KFxy5pHCb221S-kCc9BamadCVhCJWp_3tn0lnQM5dmBvpBkclFRKcGl10_CcFEdV0oR7Hwj7VgMtCdt9F513lTioV-v99p4VkbU5RhU90d7W5ytXfxT2Q=="}}
{"timestamp":"2026-02-11T04:35:50.328Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"pkill -f 'for m in \\\\[5,10,13,17' || true\"}","call_id":"call_JN3vFsuIvPBI2gsQ9NlRmDX4"}}
{"timestamp":"2026-02-11T04:35:50.355Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":3436526,"cached_input_tokens":3314176,"output_tokens":65252,"reasoning_output_tokens":39600,"total_tokens":3501778},"last_token_usage":{"input_tokens":84337,"cached_input_tokens":84224,"output_tokens":56,"reasoning_output_tokens":17,"total_tokens":84393},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":12.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:35:50.951Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_JN3vFsuIvPBI2gsQ9NlRmDX4","output":"Chunk ID: 679291\nWall time: 0.4685 seconds\nProcess exited with code 0\nOriginal token count: 0\nOutput:\n"}}
{"timestamp":"2026-02-11T04:35:50.981Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:35:52.638Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":3436526,"cached_input_tokens":3314176,"output_tokens":65252,"reasoning_output_tokens":39600,"total_tokens":3501778},"last_token_usage":{"input_tokens":84337,"cached_input_tokens":84224,"output_tokens":56,"reasoning_output_tokens":17,"total_tokens":84393},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":12.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:35:54.376Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Setting focused test parameters**"}}
{"timestamp":"2026-02-11T04:35:54.376Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Setting focused test parameters**"}],"content":null,"encrypted_content":"gAAAAABpjAcqe4AUdlCEUvxmSogq53C3i5YGSJP9GJCAa6zpb6TeiMdYe_p-wIxGCW5mc9lqwwdR6VJvmFSWeWTUxX9L1AylhImtwR01rlJ7Npq2qmZR11BVkcR0-1eKmQnTgO0zzZSEzZ7q5Zri6HYeo-8ihxSK72iMWUVjUgB5FSscW99Fe-qjSGyrDeNW7w5_Fy_eJsoNAFSa22J8ZLlLpT59t9Dn2OWB-a_6I3iN0AWsPWa3IXdhW85UXPHR4qfQChP3XDdronjr6pHC8P1z4wH4svayBKfu99RI91Z8bVSY-qoYTlViu7ScIkRIYL-y9kq-SdsP0cxVBZpin4kxn-Md5L_sqBzucUo_r1GzGZu__IwJiqiALNQtrFKNJGrIt3_Z2yU7qypFgP5d0DIhjw5lMBJyIQju3YtSVBPPLCygEZLNxGFXj7t7Yl93zFG4SfxcYeoTVJTHii2Q3M0K4yjWKlsYKRcxwPIszCSnGvyEuV_lMQBVsPYYYS4TrSWZ2ady44CQEkDPH5eijPdoZI9AMdkzbPJip6EE9FT2UrT9fVHPUDK6UsvBJs-YexDXNzpWpno9eDve_3lkiU8tnvo-Yh1fqW69ncnVR9KQK5Oxaivutima3dAhrfZsPcOuKCsU6L0dV2hMG8IAMigVIqWgcnEvoZ0FUbzLwtPNZwRqgJnTkvk34Bf1qZMuZEe68Wq4bM_LXnUkl1nV1Q0pySGmT8Bhc0yHshd1s0De91a8jmijLqSC8p8nGaXidUPw3rqaSOKvlBXMIbMXX8BvOU_ADrV_KGlAXuxcfrHvvm8xtZ3aYCp6WVcAbefoq7_qBbnPZQoVLJ2IyEYPEKoxEaGc2pzozw_ko5C5zjTSSeVkUivNJhsx8_wesXU_ThxqTqCu_VzSygEpOU87itClHRjIInZcgL-20lNwYGpVlycdh0DgRDmeaRKnHEGjWP95dYaym_MlA4TOtW6a7ftesk5RNhf8zauuNU5kr9NI4Vl2olkvvu7X4datoppghy8oYRsk8u0ig0Kwo5srRzdTl_re8FaPP5ZpZNH0jUr934BOv9h8KWgWyippYv_nK9L_ffZodQfgSUE8Ytf-1gjR2UYRjhjz2g=="}}
{"timestamp":"2026-02-11T04:35:55.205Z","type":"event_msg","payload":{"type":"agent_message","message":"The unrestricted generic search space is too large to sweep broadly. I’m narrowing to targeted probes (single \\(m\\), increasing \\(n\\)) to estimate growth ceilings and avoid wasting cycles."}}
{"timestamp":"2026-02-11T04:35:55.205Z","type":"response_item","payload":{"type":"message","role":"assistant","content":[{"type":"output_text","text":"The unrestricted generic search space is too large to sweep broadly. I’m narrowing to targeted probes (single \\(m\\), increasing \\(n\\)) to estimate growth ceilings and avoid wasting cycles."}],"phase":"commentary"}}
{"timestamp":"2026-02-11T04:36:11.926Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"python3 -u - <<'PY'\\nimport random,math,time\\n\\ndef prep(m):\\n    lim=math.isqrt(m)\\n    S=[]\\n    for x in range(-lim,lim+1):\\n        y2=m-x*x\\n        if y2<0: continue\\n        y=math.isqrt(y2)\\n        if y*y==y2:\\n            S.append((x,y));\\n            if y:S.append((x,-y))\\n    S=list(dict.fromkeys(S));Sset=set(S)\\n    md=2*lim+2\\n    D={}\\n    for dx in range(-md,md+1):\\n        for dy in range(-md,md+1):\\n            if dx==dy==0: continue\\n            if dx*dx+dy*dy==4*m: continue\\n            pts=[]\\n            for ux,uy in S:\\n                if (ux-dx,uy-dy) in Sset:\\n                    pts.append((ux,uy))\\n            if len(pts)==2:D[(dx,dy)]=tuple(pts)\\n    Tang={(dx,dy) for dx in range(-2*lim-2,2*lim+3) for dy in range(-2*lim-2,2*lim+3) if dx*dx+dy*dy==4*m}\\n    return D,Tang\\n\\ndef solver(m):\\n    D,Tang=prep(m)\\n    NBR=list(D.keys())\\n    pset={(x,y) for x in range(-160,161) for y in range(-160,161)}\\n    def eval(C):\\n        C=list(C);n=len(C);H=set();edges=[]\\n        for i in range(n):\\n            x,y=C[i]\\n            for j in range(i+1,n):\\n                dx=C[j][0]-x;dy=C[j][1]-y\\n                if (dx,dy) in Tang or (-dx,-dy) in Tang:return None\\n                if (dx,dy) in D:\\n                    off=D[(dx,dy)]\\n                    H.add((x+off[0][0],y+off[0][1]));H.add((x+off[1][0],y+off[1][1]));edges.append((i,j))\\n                elif (-dx,-dy) in D:\\n                    x2,y2=C[j];off=D[(-dx,-dy)]\\n                    H.add((x2+off[0][0],y2+off[0][1]));H.add((x2+off[1][0],y2+off[1][1]));edges.append((i,j))\\n        g=[[] for _ in range(n)]\\n        for i,j in edges:g[i].append(j);g[j].append(i)\\n        vis={0};st=[0]\\n        while st:\\n            u=st.pop()\\n            for v in g[u]:\\n                if v not in vis:vis.add(v);st.append(v)\\n        if len(vis)!=n:return None\\n        return len(H)\\n    def rand_conn(n):\\n        C={(0,0)}\\n        while len(C)<n:\\n            b=random.choice(tuple(C));dx,dy=random.choice(NBR);q=(b[0]+dx,b[1]+dy)\\n            if q not in pset or q in C: continue\\n            bad=False\\n            for c in C:\\n                dd=(q[0]-c[0],q[1]-c[1])\\n                if dd in Tang or (-dd[0],-dd[1]) in Tang:\\n                    bad=True;break\\n            if bad: continue\\n            C.add(q)\\n        return C\\n    def search(n,iters=400,steps=2500):\\n        best=10**9\\n        for _ in range(iters):\\n            C=rand_conn(n);h=eval(C)\\n            if h is None: continue\\n            val=h-n\\n            T=1.2\\n            for _ in range(steps):\\n                rem=random.choice(tuple(C-{(0,0)}))\\n                base=random.choice(tuple(C));dx,dy=random.choice(NBR);add=(base[0]+dx,base[1]+dy)\\n                if add not in pset or add in C: continue\\n                C2=set(C);C2.remove(rem);C2.add(add)\\n                h2=eval(C2)\\n                if h2 is None: continue\\n                v2=h2-n\\n                if v2<=val or random.random()<math.exp((val-v2)/max(T,1e-9)):\\n                    C=C2;val=v2\\n                T*=0.9995\\n                if val<best:best=val\\n                if best==0:return 0\\n        return best\\n    return search\\n\\nfor m in [13,25,65,85,169,221,289,325,425,625]:\\n    f=solver(m)\\n    print('m',m)\\n    for n in [8,12,16,24,32,48,64,96,128,192,256,384,512]:\\n        b=f(n,iters=100,steps=800)\\n        print(' n',n,'best',b)\\n        if n>=64 and b>0:\\n            break\\n    print('---',flush=True)\\nPY\"}","call_id":"call_kKgfEHkUVLUzLHexay7aITvs"}}
{"timestamp":"2026-02-11T04:36:11.957Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":3520963,"cached_input_tokens":3398528,"output_tokens":66574,"reasoning_output_tokens":39651,"total_tokens":3587537},"last_token_usage":{"input_tokens":84437,"cached_input_tokens":84352,"output_tokens":1322,"reasoning_output_tokens":51,"total_tokens":85759},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":12.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:36:22.081Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_kKgfEHkUVLUzLHexay7aITvs","output":"Chunk ID: 28d067\nWall time: 10.0009 seconds\nProcess running with session ID 51330\nOriginal token count: 15\nOutput:\nm 13\n n 8 best 2\n n 12 best 4\n n 16 best 6\n n 24 best 12\n"}}
{"timestamp":"2026-02-11T04:36:22.115Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:36:22.500Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":3520963,"cached_input_tokens":3398528,"output_tokens":66574,"reasoning_output_tokens":39651,"total_tokens":3587537},"last_token_usage":{"input_tokens":84437,"cached_input_tokens":84352,"output_tokens":1322,"reasoning_output_tokens":51,"total_tokens":85759},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":12.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:36:51.200Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Questioning heuristic reliability**"}}
