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obra/receiving-code-review

obra

receiving-code-review

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 implementation

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v1.1Saved Jun 28, 2026

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.

The Bottom Line

External feedback = suggestions to evaluate, not orders to follow.

Verify. Question. Then implement.

No performative agreement. Technical rigor always.

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Overall Score

88/100

Grade

A

Excellent

Safety

92

Quality

87

Clarity

89

Completeness

82

Summary

This skill teaches an AI agent how to receive and respond to code review feedback with technical rigor rather than performative agreement. It emphasizes verification before implementation, asking clarifying questions when unclear, and pushing back with technical reasoning when feedback is incorrect or incomplete. The skill is designed to prevent blind implementation, ensure architectural alignment with the human partner, and maintain technical correctness over social comfort.

Detected Capabilities

code analysiscodebase querying (grep)technical evaluationcommunication guidance

Trigger Keywords

Phrases that MCP clients use to match this skill to user intent.

code review feedbackrespond to review commentsimplement review suggestionsverify feedback correctnessreview pushbackclarify review items

Use Cases

  • Responding to code review comments with technical verification before implementation
  • Deciding whether to implement external reviewer suggestions based on codebase context
  • Clarifying unclear feedback items before proceeding with implementation
  • Evaluating whether suggested features are actually needed (YAGNI principle)
  • Pushing back on review feedback that conflicts with existing architecture or breaks functionality
  • Implementing multi-item feedback in priority order with individual testing

Quality Notes

  • Skill provides clear, actionable guidance with explicit forbidden patterns and recommended alternatives
  • Strong use of examples showing both incorrect and correct responses, making intent unambiguous
  • Structured decision trees (IF/THEN patterns) allow agents to handle ambiguous situations systematically
  • Emphasis on verification and pushback reduces risk of blind implementation that breaks functionality
  • Clear hierarchy of feedback sources (human partner vs external reviewers) with appropriate trust levels
  • Implementation order guidance prevents issues from partial, unsequenced fixes
  • Comprehensive common mistakes table with corrections provides edge case coverage
  • Real-world examples ground abstract principles in concrete scenarios
  • Absence of file operations or shell commands makes scope naturally limited and safe
Model: claude-haiku-4-5-20251001Analyzed: Jun 28, 2026

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Version History

  1. v1.1

    Content updated

    ✦ AIClarifies citation in forbidden responses from CLAUDE.md to instruction-file violation, and replaces cryptic pushback signal phrase with direct communication guidance.

    2026-06-28

    Latest
  2. v1.0

    2026-05-02

    Initial version

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