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JLMA-Agentic-Ai
JLMA-Agentic-AiCOMMUNITY
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GitHub

github-code-review

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

Updated Aug 23, 2026
Search Tags:#automation#github#swarm#code-review#ai-agents#pr-management
One-click install
npx skills add https://github.com/JLMA-Agentic-Ai/ruv_downloads --skill github-code-review-jlma-agentic-ai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: github-code-review
Source: https://github.com/JLMA-Agentic-Ai/ruv_downloads/tree/main/.claude/skills/github-code-review
Command: npx skills add https://github.com/JLMA-Agentic-Ai/ruv_downloads --skill github-code-review-jlma-agentic-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Pull requests often require lengthy, multi-faceted reviews; this Skill coordinates AI-powered swarm agents to perform thorough, consistent GitHub code reviews across PRs.

Core Features & Use Cases

  • Multi-agent review system with specialized agents for security, performance, architecture, style, and accessibility
  • Automated PR commentary, fixes suggestions, and quality gates to accelerate merges
  • Use cases include complex, high-risk PRs, architectural refactors, and security-sensitive changes

Quick Start

Initialize a swarm on a PR to spawn agents and generate actionable inline comments.

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?▼

Automated GitHub PR code reviews coordinate AI-powered swarm agents to perform multi-domain analysis for security, performance, architecture, style, and accessibility, generating inline comments and fix suggestions.

What is multi-agent swarm code review and how does it work for pull requests?▼

Multi-agent swarm code review spawns specialized AI agents to analyze pull requests across diverse projects. Agents target specific domains like security and architecture, then generate structured feedback and automated commentary.

Do I need GitHub CLI and ruv-swarm to run automated PR commentary?▼

Yes, automated PR commentary requires GitHub CLI, ruv-swarm, and claude-flow for orchestration. These dependencies coordinate the swarm agents and handle automated comment generation on your pull requests.

Can AI code review handle security-sensitive changes and architectural refactors?▼

AI code review handles security-sensitive changes and architectural refactors by deploying specialized agents for multi-domain analysis. Quality gates ensure thorough, consistent feedback for high-risk pull requests.

What's the best way to add quality gates to automated GitHub PR reviews?▼

The best way to add quality gates is through swarm-driven orchestration that coordinates specialized agents. These agents enforce quality checks and generate structured feedback before pull requests can merge.

When should I use multi-agent AI code review instead of standard automated checks?▼

Use multi-agent AI code review for complex, high-risk pull requests requiring multi-domain analysis. Standard checks lack the specialized agents needed for thorough security, performance, and architecture reviews.

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