{"timestamp":"2026-02-11T04:36:51.201Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Questioning heuristic 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ozx4bRPRaRedXslYgj7AlD3Idlgaaq-ZF0HJhwZ_V0uasRnGRypxiDNSt8jjOBLXKbYmZ-NDx0HSxYKSq6l13YeD20bqiLcULCNP0d0WFocfvZ-ISgXiXAxtvY9EEX-5EmSTK-xdGD_dH4i_4P3IHtGZbT5PK6_gBwEzAI39YOWt01Houpsff05DjPcOLJhGXxEn_8QdN5LpnRxMAqIqh3L-roY4_Ppp_PtJfWoyvQ1R24keq5epG9K6ehSk2QaujBkjf008m4yiqrTxeO-bDdSNuy6WikWarm1vXoEtg8ni39d6ljdVy3hmk1RbGs3ZZOff1fSKHCoQD2YDBAHf9z8RbFk8EVjpRgt8nH1OA-jXO1oxZZqoUxnYzv7LzbN40mdukMLaGkYwNzdumLE4rd3xvcyL0qGpfzCoTwX30OEJWLaoqN_lt6zhlpfuqtVJrm0CsaGKgHxcddhX0ewryA7tyHVstUqEcrKmk1vfUVavhQaTLjGDIAVHDgAffEg_dwuFvCtegSdYhPlDvrYhJeTymHCJpEG1WjKs31fGreh9lMriaGgRLiNeOxRxehrqTnwkq_UDbbOWbTb8FyjVt-GJQA-INF6vsjh-cNwWunhI6GIRt5cd1_iS-1wPfLkdlL19V7rzWV4SoZ6HNJ7G90y-8IygNtSUdSPdbhX5MJ5-gd5fUmmQtaJvTz0HO0qQAPOGwRZqQBOMsXoFz6EOvqFIPby9Ns7sQSSOn7QlqPrr_LCcUp_y2iAOJ4UDI8mKaLK1_MEG8LB8KCrzHk3B4LxHf-MZAzOFabnrEbzdfWagVsob1Fi7tqDes7dGcU9axeJVSOcaEjqhWg07ZdLqug71t7yRFQeV0nYpwR_m3IpvTTdEy1QU8LC1rNcYiDwpEfulXaFWWDnEYdG3Iae0oUYkUZZ6HhmCpQaXVecVFyJwMjyUuZYX-WfR4l6-o1NK1IpiAoic9boyquxOBu0OZExDNkSAQXIKjhcyzUx7rl1XoNiLpU_qb8z_EJafaWm16zVfnbDm9M3R8oh2Km9K2UgRK0Tos2jpoVZ8yOwD8IpgwDHmVhts4ADfvXvyt651SSKcQVaAzQSOHkkkeJe7fMMj5cP4oyt4UHp55oJS0X-3PNTiEcsSwWySl5f6AY8qCM6K07zylCEmwByl50vDjrbSgkNiTD5hCyeuUbkjdOUaDyFM3VZbZjpiTfM_v2Efd9zkxG8Bt_59nW-3GK_6vxpvo6eYOruzcZuoGldEYyYNrJ4XiGoIisJWZXH2eNcE4cpkiDIhT2A2jLHPl11ut2CE9lTXw4l6dpy699OlhRTGuaVmMOgJ0bfn0XvWcmtOuraYpLEgP-TJdpLHONFp83fWnuxEsbV8WLylZmk0xYfhclHVR7rKzmLJqby1Cr4CeIxo3kGJcuzfElERkGHgDQdocvqh-hMJgUx4Dnrsw6eY2wGHSvv7jr29eJfUCatIFUWky9SPmSgiI6mN55Do9MEAUZc7WT4ipPwsw50vhlXTu4R5U5oSQ-F0Xa_OmMrlCe0Tg8heYxm0a9JgK2-eVZ3QXu7QL7xX3ATT6UtIKPiO6rbRT6faRiUXsdUBhqoGJOc4ave8NZTMyk-A6yz_TIC0ROihZ_KTTe4ctolpmrDQ-1rDY5hIqPeWWRWe8WA__fukOzF5rkMBMxJ1vpCh9FI1QVSp6MW81b96poXNOzfJ_nayiVHqzTBWlxndbuRyY3xgR1GBJ-gpAyEAjvuXiM1T6AvLZ_0pMTgfZsYlBUSgNpFG3QfaS2Cp7p57quH0EBe2ZAl3iO0YZSsa54jyHDq-wPEmQ1CVJYZEJHK9b7PMVrlDGOmHEE2wSvXf91Ic5hBJVI7y2jUudig6S-mZBLR4G4-54HHBEPaIdqv8SBZRR6Us1zVueIQMMZ2kjR6UoJt6TkP3a9br3hmRaCk74ZDQ6AAWeMX5QXteWqsk_M4XihlhiV7qTG2F-oDx6HkPsbkDEiyY_CmC-xT_PyWPxWJphopiB343n-kn6t3PfQl8SDArXej58bnRjfkUDowyEtT0K7MxB2NqihRt88R18kLaZtgSdHASYMeXObbheQBWhE5ba6FZemHayAJ7bptdo_Lw4Blo7LP_30eSB5NDnmWRjCYZqay_IUItxr9QruWPePWYfEdCEAWeM4EYY_-D77yi3z0A0J05L1WefWA5pnvbXVlB06-ZJadXEAff_SWfhGSkuuEAYfbaztxh-bAnDUWrP_nboG3SKiBhjczq3JXman8jQsuhLjBG11Fy06F2qwdsnOYVosDjsLERI7vjZxpaCLazoXwY7RFUtB7cj09wgGilUH3TYbGEaEN3hpU-uaOZ1qi9Jo3qhOcQZx_oP73tM96cWPZyi1VIzuweRZCnYwZ-hYx9tNGxOHsiL80cwHUI4fbmDCEvl1JW4KUhc3euUIEMJcj4l0X_b80GJ9DaelLQ29iu2hfkwpGygnz5OIhVAaMbTjCJkrtKnhWEvRpp9FrApYONdUeEwsX6p2Moz-7QLfvh0eiYRxXzvv-rpuwYgJCkx3GGmRRLUu70I3HhaeeWIX-KyTDlDLguHhK575UsNDtAk-IEi5Z6-DvFVkX0g4ZU9kQqaJqogJoW6tx9kOqyo_c_npZjM2_oHCFf6uKASHgnxVgOyh-JHMfiAnN1DkIkseM3VBFMAXMozeoa9W5sPxPyV6rKLCUDbeSZ7VlOu6aqZH5CZCDxaVyoI4tTd88HsjmvdpapFr2iMuNEi-YbLGC_nKZmSRiVSOC9ulI_dhW2TkeSr869HDWU63jHuvez1MTZBV_tXI70NYH9zldDzIT_PKPMifuHcTVzTb1YB5rmgtGYeld34Llb8BhY2eXJfdqoyzo0oacBJ38Mt7cOoamNVx5oSZWHaJqP0CEm_6JgL9JsjgcOSBtJGKc_MKgq9x0uvNraLjO-7MuBZ45DWACLcLt58C3fhXuMrvOPCzywsB9zp3rsk3cFQCM6L275ZNm99yxwm1vxOJ4901lmdW8mdnlmRO-VwKnjrxw4zkkUJgL3Tw6VtcmxbWpBKPC9gorFTvFzja6ozK_IMfnwzRL7c4TQdUGBUmzDAmfvfIW7U82JKXG1ueOlGtehGYDj_iVVp6SpbdQXKgLeeqfY8YJNcuED6rmAPp8giNADfVTkvBIi87N6C3SSzVh8Yxym80yyt6SOuCMcaEUPAX5zZ6rcTI9YzKOpv8-ZCvV2E1CvSgt8Zt22XWfxmAe1-sgoirt3FwlvGBJJM8HU7d3QXGkK347h89WmI7JZloai1UOJ_D4w312_5KyaUZ-VAdZQQdNjkVYWxpSvBHOMEvba9L15emgCe36k89HEUzurpJ_SRBDQqeSuJxViXxdP4HYiWF0sYceuCJJs6Fb_ZDBM902rBbXFpOVsFveo1UUqkmF6iI8F7_J7oLKUH3DuAgQCDjjQNdZblredQQPycV9J8D2U2ZSjQP-vHe-xL3K1U6incJuzL6wUJ4XgNe2VjrEXaZthcd-Sux7C9k91ySMuDkrVp8QizhYJTK38x9_DG1L2N14IL5w1M419C_Xbu6tdV8XDbqMHnUey7o76__BMVMEMn0xLFz7rl_MSckWoDq4p4w3O7Jn2-OpdKwaB3pwDq90SVxS9c3uTEbkn8FJcg4l6CYTILFj4nyb04GUJRLhk1RT0vyLUEXBPKefFz10TRbkiUYgqMvCIvEyUGT-FafNs9rIoA6zoOcj4RHUDRaYJTS2GJd8Y9ru91P8OihbpD3zaiAB1O4t6j4ah0Wc096QHEyf4Yrhc0ArKKwauNUb0Sj0tgkEFxS7yYwZNu7HMutfPvj-6cW5w0f0nB61E30WrOoNjp1HXH9YakuUnJDgLh89D8w6xWnAvNRZSv8Nh4ymFHJORLsLJPaZK42tOkIh6wFk9wewFNBUu_3ng_xwnJi735QyAtDPxsePcG7D6jyQnQSB5BUmjxEb1so_ZUfN5J1GsxEFE3bp-i7JckW5HBtiUrVV1fO1bIWuWlUesIkY-fhM2b1vxLmXYb6Yk-WkgIhX7dXDt9SXjKx3mmVZmxwpshIAAzzEmtkUxYcWQ8xyl_5W4BEU9EgY4e58vRBqu6qvD-6DCwnobynbHoFuvqIJlqc4KQn5ElHoA1bHpFzagQ4QYKl4cKanDG2bUXthrWI4RZAllXMphYf1B9w3p_T-Efi7bDmmAQX3GWTAwTuu0PvGm18ukrHRj2XE_3MawrNExzZzrPR_HAKhr6TZdvhy9ymo8-_vXUakgPe9wmpzzUcmylo5cPxtP8anjLm80AIbFUcyvHPhA9bmEcCe5nLskmJSojEF7gMUjgykgeRjFYeCPenDeGg_QINZ54MF6Qvwcik2N7efxoooJfq1dAnSQfejUyZs4YZvnLmJjcUnuy85w4rRqbgJDqPxmdIzkiTFAFEVPMCiZIbRfM0Slh3w7qdw92Toz83vOXZl6i-7Ex-drphM_50PUA0nGUFid1pKth6e4hBQdVBX6MYLRHeYERJNE_6pOL4uAa2XPmfD5uXMe9u1u12BV6qNSjO6SVUanMynpvTj6VFT3VOjsrqCEv68IjK-bhbuTKH783QCvFidFblUhIJpe9VU7r66iPOZZ28unIi2CezHvFKb4S6HvxgkaHvJqNh9Y1uzppJTA5macIIl5Nst0wPju1kMMUZQ=="}}
{"timestamp":"2026-02-11T04:37:02.819Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"python3 -u - <<'PY'\\nimport math,time,functools\\n\\ndef exists(m,TARGET):\\n    lim=math.isqrt(m)\\n    S=[]\\n    for x in range(-lim,lim+1):\\n        y2=m-x*x\\n        if y2<0: continue\\n        y=math.isqrt(y2)\\n        if y*y==y2:\\n            S.append((x,y));\\n            if y:S.append((x,-y))\\n    S=list(dict.fromkeys(S));Sset=set(S)\\n    md=2*lim+2\\n    D={}\\n    for dx in range(-md,md+1):\\n        for dy in range(-md,md+1):\\n            if dx==dy==0: continue\\n            if dx*dx+dy*dy==4*m: continue\\n            pts=[]\\n            for ux,uy in S:\\n                if (ux-dx,uy-dy) in Sset:\\n                    pts.append((ux,uy))\\n            if len(pts)==2:D[(dx,dy)]=pts[0]\\n    Ds=list(D.keys())\\n    Tang={(dx,dy) for dx in range(-2*lim-2,2*lim+3) for dy in range(-2*lim-2,2*lim+3) if dx*dx+dy*dy==4*m}\\n    sy=[lambda x,y:(x,y),lambda x,y:(-x,y),lambda x,y:(x,-y),lambda x,y:(-x,-y),\\n        lambda x,y:(y,x),lambda x,y:(-y,x),lambda x,y:(y,-x),lambda x,y:(-y,-x)]\\n    def canon(C):\\n        best=None\\n        for f in sy:\\n            T=[f(x,y) for x,y in C]\\n            mn=min(T)\\n            t=tuple(sorted((x-mn[0],y-mn[1]) for x,y in T))\\n            if best is None or t<best: best=t\\n        return best\\n    @functools.lru_cache(None)\\n    def pair(a,b):\\n        ax,ay=a;bx,by=b\\n        dx,dy=bx-ax,by-ay\\n        if (dx,dy) in D:\\n            ux,uy=D[(dx,dy)]\\n            return ((ax+ux,ay+uy),(bx-ux,by-uy),2)\\n        if (-dx,-dy) in D:\\n            ux,uy=D[(-dx,-dy)]\\n            return ((bx+ux,by+uy),(ax-ux,ay-uy),2)\\n        if (dx,dy) in Tang or (-dx,-dy) in Tang:\\n            return (None,None,1)\\n        return (None,None,0)\\n    seen=[set() for _ in range(TARGET+1)]\\n    best=0;states=0;t0=time.time()\\n    def rec(C,H,F):\\n        nonlocal best,states\\n        k=len(C);states+=1\\n        if states%200000==0:\\n            print('states',states,'k',k,'best',best,'elapsed',round(time.time()-t0,1),flush=True)\\n        if len(H)>TARGET:return False\\n        if k>=2 and len(H)==k:\\n            if k>best:\\n                best=k\\n                print('new best',best,'states',states,'elapsed',round(time.time()-t0,1),flush=True)\\n            if k==TARGET:return True\\n        if k==TARGET:return False\\n        for b in sorted(F):\\n            newH=set(H);newF=set(F);newF.discard(b)\\n            harm=False\\n            for a in C:\\n                p,q,t=pair(a,b)\\n                if t==1: break\\n                if t==2:\\n                    harm=True;newH.add(p);newH.add(q)\\n            else:\\n                if not harm or len(newH)>TARGET: continue\\n                C2=tuple(sorted(C+(b,)))\\n                key=canon(C2)\\n                if key in seen[k+1]: continue\\n                seen[k+1].add(key)\\n                bx,by=b\\n                for dx,dy in Ds:\\n                    nb=(bx+dx,by+dy)\\n                    if nb not in C2:newF.add(nb)\\n                if rec(C2,newH,newF):\\n                    return True\\n        return False\\n    ok=rec(((0,0),),set(),set(Ds))\\n    return ok,best,states,time.time()-t0\\n\\nfor m in [25,50,65,85,125,130,145,169,221,289,325]:\\n    ok,b,s,t=exists(m,9)\\n    print('m',m,'target9',ok,'best',b,'states',s,'time',round(t,2),flush=True)\\nPY\"}","call_id":"call_GpxrIHkg48NrZPuQak2wBd1q"}}
{"timestamp":"2026-02-11T04:37:02.848Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":3606801,"cached_input_tokens":3484160,"output_tokens":69042,"reasoning_output_tokens":40993,"total_tokens":3675843},"last_token_usage":{"input_tokens":85838,"cached_input_tokens":85632,"output_tokens":2468,"reasoning_output_tokens":1342,"total_tokens":88306},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":12.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:37:12.976Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_GpxrIHkg48NrZPuQak2wBd1q","output":"Chunk ID: 97dcd8\nWall time: 10.0019 seconds\nProcess running with session ID 46421\nOriginal token count: 8\nOutput:\nnew best 2 states 2 elapsed 0.0\n"}}
{"timestamp":"2026-02-11T04:37:13.011Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:37:13.360Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":3606801,"cached_input_tokens":3484160,"output_tokens":69042,"reasoning_output_tokens":40993,"total_tokens":3675843},"last_token_usage":{"input_tokens":85838,"cached_input_tokens":85632,"output_tokens":2468,"reasoning_output_tokens":1342,"total_tokens":88306},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":12.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:37:14.449Z","type":"response_item","payload":{"type":"reasoning","summary":[],"content":null,"encrypted_content":"gAAAAABpjAd6HdJy_UPaPMEm65EFuJLAk-iMkaymZAShjzE7ZOqsYgw9IjRwboLm6v8VITxP2hv3vcwjL47whoj0r7EOdmCDatfUIkiLDdfVQVFGdWnWi_j1O4GKAVX3MeXsjygzu4-DVlagOEG7S0jEp8opASso-JtjszEjaIn0QYvM30L5qvRvR0qIO8XvybcrscAGdArsXY2iREndbRSdwq2P0oJtGVJlLcufx3B8qItK9TValNdvl9jX352VKzqRiAmZmjwIb3elQRjpyN86MwNnOZdfSiyGk8UTv8Yc22B8B8hnQW-jYnRL9OQeKwztcfUqFolxXF2A_vIOUd1p9Y1M6u6OUbhoBFSo16KfS8ZJfuhDKkTI83AOVXHbi5YhL4rqDtGarCSsWYUB3L167zdv0tyUnN44zV8aZPO2ArLzXGLMJI7BRmATMbF9L2b3EFZ_bS5hHxG3sW-M22mhMMhs7iARU4DTdJNMEQwtzFMSG5odagwfJfZ36Gt8qDgHJfwLT3_YmizLiEsTCy2hXom7j2WHaltPfDhBLZM4Ie9wWxuw0wFX991UmnLtoXRQ27wvixJcqQ7MgS4a47h4pi7iDfKZEz8hdESzPonSiz6Evqi-EOvjVXDvtOjLVwU7xO3fdWy_a5WE_4CYrNxsdxLa2GyXWA7aYpu3yg0lovplRpELNu_gXdIY9k4H977woUq_i_R64SvJB41h-_2F0H3_jWRJ2ci1Yy0Hh1eEKdqyHSigh34w0S7Ykh7rSgjN8hxQKgxo0jh-sDaZd2EbpGAS-yLwGQJjsEdEqL6WQnmcAGRYo6HQqfh0t9ma6u5RNo8k1ocItQOkRj7J2Y1BtVatPyjM9mlIQaLWHasLZqeFk8scFBM="}}
{"timestamp":"2026-02-11T04:37:15.245Z","type":"response_item","payload":{"type":"function_call","name":"write_stdin","arguments":"{\"session_id\":46421,\"chars\":\"\",\"yield_time_ms\":30000}","call_id":"call_lJryyyF6mJLcpJPjt88z651j"}}
{"timestamp":"2026-02-11T04:37:15.273Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":3695168,"cached_input_tokens":3572352,"output_tokens":69083,"reasoning_output_tokens":41002,"total_tokens":3764251},"last_token_usage":{"input_tokens":88367,"cached_input_tokens":88192,"output_tokens":41,"reasoning_output_tokens":9,"total_tokens":88408},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":12.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:37:45.246Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_lJryyyF6mJLcpJPjt88z651j","output":"Chunk ID: 2d1aa7\nWall time: 30.0008 seconds\nProcess running with session ID 46421\nOriginal token count: 0\nOutput:\n"}}
