When does the agent push back on a suggestion?

Pushback occurs when a suggestion breaks existing functionality, lacks context, violates YAGNI principles, or conflicts with the human partner's established architectural decisions.

Why does this skill discourage saying 'thank you' or 'great point'?

The skill prioritizes 'technical rigor over social comfort.' Eliminating performative agreement ensures the agent focuses on verification and action rather than polite but unverified compliance.

How does it handle unclear review items?

It implements a 'stop-and-clarify' rule. If any part of a feedback list is unclear, the agent must ask for clarification on those specific items before implementing any part of the request.

What is the 'verification-first' principle?

It is a requirement to check every suggestion against the actual codebase reality and project constraints before acknowledging or starting the implementation.

Technical Code Review Reception

Name: Technical Code Review Reception
Author: CommandCodeAI

byCommandCodeAI

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Collaboration Tools

Enforces a rigorous technical verification workflow for processing code review feedback while eliminating performative agreement.

This skill optimizes how Claude processes and responds to code review feedback by prioritizing technical correctness over social compliance. It establishes a 'verify-before-implementing' workflow that requires the agent to restate requirements, check codebase reality, and push back on technically unsound suggestions. By removing performative politeness and focusing on technical rigor, this skill ensures that feedback—whether from a human partner or an external reviewer—is handled with the skepticism and precision required for high-stakes software development.

Key Features

01Context-aware skepticism for external or automated review sources

02Elimination of performative phrases and unnecessary gratitude

03Structured handling for ambiguous or multi-item feedback sets

04Verification-first response pattern for all incoming feedback

05Strict YAGNI validation for suggested 'professional' features

064 GitHub stars

Use Cases

01Resolving architectural conflicts between human reviewers and AI implementations

02Managing complex multi-point feedback from senior developers

03Evaluating third-party security audits or automated PR suggestions

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add commandcodeai/agent-skills receiving-code-review

For use in Claude.ai and ChatGPT

Download Skill