정보
이 Claude Skill은 GH CLI를 사용하여 GitHub 풀 리퀘스트를 자동으로 종합 검토합니다. 변경 사항과 커밋 기록을 분석하고 CI/CD 체크를 검증한 후, '차단' 또는 '제안'과 같은 심각도 수준을 포함한 구조화된 피드백을 제출합니다. PR이 할당되었을 때 사용하여, 인간 리뷰어에게 요청하거나 병합된 코드를 감사하기 전에 철저한 검토를 보장할 수 있습니다.
빠른 설치
Claude Code
추천npx skills add pjt222/agent-almanac -a claude-code/plugin add https://github.com/pjt222/agent-almanacgit clone https://github.com/pjt222/agent-almanac.git ~/.claude/skills/review-pull-requestClaude Code에서 이 명령을 복사하여 붙여넣어 스킬을 설치하세요
문서
Review Pull Request
Review GH PR end-to-end — understand change → submit structured feedback. Uses gh CLI for all GH interactions + produces severity-leveled review comments.
Use When
- PR ready for review + assigned to you
- Second review after author addresses feedback
- Self-review before req others
- Audit merged PR for post-merge quality
- Want structured review process not ad-hoc scanning
In
- Required: PR id (number, URL,
owner/repo#number) - Optional: Review focus (security, perf, correctness, style)
- Optional: Codebase familiarity (familiar, somewhat, unfamiliar)
- Optional: Time budget (quick scan, std, thorough)
Do
Step 1: Understand Ctx
Read PR description + understand what change accomplishes.
- Fetch PR metadata:
gh pr view <number> --json title,body,author,baseRefName,headRefName,labels,additions,deletions,changedFiles,reviewDecision - Read title + description:
- What problem does PR solve?
- What approach did author take?
- Specific areas author wants reviewed?
- Check PR size + assess time req:
PR Size Guide:
+--------+-----------+---------+-------------------------------------+
| Size | Files | Lines | Review Approach |
+--------+-----------+---------+-------------------------------------+
| Small | 1-5 | <100 | Read every line, quick review |
| Medium | 5-15 | 100-500 | Focus on logic changes, skim config |
| Large | 15-30 | 500- | Review by commit, focus on critical |
| | | 1000 | files, flag if should be split |
| XL | 30+ | 1000+ | Flag for splitting. Review only the |
| | | | most critical files. |
+--------+-----------+---------+-------------------------------------+
- Review commit history:
gh pr view <number> --json commits --jq '.commits[].messageHeadline'- Commits logical + well-structured?
- History tells story (each commit coherent step)?
- Check CI/CD status:
gh pr checks <number>- All checks passing?
- If failing, note which → affects review
→ Clear understanding of what PR does, why exists, how big, CI green. Ctx shapes review approach.
If err: PR description empty/unclear → note as first feedback. PR w/o ctx = review antipattern. gh cmds fail → verify auth (gh auth status) + repo access.
Step 2: Analyze Diff
Read actual code changes systematically.
- Fetch full diff:
gh pr diff <number> - Small/medium PRs: read entire diff sequential
- Large PRs: review by commit:
gh pr diff <number> --patch # full patch format - Each changed file eval:
- Correctness: Code does what PR says?
- Edge cases: Boundary conditions handled?
- Error handling: Caught + handled appropriately?
- Security: Injection, auth, data exposure risks?
- Perf: Obvious O(n^2), missing indexes, mem issues?
- Naming: New vars/fns/classes named clearly?
- Tests: New behaviors covered by tests?
- Take notes as read, classifying each by severity
→ Set of obs covering correctness, security, perf, quality for every meaningful change. Each obs has severity.
If err: diff too large to review effectively → flag: "This PR changes {N} files and {M} lines. I recommend splitting it into smaller PRs for more effective review." Still review highest-risk files.
Step 3: Classify Feedback
Organize obs into severity levels.
- Classify each obs:
Feedback Severity Levels:
+-----------+------+----------------------------------------------------+
| Level | Icon | Description |
+-----------+------+----------------------------------------------------+
| Blocking | [B] | Must fix before merge. Bugs, security issues, |
| | | data loss risks, broken functionality. |
| Suggest | [S] | Should fix, but won't block merge. Better |
| | | approaches, missing edge cases, style issues that |
| | | affect maintainability. |
| Nit | [N] | Optional improvement. Style preferences, minor |
| | | naming suggestions, formatting. |
| Praise | [P] | Good work worth calling out. Clever solutions, |
| | | thorough testing, clean abstractions. |
+-----------+------+----------------------------------------------------+
- Each Blocking explain:
- What's wrong (specific issue)
- Why matters (impact)
- How to fix (concrete suggestion)
- Each Suggest explain alternative + why better
- Keep Nits brief — one sentence enough
- Include ≥1 Praise if anything positive stands out
→ Sorted feedback list w/ clear severity. Blocking has fix suggestions. Ratio: few Blocking, some Suggest, minimal Nit, ≥1 Praise.