{"timestamp":"2026-02-11T04:37:45.281Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:37:45.997Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":3695168,"cached_input_tokens":3572352,"output_tokens":69083,"reasoning_output_tokens":41002,"total_tokens":3764251},"last_token_usage":{"input_tokens":88367,"cached_input_tokens":88192,"output_tokens":41,"reasoning_output_tokens":9,"total_tokens":88408},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":12.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:37:47.782Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Considering early termination**"}}
{"timestamp":"2026-02-11T04:37:47.782Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Considering early termination**"}],"content":null,"encrypted_content":"gAAAAABpjAebVSjK_I4LsuIZMeoCV68P9knEGkhp58_DLLjxyuiDdTGb06hHtRi9mx_UvmPlXqUOb28CCkxhPm7OTccxjEvja6JGvaM7Oeqj1GOPIY-fNVbydl4Iz2V9vWefnyzLBHXXQtpfCAEJvzUEz3HjHSiyx3E7cQStZzxnRrykaPg13uWfBzqzQ3lltpl9uv8bnYLgosiKzPYtR5zIiG7u1iRH4ZN4906dCUOHuv7qC1vZtsR6fGo-DZ7hXECn42ckmw5yChxFK2eyyTVMlonENe_1bUsC_x2kGcm-oRLvhl96vXN1lfPCu4lXFzJ8xQEJZ5HrGC_Dp58_mV0Cly45z-o5MLOx84XyZd3yW3-OHcme7tvYocOpPjkrx6CwtBfLr6XwuWIMDr_Nk_0dBiuugO8HnDoiPp4ARJXf4bM1w3lNv_6s5EFA1I61vnsVs--hLA_WJ_j9bb0-snG-RnelrdtR-aSiA0J1Vnqc_iHXbbta1jpjDpouBPWSjssXvau_JCHky6BPg8bvi_S4BBqU2kH6URsoMA1sqYKgorvIjFjtmbayglo8rN_sh1NOsbxjB_3JeRtNu-ylWmMiuf0F6Uw4BCo-fnrYn42nx4Ht3o8vJEJf1-Tl2vaQCNN_QLH0Kv85RYyjOyP3WNeSNARc8Lf-FNuMh9ymaOfbBFw2eZE-hhsQcTcx0Pc_4eLVAe6KaUzSOhTX8dXvLBsJXX-EY5R-IoZAlUiYjbCM2oRU6mXc-4G0p7TWRO7tbuFX-DDvYH77W9l43M5eDMbuFYpRPul7pagFogS4EXJ8WrsUq8LTKA6TTagoPKvZMXMXNefjU2Is-2UzunT-I5tu-i7AD5ehwpOHFQfbdHeKgUhtu3GBMZzv13HBSBTYlZY_LfmEtcQLWsG3B8D6q3Un78azKk3yGgHk1leI7079wn8wk9Z66MciNiOfwLXd9qMgvdmFQ0VEXppJW2FiTN5IgRTPfnLNJdhmYoEwFzl6Ptxac2PB_PIFLUHdVEAeNneqUklQeiowHi75ZgI3g24ts_JubzM8yJBfh-1Qbqv9o7biZyjfL47Css7XpcLpQ_jp6YJLrcjp3V1wKdEjYCKSvmx_gAuaFHq1Jh-pBe_fzLFJX1O33rJ3tME2uwCvekeDvQiAjviReVqTJDlk8BfZooEnHhWYP1LKfORVZ-Sq0ohFB07lAdk="}}
{"timestamp":"2026-02-11T04:37:48.248Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"kill $(pgrep -f 'for m in \\\\[25,50,65' | tr '\\\\n' ' ') || true\"}","call_id":"call_SkXr3qUEgeJLws0On47UByIV"}}
{"timestamp":"2026-02-11T04:37:48.251Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":3783626,"cached_input_tokens":3660672,"output_tokens":69188,"reasoning_output_tokens":41061,"total_tokens":3852814},"last_token_usage":{"input_tokens":88458,"cached_input_tokens":88320,"output_tokens":105,"reasoning_output_tokens":59,"total_tokens":88563},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":12.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:37:48.959Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_SkXr3qUEgeJLws0On47UByIV","output":"Chunk ID: 93a2ca\nWall time: 0.5554 seconds\nProcess exited with code 0\nOriginal token count: 0\nOutput:\n"}}
{"timestamp":"2026-02-11T04:37:48.992Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:37:49.477Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":3783626,"cached_input_tokens":3660672,"output_tokens":69188,"reasoning_output_tokens":41061,"total_tokens":3852814},"last_token_usage":{"input_tokens":88458,"cached_input_tokens":88320,"output_tokens":105,"reasoning_output_tokens":59,"total_tokens":88563},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":12.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:38:03.755Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Evaluating combinatorial bounds and search strategies**"}}
{"timestamp":"2026-02-11T04:38:03.755Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Evaluating combinatorial bounds and search strategies**"}],"content":null,"encrypted_content":"gAAAAABpjAer1k9dnvtqQZpjM9F-WMGXOP4Ti1YRk3fcn93yIjTNlFGuyfWOVh_OLy4hKK2rN6tYdbco-O2ZDIcoCaaSNGAjrE1K4kolAfjYe3c_d9lvY5VU5UjJt9bkLT1Ar5LmxoCLWzmW_6LfS9TL87EFblswjcFi4t8rFW6fzjR_2nRjI02tJhm5mcVUgkJ-BfLrbttM0KODFKA6FIyaGIElN82YdB5us2r2THgFwITuNlCQvQNC4lzCVPO0TQP6McP_wbc3aZJcvgPaRKAoFwVyAap2kUGTAQnL1tM_OfoPp19-N6WcOWgMs4pMbUfFdXeDDJSJREW5y3wCzo0E7px6jCaqfity3wkemjjqZ_Hw-xDHiOdAqWd83AX-eMuEDHIu4BXYPQdbQWaHmNsPrbDCeZx2m6tHYo5WPIOyzsuPbDYZzNr8SDWjUr5fWSxbfLob3eYJtvtozh7JJ2oBQFl6qqBTEmtwvhU6tbpWxX-_xU8BArpFvjMxEMAGxy2CaHNSKhR_In6EgAYzuSVpe656A32EBvNVQNVzeXOs4fZ2Xehjfvq-EfttdYT91sF0g3G0G7tXtUCUpH6EKrJC-AMW_VZKPzVk28P_2prJzas4pWE04VukCNM9WkiW-YYhDWGRNWseZiHlfUJZAc3pc0kyvFzkfE7B1uQifmA8TJiMK3jg9QWABUKIje0f_y_oGALRPsZXwj1Z5G6VIqEgt1YJSj4o3dVtpIFtojHsV96kJAN4LD9Rylcjy5II_WkTCQHQljoRJWFDkB8Dmom5F1awZnHICv5Vzfp53lRtlpPv3ISJl58492GJ_jg-u6B9Xls4TeX7kiZImyyUbN2dliX6xaqRqRgFPNCN_1OtZ5XxldjTmGCjHryz0aVCgu2JV3J0WhsLssPUIw2FOsfDpTq_sWGI2GmWz2cUHBHKCPwyKdDJ6924fJrXhRtpAskqaFoUS_E4CKHjtOSG8rGpDIKZh0Uzk4zVRY89x7da7lPkP0gyrW_5iXeRynoBoHtJHaBVOmnOaaM0caAoyirbVEG9Qhwl-2Z7-AQcx3C6eaNl94ePnWxuLAkz8JohjygdQmpB6QCIpInru49DcJymFSZfCsCaIXmEVA41m6BAt73AG35XRXnt8gN7aQTTR3bympQDlL05nmKL96EAXyw8WI4Ot-DZPtTH_a-n6_Sm-3sIwpnZrGonXTnBAgKG8xYQxfblALY-UW3B_Llj_wceTUaCkGsrM3wdafW6U_emIXlfkVL-82Gp6dof9MXMvavy8m7irvVZ46DRtsZwY9qHTcoY3UNU4VLVTTxnzhUEjxxQ68-KesLpB7cB13Gcft5AEH73aT-2bpDMy5CUMuSHEb-8aUkaXG-kO4g0-rZtf9gzFMKL95nR-1N3ytS3sJjQei0gbNkY9fOtSDCbhTp9zDMZAkTK8U05EwCgOw6pCHFpSLA_Y_deckT8RlBHLr87nud0TF8cVgmQ_uQcdy0hvE-o2fpVHcXo85SiQQh3K1EbdC1hWsWkTrbItlLezK2e52dBAmngH-KdbTZcycKWB6C4SuXTcxJwGlMBryv-TBow-t6uTMzjOz5NEIyfxHlKikY7Lc3PWXhwneRbL0uaoEtS3ervHNuKNBUE609FeJU_4ZoaiZyKpo3lnas0Jd3T8c2NvGMUndKyBggkvdaH4np6pIaAKxBuVIQ-K5mLHT8utUnMf0Q4KXIlS4Hd4ao1LDgdPa2rcLzLkD2iIfHm6pNzQXDOfNCMvvaul0bweCFFcZLx-rhQCpjGokCxx6GgUvmGPjILQ2KIbI4jXzyqcd0-0wWsiSLFrJaoIStqimAdwy5-O5vr9ek-25yrjlsxTuis0oWaxao_-cYZnKi0EdQtE9Va1VjqTAr6ERp1FeVqSmWpXcouNnmzz6SzBhKqUePtmDYhp7LXqrq0ML22fw9wVmlJx-Nzl9dnsv8xZfTRLSFKulmC9ILoBgqpWXGTZ9526Tfejd55OcBboFkrhCYrPTfFJJ1TIIsOBVCaR1OeXGwA63Q35B4dIWqdISJ01vhyWhWjaCd3yv7QfT3rE8lHW0c3NjmUOTYXAadjYtYepL8m6ywlDobiuUks4ESKHkb4Jl1eQEuO9w_n-KLTuZsPYh7WHahUb1i7ej9WF20vRek7eQHl2IQEsvhj3zKZWIrKdePvjFdRdlXidcCH4AALjaq_Enjqajbhrhola6hCeBSLWXprCCqDod3Acjaew-gH8ORXfLbTDcVde0WmQZ3pq2e1rkfmTWUj_ACek8RKfutKaAoLZeNOoSDvlfHHTatyVIiiw-TSWad08a6LKrwzEFNLdEoW8OZ9F2Z2oOaXSa8OUhwUJ0K19PDUGhtgeOBFAri9wOjnxxZHyixgp_FVfc2KzvdfyGXhNHsNyvwE7DlNyMcQnJ2eby5skjYS0785_qgGLrdAgi8MzG0wMb-FPR1_fmuAo14pVvJlwl90xIfsnyGVa_P4hrYjDrWkqBKLoWWEzXysgem6OEBxw7F_uFcKZODtWeUu_M6TTbmu2aGC0g-YOCcEmqlF7m3wlUCYsOfPxUhZYB2VZ5YbkRUbwFXlbSk8ywPvqYM1NDDVYoYUVxhdCvb1ImBK61R0Aj1wuqowbFpqPkg23cXqVyPxY_Gft3My3jyI76K5j535LJJv86mDd1jgbi_3zmzJKHrTOqUxfvpVYNX82_dHMCXoLyaNijQYGk38PbrqT1NLcCag65fMCYI-l8r0NWlSBJyjf3BlVLUnzqjEnloGJvbsLePEHz03AaI6-agnslRLufeXSi12dkR8p_lU5Uz0Cf-sDsVEi8xS8kCC60Ny5ytAQ0hZ7lV-W-TI4aJTGMAKhmOa3OHxlvogWA6R4mJg7ArwHL3l8MdMJk1QVB-x2n0-prFUFbEpUgTSkQFbtf35BUpUMyb8XTVCpyO6Xck7jIhs4EQygBQCHKFV-AAKIbRZx-wecSQS2hxpiO1IzN7Hma6XAjQ-uzVA_cnyoUiFz3ZybQVPx6RsxWzileb3mQOormDZlU-xe4heNw_5kuF67mh9Vw4ZL93TceVa5N97Ew9ylE6G0BewCDarj_h9lby74GiQ4R95v7ld7_dNwccXgCiHBnfUEyQUYPsoiBJ8utXm-0tWOQ-b8dg5bsV7fjhHcJ6XQGzFRv6hS6aas6oE1psX0o-p133Qa_m_z9JArsOTn3woEbJstikLYNU9Te-YZ23RNvioI_W3__gflQVuQ_avVxMJ4i1AJC9Cz9d_lNWWKs0Uleohs3dYj8EbocRRSEwnw4jy7JyjdrtGg5yCitYfba_7_Rp5aaBW932JfSiLF0fSI3c_fxldNgwi9fDGCiFOsF7a0AtIzkSty0YeuSAz0sPEHPEIj2-49WovPkEYHhCVdHYgPYKr1mz0dH3LI0JqB-0P6BgwVVKciXx8AKDX8cdFDcuXSNjMmeZtgKmZ1w3Yi0ed_tzA0H1GMENIX5p8PmaS5CiudgGw9ZniLxrEtQDk2XWXZ6ATpkxlLICH87DqWWQkQr0tkBfqPZNwb9SXkfNju5VZPjvq9kDyG2iRPuLvL4Kr_5ufC1vs38EaT3Saj1Ix3mJ01WNZCjLmV-viy-4b8vIpzfbZ3KhgwysQ94c7Qy3zkO8zWx-qRwBobkqySm1jPlPWlZHvq17VlCxDa65KK5hknmC0IhTslWSpt_In2msniFJgOIto1iTbf_LWtS2D49IhTSe_mX2AT2xJiew6Ms3smvvid62SJr22OikFhzw-V9knzxrcwImtfPCJcf6rKg357lIvSdutjBTfQPFhdHp9YE9DIhQoHmcXWpfZ_re2MFMQpPhkI8MnMDseIWh0GD3PPYvn7jqi2MQB7cxMjGo_XnWfMv-8S1HaU9ysWnplcA1bItPBT7bCGtw1h3FiR-ZfJ3Rh8ve47fswXclMXE5KyGYKJHtvTlyeaUb0hBoIa71wBl5jkLH6exK7QS40T2wVoIcSeRer5OXoL7tKf4FqyYzh_4bBCqcYBhNgLvXwrdBLDqAcNJwrfzBeZhTG0Oy9Xhldsa1RmfkclT6ZyyG2LrqEQGZc7GqY0QQOaHT0DuvkNyKpjLjhizhxieUpGcN_1CWELOZOoJ82WKCUzSJdMjudg-yKu59NuLN3m9tGSuPAh6sURcXDG9u7uMMGhGo4aheWj6nozKFgABpNIR3xh828RcEzJLGlWMXR9QftFb7_UIfJVbMQ8BWK-bc6gq-J5YRwPjpHB6Wxg2ZPxff37IvWIS29dKhSSBMvwfCktdJcyu6NOdrZt24uMtXxFT_4nTqaIyiUoIITtaBdHk43tM76Z_rWTem-2Hn01KXWF0czgSQKvrBDppZ1i3GqAypLKAE9P7x9sylD5AKtnDXNP_vcJjanl_ZyPc8omVTnTAVqmtUIZyuHMhJcUbZtgwEyBORBGl_jqNL7w8eM0f5nNi2gHTEosTcUKfnT_6CpCaf5ush_hQED_OcfC21b3IqDZLz5KPRmq4kMZ6V32iFaGCYEp-C5fdc2_1-slBKQ8ytlLIt9mAEImcBUOmXwVc_gBySRziN14Dwgse13FV_PGMS2oEzPqSAzQwEg1P3eNSTaE_bW3YNN-MeVBFp1VfajK0sEL0MXteSZ6kvrqn7n5YFYLbPczQqBTvV8V8hzgXl5JfOU2BgtRu015UtG1v3XSviUjnaFuVuCFTnAc65Y-tH1bLtTp-MPigwfSa2dVQovItSYodJB9gx3"}}
{"timestamp":"2026-02-11T04:38:05.041Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"python3 - <<'PY'\\nimport urllib.request,urllib.parse,json\\nq='project euler 983'\\nurl='https://api.github.com/search/code?q='+urllib.parse.quote(q)\\nreq=urllib.request.Request(url,headers={'Accept':'application/vnd.github+json','User-Agent':'codex'})\\ntry:\\n    data=urllib.request.urlopen(req,timeout=20).read().decode('utf-8')\\n    print(data[:500])\\nexcept Exception as e:\\n    print('err',e)\\nPY\"}","call_id":"call_kfuYFXJizqypxMjXKvTTBGtI"}}
{"timestamp":"2026-02-11T04:38:05.044Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":3872235,"cached_input_tokens":3749120,"output_tokens":69956,"reasoning_output_tokens":41695,"total_tokens":3942191},"last_token_usage":{"input_tokens":88609,"cached_input_tokens":88448,"output_tokens":768,"reasoning_output_tokens":634,"total_tokens":89377},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":12.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:38:05.956Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_kfuYFXJizqypxMjXKvTTBGtI","output":"Chunk ID: 3be038\nWall time: 0.7595 seconds\nProcess exited with code 0\nOriginal token count: 9\nOutput:\nerr HTTP Error 401: Unauthorized\n"}}
