receiving-code-review

Verify code review feedback against codebase reality before implementation.

58|6|Updated Jan 20, 2026
One-click install
npx skills add https://github.com/barretstorck/gemini-superpowers --skill receiving-code-review-barretstorck
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: receiving-code-review
Source: https://github.com/barretstorck/gemini-superpowers/tree/main/skills/receiving-code-review
Command: npx skills add https://github.com/barretstorck/gemini-superpowers --skill receiving-code-review-barretstorck

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill prevents the AI from blindly accepting code review feedback, ensuring that suggestions are technically sound, relevant to the codebase, and align with project goals before implementation. It promotes critical evaluation over performative agreement.

Core Features & Use Cases

  • Verification Protocol: Guides the AI through a structured process to understand, verify, and evaluate feedback.
  • Reasoned Pushback: Enables the AI to question or reject feedback with technical justification, rather than accepting it unquestioningly.
  • Use Case: When a reviewer suggests a change, the AI will first check if the suggestion breaks existing functionality, aligns with the project's architecture, and is actually necessary (YAGNI), before proceeding with implementation.

Quick Start

When receiving code review feedback, verify each item against the codebase and respond with technical acknowledgment or reasoned pushback.

Frequently Asked Questions about receiving-code-review

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I evaluate code review feedback before implementing changes?

Handling code review feedback requires checking each suggestion against existing functionality and project architecture, ensuring technical accuracy and alignment before implementation rather than performative agreement.

How do I push back on code review comments with technical justification?

Push back on code review comments by evaluating suggestions for technical correctness and project alignment, providing reasoned technical justification to reject feedback that breaks existing functionality or violates YAGNI.

Why does AI blindly accept code review suggestions without checking the codebase?

AI blindly accepts code review suggestions due to performative agreement, bypassing the necessary verification of whether the feedback breaks existing functionality or aligns with project-specific rules.

What is the best way to verify code review suggestions against project architecture?

The best way to verify code review suggestions is a verification-first protocol that checks feedback for technical accuracy, codebase relevance, and project alignment before proceeding with implementation.

When should I reject code review feedback based on YAGNI principles?

Reject code review feedback based on YAGNI principles when the suggested change is not actually necessary, breaks existing functionality, or fails to align with the project's architecture and technical accuracy standards.