How does the multi-agent approach differ from a standard AI review?

Standard reviews use one model for all tasks; this skill orchestrates four specialized agents focused on logic, security, architecture, and testing, providing significantly higher accuracy for complex changes.

Can I use this for security audits?

Yes, it includes a dedicated Security Auditor agent that checks for OWASP Top 10 vulnerabilities, SQL injection, XSS, and exposed secrets.

What are the different review modes available?

It offers 'Quick' for fast feedback, 'Standard' for full parallel analysis, and 'Thorough' which includes extended agents for silent failure hunting and comment analysis.

Does it integrate with my CI/CD pipeline?

Absolutely. It is designed to work with GitHub Actions and pre-commit hooks, allowing you to enforce quality gates automatically during the development lifecycle.

Code Review Pipeline

Name: Code Review Pipeline
Author: pagerguild

bypagerguild

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Collaboration Tools

Orchestrates multi-agent AI code reviews using specialized security, architectural, and logic auditors to ensure production-grade code quality.

The Code Review Pipeline skill transforms standard AI code reviews into a sophisticated multi-agent orchestration process. By utilizing specialized agents for security, architecture, logic, and testing, it achieves significantly higher accuracy than single-model reviews. It implements a scatter-gather pattern that parallelizes deep analysis, aggregates findings through a consensus mechanism, and generates a unified report with severity classifications, making it an essential tool for teams enforcing high code quality standards before commits or merges.

Key Features

010 GitHub stars

02Integrated security auditing for OWASP Top 10 and secret exposure

03Flexible review modes ranging from quick WIP checks to thorough production-grade audits

04Consensus-based aggregation to de-duplicate findings and prioritize critical issues

05Automated test coverage analysis and edge-case detection

06Multi-agent orchestration for parallelized logic, security, and architectural analysis

Use Cases

01Performing comprehensive security and logic audits before merging major PRs

02Validating AI-generated code to ensure it meets architectural standards and test requirements

03Enforcing consistent code quality gates within CI/CD pipelines and pre-commit hooks

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add pagerguild/guilde-lite code-review-pipeline

For use in Claude.ai and ChatGPT

Download Skill