learn-from-code-review
Learn from Code Review
Analyze code review comments from GitHub pull requests and distill them into reusable skills or repository guidelines that improve future code quality.
Overview
Code review feedback contains valuable institutional knowledge that often gets buried across hundreds of PRs. This skill extracts meaningful patterns from review comments and transforms them into:
- Repository-specific skills - Placed in
.openhands/skills/for domain-specific patterns - AGENTS.md guidelines - Overall repository conventions and best practices
Prerequisites
GITHUB_TOKENenvironment variable must be set- GitHub CLI (
gh) should be available
Workflow
Step 1: Identify Target Repository
More from openhands/skills
ssh
Establish and manage SSH connections to remote machines, including key generation, configuration, and file transfers. Use when connecting to remote servers, executing remote commands, or transferring files via SCP.
478codereview-roasted
Brutally honest code review in the style of Linus Torvalds, focusing on data structures, simplicity, and pragmatism. Use when you want critical, no-nonsense feedback that prioritizes engineering fundamentals over style preferences.
119jupyter
Read, modify, execute, and convert Jupyter notebooks programmatically. Use when working with .ipynb files for data science workflows, including editing cells, clearing outputs, or converting to other formats.
88code-review
Rigorous code review focusing on data structures, simplicity, security, pragmatism, and risk/safety evaluation. Provides brutally honest, actionable feedback on pull requests or merge requests, including a risk assessment for every review. Use when reviewing code changes.
82readiness-report
Evaluate how well a codebase supports autonomous AI development. Analyzes repositories across eight technical pillars (Style & Validation, Build System, Testing, Documentation, Dev Environment, Debugging & Observability, Security, Task Discovery) and five maturity levels. Use when users request `/readiness-report` or want to assess agent readiness, codebase maturity, or identify gaps preventing effective AI-assisted development.
74security
Security best practices for secure coding, authentication, authorization, and data protection. Use when developing features that handle sensitive data, user authentication, or require security review.
69