AgentSkillsCN

team-review

借助 Agent Teams 开展并行代码审查。为不同视角的实施成果分别配备专业评审人员(如安全专家、质量专家、测试覆盖率专家),同时从多角度审视代码实现。实施完成后即可展开代码审查。

SKILL.md
--- frontmatter
name: team-review
description: |
  Parallel code review using Agent Teams. Spawns specialized reviewers
  (security, quality, test coverage) to review implementation from
  different perspectives simultaneously. Run after implementation.
metadata:
  short-description: Parallel review with Agent Teams

Team Review

Agent Teams による並列レビュー。実装完了後に複数の視点から同時にレビューする。

Prerequisites

  • 実装が完了していること(/team-implement 後、または手動実装後)
  • 全テストが通過していること

Workflow

code
Step 1: Gather Diff
  実装範囲の変更差分を収集
    ↓
Step 2: Spawn Review Team
  専門レビュアーを並列起動
    ↓
Step 3: Synthesize Findings
  レビュー結果を統合、優先度付け
    ↓
Step 4: Report to User
  発見事項と推奨アクションを提示

Step 1: Gather Diff

レビュー対象の変更範囲を特定する。

bash
# All changes from main branch
git diff main...HEAD

# Changed files list
git diff main...HEAD --name-only

# Commit history
git log main..HEAD --oneline

Step 2: Spawn Review Team

専門的な視点を持つレビュアーを並列起動する。

code
Create an agent team to review implementation of: {feature}

The following files were changed:
{changed files list}

Spawn reviewers:

1. **Security Reviewer**
   Prompt: "You are a Security Reviewer for: {feature}.

   Review all changed files for security vulnerabilities:
   - Hardcoded secrets or credentials
   - SQL injection, XSS, command injection
   - Input validation gaps
   - Authentication/authorization issues
   - Sensitive data exposure in logs/errors
   - Dependency vulnerabilities

   Changed files: {list}

   Reference: .claude/rules/security.md

   For each finding:
   - Severity: Critical / High / Medium / Low
   - File and line number
   - Description of the issue
   - Recommended fix

   Save report to .claude/docs/research/review-security-{feature}.md"

2. **Quality Reviewer**
   Prompt: "You are a Quality Reviewer for: {feature}.

   Review all changed files for code quality:
   - Adherence to coding principles (.claude/rules/coding-principles.md)
   - Single responsibility violations
   - Deep nesting (should use early return)
   - Missing type hints
   - Magic numbers
   - Naming clarity
   - Function length (target < 20 lines)
   - Library constraint violations (.claude/docs/libraries/)

   Use Codex CLI for deep analysis of complex logic:
   codex exec --model gpt-5.3-codex --sandbox read-only --full-auto "{question}" 2>/dev/null

   Changed files: {list}

   For each finding:
   - Severity: High / Medium / Low
   - File and line number
   - Current code
   - Suggested improvement

   Save report to .claude/docs/research/review-quality-{feature}.md"

3. **Test Reviewer**
   Prompt: "You are a Test Reviewer for: {feature}.

   Review test coverage and quality:
   - Run: uv run pytest --cov=src --cov-report=term-missing
   - Check: Are all happy paths tested?
   - Check: Are error cases covered?
   - Check: Are boundary values tested?
   - Check: Are edge cases handled?
   - Check: Are external deps properly mocked?
   - Check: Do tests follow AAA pattern?
   - Check: Are tests independent (no order dependency)?

   Reference: .claude/rules/testing.md

   For each gap:
   - File/function missing coverage
   - What test cases are needed
   - Priority: High / Medium / Low

   Save report to .claude/docs/research/review-tests-{feature}.md"

Wait for all reviewers to complete.

Optional: Competing Hypotheses (for debugging)

For bug investigation, add adversarial reviewers:

code
Spawn 3-5 teammates with different hypotheses about the bug.
Have them actively try to disprove each other's theories.

Step 3: Synthesize Findings

全レビュアーの結果を統合し、優先度付けする。

Read review reports:

  • .claude/docs/research/review-security-{feature}.md
  • .claude/docs/research/review-quality-{feature}.md
  • .claude/docs/research/review-tests-{feature}.md

Prioritization

PriorityCriteriaAction
CriticalSecurity vulnerabilities, data loss riskMust fix before merge
HighBugs, missing critical tests, type errorsShould fix before merge
MediumCode quality, naming, patternsFix if time allows
LowStyle, minor improvementsTrack for later

Step 4: Report to User

統合レビュー結果をユーザーに提示する(日本語)。

markdown
## レビュー結果: {feature}

### サマリー
- セキュリティ: {N}件 (Critical: {n}, High: {n}, Medium: {n})
- コード品質: {N}件 (High: {n}, Medium: {n}, Low: {n})
- テストカバレッジ: {N}% (目標80%に対して {above/below})

### Critical / High 発見事項

#### [{Severity}] {Issue Title}
- **ファイル**: `{file}:{line}`
- **問題**: {description}
- **修正案**: {recommended fix}

...

### 推奨アクション
1. {Action 1 — Critical fix}
2. {Action 2 — High priority fix}
3. {Action 3 — Test gap to fill}

### Medium / Low 発見事項
{Brief list — details in review reports}

---
修正を行いますか?

Cleanup

code
Clean up the team

Tips

  • レビュアーの専門分化: 各レビュアーが異なる視点に集中することで漏れを防ぐ
  • Codex 活用: Quality Reviewer が複雑なロジックを Codex に分析させる
  • レポート永続化: .claude/docs/research/ にレビュー結果を保存し、修正時の参照に
  • 競合仮説モード: バグ調査時は adversarial review パターンが有効
  • コスト注意: 3レビュアー = 3x トークン消費。小規模変更にはサブエージェント経由のレビューで十分