receiving-code-review

Evaluate code review feedback against the codebase before implementing changes.

69|19|Updated Jan 26, 2026
One-click install
npx skills add https://github.com/alffei/skill_share --skill receiving-code-review-alffei
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: receiving-code-review
Source: https://github.com/alffei/skill_share/tree/main/superpowers-antigravity/skills/receiving-code-review
Command: npx skills add https://github.com/alffei/skill_share --skill receiving-code-review-alffei

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill guides an AI agent to evaluate code review feedback with technical rigor before implementing any suggestions.

Core Features & Use Cases

  • Follow a six-step workflow (READ, UNDERSTAND, VERIFY, EVALUATE, RESPOND, IMPLEMENT) to handle feedback.
  • Handle unclear feedback with STOP and request clarification to avoid blind agreement.
  • Apply across code review interactions from human partners to external reviewers, ensuring verifiable changes.

Quick Start

Upon receiving code review feedback, read the message, restate requirements if unclear, verify against the codebase, evaluate technical correctness, respond with a reasoned pushback or acknowledgment, then implement changes one at a time and test.

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?

To evaluate code review feedback, follow a six-step workflow: READ, UNDERSTAND, VERIFY, EVALUATE, RESPOND, and IMPLEMENT. This ensures you verify suggestions against the codebase and test staged changes one at a time.

What is the best way to handle unclear code review comments?

The best way to handle unclear code review comments is to STOP and request clarification immediately. This prevents blind agreement and ensures you fully understand the technical requirements before modifying any code.

How does an AI agent workflow process code review interactions?

An AI agent workflow processes code review interactions by applying technical rigor across human and external feedback. It reads messages, verifies technical correctness against the codebase, and responds with reasoned pushback or acknowledgment before implementation.

Can I use a structured workflow to push back on incorrect code review suggestions?

Yes, you can use a structured workflow to push back on incorrect code review suggestions. During the EVALUATE and RESPOND stages, you assess technical correctness and provide a reasoned pushback or acknowledgment before implementing any verifiable changes.

Why does blindly implementing code review feedback cause issues?

Blindly implementing code review feedback causes issues because it skips verifying suggestions against the actual codebase. Applying technical rigor through a staged, testable workflow prevents integrating incorrect or unverified changes into your project.