What problem does it solve?
It prevents incorrect, premature, or performative changes by ensuring you process code review feedback as a technical evaluation workflow before implementing anything.
Core Features & Use Cases
- Structured reception workflow: Read feedback fully, restate requirements, verify against the codebase, then evaluate and respond technically.
- Clarification-first safety: Stops implementation when any item is unclear and asks for clarification to avoid partial misunderstanding.
- Phrasing discipline for GitHub/threads: Uses specific non-performative language rules and avoids gratitude/apologies in favor of concrete, verifiable actions.
- Implementation sequencing & testing: Implements multi-item feedback one item at a time with tests and regression checks, prioritizing blocking issues first.
- YAGNI and pushback handling: Checks actual code usage, avoids adding unused “proper” features, and pushes back with technical reasoning when suggestions conflict with reality or prior decisions.
Quick Start
Ask your AI to process incoming code review comments using the skill’s verify-first pattern, requesting clarification for any unclear items before making changes.
