What problem does it solve? When receiving code review feedback, AI agents often respond with performative agreement or blindly implement suggestions without verifying them against the actual codebase, leading to broken functionality, unnecessary features, and wasted effort. ## Core Features & Use Cases - Structured Response Pattern: Enforces a read-understand-verify-evaluate-respond-implement workflow for every piece of review feedback. - Pushback Guidance: Provides criteria for when and how to challenge incorrect suggestions using technical reasoning instead of blind compliance. - YAGNI Checks: Instructs verification of actual code usage before implementing "proper" features that nothing calls. - Use Case: A reviewer suggests removing legacy compatibility code. Instead of agreeing, the agent checks build targets, discovers the code is still required, and responds with the technical reason plus a targeted fix proposal. ## Quick Start Apply the receiving-code-review skill to evaluate the reviewer comments on my pull request before implementing any changes.