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nidhi-subrah
nidhi-subrahCOMMUNITY
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GitHub

github-code-review

Orchestrate multi-agent code reviews on GitHub pull requests.

3|Updated Mar 7, 2026
Search Tags:#automation#github#swarm#code-review#pr-management#ai-assist
One-click install
npx skills add https://github.com/nidhi-subrah/HackCanada2026 --skill github-code-review-nidhi-subrah
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: github-code-review
Source: https://github.com/nidhi-subrah/HackCanada2026/tree/main/.agents/skills/github-code-review
Command: npx skills add https://github.com/nidhi-subrah/HackCanada2026 --skill github-code-review-nidhi-subrah

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Streamline and amplify code review workflows on GitHub by coordinating a swarm of specialized AI agents to assess pull requests quickly and thoroughly.

Core Features & Use Cases

  • Multi-Agent Review: parallel evaluation of changes across security, performance, style, architecture, and more.
  • Automated PR Management: comments, approvals, and labels updated automatically based on findings.
  • Quality Gates & Compliance: enforce checks and guide fixes to raise code quality.
  • Swarm Orchestration: coordinated tasks prevent duplication and ensure comprehensive coverage.
  • Actionable Comment Synthesis: generate precise, helpful review notes for developers.

Quick Start

Initialize a swarm on a specific PR and let agents begin the analysis.

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 code reviews on GitHub pull requests?▼

You can automate code reviews on GitHub pull requests by orchestrating a multi-agent AI swarm to evaluate changes in parallel. This coordinates specialized agents to analyze security, performance, and style, automatically posting synthesized feedback and labels directly to the PR.

What is multi-agent swarm code review for GitHub?▼

Multi-agent swarm code review is a process where specialized AI agents evaluate GitHub pull requests in parallel. This orchestrated topology prevents duplicate analysis, ensuring comprehensive coverage across security, architecture, and performance to provide actionable review notes quickly.

Can I use AI-assisted code review for enterprise GitHub repositories?▼

Yes, AI-assisted code review supports both open-source and enterprise GitHub repositories. It integrates with GitHub CLI to enforce quality gates, manage PR comments, apply automated labels, and guide fixes for fast, thorough pull request evaluation at scale.

What's the best way to manage pull request feedback automatically?▼

The best way to manage pull request feedback automatically is using an orchestrated AI swarm to synthesize actionable comments. Agents evaluate changes across multiple dimensions, updating PR comments, approvals, and labels based on their findings without manual intervention.

Does automated PR review work with the GitHub CLI?▼

Yes, automated PR review integrates directly with the GitHub CLI. This integration enables the AI swarm to access pull request data, apply automated labels, post synthesized review comments, and enforce quality gates on open-source and enterprise repositories.

How do I configure a swarm topology for AI code review?▼

You configure a swarm topology by initializing an AI agent swarm on a specific GitHub pull request. This orchestrates specialized agents to perform parallel analysis across different code dimensions, preventing duplication and ensuring comprehensive automated feedback.

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