{"timestamp":"2026-02-11T04:38:05.989Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:38:06.477Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":3872235,"cached_input_tokens":3749120,"output_tokens":69956,"reasoning_output_tokens":41695,"total_tokens":3942191},"last_token_usage":{"input_tokens":88609,"cached_input_tokens":88448,"output_tokens":768,"reasoning_output_tokens":634,"total_tokens":89377},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":12.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:38:09.546Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Testing unauthenticated Sourcegraph search**"}}
{"timestamp":"2026-02-11T04:38:09.546Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Testing unauthenticated Sourcegraph search**"}],"content":null,"encrypted_content":"gAAAAABpjAexuoo6E8MQjSGfyoKSotCx9wN5W3P-2iHSD6-H0goSI393HzQQePBpvLEScXVvAkofAJtfXgxYCrmi1EkzSN2ohHpnEgSrlXyB4hviBk_kIlojt2PXssbEmGu5BYkIk7U1fTyS3MHKGqY0LDJvwxKxPakvyvBLmF5iE4viglw4Gheo1rMQthPElCha4Y0VV_aN-AVAW4Owx1pzPSj6kCHvEA7fB83I8fizYgRLlKNyx4rAHJjo67WrUpdKqKXb4ws734z8pHPHYDIeXIwWL5dMulS3BrVsfpdJnDXyQm9MNUpZOZEmJ4CE22vwEWK_XfeBsyYycUYSVw6PwvFe-znpa_yLPQ4yyH0k_wtKQRXEidUD5cH0bPPNqaNkBzlJVDu3AaW3ftK0jMaY9fGED9LLfDgjNvtEHO_OlLUI0tkXKDWpiTLvJBczzkfuwvhytISPxsTzEp4wTI2xj8g_ehrIebkMGhej1LuzkPio7yWqY_qb8jPivO41UlZeOMKhNGZcP23Xd_WQbxKCX0WEYLchGIw-dBiVIYyv2RuBEvRumYSHu_mnzsRxwT49r7O7jD6IgqklEBZyxNN_4nYfjbtBJ0JfiZgc4o4d4iseE9r74xGharHXTNn7AqVWGzX7-jbX0OlEaj7hw2JoTH8F1CwxcUnzEG0nPKU72D0ZLhRPQhgpXfudHT_mxBsoh-O_sdEO561pV_UGzkqBXG50Dp4gucogkeUXrBLV3itSxZKs0mFwzEaSctR3PKDjeYbRyUDYjchoUUTq4Xss-q8g4w7R8ONtWGebsTRR_a5a2rzeDtqcwM_6EmrgBpHMqJUpjiErD2sjxSYS6yOnsIKHKvuPNjRJMWC1SdMnIso00I0FjlcraoLZ3ibXeS0_oz6zH8yLrQCrCk-Z-GOgg5R-rzpuV9zlJPQ9RX9KIhFdZ0oSdBhJXdPemHkhxukhELBEjEfGppp-Q6JIMJTzopO--Z8zIEsufNmAh2Sb2OhqCTssN5mSj3vUwuR5FjZlDvoQF7OD3olvt9tywdPVP8KgilyRQvz76EQYoYwxKSPMdNFDELNLEBB34ziNc-je1WujZCeNphjlIBbTmj2W5CaLhdXMemCzFmJP7skWl4UgQjqd72vIe9nqasYamTVnu7V_tf6hr_kZ9zoQYVZB5D1zCNLsH9uwoTDp8wIt3u4_Yjb-r4vweFL5yg3nVyCKzj3MnH5uI1MPc9uJNKogUGqHAG5etL17Q_pwzXsD287wO4zmoYPZgYpEiGf-gU4oUIuHNsWij1VOLL8Xu3oUQLrQdieTdaIa7rIo3iWY89s79kTOnaxIb03K-T4EGpyDqbI0oQPy"}}
{"timestamp":"2026-02-11T04:38:11.494Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"python3 - <<'PY'\\nimport urllib.parse,urllib.request,re\\nq='Project Euler 983'\\nurl='https://sourcegraph.com/search?q='+urllib.parse.quote(q)+'&patternType=literal'\\nhtml=urllib.request.urlopen(url,timeout=20).read().decode('utf-8','ignore')\\nprint('len',len(html))\\nfor m in re.finditer(r'href=\\\"(/[^\\\"]+)\\\"',html):\\n    h=m.group(1)\\n    if 'github.com' in h or '/github.com/' in h:\\n        print(h)\\n        break\\nprint(html[:300])\\nPY\"}","call_id":"call_0j4xQKVWja4IoI5OYNHOZI00"}}
{"timestamp":"2026-02-11T04:38:11.501Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":3961665,"cached_input_tokens":3838464,"output_tokens":70198,"reasoning_output_tokens":41779,"total_tokens":4031863},"last_token_usage":{"input_tokens":89430,"cached_input_tokens":89344,"output_tokens":242,"reasoning_output_tokens":84,"total_tokens":89672},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":12.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:38:12.569Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_0j4xQKVWja4IoI5OYNHOZI00","output":"Chunk ID: 719c74\nWall time: 0.9198 seconds\nProcess exited with code 1\nOriginal token count: 228\nOutput:\nTraceback (most recent call last):\n  File \"<stdin>\", line 4, in <module>\n  File \"/usr/lib/python3.13/urllib/request.py\", line 189, in urlopen\n    return opener.open(url, data, timeout)\n           ~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^\n  File \"/usr/lib/python3.13/urllib/request.py\", line 495, in open\n    response = meth(req, response)\n  File \"/usr/lib/python3.13/urllib/request.py\", line 604, in http_response\n    response = self.parent.error(\n        'http', request, response, code, msg, hdrs)\n  File \"/usr/lib/python3.13/urllib/request.py\", line 533, in error\n    return self._call_chain(*args)\n           ~~~~~~~~~~~~~~~~^^^^^^^\n  File \"/usr/lib/python3.13/urllib/request.py\", line 466, in _call_chain\n    result = func(*args)\n  File \"/usr/lib/python3.13/urllib/request.py\", line 613, in http_error_default\n    raise HTTPError(req.full_url, code, msg, hdrs, fp)\nurllib.error.HTTPError: HTTP Error 403: Forbidden\n"}}
{"timestamp":"2026-02-11T04:38:12.603Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:38:12.945Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":3961665,"cached_input_tokens":3838464,"output_tokens":70198,"reasoning_output_tokens":41779,"total_tokens":4031863},"last_token_usage":{"input_tokens":89430,"cached_input_tokens":89344,"output_tokens":242,"reasoning_output_tokens":84,"total_tokens":89672},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":12.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:38:20.607Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Considering targeted web search**"}}
{"timestamp":"2026-02-11T04:38:20.607Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Exploring GitHub search strategies**"}}
{"timestamp":"2026-02-11T04:38:20.607Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Considering targeted web search**"},{"type":"summary_text","text":"**Exploring GitHub search strategies**"}],"content":null,"encrypted_content":"gAAAAABpjAe8L6WJ3s6rm9Lbr2HtJb_tvI-b6mLvPWVDtktjmJMNImQDeb6WVBAU267kC2GMXufsiXhNVpKIA2Ywk0MWwSPI_TAn9QfMP86KtAwAEpE2xm3W1EcD17zD5rmy_rCDDCn3qCfJmIxDiN4e-koM32MhOOw8rBThbHvQFupNn1a_aco9CLokak_zDNAXm46rDo27ctuNemin8pXA_pkbHGsMxMWPV587SWcEn_PlT98kv1X0dgQXxaOk6mWGX7p9tLdqIlpanFTkx0SPzyCtPlvUaHxHftEVTu-ScKVw8WnLqWvBBV3G95-XTZn7cuyRL3fdkwARbECkea_H36bHsVH6MmObbV86XjgIzkofAvAKoOizF5NjABwYHXBroym_t63N-Jhf_0HlAcvs7jVT1XYTGZQrt-Wk4ieHywzoiqr4uvwuXT746tYQ90-ToHtEAXbFhRsmog-wwsdAaTzQ9zUBoj9INl25CL3HPkiZcsmkUKuo3xOpjnG_V7qwqBnA_S3lORlp7lKwTCpEeiE_vog-LtVRIDL_3dmTqVgShuXyKEAW_LYEAyPG2JkU7w5BGoP5NAxrbWpMGSqPsNB9VnWTuEn3DmvlnMr06eRPXqxyi25afAvaktuyuLN3RWg1WWrksjYyd8i6X1a4VXA8hH13v7_oMqRAIOrMLsxXd-BXrWfkEuR7kb2Z-bVTvOtCrkvp4mhO5dupP0SBVv2rZD78-oYC8oC6mxdePLi-scpnslgLrJ6hVgqthqhzsF_Lnm8KhUrmAC_35bpesgAqDmwu1-3ekYo99Kirt12YEeRDkzCDawvd6ky7Hq5I5CX3o7-ppsCkOIFhYWnVfuFQyWIUKyIFjJeu8lFW4DA-gY32ibbfTQ4sARD4TisR5yLZJ5ezvU4Y4uHcYSN35-rnDpG1WpDl-A84sctVZjv6JtPL5dpDVpYeRBi2O7Vgq1ReSNXLqs2x2iHlO-Y1iESk40SiBEvbRdqa3J1Pobi6yv7Kcm99WFAfDgHbxXXzenz8WPushmSdP18RGkxuD-Ym-JqjfDtO6DywhG8hLRmS7qxzhpcQC1ZfH74sHqXLrMrNtNgjePz7BegGA5SKDYI9fUSulsxdjg65O0skKXZZUAErjO3_pPpy9LwB8GBq8uOLtOjq43dbvSldAT6kwROGu9bVbe0aMBjP2XQWYn1waJLcYKIzPZObp8Wa9g557p9tQj147AVWGOIcJ1hUExodTCqEWGoqGptzFNYIuHbJk6jlz-j4T7gUUV7N92Nipp7TIrdP8fpz824AEbgO9J46HgRmn9RxLyGAuWFQURFyOIeav7XmX5nzwDgPycNWIZ03zWzi7F8wu8juMe-Jxhm51z62kZSeH-y6f2KfXglMjM0whEqlJ9CCljXS6nb--yvLinsVk8UeE4MAXnu1pSenMaNS8lpAy-mT06FKaqzEbAJnNw3Yu2qp70iwXhru4NpmTe7EZ_Sfe7z7ScCJKhO-_CEmnZRGle8X0pLoqXfaxrX0tK3MXB4zEGgTMbHVTanJSFq_izVJj9Rl6weDIFpaEagDCDU1F5hk-FRXhtsA4Ga_ILrhImtLnjdrGO5p1fope-KaDZkSh9izXmcwvkrE6A8uGS4SmPxvQtZkitvGRqDKjkf9bwY88iI0FMSBH1iteEVDAiaVOxlj4te5dECzueBBINo-hyKthUOIX70PPXdESLJ9c4udezNHHZrM1MDWsyb_AwvBu3djyvH9tkWgS5fLOOokfWbMmqq3jxVtxMU_y_Cj9ExI2CnDW3TLLttaCZpgYnBJL9KdlfgPvkB3skqNKnjlimsiaoxdKOjKchczWlhiOlqsYnbPUi1SG8wDOJMNsifbGLKoLPYNtD4TntFAKpPntZ_eDZiyMTZhfwjOuZ6tFgdrjrVXc1zCfCMRtt0-hJCxSH8tfHCicrERw-qxf9xfI5srQgWFihi0TzpsXM_5KUyaQU-4W_UJSljBIEBOajOUJdAfMVobdhAA9X2pqRieshX8V0bfYsKv1MXDR1Tua9TSmeWaheiJ7abNspvGEAmtnLTNone4cVzC0kyfgSuT0yB34f-SXttC3C5DdHAscE14H74_VxN0gXiuidP2QgIf9N8O23i9ka2euOSF9KgQmNOJuvLJQrvZnRfhHon2Yi7_BVagdAgSpV67_zpGGLdW3HgW_ZQjAEYEWbPMi3q3HNH2u7im23bvXtRX5xcp2gvY3JMaFsCHvvY0XaKfAqYnVHYEnoJuWPiWYIlY2zIqLKdct4O31no4P6xfp29AzJWZcZM-bjg4jFCKBFbzJXyC3__ERq9e2LBZn_iBzCRBnwr_fGORzDI0ac5xh2WFo-8McmJDLEYucHx3tPx7T9TvZy5C_FzMZLIcKxyfXMkVpo_99WNdaxKL0y97GNG74PfYU-6KulGbuCmOsHiI_2i0IYqOARr5mQWADLZpcPoggO-LofSfjkbs8af-O_BuLUEGaOvwu5uJAUshSZ9bXbcUCWONlB9lLvPpkPct-AbNrLcPuDclGOZMiT8zkbIHce0FXG3nqL6gTw140uEEvM0aa0X04BUcUZpUYzzalUafJ2pfmyuJL4ym-vgEzBDMJdvPPdm5h9o5ZpqAWhxl34-g65bgTgI_v19zzdKHcld-N1u1HOXdi8Rz00NfaFt7tczx_-Hp44rX5VMM5F4tZ9xYEClTxlpAOjCXy5LLL66YDG5wFn0uPefAzNrwLfCSOVYBu4Zv7K-NqRX-C5uJ190k2pQQeFxxLIs1quraolo9NAWnrnMZOpKBjJWpT6YzIbSKM4tLIbBjtGC6meAwi7HlM5EONC9Z6VSjILAxogHa8ITR3Puo-83apmNHNk4lbCHgDcmkAztyeweTbiMWXkliilb1XBKXtIfNO3jHxt4ZF6TZjk1inYw2U5-QPI668zfpR-sN-RHiS3AOR3yUw30rSo6IPLDlOs0bEU5T_8Mu8wNYkQwN3iANGmauI8TogXeHd1kuIscxLVNteXU4yqA_mK3VoXfAv2t-IOXojw=="}}
{"timestamp":"2026-02-11T04:38:21.632Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"python3 - <<'PY'\\nimport urllib.request,urllib.parse,re\\nq='\\\"Project Euler\\\" 983'\\nurl='https://github.com/search?q='+urllib.parse.quote(q)+'&type=code'\\nreq=urllib.request.Request(url,headers={'User-Agent':'Mozilla/5.0'})\\nhtml=urllib.request.urlopen(req,timeout=20).read().decode('utf-8','ignore')\\nprint('len',len(html))\\nprint(html[:300])\\nprint('contains login?', 'Sign in' in html)\\nfor m in re.finditer(r'href=\\\"(/[^\\\"]+/blob/[^\\\"]+)\\\"',html):\\n    h=m.group(1)\\n    if 'search' not in h:\\n        print('res',h)\\n        break\\nPY\"}","call_id":"call_Roh8h8uRo9g468vynpZOhMVe"}}
{"timestamp":"2026-02-11T04:38:21.635Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":4051637,"cached_input_tokens":3904384,"output_tokens":70687,"reasoning_output_tokens":42076,"total_tokens":4122324},"last_token_usage":{"input_tokens":89972,"cached_input_tokens":65920,"output_tokens":489,"reasoning_output_tokens":297,"total_tokens":90461},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":12.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:38:22.800Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_Roh8h8uRo9g468vynpZOhMVe","output":"Chunk ID: 618906\nWall time: 1.0139 seconds\nProcess exited with code 0\nOriginal token count: 84\nOutput:\nlen 173575\n\n\n<!DOCTYPE html>\n<html\n  lang=\"en\"\n  \n  data-color-mode=\"auto\" data-light-theme=\"light\" data-dark-theme=\"dark\"\n  data-a11y-animated-images=\"system\" data-a11y-link-underlines=\"true\"\n  \n  >\n\n\n\n\n  <head>\n    <meta charset=\"utf-8\">\n  <link rel=\"dns-prefetch\" href=\"https://github.githubassets.com\">\n  <l\ncontains login? True\n"}}
