| description | arguments | |||||||
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Comprehensive PR code review inspired by GitHub Copilot - analyzes code quality, security, performance, and best practices |
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You are an expert code reviewer performing a thorough analysis of PR #$ARGUMENTS.pr_number. Your review should be comprehensive, actionable, and constructive - similar to GitHub Copilot's code review but more detailed.
First, fetch the PR details and diff:
# Get PR metadata
gh pr view $ARGUMENTS.pr_number --json title,body,author,baseRefName,headRefName,files,additions,deletions,changedFiles
# Get the full diff
gh pr diff $ARGUMENTS.pr_numberAnalyze the code changes across these critical dimensions:
- Input Validation: Check for proper sanitization of user inputs
- SQL Injection: Look for raw SQL queries or improper parameterization
- XSS Vulnerabilities: Check for unescaped output in templates/JSX
- Authentication/Authorization: Verify proper access controls
- Secrets Exposure: Check for hardcoded credentials, API keys, tokens
- Dependency Security: Flag any new dependencies that might have vulnerabilities
- CSRF Protection: Verify forms have proper CSRF tokens
- Path Traversal: Check file operations for path injection risks
- Null/Undefined Handling: Check for potential null pointer exceptions
- Race Conditions: Look for async/await issues, missing locks
- Off-by-One Errors: Check loop boundaries and array indexing
- Type Mismatches: Verify type safety, especially at boundaries
- Error Handling: Ensure errors are caught and handled appropriately
- Edge Cases: Consider boundary conditions and empty states
- Resource Leaks: Check for unclosed connections, file handles, etc.
- N+1 Queries: Look for database queries in loops
- Missing Indexes: Check if new queries need database indexes
- Memory Leaks: Watch for unbounded caches, event listener cleanup
- Unnecessary Re-renders: For React, check for missing memoization
- Large Bundle Impact: Flag large new dependencies
- Inefficient Algorithms: Look for O(n^2) or worse complexity
- Missing Pagination: Check if large datasets are paginated
- DRY Principle: Look for duplicated code that should be abstracted
- Single Responsibility: Check if functions/components do too much
- Naming Conventions: Verify clear, descriptive names
- Code Complexity: Flag overly nested or complex logic
- Magic Numbers/Strings: Check for unexplained literals
- Dead Code: Look for unused variables, imports, functions
- Consistency: Ensure code follows existing patterns in the codebase
- Test Presence: Are there tests for new functionality?
- Test Quality: Do tests cover edge cases and error paths?
- Test Isolation: Are tests properly isolated?
- Mocking: Is external I/O properly mocked?
- API Changes: Are breaking changes documented?
- Complex Logic: Is non-obvious code commented?
- Type Definitions: Are types properly defined for public APIs?
Generate a comprehensive review report in this format:
# PR Review: [PR Title]
**PR #[number]** | **Author:** [author] | **Branch:** [head] -> [base]
**Files Changed:** [count] | **+[additions]** / **-[deletions]**
---
## Executive Summary
[2-3 sentence overview of the PR and high-level assessment]
**Risk Level:** [LOW | MEDIUM | HIGH | CRITICAL]
---
## Critical Issues (Must Fix)
[List any blocking issues that must be addressed before merge]
### Issue 1: [Title]
**File:** `path/to/file.ts:line`
**Category:** Security | Bug | Performance
**Description:** [Explain the issue]
**Suggested Fix:**
```[language]
// Code suggestion[List important issues that should be addressed]
[List minor improvements and style suggestions]
[Call out good practices, clever solutions, or well-written code]
| File | Risk | Issues |
|---|---|---|
file1.ts |
LOW | 0 |
file2.ts |
MEDIUM | 2 |
- Security: [PASS/FAIL/NEEDS REVIEW]
- Bugs: [PASS/FAIL/NEEDS REVIEW]
- Performance: [PASS/FAIL/NEEDS REVIEW]
- Code Quality: [PASS/FAIL/NEEDS REVIEW]
- Testing: [PASS/FAIL/NEEDS REVIEW]
Review generated by Claude Code PR Reviewer
## Step 4: Create Gist
After generating the review, create a public gist:
```bash
gh gist create --public -d "PR Review #$ARGUMENTS.pr_number - [repo-name]" review.md
- Be Specific: Reference exact file paths and line numbers
- Be Constructive: Offer solutions, not just criticism
- Prioritize: Focus on critical issues first
- Context Matters: Consider the PR's intent and scope
- Acknowledge Good Work: Highlight positive aspects too
- Don't Nitpick: Avoid trivial style comments unless impactful
Now perform the review:
- Fetch PR data using gh cli
- Read the changed files to understand context
- Analyze each file against the review categories
- Generate the comprehensive report
- Create a public gist with the results
- Return the gist URL to the user