本文へ移動
cccskills
無料GitHub で公開

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

インストール方法を見る

含まれるファイル(1)

  • SKILL.md6.2 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

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 CLAUDE.md 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

Signal if uncomfortable pushing back out loud: "Strange things are afoot at the Circle K"

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

MistakeFix
Performative agreementState requirement or just act
Blind implementationVerify against codebase first
Batch without testingOne at a time, test each
Assuming reviewer is rightCheck if breaks things
Avoiding pushbackTechnical correctness > comfort
Partial implementationClarify all items first
Can't verify, proceed anywayState 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.

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

Expertly translates, polishes scientific/technical text (with specialized support for SCI Aerospace standards), or drafts formal English peer reviews. Ensures accuracy, clarity, and adherence to high academic standards.

日本語の概要は準備中です。原文の説明を表示しています。

ECNU-ICALK/AutoSkill5972026年5月10日 更新

将中文学术文本翻译为符合国际期刊标准的高级英语,并提供多个润色版本以供选择。确保术语准确、逻辑严谨、句式复杂,彻底消除中式英语。

日本語の概要は準備中です。原文の説明を表示しています。

ECNU-ICALK/AutoSkill5972026年5月10日 更新

Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction.

日本語の概要は準備中です。原文の説明を表示しています。

ECNU-ICALK/AutoSkill5972026年5月10日 更新

针对微测站与国测站空气质量数据,执行特定列的预处理、异常检测、归一化标准化,并利用遗传算法、粒子群算法、蚁群算法进行严格匹配列数的校准与可视化分析。

日本語の概要は準備中です。原文の説明を表示しています。

ECNU-ICALK/AutoSkill5972026年5月10日 更新

扮演人工智能辅助医生,结合最新AI工具(如医学成像、机器学习)和传统方法(如体检、实验室测试)来诊断病人症状的最可能原因。

日本語の概要は準備中です。原文の説明を表示しています。

ECNU-ICALK/AutoSkill5972026年5月10日 更新

Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.

日本語の概要は準備中です。原文の説明を表示しています。

ECNU-ICALK/AutoSkill5972026年5月10日 更新

ECNU-ICALK のスキルをすべて見る

このスキルの問題を報告する