{"timestamp":"2026-02-11T04:38:22.835Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:38:23.263Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":4051637,"cached_input_tokens":3904384,"output_tokens":70687,"reasoning_output_tokens":42076,"total_tokens":4122324},"last_token_usage":{"input_tokens":89972,"cached_input_tokens":65920,"output_tokens":489,"reasoning_output_tokens":297,"total_tokens":90461},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":12.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:38:25.318Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Identifying login-required search patterns**"}}
{"timestamp":"2026-02-11T04:38:25.318Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Identifying login-required search patterns**"}],"content":null,"encrypted_content":"gAAAAABpjAfB9bdtSZPp42OlOKtTISC0NUTfwX7X9qqg92fvPlpp1syMOLZA01xtvqsdS3F78bU8teBxRK3yZTcdd62gpvuXf_7LIwaphXdXguJtgmc-yLHN7F9B8C_Re45ch8ibne1vx7Dn0Lzpmq8YZ2YHNTtiS84czOCOGi1m-H3poXgMwZH32zrtOvMKpyckjh3J89ASKD62qlMnizaJnWesmx1hgs-tz1hTMFsFHcvhRTLP66Dba9kEBvNaZD6-KpdKfh77unPZV7W7DXdqCbe1p50PrfpIjaKfxtlWhFCHoiGZx0JKJkvT4RxAEd2Tq53aXh26xL67C1dln0zitUq25ORdsbFsvcbB2iP2iWpcSJivxLKfCQK5qsximLr8jqpfaJQP8Mxwt_ICACUPy8IB3QUByE6ywMZ6QJyK1MnAcZGKIy7pVcuoZ-W6wrax4486kdS-DLNmYJeCFtQynEKcDjC3bKvIDCvbW7neAoR-OMmksJw2hJQWZEMtTEf5ZAppulONTh36wsDRt6-fsXQ0xtOqmah0L7ttOAJtlq9f4HJw0Z4ZDFiv4Mu4I7gMiG2GxC4R-bcqrWD2eP3TnxamW13DuHEiYKlnx-7wvZhHhK_yCfz20XOIJENmkguBwBW0uWjF4z6-8xQwblK9WLNRQ-y7xZ2sQAs15bHRUPjXOmeLaIZ0Z2Aq5iZ4dlopAfnZjAS_rQ7f43Px9vZwiZugT-V7O7j1W55BMuSUGg2ni0xkyoO0xnvM6GX93hETQF7rhDzAYV4yVvyEdf9cWnaQutZ0NM-y7YMH-1UzJG5TPeHEorEjKp4Wp_pafL0wsRxB6deRqMm5VeMs17MWxOEHJyuTIWATsfrebupBFblpZ3L8mo8_xGGaLW5RgSFuAFI9MJC_Zwy9hvsqXaiuiQxtb8Yi-pp46oCw6FyHfRtisK3vk0CePLMby0K3IJXbKYGDUD2qvS7iVV3zy9rcEbO58PW1UCALWHTegE81AH5Va3aLkOcOKf7F3lfwV8ADSgC_7ZmnOaZnisKAHxrUnSCMyXMwZ3_OBhqzbHmUAxtnUoXEOY0OIKKkp6RXPIZtcYSHSL7-obHh2ZMbvrfB6v4w2toElA3u0WoDlYPz8jJM7TbBB7j8zFlllQQdi6lLtO1jMkN2qJf0dz-zdQtl3EslfwbZi1yWtlUkexZSJ_U3Pc3-op9zall9_T-8vnKNbRFi244w"}}
{"timestamp":"2026-02-11T04:38:26.956Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"python3 - <<'PY'\\nimport urllib.request,urllib.parse,re\\nq='project euler 983'\\nurl='https://github.com/search?q='+urllib.parse.quote(q)+'&type=code'\\nhtml=urllib.request.urlopen(urllib.request.Request(url,headers={'User-Agent':'Mozilla/5.0'}),timeout=20).read().decode('utf-8','ignore')\\nfor pat in ['Sign in to search code','code search','results']:\\n    idx=html.lower().find(pat.lower())\\n    print(pat,idx)\\n    if idx!=-1:\\n        print(html[idx:idx+200])\\nPY\"}","call_id":"call_7tgVvhIgnXRtPpw1jK6F06tg"}}
{"timestamp":"2026-02-11T04:38:26.957Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":4142243,"cached_input_tokens":3994752,"output_tokens":70902,"reasoning_output_tokens":42131,"total_tokens":4213145},"last_token_usage":{"input_tokens":90606,"cached_input_tokens":90368,"output_tokens":215,"reasoning_output_tokens":55,"total_tokens":90821},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":12.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:38:28.099Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_7tgVvhIgnXRtPpw1jK6F06tg","output":"Chunk ID: 59b722\nWall time: 0.9877 seconds\nProcess exited with code 0\nOriginal token count: 167\nOutput:\nSign in to search code 166105\nSign in to search code on GitHub</span><span class=\"Text__StyledText-sc-1klmep6-0 iQSLul prc-Text-Text-9mHv3\">Before you can access our code search functionality please sign in or create a free accoun\ncode search 17588\nCode search results · GitHub</title>\n\n\n\n  <meta name=\"route-pattern\" content=\"/search(.:format)\" data-turbo-transient>\n  <meta name=\"route-controller\" content=\"codesearch\" data-turbo-transient>\n  <met\nresults 17600\nresults · GitHub</title>\n\n\n\n  <meta name=\"route-pattern\" content=\"/search(.:format)\" data-turbo-transient>\n  <meta name=\"route-controller\" content=\"codesearch\" data-turbo-transient>\n  <meta name=\"rout\n"}}
{"timestamp":"2026-02-11T04:38:28.137Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:38:28.613Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":4142243,"cached_input_tokens":3994752,"output_tokens":70902,"reasoning_output_tokens":42131,"total_tokens":4213145},"last_token_usage":{"input_tokens":90606,"cached_input_tokens":90368,"output_tokens":215,"reasoning_output_tokens":55,"total_tokens":90821},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":13.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:38:31.804Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Exploring code search strategies**"}}
{"timestamp":"2026-02-11T04:38:31.804Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Exploring code search strategies**"}],"content":null,"encrypted_content":"gAAAAABpjAfH7Cob9aKHEOjprk6GJ8fSM2UtgJtDuyY9kg7byhlmJvzAZOyPrYEgelmFxXAPkf4xuE1fv_IROq9O9Vk0wIAMeG44bhAgBCm1XOH8Bi0b5RJrPJU8QcBLVKGa6yT8O73YAB4zPAfft8gWzreWwnyhdt75RfvFaC0VrWavsV0Gmxf8MJfEHGs_ZS9WI_UQtA-OMAL00azzY-Qt7CofCb_zMCCkQTIQbDAuVh2VIZd81ZrpCXctE82G593-Y0nSVJSe4oAraMLHzsUAWtE8ZDDR-2K9zrdRlut4LF1cwS8VEyrH2w6v9xAFHL8s7IkS1uiCRKu2rNbqI2HtwCzgL7TB1xYK6rLEtUhGRujlJ_n-uhGUTGI6jjNbodhiKXxpVVSwQJzvZa1bOaiJBrsRl78EMWtBo0vOwqwD6eIApAYHe-SG6Gfn47obSdqI4O4u70gpUf2Q_TNYFM39Uzhvand2zDVdFXr1zNsWAPLgjfZdHR8-O2j_WpoK-Wx5Rb-xwj6snI4A-642kz6YkBO0v5hu7FqDPUvEURU0kj7NW2DOBH5OIBnu40rIAISrB4mILxL4vkVuSlEShjecsIXqUqM6UZMSOuqX0H5Y4qjj-MI4M56nvSTG_VjaW-hC-3-JS4gUaogpJwTxcJs4qXT9mFuTHX9kUvWYhKZGu83Pv6wcYQ9j4ksLCyf4xfCj7ralhYsf5pUoBb8P34SVivlceqGVOHbk4cBsEwHO87_hLLJNs__pipoOTbfCJq0QYNvSAMLt-NHdEmE5U1E_vsUUll1ap5qAZ0njR9l22RBpyjZnGNMBrIRw9vlNBOMBorehfN-CKrSjn84mQPQUAURbjE0rrYKwg-FnqDmNhkysdHNwExQFKn6IkU8UakrU-DGQrQQQKMtnkXgSCuISKU94_90MNZn2clWJp_b12DKh269nXao5jn8VZBsCvEfflj1b3aX81Y8JGnZ0eW2XwRJ-rSOgLRe_Np1Vv-Q1ogzx1uuPA2ZsqSiEdqZBGPWzx7CtWm4gUh7GvJx2ResdbE76ktH2_iNtdiADd8_5xZv1CWy_tgteVShA2LtSPkJG5FSnKDD_x_sRlfTg32n4IJgYkWoIf0TkHKX1fPnaIscY7HdXAGN9ETjcY3U0P_TgKZiTQnzJCYJxML7WHTa8nK9pX38ab_8IPANf1CDANpddJyA0hWf9k1iGzeWWjvyc5tseF2G0pWYeDJmQoxAfurye_VMQZSm4Z_pvSW33gNPRKOLa3nwRs-Udt3jNJrH_M0uJ3affUnKnRkP7N8W3aLG2LTdzsUmAftTc8-mwnusleElZCKC7RXEpqOiCegryDkub1D0MFllEcuIVJgG7qBaV1vt21tR6Em6wnxUt-lBINVj_wSPmzxLq-cgDFRe-I8xJhTI5--ivvRg43B2qzrkKBgkHkjSQsLQNA9UFdyCfUOAL2aVhlxWmhkWtTCTE4KCMmVkfWFdKGKeCmqPxAUeSg0nJN1aNuJxMOUKMiHWlJL0AseCCuLDSQuDell6F0Ru9p2VHCNB9VZailuFIXGVty0oW8TEtgfH7HRjAQaa-yc-Y4CrZIieAwjIPgibecgpZeudGNSYPZ8VWqoMVKogfhu2qzIlNgjwAUbJmTxsPy13I_rD21T0I6FJYrehrhQsV1fTM"}}
{"timestamp":"2026-02-11T04:38:33.817Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"python3 - <<'PY'\\nimport urllib.request,urllib.parse,json\\nqueries=['983.cpp','p983','problem983','Euler 983','PE983','R(500)']\\nfor q in queries:\\n    url='https://grep.app/api/search?q='+urllib.parse.quote(q)\\n    js=json.loads(urllib.request.urlopen(url,timeout=20).read().decode())\\n    print(q,'total',js['hits']['total'])\\n    for h in js['hits']['hits'][:3]:\\n        repo=h.get('repo',{}).get('raw','')\\n        path=h.get('path','')\\n        print(' ',repo,path)\\nPY\"}","call_id":"call_ERE3O4QPWXmJU6CmLmE1PGxx"}}
{"timestamp":"2026-02-11T04:38:33.818Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":4233298,"cached_input_tokens":4085504,"output_tokens":71209,"reasoning_output_tokens":42271,"total_tokens":4304507},"last_token_usage":{"input_tokens":91055,"cached_input_tokens":90752,"output_tokens":307,"reasoning_output_tokens":140,"total_tokens":91362},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":13.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:38:34.974Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_ERE3O4QPWXmJU6CmLmE1PGxx","output":"Chunk ID: 9f9302\nWall time: 1.0020 seconds\nProcess exited with code 1\nOriginal token count: 36\nOutput:\n983.cpp total 7\nTraceback (most recent call last):\n  File \"<stdin>\", line 8, in <module>\nAttributeError: 'str' object has no attribute 'get'\n"}}
{"timestamp":"2026-02-11T04:38:35.007Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:38:35.451Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":4233298,"cached_input_tokens":4085504,"output_tokens":71209,"reasoning_output_tokens":42271,"total_tokens":4304507},"last_token_usage":{"input_tokens":91055,"cached_input_tokens":90752,"output_tokens":307,"reasoning_output_tokens":140,"total_tokens":91362},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":13.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:38:36.583Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Preparing sample JSON output**"}}
{"timestamp":"2026-02-11T04:38:36.583Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Preparing sample JSON output**"}],"content":null,"encrypted_content":"gAAAAABpjAfMlD3bbaO0-zNYbLjkDIszg05l43eflL1o_8NpkA7NpL8ycSSzG4S0q41b448NYyQQyadteBDeJE0sghEY5XVg3Wyf7iMDUI_0t3X8lzcaFqTHvWXIYEVqe4x4huP6bFhGH_9hdiH_07hLJ7PcTU805dnfjRJZTFmZpcyExbOrZc_jG-odN_ukG4EOsXbEo8ZgP0sywisVMdJU0QqbWMYrOFsgpY2LsPzWvTemrVlh7QQmN9TzZksaiPXPenbGWHKuV92ZhEX6fMoXyvZUgFjykAAJoPQldveYJ6z9xhfbXIfGB45oTUvxM7zty0j3q_I3L0qAQQycDHo-HB6yjEThFT2TYhJHCEiIdAnWIuRJkhD62rb9rRppuK-K14IcUxn_LJM_3yR8oWwENytcQ9S3pirTEty9JSzHzWFY4Oi0V0kOgrUMq2xgsJ95YcGbVh5M1uviUdjngtUxHh8G0WFhmrRCN376GjsJQcsF5AEuvdSxepVMZjGKuU0X6B3ekzVmxvH7DZpeotagluD8ylWQDfIN-i43dRACAp4d3PsfEM40bsbCFG6Rz3tS749j0B_oC35tYOUU74w7QtqqRD7NvW8B1OQHGdtyVSbsCnYGp1CFZ8Zg5c1e6C1OMLn3ekNG1bm5SbaBdckwP7-rYuZQmhMS81E9ngypiWI69EIHMDR-7kO2f85_psm-ctBog5oIx6kMj5nhI9BIsDI21AuL2DQwKXafZO5rF-rHjCSxy4lTe-N3v8oaqgVrer6xzbIa7Kb339-BEs9aDoSHYfoeGmDGaqZ_vAo0RGKbSvr6zQSSxP4FLvrSzJTofmKcXnGRDffffF1aJL5-ENSw7VhxMSoZhBA63TK_4mIHZH0G6uNUf5CswfllP65FU3PPSO-KubuCYX_6hlV1sRgYCdJu3g=="}}
{"timestamp":"2026-02-11T04:38:37.822Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"python3 - <<'PY'\\nimport urllib.request,urllib.parse,json\\nq='983.cpp'\\nurl='https://grep.app/api/search?q='+urllib.parse.quote(q)\\njs=json.loads(urllib.request.urlopen(url,timeout=20).read().decode())\\nprint(js.keys())\\nprint(type(js['hits']))\\nprint(js['hits'].keys())\\nprint(js['hits']['hits'][:2])\\nPY\"}","call_id":"call_I4LIqltPv1aPDZoecbLhZuf1"}}
