What happens if a code review suggestion is unclear?

The skill mandates a full stop; the AI will ask for clarification on all ambiguous items before implementing any part of the feedback to avoid partial or incorrect fixes.

How does this skill handle polite or performative phrases?

It explicitly forbids phrases like 'You're absolutely right!' or 'Great point!', replacing them with technical acknowledgments or direct action to maintain professional rigor and focus on the code.

How does it handle feedback that conflicts with the codebase?

It instructs the AI to push back with technical reasoning, specific questions, or references to existing tests rather than blindly following incorrect suggestions.

Does this skill support GitHub reviews?

Yes, it includes specific instructions for replying within GitHub comment threads using the appropriate API calls rather than posting top-level PR comments.

Code Review Reception Rigor

Name: Code Review Reception Rigor
Author: pedropaulovc

bypedropaulovc

0•

Collaboration Tools

Standardizes how AI agents process and implement code review feedback with technical rigor and zero performative bias.

This skill equips Claude with a structured framework for handling code review feedback, moving beyond blind implementation toward critical technical evaluation. It enforces a "verify before acting" protocol that prioritizes codebase reality over social compliance, ensuring that suggestions are technically sound, necessary (YAGNI), and aligned with existing architectural decisions. By eliminating performative phrases and requiring clarification for ambiguous tasks, it maintains high code quality and prevents regressions during the collaborative review cycle.

Key Features

01Identifies YAGNI (You Ain't Gonna Need It) violations in reviewer suggestions to prevent bloat.

02Provides a structured response pattern for handling unclear or conflicting reviewer instructions.

03Enforces a 'No Performative Agreement' policy to prioritize technical facts over social politeness.

04Standardizes GitHub thread replies and multi-item implementation order for better collaboration.

05Verifies feedback against the actual codebase before implementation to ensure technical accuracy.

060 GitHub stars

Use Cases

01Evaluating external pull request suggestions for compatibility and potential regressions.

02Managing multi-step refactoring tasks where feedback items are highly interdependent.

03Processing complex feedback from multiple human reviewers with potentially conflicting technical opinions.

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add pedropaulovc/personal-marketplace receiving-code-review

For use in Claude.ai and ChatGPT

Download Skill