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name	description
orchestrating-swarms	Master multi-agent orchestration using Claude Code's TeammateTool and Task system. Use when coordinating multiple agents, running parallel code reviews, creating pipeline workflows with dependencies, building self-organizing task queues, or any task benefiting from divide-and-conquer patterns.

Claude Code Swarm Orchestration

Master multi-agent orchestration using Claude Code's TeammateTool and Task system.

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How Claude Code Team Coordination Works

Observed by: observer agent Date: 2026-02-09 Team: moltbook-tui (1 lead + 4 agents, observed over ~10 minutes of activity) Snapshots taken: 7 (see snapshot-1.md through snapshot-7.md for raw data)

Architecture Overview

Claude Code teams use a filesystem-based coordination system. There are no sockets, databases, or message queues - everything is stored as JSON files on disk. Agents coordinate through:

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Developer Productivity Reports - Index

Organization: N1CO Finance Development Team
Report Date: February 7, 2026
Repositories Analyzed:

• n1co-finance-backend
• n1co-app-gateway

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Developer Productivity & Code Quality Report

h4b-dev/n1co-finance-backend & h4b-dev/n1co-app-gateway

Report Period: October 1, 2025 - February 7, 2026
Generated: 2026-02-07
Total PRs Analyzed: 163 (Backend: 100, Gateway: 63)

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2026-02-04 — Memory Log

Summary

Day split between infrastructure lookups and a deep GCP cross-project data access investigation. Located ArgoCD configs and traced how hugofun-prod data flows into BI/analytics projects.

Completed

GCP Cross-Project Data Access Investigation

Status: ✅ Root cause identified (Dataset-Level ACLs)

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Agent Guidelines for Python Code Quality

This document provides guidelines for maintaining high-quality Python code. These rules MUST be followed by all AI coding agents and contributors.

Your Core Principles

All code you write MUST be fully optimized.

"Fully optimized" includes:

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At the end of this message, I will ask you to do something. Please follow the "Explore, Plan, Code, Test" workflow when you start.

Explore

First, use parallel subagents to find and read all files that may be useful for implementing the ticket, either as examples or as edit targets. The subagents should return relevant file paths, and any other info that may be useful.

Plan

Next, think hard and write up a detailed implementation plan. Don't forget to include tests, lookbook components, and documentation. Use your judgement as to what is necessary, given the standards of this repo.

If there are things you are not sure about, use parallel subagents to do some web research. They should only return useful information, no noise.

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import _ from "lodash"
import React from "react"
import moment from "moment"
import { connect } from "react-redux"
import API from "@Services/Api/profile"
import { ApiManager } from "../../api/apiManager"
import ParsedText from "react-native-parsed-text"
import { NavigationEvents } from "react-navigation"
import { DateToWordsFromNow } from "../../helpers/helper"
import { ACTIVITY_NOTIFICATION } from "../../api/constants"