github-code-review

You can automate GitHub code reviews by coordinating a multi-agent AI swarm to analyze pull requests for security, performance, architecture, style, and accessibility. This system orchestrates specialized agents to generate inline comments and run quality gates.

A multi-agent swarm for PR management is a coordinated group of specialized AI agents that review different codebase aspects simultaneously. It orchestrates security, performance, architecture, and accessibility checks to generate inline comments across pull requests.

Yes, you need the gh CLI to fetch pull request data, alongside ruv-swarm and claude-flow to orchestrate the AI agents. These tools enable the automated workflow to initialize reviews and generate inline comments on GitHub.

Yes, AI code review swarms apply to pull requests of varying sizes and ecosystems. The multi-agent system deploys specialized agents to analyze security, performance, architecture, style, and accessibility across diverse codebases.

To start a swarm review, initialize the multi-agent system using gh pr view to fetch pull request data and ruv-swarm to trigger review-init. This launches specialized agents to perform automated analysis and generate inline comments.

AI swarm agents perform specialized code checks including security, performance, architecture, style, and accessibility reviews. These coordinated agents analyze codebases and generate inline comments to enforce quality gates across pull requests.