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receiving-code-review

Guides verification and implementation of code review feedback with technical rigor.

Updated Dec 20, 2025
Search Tags:#code review#pull request#github#verification#yagni#pushback#feedback handling
One-click install
npx skills add https://github.com/cristoslc/LLM-personal-agent-patterns --skill receiving-code-review-cristoslc
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: receiving-code-review
Source: https://github.com/cristoslc/LLM-personal-agent-patterns/tree/main/L3-agents-core/.agents/skills/receiving-code-review
Command: npx skills add https://github.com/cristoslc/LLM-personal-agent-patterns --skill receiving-code-review-cristoslc

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? AI agents often respond to code review feedback with performative agreement or blind implementation, leading to wrong changes, broken functionality, and unverified assumptions. This Skill enforces a verify-before-implement discipline when handling review comments. ## Core Features & Use Cases - Structured Response Pattern: Read, understand, verify against the codebase, evaluate, respond, then implement one item at a time with testing. - Source-Specific Handling: Different rules for trusted human partner feedback versus external reviewer suggestions, including pushback criteria and YAGNI checks. - Use Case: A reviewer suggests removing legacy code or adding a metrics endpoint. Instead of agreeing immediately, the agent greps the codebase, finds the endpoint is unused or the legacy code is required for backward compatibility, and responds with technical reasoning. ## Quick Start Apply the receiving-code-review skill to evaluate and respond to the review comments on my current pull request.

Frequently Asked Questions about receiving-code-review

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

FAQPage Schema
How should an AI agent respond to code review feedback?▼

The agent should read all feedback, restate the requirement, verify it against the actual codebase, then implement one item at a time with testing. It must avoid performative phrases like "You're absolutely right" and instead state the fix or ask clarifying questions.

How to handle unclear code review comments before implementing?▼

Stop and ask for clarification on any unclear items before implementing anything. Partial understanding leads to wrong implementations because feedback items are often related, so clarify all items first rather than implementing only the understood ones.

When should you push back on a code review suggestion?▼

Push back when a suggestion breaks existing functionality, violates YAGNI for unused features, is technically incorrect for the stack, or conflicts with prior architectural decisions. Use technical reasoning and reference working code or tests rather than being defensive.

Should external reviewer feedback be implemented directly?▼

No, external feedback should be treated as suggestions to evaluate, not orders. Verify technical correctness for the specific codebase, check for regressions and platform compatibility, and confirm the reviewer understands the full context before implementing.

How do I reply to inline GitHub review comments?▼

Reply within the comment thread using the GitHub API endpoint for pull request comment replies, not as a top-level PR comment. This keeps the discussion attached to the specific line of code being reviewed.

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