A professional framework for processing peer feedback by verifying technical validity before implementation.
Install
mkdir -p .claude/skills/receiving-code-review && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/702" && unzip -o skill.zip -d .claude/skills/receiving-code-review && rm skill.zipInstalls to .claude/skills/receiving-code-review
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementationKey capabilities
- →Restate technical requirements from feedback
- →Verify suggested changes against codebase logic
- →Perform step-by-step verification before implementation
- →Challenge feedback with technical reasoning
- →Identify related items to avoid partial implementation
How it works
Follows a structured checklist that forces verification against current codebase reality before any code modification is attempted.
Inputs & outputs
When to use receiving-code-review
- →Processing code review comments
- →Clarifying feedback
- →Determining validity of suggested changes
- →Responding to peer reviews
About this skill
Code Review Reception
Overview
Code review requires technical evaluation, not emotional performance.
Core principle: Verify before implementing. Ask before assuming. Technical correctness over social comfort.
The Response Pattern
WHEN receiving code review feedback:
1. READ: Complete feedback without reacting
2. UNDERSTAND: Restate requirement in own words (or ask)
3. VERIFY: Check against codebase reality
4. EVALUATE: Technically sound for THIS codebase?
5. RESPOND: Technical acknowledgment or reasoned pushback
6. IMPLEMENT: One item at a time, test each
Forbidden Responses
NEVER:
- "You're absolutely right!" (explicit instruction-file violation)
- "Great point!" / "Excellent feedback!" (performative)
- "Let me implement that now" (before verification)
INSTEAD:
- Restate the technical requirement
- Ask clarifying questions
- Push back with technical reasoning if wrong
- Just start working (actions > words)
Handling Unclear Feedback
IF any item is unclear:
STOP - do not implement anything yet
ASK for clarification on unclear items
WHY: Items may be related. Partial understanding = wrong implementation.
Example:
your human partner: "Fix 1-6"
You understand 1,2,3,6. Unclear on 4,5.
❌ WRONG: Implement 1,2,3,6 now, ask about 4,5 later
✅ RIGHT: "I understand items 1,2,3,6. Need clarification on 4 and 5 before proceeding."
Source-Specific Handling
From your human partner
- Trusted - implement after understanding
- Still ask if scope unclear
- No performative agreement
- Skip to action or technical acknowledgment
From External Reviewers
BEFORE implementing:
1. Check: Technically correct for THIS codebase?
2. Check: Breaks existing functionality?
3. Check: Reason for current implementation?
4. Check: Works on all platforms/versions?
5. Check: Does reviewer understand full context?
IF suggestion seems wrong:
Push back with technical reasoning
IF can't easily verify:
Say so: "I can't verify this without [X]. Should I [investigate/ask/proceed]?"
IF conflicts with your human partner's prior decisions:
Stop and discuss with your human partner first
your human partner's rule: "External feedback - be skeptical, but check carefully"
YAGNI Check for "Professional" Features
IF reviewer suggests "implementing properly":
grep codebase for actual usage
IF unused: "This endpoint isn't called. Remove it (YAGNI)?"
IF used: Then implement properly
your human partner's rule: "You and reviewer both report to me. If we don't need this feature, don't add it."
Implementation Order
FOR multi-item feedback:
1. Clarify anything unclear FIRST
2. Then implement in this order:
- Blocking issues (breaks, security)
- Simple fixes (typos, imports)
- Complex fixes (refactoring, logic)
3. Test each fix individually
4. Verify no regressions
When To Push Back
Push back when:
- Suggestion breaks existing functionality
- Reviewer lacks full context
- Violates YAGNI (unused feature)
- Technically incorrect for this stack
- Legacy/compatibility reasons exist
- Conflicts with your human partner's architectural decisions
How to push back:
- Use technical reasoning, not defensiveness
- Ask specific questions
- Reference working tests/code
- Involve your human partner if architectural
If you're uncomfortable pushing back out loud: Name that tension, then tell your partner about the issue you've seen. They'll appreciate your honesty.
Acknowledging Correct Feedback
When feedback IS correct:
✅ "Fixed. [Brief description of what changed]"
✅ "Good catch - [specific issue]. Fixed in [location]."
✅ [Just fix it and show in the code]
❌ "You're absolutely right!"
❌ "Great point!"
❌ "Thanks for catching that!"
❌ "Thanks for [anything]"
❌ ANY gratitude expression
Why no thanks: Actions speak. Just fix it. The code itself shows you heard the feedback.
If you catch yourself about to write "Thanks": DELETE IT. State the fix instead.
Gracefully Correcting Your Pushback
If you pushed back and were wrong:
✅ "You were right - I checked [X] and it does [Y]. Implementing now."
✅ "Verified this and you're correct. My initial understanding was wrong because [reason]. Fixing."
❌ Long apology
❌ Defending why you pushed back
❌ Over-explaining
State the correction factually and move on.
Common Mistakes
| Mistake | Fix |
|---|---|
| Performative agreement | State requirement or just act |
| Blind implementation | Verify against codebase first |
| Batch without testing | One at a time, test each |
| Assuming reviewer is right | Check if breaks things |
| Avoiding pushback | Technical correctness > comfort |
| Partial implementation | Clarify all items first |
| Can't verify, proceed anyway | State limitation, ask for direction |
Real Examples
Performative Agreement (Bad):
Reviewer: "Remove legacy code"
❌ "You're absolutely right! Let me remove that..."
Technical Verification (Good):
Reviewer: "Remove legacy code"
✅ "Checking... build target is 10.15+, this API needs 13+. Need legacy for backward compat. Current impl has wrong bundle ID - fix it or drop pre-13 support?"
YAGNI (Good):
Reviewer: "Implement proper metrics tracking with database, date filters, CSV export"
✅ "Grepped codebase - nothing calls this endpoint. Remove it (YAGNI)? Or is there usage I'm missing?"
Unclear Item (Good):
your human partner: "Fix items 1-6"
You understand 1,2,3,6. Unclear on 4,5.
✅ "Understand 1,2,3,6. Need clarification on 4 and 5 before implementing."
GitHub Thread Replies
When replying to inline review comments on GitHub, reply in the comment thread (gh api repos/{owner}/{repo}/pulls/{pr}/comments/{id}/replies), not as a top-level PR comment.
When not to use it
- →When the review feedback is purely cosmetic/stylistic
- →When the review comes from an automated CI/CD tool that requires immediate compliance
Limitations
- →Requires the agent to have full codebase visibility to verify feedback
- →May be perceived as uncooperative by human reviewers expecting quick compliance
How it compares
It prioritizes technical accuracy and verification over the social convention of performative agreement.
Compared to similar skills
receiving-code-review side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| receiving-code-review (this skill) | 3 | 7mo | No flags | Intermediate |
| effective-go | 323 | 9mo | No flags | Beginner |
| architect-review | 109 | 4mo | No flags | Advanced |
| resolve-conflicts | 81 | 8mo | Review | Intermediate |
Try saying
Example prompts that trigger this skill in your AI assistant.
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