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GitHub

github-code-review

Coordinate specialized AI agents to review GitHub pull requests.

Updated Feb 10, 2026
Search Tags:#code review#pull request#github#security analysis#ai agents#quality gates#swarm orchestration
One-click install
npx skills add https://github.com/monktui/git-review --skill github-code-review-monktui
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: github-code-review
Source: https://github.com/monktui/git-review/tree/main/.claude/skills/github-code-review
Command: npx skills add https://github.com/monktui/git-review --skill github-code-review-monktui

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It helps teams perform thorough GitHub pull request reviews by coordinating specialized AI analysis across security, performance, style, architecture, and accessibility to reduce missed issues and speed up decision-making.

Core Features & Use Cases

  • Multi-agent PR review orchestration (swarm coordination): Launch multiple specialized reviewers in parallel to cover different quality dimensions on the same PR.
  • Automated GitHub workflow actions: Generate review comments, request changes, post status updates, and manage labels based on results.
  • Quality gate enforcement: Apply configurable thresholds (for example block on critical security issues, warn on performance regressions, suggest style improvements) to support consistent merge readiness.

Quick Start

Initialize a comprehensive multi-agent review for PR 123 by fetching its diff and metadata with GitHub CLI and starting a swarm with agents for security, performance, style, architecture, and accessibility.

Frequently Asked Questions about github-code-review

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate GitHub pull request code reviews using AI agents?▼

Multi-agent PR review orchestration launches specialized AI agents in parallel to analyze security, performance, style, architecture, and accessibility dimensions. Agents fetch PR diffs via GitHub CLI and post automated comments, status updates, and label management actions back to GitHub.

Can I enforce quality gates on pull requests with AI code review?▼

Quality gate enforcement applies configurable thresholds to PR reviews, such as blocking critical security issues, warning on performance regressions, and suggesting style improvements. This supports consistent merge readiness by automatically requesting changes based on AI analysis results.

Do I need GitHub CLI and a swarm toolchain to run multi-agent code reviews?▼

Yes, GitHub CLI is required to retrieve pull request context, diffs, and metadata. A swarm or review toolchain like ruv-swarm or claude-flow is necessary to orchestrate and run the specialized AI agents that analyze the diffs and post results back to GitHub.

What is the best way to coordinate multiple AI reviewers for a single pull request?▼

Coordinating multiple AI reviewers requires launching a swarm with specialized agents for security, performance, style, architecture, and accessibility. This parallel orchestration covers different quality dimensions on the same PR to reduce missed issues and accelerate decision-making.

How does AI swarm orchestration handle security analysis and performance regressions in PR diffs?▼

Swarm orchestration deploys dedicated security and performance AI agents to analyze PR diffs. The security agent identifies critical vulnerabilities to block merges, while the performance agent detects regressions to trigger warnings, ensuring comprehensive automated quality checks.

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