How does this skill handle social interactions in code reviews?

It intentionally removes performative agreement and gratitude expressions like 'Excellent point' or 'You're absolutely right,' focusing instead on technical acknowledgment and direct action to maintain professional rigor.

How does this skill help maintain the YAGNI principle?

It prompts the AI to grep the codebase for actual usage before implementing complex features suggested by reviewers, ensuring that unnecessary endpoints or logic aren't added.

What happens if the code review feedback is unclear?

The skill mandates a full stop on implementation. The AI is instructed to ask for clarification on all unclear items before proceeding to ensure a partial understanding doesn't lead to incorrect code.

Can the AI push back on a human reviewer's suggestion?

Yes, the skill explicitly instructs the AI to push back with technical reasoning if a suggestion is incorrect, violates YAGNI, or conflicts with established architectural decisions.

Code Review Reception

Name: Code Review Reception
Author: dsifry

bydsifry

•

Herramientas de Colaboración

Standardizes a rigorous, technical-first approach to processing and implementing code review feedback without performative agreement.

This skill transforms how Claude interacts with code review feedback by prioritizing technical verification and skepticism over social compliance. It establishes a structured workflow for evaluating suggestions against the codebase reality, ensuring that implementations are technically sound rather than just polite. By stripping away conversational filler and enforcing a 'verify-before-acting' mentality, it empowers the AI to provide reasoned pushback when suggestions violate architectural patterns or the YAGNI principle, ultimately leading to higher-quality code and fewer unnecessary features.

Características Principales

01Strict non-performative response protocol to eliminate conversational filler

02YAGNI (You Ain't Gonna Need It) evaluation for suggested 'professional' features

03Context-aware skepticism for external reviewer suggestions versus partner decisions

04Structured handling for unclear or multi-item feedback to prevent partial implementations

0529 GitHub stars

06Technical verification workflow that checks suggestions against codebase reality

Casos de Uso

01Maintaining architectural integrity by providing technical pushback on incorrect suggestions

02Preventing the implementation of unnecessary code bloat suggested during the PR process

03Processing complex feedback from multiple human reviewers with conflicting perspectives

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add dsifry/goodtogo receiving-code-review

For use in Claude.ai and ChatGPT

Download Skill