github-code-review

Coordinate multiple AI agents to review GitHub pull requests across code quality domains.

1|Updated Apr 14, 2026
One-click install
npx skills add https://github.com/Krishpotanwar/my-personal-vibe-coding-setup --skill github-code-review-krishpotanwar
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: github-code-review
Source: https://github.com/Krishpotanwar/my-personal-vibe-coding-setup/tree/main/.agents/skills/github-code-review
Command: npx skills add https://github.com/Krishpotanwar/my-personal-vibe-coding-setup --skill github-code-review-krishpotanwar

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill streamlines the process of conducting in-depth code reviews on GitHub by deploying multiple AI-powered agents to analyze security, performance, architecture, style, and accessibility aspects, ensuring high-quality code before merge.

Core Features & Use Cases

  • Multi-agent review system: Deploys specialized AI agents simultaneously to evaluate different code quality facets.
  • PR-based swarm management: Automates swarm creation, agent spawning, and workflow orchestration directly from GitHub PRs.
  • Automated workflows: Integrates with CI/CD pipelines to run reviews during PR creation or updates.
  • Comment generation: Produces contextual inline comments and summaries, simplifying reviewer collaboration.
  • Quality gates: Enforces policy thresholds and triggers alerts or blocks based on security, performance, or style issues.
  • Custom agent support: Allows creation and registration of tailored review agents aligned with project standards.

Quick Start

To initiate a multi-agent code review on a pull request, retrieve PR details with GitHub CLI, then run the swarm initialization command specifying the PR number and desired agents to coordinate analysis and generate comments automatically.

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 code reviews for pull requests?

To automate GitHub code reviews, you can coordinate multiple AI agents to analyze pull requests. This system integrates with CI/CD pipelines to trigger reviews during PR creation or updates, evaluating security and performance automatically.

What is multi-agent code review and how does it work?

Multi-agent code review deploys specialized AI agents simultaneously to evaluate different code quality facets like architecture, style, and accessibility. It manages workflows and generates contextual inline comments directly on GitHub pull requests.

Can I use custom AI agents to check project-specific code standards?

Yes, you can create and register tailored review agents aligned with your project standards. The system allows custom agent support to enforce specific policy thresholds and trigger alerts based on your unique requirements.

Does automated code review work with existing CI/CD pipelines?

Automated code review integrates directly with CI/CD pipelines to run during PR creation or updates. It orchestrates swarm creation and agent spawning directly from GitHub PRs to ensure high-quality code before merge.

How do I enforce quality gates for security and performance on GitHub PRs?

You can enforce quality gates by setting policy thresholds that trigger alerts or block merges based on security, performance, or style issues. The multi-agent system evaluates these facets and generates summaries to simplify reviewer collaboration.

What is the best way to run security and performance analysis on a GitHub pull request?

The best way to run security and performance analysis is using a multi-agent swarm system. By retrieving PR details with GitHub CLI and running the initialization command, specialized agents coordinate analysis and generate comments automatically.