{"timestamp":"2026-02-11T04:38:37.848Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":4324746,"cached_input_tokens":4176768,"output_tokens":71336,"reasoning_output_tokens":42286,"total_tokens":4396082},"last_token_usage":{"input_tokens":91448,"cached_input_tokens":91264,"output_tokens":127,"reasoning_output_tokens":15,"total_tokens":91575},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":13.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:38:38.796Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_I4LIqltPv1aPDZoecbLhZuf1","output":"Chunk ID: 5d27e8\nWall time: 0.8187 seconds\nProcess exited with code 0\nOriginal token count: 455\nOutput:\ndict_keys(['time', 'facets', 'hits'])\n<class 'dict'>\ndict_keys(['total', 'hits'])\n[{'owner_id': '21157610', 'repo': 'ROCm/aomp', 'branch': 'aomp-dev', 'path': 'test/smoke/targc-274983/Makefile', 'content': {'snippet': '<table class=\"highlight-table\"><tr data-line=\"3\"><td><div class=\"lineno\">3</div></td><td><div class=\"highlight\"><pre><span class=\"nv\">TESTNAME</span><span class=\"w\">     </span><span class=\"o\">=</span><span class=\"w\"> </span>targc-274983</pre></div></td></tr><tr data-line=\"4\"><td><div class=\"lineno\">4</div></td><td><div class=\"highlight\"><pre><span class=\"nv\">TESTSRC_MAIN</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span>targc-274<mark>983.cpp</mark></pre></div></td></tr><tr data-line=\"5\"><td><div class=\"lineno\">5</div></td><td><div class=\"highlight\"><pre><span class=\"nv\">TESTSRC_AUX</span><span class=\"w\">  </span><span class=\"o\">=</span></pre></div></td></tr></table>'}, 'total_matches': '1'}, {'owner_id': '21157610', 'repo': 'ROCm/aomp', 'branch': 'aomp-dev', 'path': 'test/smoke/clang-274983/Makefile', 'content': {'snippet': '<table class=\"highlight-table\"><tr data-line=\"5\"><td><div class=\"lineno\">5</div></td><td><div class=\"highlight\"><pre><span class=\"nv\">TESTNAME</span><span class=\"w\">     </span><span class=\"o\">=</span><span class=\"w\"> </span>clang-274983</pre></div></td></tr><tr data-line=\"6\"><td><div class=\"lineno\">6</div></td><td><div class=\"highlight\"><pre><span class=\"nv\">TESTSRC_MAIN</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span>clang-274<mark>983.cpp</mark></pre></div></td></tr><tr data-line=\"7\"><td><div class=\"lineno\">7</div></td><td><div class=\"highlight\"><pre><span class=\"nv\">TESTSRC_AUX</span><span class=\"w\">  </span><span class=\"o\">=</span></pre></div></td></tr></table>'}, 'total_matches': '1'}]\n"}}
{"timestamp":"2026-02-11T04:38:38.832Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:38:39.348Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":4324746,"cached_input_tokens":4176768,"output_tokens":71336,"reasoning_output_tokens":42286,"total_tokens":4396082},"last_token_usage":{"input_tokens":91448,"cached_input_tokens":91264,"output_tokens":127,"reasoning_output_tokens":15,"total_tokens":91575},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":13.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:38:41.939Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Considering query strategies for repo filtering**"}}
{"timestamp":"2026-02-11T04:38:41.940Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Considering query strategies for repo filtering**"}],"content":null,"encrypted_content":"gAAAAABpjAfRBi047VNf2mlG5MJnJ92xg_KNaZ4vM05BbLO5Hy8ffu16LNP8V7mAISizgkZe4j1UJ_6IKB-3S6DDIsrrj8j2EvL3k8mvg2cQpkpz0BkD2aWTCPn-FKZxkulNpyoLPkcD4y0EtOiwMpQZZdWblfm56wEU9dsx8IAEXJtsX2BBX15JcizHHwRfAFt2G-XKnz8105KO6akWtf5rKVv-Q7GlTVDYxDGVMSNg04WIMrgGs35Su3dLYvsXVvNlvR6-sKnQGpxBtnAb6Llv-aWoOhdTGegxBPDEMX5ObeCCzO7b14np5l6T6mXHZIkW06rN1zII4UIOqOwk8Xo3SYMe_Bho5lBteHU0lXc99560JESRNKsJWxIiw_y8tPmuj0jLXgWJyUSoy4R1pIXO4Y4zWvbV5KTuvMxemOl7qQDONPQXzXl3hFyjBPsYmYoqbMUPE0sRWB6DC_E8vx4KifbdiT_NCu43-0Yx1oX_6FuKD33aTJHDbMeH0OTlKI_9n1H3v9YDK5s5A-3B93zMroFfF-uwLUuFvLP43RtwMC8ERZY3_cKsQyQ-xVhqOwW18F_WSSebUKPGc3nv4SpgeKZHdBIDsjK0SUIOp7LTZEawQ4UdpPzC39DFvOIMFjTFOFrufrwY3IOAbhFewiFulSS_K9GZwU2LqsKOGQDSgxvL5_r_wJjzT17vH_lkD2bfRXZsWCuY-qutEv5YSyYFLHiAutzQhSv2xton6STI6u33-QzHb4S_QtbAiwjgNYxdOJF-AKsEBV-KX7Hz9HGlwelntJjtXhlAGDbC5Yrc7_ndBwiEhq3upzEyXI5XXytNAjjBFAB1cTrO6KWc4d3tP61GLc9O743UKl3g_UFVYolS4bwRbw6tTehCF0FSyWG68ZfUf1eq6ScNwJ92nt76XRolfSyP5NG_i8gSLJWBwM53Fpa_wrGud-2bdBBmso948ZyFJfA334nyPCoUMDMvdNWER88h0gcng9VrZuB4aWl0oZL_f48x-e_-bL2-2HoY3OY4vyt5UwIAv5ZDXgFD-ugUFOK83lrBweydaRZ-e63Iw2Sm81mdu6F0nIwnmS3N_ugUffLqPJs9LbRyMWxOLKUmn918pzXEYDLNfHhbyyLH0pnIV5qVWuufO18ZmW5rwK2xEV0SnhTs0v4Xg2jnYqQ2ewbEHNPk8sHZhB9oep91WCwGWh0VMzWaMIRHVglNUykl_YZf6KUpc1J3PPk6iXStUfcxUlp_-ytdnYwzaiU3zoThdlb7biPkS2a4KCQ3Ni9y91vmFS61LLXo0KbnmFzLXbnYoh43j9J8ZoVBR02GpZbmFC59o1579aejqTUWXn1eO4G5"}}
{"timestamp":"2026-02-11T04:38:43.040Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"python3 - <<'PY'\\nimport urllib.request,urllib.parse,json\\nq='harmonise circles'\\nurl='https://grep.app/api/search?q='+urllib.parse.quote(q)\\njs=json.loads(urllib.request.urlopen(url,timeout=20).read().decode())\\nprint('total',js['hits']['total'])\\nfor h in js['hits']['hits'][:20]:\\n    print(h['repo'],h['path'])\\nPY\"}","call_id":"call_THAJYbbAxYWZfKRQj0mcPWJ8"}}
{"timestamp":"2026-02-11T04:38:43.079Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":4416986,"cached_input_tokens":4266368,"output_tokens":71546,"reasoning_output_tokens":42379,"total_tokens":4488532},"last_token_usage":{"input_tokens":92240,"cached_input_tokens":89600,"output_tokens":210,"reasoning_output_tokens":93,"total_tokens":92450},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":13.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:38:44.121Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_THAJYbbAxYWZfKRQj0mcPWJ8","output":"Chunk ID: 6f168e\nWall time: 0.9253 seconds\nProcess exited with code 0\nOriginal token count: 2\nOutput:\ntotal 0\n"}}
{"timestamp":"2026-02-11T04:38:44.156Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:38:44.672Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":4416986,"cached_input_tokens":4266368,"output_tokens":71546,"reasoning_output_tokens":42379,"total_tokens":4488532},"last_token_usage":{"input_tokens":92240,"cached_input_tokens":89600,"output_tokens":210,"reasoning_output_tokens":93,"total_tokens":92450},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":13.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:38:54.120Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Considering web search approach**"}}
{"timestamp":"2026-02-11T04:38:54.120Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Inspecting notebook search result**"}}
{"timestamp":"2026-02-11T04:38:54.120Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Inspecting search result source**"}}
{"timestamp":"2026-02-11T04:38:54.120Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Locating link by pattern**"}}
{"timestamp":"2026-02-11T04:38:54.120Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Verifying link ID extraction via open call**"}}
{"timestamp":"2026-02-11T04:38:54.120Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Exploring Bing RSS search for results**"}}
{"timestamp":"2026-02-11T04:38:54.120Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Considering web search approach**"},{"type":"summary_text","text":"**Inspecting notebook search result**"},{"type":"summary_text","text":"**Inspecting search result source**"},{"type":"summary_text","text":"**Locating link by pattern**"},{"type":"summary_text","text":"**Verifying link ID extraction via open call**"},{"type":"summary_text","text":"**Exploring Bing RSS search for results**"}],"content":null,"encrypted_content":"gAAAAABpjAfewE_USaftZRH0YtXcIjcsScMH8lbD5VgTRTCdRC5GVLEB7XwzlX7MXJShc0T4tYWTfZlrAWqFAfx2hVPPSz5ZjmsVjggK6oqMsslRY8dwlMMbgdslTorG9sCCHsaZdN4mzX_KVZl4gDtn8nFubMrhE9-Gnb6RcdwimytOa1Qa4UCA-XbldSf_T0bs1Dd7zHy8JSb5kqMJDD7-rSyHaDPc0ynirEVxrrLx09DgwjvPSId6lK-1_ei4XPhyvgntgmd1Sj6idaWKuYqx3oa2YrKxCJFOmrOvmpdsaW87z_JpI66YZo9u5qCWQRbppksTJJxqjES0hBmy_TP_MJzx-EP0Q5sJuAjrNQpdJ4FELHcGzJQ5yIzySRNh-yAaEfZPsnfxwzcrtDw315vuta_-N4Jx3YEmvJlEb3nwpZaVvRQAIPxrxj51M2UOtn9J9yFTrL6m6DqZNrpoWAkrWTXFFqzFk7BW-j2S1I5MD_32PxbWi8ZbXKe6NakLFDssGiDpgP_uU0COqRPGxI1OXuEtUihatohczhvGvfSuS2exGzrcwvJsqCv--moN_6XAkQt7lyF9EVkj_H3CkBo2JynOa-XINKIJM1S2otyTLNI7fakBKRKcdgv34n-6VxKks0LkjLqRocob4Lig4OQLz5XosarJToejFW1i19aJVoUuHBI-fqdVbv-JJmH4XixFd4nSu-7odg-MiKMcN1Rn4zOZVAzz9ro10aB4ZNG6FeIwvW63kdM2QAb-4xlVXgytCfZzAMmBqUMJ59dZP30h4bLf6qorACbgoVtC_kZ3aBV4xdLbkQ4rQd-pFHjFItNt_Ps03d_aIh8_w8hecLs1j_wSGsb41kLrxxX7vWCo_5_8MxhxXK8OCHQEtTvdavJh2vlOQqTuB4QBqzXuE-zjlY-XMlvyDkvMH3nDeMgwVlNGLmWWiKlDa47YmNER0-Lyk6tB1YS-LI2oF7vdSkjKeiyJyeDVgwyqDlsmPVFXj17xuf8qYyHIokFzw6UowC1ferxUn2a-5y4-8PiJEdRsMExx3eQflrhXA_Ojs5Vb_FqPJ-dAFHrxVVkZ0kNOTrxbcVxLwe4D8AL6bQi1TitmD0rH2IFuaGBAO0HZFRPkSt16Mw_1Bz-t0N9p0VQv8--wVaxQpDT1BkY_3dy4ZO4ngTmGnX-k4VPmvG6EuqV345SRLjuFkfsIbZcP0-mMRgraw_lOjegJ1EP3tqaH-OENdG9ZAi9euEyevKkrU22eRdPazUlX0qRZGHzJprJil6qV080VpxeXlJVD9Eyljm7P683gF57o4HRrSNcCpYCWgYVzuWAtR-4MP9d1IXIELgDjMrviWsgu6UwMKj9AQWtUYkEWOS4Mi2U6KKCNyHTLh8jwd9kJpDwGmSuNpb3C-sBBTFT15bHhxbNj6kcDqe1HuAIl9DtKk63tLM1WYT0k16aJbX-6yosrVN5_WwFsm5WlUz8OS4VysuC5Uu-Ods3iceDl-Ad25hrVRggVmfg7PysphnJvco2UMAa8h2q4fGPPnBGAiE6L5cAk-PYfupPR2-E5GLJMTGISf7bSyE2vYX7PnexlI15_hgeekP_du4tnRG0Md-QFAnXGpt96jZG44flaQXVLUpm-SecQ_fJOTKprZq6ZMQmEfZyMhtMzaurbCcC-nSdSwdlCD6mR9J8OHB1ShHk5vttsqFZLJnfLjYecuCH1uQpKuk7mO98G4x4CvK4Stn17AtSukZO03yvPzL2mi0Yx0yEIx7j_o79uiiuSeNJPCxNLnYu91QbejakjFNsudEw5CQjG8h8ZV22sFFDRj48Fkv4ZNaiPxoEORVl9m9POL0QRSS9QCx_Yi_Eau6N5GCjb3Luw9xK6jfiUsqifgcWwS_dUTnSCed5U9y3A3xDAzdb-AYctCdPIWRCLa5It6Y-2PYSQYMj1IgbPbi6dXvxIqZlUr0VK_LYTRp76sk8-WGAcgHz-FxknB6lcwGSIi2CQxVcVQzb5CYmn1Dyq80QWZeiKOQ6T9GAMGEoaBYoTUK2P9EuAYz6uW-DSxsX9nMFea-3rqDFnGi_Pv1XBK3lSXwY25mGILyjVUBu2OW5RP-qSVukDUVc1Sd4iE2Kc49XsXjJWRNMRrh-51KXrCB4owVJJDzFZKGHQAimhyfaKZCgronWY3oOxXF_Gt8_sCOAiuCTsJWuYM8N6ngG737aDCa3NMICb-6OtDjbomF0MoG5ki5SZ4J6dbQzOZSKJX1fVNrbw7CvMfBQ6Ne-h-ZMspA2orYxo_cTzFsbaQjDIl-yIo8GAV6NktKLk8oOsO3X1T0ZrPS09XxTepQ_H6yaadVoXWuJcG05uHDNHmVNK3kbOp_7o0HlVWX1Ppbqcmq_jpit3iyd8nAQhj9K8XLMRLcIcx4N4qSojBYyZrjHYm__76GQ2aJyyJ65tGxhkVpTekLDS2u7M_yQUlipMhZQFJEx0_7mUcoe182frR4cu_lA72OVVLHchaR0nZlQVhX5P29lgNdneN-Q5xmy0-_SwBaCNhAt3CjUz7vffxwYr4uLLoTn6tlVnFOHHJrXrezMRx1VKOQZuS0tnUH7okMmNLdM5s9KSC1GTfin_JnVNvPYRGzpQK9EU8sBErYIb6UTFHDSqMtbAYNIrzNEMzeVadtjPcEZQDXUS1coyD_nUiRWrOQ0cV6g5rXTllzokj06Szp20dr8ZR_SHHJxtg8K8qvuBQab3xrIAYVshhSEa1dy9wyxSi22zYmEthdbUWUMIMUw_Ly7ACKd4fVE1e7Zm1ssG6LeBOWOqnqdEPQu1AdK4CTs451p2ive-_f67BN3I55rWIoQ5H0ytoLq3anhiSoIqpk2BUXIVyQ1xvE0GbSi4V5YfyoZQCIM82jq26f-8rGTq4171857eyhrFn-Gl6b_fKmPTbk6w9ZqlFTnW_oWEmFQH0Imhr6S0agZOSlS1uoh3S1TvpM5UF1E7jIJ2-l4Zo8lqmGEElqrGPbuMLDwv1SPiDq-hO7KqVqTvKZ6VxafW6aKq2yC1aPPXCnhTPmpDtsO0fwOMFJpSnSJtEb92pjgKNnN78ewTkOYXkdtHW1ydunjVUwWo4kSvv7vZqIoZjs88of6Ya1RADtonsz8EWcwqkVi1vltyKk4kT9q3DuSUibDmzH8wVrrZVm6wdo2C_hf5cUHUb1-_ZbYfA_gEWY3lwYs4ZpBo5tNIDKH3idEKOa4ONqFcvv0tFOSfGK1gn4Vjznn6yi5HEGxIoFRv5UUWqZrr43r3Avca2e0awg2YbTFjDSXdS7piXDcIXEXtXKgNcBQ_dB9M7WXyXRw96BTk7agJjtAWtCdf8hC1o7qSLebRqnW3-mZHfvhC9Lq_CBNPtO_veER2rwsqzQh5-2q9nVdyyiHPq2J3Mn9ATMxKfDzOwr8qPf8lINAohGqqqjWSx5RiDVCwyGZBll2Z6GCguyDXg0Wtw5Cn3hPEx8K17ENtqFUUwF-pABjdJ5VT_bB3d4xMpdlv1IxpJWzRhdUtmM19a3S8wgevaQDvQ6rUIEz88fsLiTjkHwMzTnp-uDUUrdYmFMIj0AhdJM5G7ROv0xKF6_Ev5ictPdpzPgTa-R2oHnUvMkuBM14eZby4sLFI9WyYcTaYaNuODEnnde_Jt_rZvvoZPAk4gE8-d5NIbOrrjl5G-tryE-nZeIOsAMyv6-wBPdKTW_tHQ0ODRYhI10SHz7hhXdIgxXAyQOwpLx-0kpT9HWqU85CAOm9xNgP6UfRE3Ce3PfhtJ8uAhr4xKV9hm-I4aaZkK3rajDwSzhXnWqOVMgibSqawiOr6v8qFR0wd9tRNM_-JkzmUqniepw4cspHWUQI2MxvLGdjLnZgRVCVXxUy6lRmRJqFFeyHbG5kEQ2RmF45Ac_9tS1Wf1UaxCNT4QY3rUDy3-p7ZyP1H4rc0GfjSI4USZKHMjLjJF3KuURXSGgprFFks_GKtqirDV-pwsWPowPN3G1xfFld-TCte4flVKjRyNR0LrVoY4fhEjOvzJ7lkQ4ux_r1jRFAbwzxfVxUogsxJhbPFnrFLsFQ6j-mkoNQLe_SVG6KjrX0a0bpHURHWz15BYn5vtpb8nmu95_hQiT0h3J6fp5yqsfGrM44yHtm9vdYuurnWiFQpGNKaLGIj2Y-VUyyDIX6Elc94yvD5-Kgb81lDNkle6KRZqjdTXuZfFByCxmqqJni1VTmeCc87D-A57Xk_HZ2mZS1X4QzsUhXEPqmmh5INowzkV9KRp3HHVkZmfycIDb7XQzAVgEHp2NNuMjGZKJ7r18IH_9Ov6kdP12J3w88XvRT1YNkJtrsTs1SamZZ0Dx3NqN7LsUT11HcsWfvgpOqBKvvMu2337uPJjgVwcYYRzdQLxCfQ0-Ci6_g2iXAgplKll_MBOWGJqU8s-YJJTDEqgvhdpzvzaQMZEe-hQQmGNstjTIfHjxeE7iRWxYb_N9JhtXWjqcwLlfNdpQrkcW3fqvFc2pYl3u5J-_LO83bc0SMhAnm3YVkGEhz51lPJNC_RXqgqcpjvALmqhV6edDH73wRNqvQcFvyEdHXRILvPzOrOQesOd2Qz2rtX48A9juaUuxuFpcMjs0fKVwxA38vATiGwNiryPjPysFKgAtACaUvnTXxWyh1zujDCF0J6hlbYYRjPcBVIamNp7ntpFA-_hjEDuHVKVW_6HH8pc1WVFxOH-3WXAcvcpv3Dfa39sSvjv1mmLDvkyFuRv28-qg4JDH8UGo09QMA8Uugq-Ht6pMBlrmxcqTRns6xNEHRFTq_qFQzVitdY89QHfodQq0QDHXTwFOlC7C_Z8fD7VWjxG03n6mlpwf1bDpbqIK4VRZnXYzR4SYEIoOfwslrCyXZfdnbYPGn0qsN9Ezv5AsNPbtfvrtSWlAyM3R4wS5RP2DWKdWhIT7RGS_9k-1spfqtJ-F8_f_iwYUsilTqsm2ImLql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{"timestamp":"2026-02-11T04:38:55.629Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"python3 - <<'PY'\\nimport urllib.parse,urllib.request,xml.etree.ElementTree as ET\\nq='\\\"harmonise\\\" \\\"consonant\\\" circles'\\nurl='https://www.bing.com/search?format=rss&q='+urllib.parse.quote(q)\\nxml=urllib.request.urlopen(url,timeout=20).read()\\nroot=ET.fromstring(xml)\\nfor item in root.findall('./channel/item')[:20]:\\n    print(item.findtext('title'))\\n    print(item.findtext('link'))\\n    print(item.findtext('description')[:120])\\n    print('---')\\nPY\"}","call_id":"call_tNOnsphPkdddFtqgGDOrIPB5"}}
{"timestamp":"2026-02-11T04:38:55.633Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":4509486,"cached_input_tokens":4358784,"output_tokens":72213,"reasoning_output_tokens":42891,"total_tokens":4581699},"last_token_usage":{"input_tokens":92500,"cached_input_tokens":92416,"output_tokens":667,"reasoning_output_tokens":512,"total_tokens":93167},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":13.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":17.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:38:56.664Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_tNOnsphPkdddFtqgGDOrIPB5","output":"Chunk ID: 53ced8\nWall time: 0.8793 seconds\nProcess exited with code 0\nOriginal token count: 561\nOutput:\nHARMONIZE | English meaning - Cambridge Dictionary\nhttps://dictionary.cambridge.org/dictionary/english/harmonize\nHARMONIZE definition: 1. to add harmonies to a tune 2. to be suitable together, or to make different people, plans…. Lea\n---\nHARMONIZE definition and meaning | Collins English Dictionary\nhttps://www.collinsdictionary.com/dictionary/english/harmonize\n4 meanings: 1. to make or become harmonious 2. music to provide a harmony for (a melody, tune, etc) 3. to sing in harmon\n---\nHARMONISE Definition & Meaning - Merriam-Webster\nhttps://www.merriam-webster.com/dictionary/harmonise\nThe meaning of HARMONISE is British spelling of harmonize.\n---\nHarmonise - Definition, Meaning & Synonyms | Vocabulary.com\nhttps://www.vocabulary.com/dictionary/harmonise\nbring into consonance or accord \"Harmonise.\" Vocabulary.com Dictionary, Vocabulary.com, https://www.vocabulary.com/dicti\n---\nharmonize verb - Definition, pictures, pronunciation and ...\nhttps://www.oxfordlearnersdictionaries.com/definition/english/harmonize\nDefinition of harmonize verb in Oxford Advanced Learner's Dictionary. Meaning, pronunciation, picture, example sentences\n---\nHarmonise - definition of harmonise by The Free Dictionary\nhttps://www.thefreedictionary.com/harmonise\nDefine harmonise. harmonise synonyms, harmonise pronunciation, harmonise translation, English dictionary definition of h\n---\n“Harmonize” or “Harmonise”—What's the difference? | Sapling\nhttps://sapling.ai/usage/harmonize-vs-harmonise\nExplanation of the difference between harmonize and harmonise with example usage of each in context.\n---\nharmonise - WordReference.com Dictionary of English\nhttps://www.wordreference.com/definition/harmonise\nharmonise - WordReference English dictionary, questions, discussion and forums. All Free.\n---\nWhat does harmonise mean? - Definitions.net\nhttps://www.definitions.net/definition/harmonise\nDefinition of harmonise in the Definitions.net dictionary. Meaning of harmonise. What does harmonise mean? Information a\n---\nWhat does harmonise mean? definition, meaning and audio ...\nhttps://www.audioenglish.org/z/harmonise.htm\nDefinition of harmonise in the AudioEnglish.org Dictionary. Meaning of harmonise. What does harmonise mean? Proper usage\n---\n"}}
{"timestamp":"2026-02-11T04:38:56.703Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:38:57.127Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":4509486,"cached_input_tokens":4358784,"output_tokens":72213,"reasoning_output_tokens":42891,"total_tokens":4581699},"last_token_usage":{"input_tokens":92500,"cached_input_tokens":92416,"output_tokens":667,"reasoning_output_tokens":512,"total_tokens":93167},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":13.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":18.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:38:58.923Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Refining search query strategy**"}}
{"timestamp":"2026-02-11T04:38:58.923Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Refining search query strategy**"}],"content":null,"encrypted_content":"gAAAAABpjAfiYK2Yh4V3P0rBIwF9qR-sh5XR9SqSON_mOdAquDaYRePT0cQlzmBQENS0GTItrpLOIIIzOQadLY_kVZvacpnxD2O2C0ac5WcwJTSgFnfEzNXp7SfdyrgdLQy9dCpRtPxdVYs_qKSgCHEyGYBwwJhEZULvs8zB4i23p0Smr148Bb6zhi9KPrdRe1vH-INigqmEpKauBjS2Gi7jsvZVExAJ8Cxabd5MAHFHVg6oNw9kbrJbrTKDdKCQqui7ZpMc8765ihGq8ISiwrwq1usHtbOaN_vPgkjbJZzeL5GyRAkQpygnhDRIF66KisfrCDGsD4e31nZL8pgQhpfZeXC_oXwYvIV1TK94AYmvqTC0CrJ7agz4102axpnlNfcZ9Rb9vWAG8zW-ho_E86nmcJLM7HO2I4H15EoNmZVU11qtMz_PsKTuiWytQlbdSK7L9tCruQSSSGOMtzGViGRtRAESwZxPLtWvZ1OXB5sgVXk9_w-hAPYZ3_jJMibP7wEGjWfHuoJDgts-BYq3JoptG9ItmHWx59L2jn2xWvMlLHSaUKpbNJMhMeTGBh7-R2LGOo0tPytsittFm3-p08OVJPUhr8-ACJQHcIYzu5-nUWX9ca48S1gvGiF2xlzaHIZrv0FwJLA3gWOhOAkAv9rEjxkEFriQQPL_E06Z56UFi3fp6H-lmHvXky9oXDOzjpAN2UYHCTqEclxGoCE_upgICg2U9dRDJm_DjoctZrHlE0qxDx2UICToOdExWeWmmMYnFK8BNAWUG0F5svaCDn1vovdNLZcVLqhnRaqURIDyF_0ptZudtVWCkjFGC-72ASLmG-l8GHLVXZ3sAAReuZDOrajN4I68jiUwzfYa8UQvWUsDkP94I-InuFf-0I8IWDNPpbV042h7xFKQAt9wcp5GAH9BCN9SVh-u67GR-NhBvy8Ld7TDuIjDyOugaWqRct3SHBsSk1PmV1UO-yk8vTxhdaUWOvkgew=="}}
{"timestamp":"2026-02-11T04:39:00.443Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"python3 - <<'PY'\\nimport urllib.parse,urllib.request,xml.etree.ElementTree as ET\\nq='\\\"R(4)\\\" \\\"sqrt(5)\\\" \\\"Project Euler\\\"'\\nurl='https://www.bing.com/search?format=rss&q='+urllib.parse.quote(q)\\nxml=urllib.request.urlopen(url,timeout=20).read()\\nroot=ET.fromstring(xml)\\nfor item in root.findall('./channel/item')[:20]:\\n    print(item.findtext('title'))\\n    print(item.findtext('link'))\\n    print('---')\\nPY\"}","call_id":"call_J22weAAnGYaNnsSdn9tu1j2l"}}
{"timestamp":"2026-02-11T04:39:00.445Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":4603214,"cached_input_tokens":4451840,"output_tokens":72391,"reasoning_output_tokens":42922,"total_tokens":4675605},"last_token_usage":{"input_tokens":93728,"cached_input_tokens":93056,"output_tokens":178,"reasoning_output_tokens":31,"total_tokens":93906},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":13.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":18.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:39:01.306Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_J22weAAnGYaNnsSdn9tu1j2l","output":"Chunk ID: efde74\nWall time: 0.7069 seconds\nProcess exited with code 0\nOriginal token count: 327\nOutput:\nWhat does |> (pipe greater than) mean in R? - Stack Overflow\nhttps://stackoverflow.com/questions/67744604/what-does-pipe-greater-than-mean-in-r\n---\nsyntax - What does %>% function mean in R? - Stack Overflow\nhttps://stackoverflow.com/questions/27125672/what-does-function-mean-in-r\n---\nWhat is the difference between \\r\\n, \\r, and \\n? [duplicate]\nhttps://stackoverflow.com/questions/15433188/what-is-the-difference-between-r-n-r-and-n\n---\n该如何学习 R 语言？ - 知乎\nhttps://www.zhihu.com/question/21654166\n---\nDifference between Boolean operators && and & and between || and | in R\nhttps://stackoverflow.com/questions/6558921/difference-between-boolean-operators-and-and-between-and-in-r\n---\nmagrittr - What does %>% mean in R - Stack Overflow\nhttps://stackoverflow.com/questions/24536154/what-does-mean-in-r\n---\nThe R %*% operator - Stack Overflow\nhttps://stackoverflow.com/questions/22060515/the-r-operator\n---\nNewest 'r' Questions - Stack Overflow\nhttps://stackoverflow.com/questions/tagged/r?tab=Newest\n---\nWhat is the difference between = and == in R? - Stack Overflow\nhttps://stackoverflow.com/questions/28176650/what-is-the-difference-between-and-in-r\n---\nnewline - Difference between \\n and \\r? - Stack Overflow\nhttps://stackoverflow.com/questions/1761051/difference-between-n-and-r\n---\n"}}
