What problem does it solve?
Human reviewers have limited time and cannot inspect every changed file in a large pull request or branch. This Skill builds a focused list of the files most likely to cause a review to fail, so reviewers spend attention where it matters.
Core Features & Use Cases
- Multi-Agent Triage: Launches four parallel agents (change-story, change-impact, change-failure, change-expectation) that each rank files by importance, severity, detectability, and confidence.
- Three Review Modes: Supports local-changes (staged/unstaged/untracked), branch-diff against the detected default branch, and single-commit review workflows.
- Random Sampling: Adds a random sample of changed files via a Python script to catch issues the agents may have missed, plus a separate list of declarative files.
- Use Case: Before reviewing a 200-file pull request, run this Skill to get a ranked table of roughly 25 key files with key facts, risks, and design decisions summarized.
Quick Start
Ask the agent to triage the current changes for review, for example: prioritize which changed files in this branch I should review first.