code-review

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Perform thorough code reviews with security, performance, and maintainability analysis. Use when user asks to review code, check for bugs, or audit a codebase.

Code & Development 62,572 stars 10220 forks Updated today MIT

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Quality Score: 93/100

Stars 20%
100
Recency 20%
100
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

# Code Review Skill You now have expertise in conducting comprehensive code reviews. Follow this structured approach: ## Review Checklist ### 1. Security (Critical) Check for: - [ ] **Injection vulnerabilities**: SQL, command, XSS, template injection - [ ] **Authentication issues**: Hardcoded credentials, weak auth - [ ] **Authorization flaws**: Missing access controls, IDOR - [ ] **Data exposure**: Sensitive data in logs, error messages - [ ] **Cryptography**: Weak algorithms, improper key management - [ ] **Dependencies**: Known vulnerabilities (check with `npm audit`, `pip-audit`) ```bash # Quick security scans npm audit # Node.js pip-audit # Python cargo audit # Rust grep -r "password\|secret\|api_key" --include="*.py" --include="*.js" ``` ### 2. Correctness Check for: - [ ] **Logic errors**: Off-by-one, null handling, edge cases - [ ] **Race conditions**: Concurrent access without synchronization - [ ] **Resource leaks**: Unclosed files, connections, memory - [ ] **Error handling**: Swallowed exceptions, missing error paths - [ ] **Type safety**: Implicit conversions, any types ### 3. Performance Check for: - [ ] **N+1 queries**: Database calls in loops - [ ] **Memory issues**: Large allocations, retained references - [ ] **Blocking operations**: Sync I/O in async code - [ ] **Inefficient algorithms**: O(n^2) when O(n) possible - [ ] **Missing caching**: Repeated expensive computations ### 4. Maintainabilit...

Details

Author
shareAI-lab
Repository
shareAI-lab/learn-claude-code
Created
11 months ago
Last Updated
today
Language
Python
License
MIT

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