{"timestamp":"2026-02-11T04:39:01.344Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:39:01.795Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":4603214,"cached_input_tokens":4451840,"output_tokens":72391,"reasoning_output_tokens":42922,"total_tokens":4675605},"last_token_usage":{"input_tokens":93728,"cached_input_tokens":93056,"output_tokens":178,"reasoning_output_tokens":31,"total_tokens":93906},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":13.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":18.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:39:03.153Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Refining search strategy**"}}
{"timestamp":"2026-02-11T04:39:03.153Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Refining search strategy**"}],"content":null,"encrypted_content":"gAAAAABpjAfnQESY5xmO29dK9TQ3paY_4tkSpT7qBnlcqwU8DeEXBi7ahicyBHP3BnSDWQXNA65hApyc3ytDiqbYNUc1i32cez18Ot4sbTRSv-v-DP-BHYj40HhkM_jiBBuokR9Q-AhrUyitSF15c7tnydHzxcIUPmpRLZsdLznDSCYBUYSpidMr7rWtlpZfuKrnYshUIkkBvJ7RMskWa2vOCyq6Hwcx7CwrUk8fKFOQiG1qiCxoP5yZEux0hQRPS0f3Mg09MqatcfYnnmFKUNUFsmKaKg39tS0rfNwSsmPdH28rU0y0sbksOJsDE-1fiiqEqrAJvhs6mJYDHfpm68lFC495MfJIKhzcPZQIOE4ut180Aqi-zqH6MQMZOIayWEUlUzioJzAIQM8gMU6GH1Wb-2YHEXCVuPyxsOeqeIuhx7DBwvNmWueLCKTejEhLXO2Xgg5rh2_tgixlzdyKOBHLcq39jslXioXXzlpsug1sj6mw3g3v0I3crjiwPaw8jAGZjW_26WhUm8rgLsNpj4U-WCb6Jnpj0QRnWBu55h_SIWn1jRPU2vxAnSRjlWFy3bdeHAgZke4dbzcAlm3fxXMICPyca6hd2B2bWxPgmcLgOHnhsUv2Qv1yRg8_1i_dN1zwnr7T37FzRTR3IYx37YuW0rGZwOH3hcu3Nq9TP5FPpPAqbbIFJsXEHf0LQYaxTgg_PkiDSGtn35-s58jP8J9VJog0HR0C0ehWx60QAwv8oO5L9VipGIIx0s_510LP8jUm7g8XvidMkbqp1WnIvNkKKNjy5FvgAz0ZTwF_vPkm0-RpDtDORrmsmZJz_3KOqZ4ePpodVBUieUfxG0FKGCIG3fEsud70_SXbRKS7C4OuT-K1OhjudWvnHnQxXdsckRhDh1sQsF-lEnUa5gYoIuhx_xw3bes9iXM51JcHTPwhS_EckeavB8SBP1IJJ9KJlN1PEZqZpJCZ3o7bFgxJJ2yUdY7a-hWeowlVrDmQVsZDQ0Z7t5K28s88ZMxLnsTYXo8o7CgcZC4f"}}
{"timestamp":"2026-02-11T04:39:04.932Z","type":"response_item","payload":{"type":"function_call","name":"exec_command","arguments":"{\"cmd\":\"python3 - <<'PY'\\nimport urllib.parse,urllib.request,xml.etree.ElementTree as ET\\nq='\\\"intersect at two grid points\\\" circles'\\nurl='https://www.bing.com/search?format=rss&q='+urllib.parse.quote(q)\\nxml=urllib.request.urlopen(url,timeout=20).read()\\nroot=ET.fromstring(xml)\\nfor item in root.findall('./channel/item')[:20]:\\n    print(item.findtext('title'))\\n    print(item.findtext('link'))\\n    print('---')\\nPY\"}","call_id":"call_zBCsnqykjLXOYqWeSCvuLB3C"}}
{"timestamp":"2026-02-11T04:39:04.960Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":4697494,"cached_input_tokens":4545408,"output_tokens":72563,"reasoning_output_tokens":42954,"total_tokens":4770057},"last_token_usage":{"input_tokens":94280,"cached_input_tokens":93568,"output_tokens":172,"reasoning_output_tokens":32,"total_tokens":94452},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":13.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":18.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:39:05.932Z","type":"response_item","payload":{"type":"function_call_output","call_id":"call_zBCsnqykjLXOYqWeSCvuLB3C","output":"Chunk ID: 6d5f4d\nWall time: 0.8454 seconds\nProcess exited with code 0\nOriginal token count: 330\nOutput:\narcgis 实用教程系列： [9]叠加分析Intersect-百度经验\nhttps://jingyan.baidu.com/article/656db918872b68e380249c71.html\n---\n[VBA] Utilisation de la méthode Intersect - Forum Excel-Pratique\nhttps://forum.excel-pratique.com/astuces/vba-utilisation-de-la-methode-intersect-1314\n---\nAide + explication If Not Intersect - Forum Excel-Pratique\nhttps://forum.excel-pratique.com/excel/aide-explication-if-not-intersect-162580\n---\nIf Not Intersect ( [G5:G20], Target) Is Nothing - Forum Excel-Pratique\nhttps://forum.excel-pratique.com/excel/if-not-intersect-g5-g20-target-is-nothing-187328\n---\nArcgis进阶：分析工具（相交）-百度经验\nhttps://jingyan.baidu.com/article/5225f26b5a3720e6fa090839.html\n---\n[GR] GR Casio intersect - Scholieren.com forum\nhttps://forum.scholieren.com/showthread.php?t=1832568\n---\nMATLAB求数组交集和并集的方法 - 百度经验\nhttps://jingyan.baidu.com/article/36d6ed1f807cac1bcf48833a.html\n---\nSnijpunten met de grafische rekenmachine? - Scholieren.com\nhttps://forum.scholieren.com/showthread.php?t=8908\n---\n在VBA中，intersect的实例应用！ - 百度经验\nhttps://jingyan.baidu.com/article/37bce2bea1c97d1002f3a223.html\n---\nBlender入门教程-4.12、布尔交切与切刀交切-百度经验\nhttps://jingyan.baidu.com/article/e73e26c091f24d24acb6a743.html\n---\n"}}
{"timestamp":"2026-02-11T04:39:05.966Z","type":"turn_context","payload":{"cwd":"/home/ciro/tmp/983_3","approval_policy":"never","sandbox_policy":{"type":"workspace-write","network_access":true,"exclude_tmpdir_env_var":false,"exclude_slash_tmp":false},"model":"gpt-5.3-codex","personality":"pragmatic","collaboration_mode":{"mode":"default","settings":{"model":"gpt-5.3-codex","reasoning_effort":"xhigh","developer_instructions":null}},"effort":"xhigh","summary":"auto","user_instructions":"## Skills\nA skill is a set of local instructions to follow that is stored in a `SKILL.md` file. Below is the list of skills that can be used. Each entry includes a name, description, and file path so you can open the source for full instructions when using a specific skill.\n### Available skills\n- skill-creator: Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Codex's capabilities with specialized knowledge, workflows, or tool integrations. (file: /home/ciro/.codex/skills/.system/skill-creator/SKILL.md)\n- skill-installer: Install Codex skills into $CODEX_HOME/skills from a curated list or a GitHub repo path. Use when a user asks to list installable skills, install a curated skill, or install a skill from another repo (including private repos). (file: /home/ciro/.codex/skills/.system/skill-installer/SKILL.md)\n### How to use skills\n- Discovery: The list above is the skills available in this session (name + description + file path). Skill bodies live on disk at the listed paths.\n- Trigger rules: If the user names a skill (with `$SkillName` or plain text) OR the task clearly matches a skill's description shown above, you must use that skill for that turn. Multiple mentions mean use them all. Do not carry skills across turns unless re-mentioned.\n- Missing/blocked: If a named skill isn't in the list or the path can't be read, say so briefly and continue with the best fallback.\n- How to use a skill (progressive disclosure):\n  1) After deciding to use a skill, open its `SKILL.md`. Read only enough to follow the workflow.\n  2) When `SKILL.md` references relative paths (e.g., `scripts/foo.py`), resolve them relative to the skill directory listed above first, and only consider other paths if needed.\n  3) If `SKILL.md` points to extra folders such as `references/`, load only the specific files needed for the request; don't bulk-load everything.\n  4) If `scripts/` exist, prefer running or patching them instead of retyping large code blocks.\n  5) If `assets/` or templates exist, reuse them instead of recreating from scratch.\n- Coordination and sequencing:\n  - If multiple skills apply, choose the minimal set that covers the request and state the order you'll use them.\n  - Announce which skill(s) you're using and why (one short line). If you skip an obvious skill, say why.\n- Context hygiene:\n  - Keep context small: summarize long sections instead of pasting them; only load extra files when needed.\n  - Avoid deep reference-chasing: prefer opening only files directly linked from `SKILL.md` unless you're blocked.\n  - When variants exist (frameworks, providers, domains), pick only the relevant reference file(s) and note that choice.\n- Safety and fallback: If a skill can't be applied cleanly (missing files, unclear instructions), state the issue, pick the next-best approach, and continue.","truncation_policy":{"mode":"tokens","limit":10000}}}
{"timestamp":"2026-02-11T04:39:06.485Z","type":"event_msg","payload":{"type":"token_count","info":{"total_token_usage":{"input_tokens":4697494,"cached_input_tokens":4545408,"output_tokens":72563,"reasoning_output_tokens":42954,"total_tokens":4770057},"last_token_usage":{"input_tokens":94280,"cached_input_tokens":93568,"output_tokens":172,"reasoning_output_tokens":32,"total_tokens":94452},"model_context_window":258400},"rate_limits":{"primary":{"used_percent":13.0,"window_minutes":300,"resets_at":1770800461},"secondary":{"used_percent":18.0,"window_minutes":10080,"resets_at":1771313591},"credits":{"has_credits":false,"unlimited":false,"balance":null},"plan_type":null}}}
{"timestamp":"2026-02-11T04:39:11.687Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Exploring external problem solution sources**"}}
{"timestamp":"2026-02-11T04:39:11.688Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Considering targeted domain search**"}}
{"timestamp":"2026-02-11T04:39:11.688Z","type":"event_msg","payload":{"type":"agent_reasoning","text":"**Exploring direct challenge URL**"}}
{"timestamp":"2026-02-11T04:39:11.688Z","type":"response_item","payload":{"type":"reasoning","summary":[{"type":"summary_text","text":"**Exploring external problem solution sources**"},{"type":"summary_text","text":"**Considering targeted domain search**"},{"type":"summary_text","text":"**Exploring direct challenge URL**"}]