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bmad-os-review-pr

Review GitHub Pull Requests and generate severity-rated engineering findings.

Updated Mar 7, 2026
Search Tags:#code quality#automation#github#pr review#adversarial testing#engineering findings
One-click install
npx skills add https://github.com/Geargrindadmin/gg-agentic-harness --skill bmad-os-review-pr
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: bmad-os-review-pr
Source: https://github.com/Geargrindadmin/gg-agentic-harness/tree/main/.agent/skills/bmad-os-review-pr
Command: npx skills add https://github.com/Geargrindadmin/gg-agentic-harness --skill bmad-os-review-pr

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill automates the process of performing a deep, adversarial review of a GitHub Pull Request, transforming cynical feedback into actionable engineering findings.

Core Features & Use Cases

  • Automated PR Analysis: Scans PRs for potential issues, security vulnerabilities, and areas for improvement.
  • Structured Feedback Generation: Outputs findings in a professional, engineering-focused format, suitable for direct posting to a PR.
  • Use Case: When a developer asks to "review a PR," this skill can be invoked to provide a thorough, critical assessment, ensuring code quality and robustness before merging.

Quick Start

Use the bmad-os-review-pr skill to review the pull request with the number 123.

Frequently Asked Questions about bmad-os-review-pr

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

FAQPage Schema
How do I automate an adversarial code review on a GitHub pull request?▼

Automated adversarial PR review parses GitHub pull request details, simulates a cynical reviewer to identify issues, then transforms feedback into neutral engineering findings with severity ratings before posting.

What is adversarial testing for GitHub PR reviews?▼

Adversarial PR review simulates a cynical reviewer to critically analyze code changes, identifying potential issues and areas for improvement before converting the feedback into professional engineering findings.

How do I generate professional engineering findings from a PR review?▼

Generating professional engineering findings involves parsing PR details, checking for explicit input, ensuring a clean git checkout, analyzing PR size and binary files, and transforming cynical feedback into actionable advice with severity ratings.

Do I need the gh CLI installed to review pull requests with this automation?▼

Yes, the gh CLI is required as a dependency to fetch PR details and post the automated adversarial code review as a comment directly to the GitHub pull request.

Can I review large pull requests with binary files using automated adversarial testing?▼

Automated adversarial PR review analyzes PR size and binary files during processing, but does not post the review until you confirm the generated engineering findings.

When should I not use an automated adversarial approach for PR review?▼

Avoid automated adversarial PR review when you need a simple syntax check, as this approach focuses on deep critical analysis, simulating cynical feedback transformed into structured engineering findings with severity ratings.

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