What problem does it solve? When receiving code review feedback, AI assistants often respond with performative agreement or blindly implement suggestions without verifying them against the actual codebase. This Skill enforces a disciplined response pattern: read, understand, verify, evaluate, then implement or push back with technical reasoning. ## Core Features & Use Cases - Structured Response Pattern: A six-step workflow (read, understand, verify, evaluate, respond, implement) that prevents premature implementation of unverified feedback. - Source-Specific Handling: Different rules for feedback from your human partner versus external reviewers, including skepticism checks and YAGNI validation for suggested features. - Pushback and Clarification Guidance: Concrete rules for when to push back with technical reasoning, when to ask for clarification on unclear items, and how to reply to GitHub inline review threads. - Use Case: A reviewer suggests removing legacy code or adding a metrics endpoint. Instead of agreeing immediately, you grep the codebase, find the endpoint is unused, and respond with a YAGNI-based question before changing anything. ## Quick Start Use the receiving-code-review skill to evaluate this reviewer's feedback against the codebase before implementing any changes.
