ralph-review

Automates per-story code review and PR readiness reporting for Ralph-generated commits.

Updated Jul 6, 2020
One-click install
npx skills add https://github.com/guifry/devconfig --skill ralph-review-guifry
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: ralph-review
Source: https://github.com/guifry/devconfig/tree/main/claude/skills/ralph-review
Command: npx skills add https://github.com/guifry/devconfig --skill ralph-review-guifry

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Post-loop code reviews can be tedious and error-prone, especially when Ralph-generated commits must be verified against requirements, tested, and prepared for PR.

Core Features & Use Cases

  • Automated Ralph commit identification: Detect commits produced by the Ralph loop and collate related stories.
  • PRD.json guidance integration: Load story details, acceptance criteria, and test expectations to validate changes.
  • Per-story quality audits: For each story with a story-{id}: prefix, review diffs, verify acceptance criteria, assess code quality, and confirm test coverage.
  • Full-suite validation & reporting: Run the project’s test suite, generate per-story verdicts, and produce an overall PR readiness report.

Quick Start

Run the Ralph Review skill on a branch containing Ralph-generated commits to produce a per-story verdict and PR-ready report.

Frequently Asked Questions about ralph-review

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

FAQPage Schema
How do I automate code review for pull requests generated by AI loops?

Automated post-loop code review identifies AI-generated commits and collates related stories to streamline pull request preparation. It validates diffs, verifies acceptance criteria, checks test coverage, and generates per-story verdicts.

How do I verify per-story acceptance criteria from PRD.json in a code review?

You can verify per-story acceptance criteria by loading PRD.json details and matching them against story-specific code diffs. The review process checks each story prefix, audits code quality, and confirms test coverage to ensure requirements are met.

Can I generate a PR readiness report for multiple commits on a branch?

Yes, running a post-loop review on a branch containing AI-generated commits produces an overall PR readiness report. It executes the project's test suite, generates per-story verdicts, and aggregates them into a final readiness assessment.

Does the code review process check test execution and coverage automatically?

Yes, the review process includes full-suite validation by running the project's test suite. It assesses test execution checks and confirms test coverage for each story to ensure the generated commits pass quality audits.

What is the best way to review diffs for commits with story-specific prefixes?

The best way to review story-specific prefixed commits is to perform per-story diff analysis. This approach isolates changes for each story, verifies acceptance criteria, assesses code quality, and confirms test coverage before generating a verdict.

When should I avoid using automated post-loop commit review?

You should avoid using automated post-loop review for projects not utilizing AI loops to generate commits and PRs. It specifically requires generated commits and PRD.json interpretation to function correctly.