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review-pr

Orchestrate multi-agent code reviews on GitHub pull requests.

Updated Feb 12, 2026
Search Tags:#automation#developer tools#code review#pull request#github#ai agents
One-click install
npx skills add https://github.com/sdebaun/turnout-mvp --skill review-pr-sdebaun
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: review-pr
Source: https://github.com/sdebaun/turnout-mvp/tree/main/.claude/skills/review-pr
Command: npx skills add https://github.com/sdebaun/turnout-mvp --skill review-pr-sdebaun

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates the process of code review for pull requests by leveraging specialized AI agents, ensuring comprehensive feedback across various aspects of code quality.

Core Features & Use Cases

  • Systematic Code Review: Engages multiple AI agents, each focusing on specific areas like architecture, security, testing, and style.
  • Automated Feedback: Generates inline comments and a synthesized review summary directly on GitHub.
  • Use Case: When submitting a complex feature branch, invoke this Skill to get immediate, detailed feedback on architectural alignment, potential security flaws, test coverage, and adherence to coding standards, significantly speeding up the development cycle.

Quick Start

Use the review-pr skill to perform a full review on pull request number 42.

Frequently Asked Questions about review-pr

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

FAQPage Schema
How do I automate code review for GitHub pull requests?▼

To automate code review for GitHub pull requests, this system orchestrates multiple specialized AI agents to fetch PR details, analyze architecture, testing, security, and style, then synthesizes the findings into a single comprehensive report optionally posted directly to GitHub.

What does multi-agent code review look for in a pull request?▼

Multi-agent code review evaluates pull requests by spawning specialized agents that independently assess architectural alignment, potential security flaws, test coverage, and adherence to coding standards before synthesizing the collected findings into a coherent summary.

Can I use AI agents to post inline review comments directly on GitHub?▼

Yes, you can use AI agents to post inline review comments directly on GitHub, as the system synthesizes findings from specialized reviewers and optionally posts the generated feedback and summary back to the pull request.

Do I need a GitHub MCP server to run automated PR reviews?▼

Yes, you need a GitHub MCP server integration to run automated PR reviews, because the system requires it to perform pull request operations and retrieve file content for the specialized agents to analyze.

What is the best way to review complex feature branches before merging?▼

The best way to review complex feature branches is invoking this multi-agent system to get immediate, detailed feedback across architectural alignment, security flaws, test coverage, and coding standards, significantly speeding up the development cycle.

Are there limitations to using AI for code review on GitHub?▼

A limitation of using AI for code review is that it requires a GitHub MCP server for pull request operations, and while it synthesizes feedback across multiple domains, developers must still manually validate the generated architectural and security findings before merging.

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