If err: everything seems blocking → PR may need rework not patch. Consider req changes at PR level vs line-by-line. Nothing wrong → say so — "LGTM" valid when code good.
Step 4: Write Comments
Compose review w/ structured actionable feedback.
- Write review summary (top-level):
- One sentence: what PR does (confirm understanding)
- Overall: approve, req changes, comment
- Key items: list Blocking (if any) + top Suggest
- Praise: call out good work
- Write inline comments for specific code locations:
# Post inline comments via gh API gh api repos/{owner}/{repo}/pulls/{number}/comments \ -f body="[B] This SQL query is vulnerable to injection. Use parameterized queries instead.\n\n\`\`\`suggestion\ndb.query('SELECT * FROM users WHERE id = $1', [userId])\n\`\`\`" \ -f commit_id="<sha>" \ -f path="src/users.js" \ -F line=42 \ -f side="RIGHT" - Format feedback consistent:
- Start each comment w/ severity tag:
[B],[S],[N],[P] - Use GH suggestion blocks for concrete fixes
- Link to docs for style/pattern suggestions
- Start each comment w/ severity tag:
- Submit review:
# Approve gh pr review <number> --approve --body "Review summary here" # Request changes (when blocking issues exist) gh pr review <number> --request-changes --body "Review summary here" # Comment only (when unsure or providing FYI feedback) gh pr review <number> --comment --body "Review summary here"
→ Submitted review w/ clear actionable feedback. Author knows exactly what to fix (Blocking), consider (Suggest), what went well (Praise).
If err: gh pr review fails → check perms. Need write access or be requested reviewer. Inline comments fail → fall back to all feedback in review body w/ file:line refs.
Step 5: Follow Up
Track resolution.
- After author responds or pushes updates:
gh pr view <number> --json reviewDecision,reviews - Re-review only changes addressing feedback:
gh pr diff <number> # check new commits - Verify Blocking resolved before approving
- Resolve comment threads as issues addressed
- Approve when all Blocking fixed:
gh pr review <number> --approve --body "All blocking issues resolved. LGTM."
→ Blocking verified fixed. Conversation resolved. PR approved or further changes req'd w/ specific remaining items.
If err: author disagrees → discuss in PR thread. Focus on impact (why matters) not authority. Disagreement persists on non-blocking → yield gracefully. Author owns code.
Check
- PR ctx understood (purpose, size, CI status)
- All changed files reviewed (or highest-risk for XL PRs)
- Feedback classified by severity (Blocking/Suggest/Nit/Praise)
- Blocking has specific fix suggestions
- ≥1 Praise for positive aspects
- Review decision matches feedback (approve only if no Blocking)
- Inline comments ref specific lines w/ severity tags
- CI/CD checks verified (green before approval)
- Follow-up done after author revisions
Traps
- Rubber-stamping: Approving w/o reading diff. Every approval = assertion of quality.
- Nit avalanche: Drowning author in style prefs. Save nits for mentoring; skip in time-sensitive reviews.
- Miss forest: Reviewing line-by-line w/o understanding overall design. Read description + commit history first.
- Block on style: Formatting + naming almost never blocking. Reserve Blocking for bugs, security, data integrity.
- No praise: Only pointing problems = demoralizing. Good code deserves recognition.
- Scope creep: Commenting on code not changed in PR. Pre-existing issues → file separate issue.
→
review-software-architecture— system-level architecture review (complementary)security-audit-codebase— deep security analysis for security-sensitive PRscreate-pull-request— other side: creating PRs easy to reviewcommit-changes— clean commit history makes PR review easier
GitHub 저장소
Frequently asked questions
What is the review-pull-request skill?
review-pull-request is a Claude Skill by pjt222. Skills package instructions and resources that Claude loads on demand, so Claude can perform review-pull-request-related tasks without extra prompting.
How do I install review-pull-request?
Use the install commands on this page: add review-pull-request to Claude Code as a plugin, or clone its repository into your skills directory, then restart Claude so it picks up the skill.
What category does review-pull-request belong to?
review-pull-request is in the Other category, tagged ai.
Is review-pull-request free to use?
Yes. review-pull-request is listed on AIMCP and free to install. It runs inside Claude, so no separate service account is required to use the skill itself.
연관 스킬
LlamaGuard는 폭력 및 혐오 발언 등 6가지 안전 범주에서 LLM 입력과 출력을 조정하기 위한 Meta의 70-80억 파라미터 모델입니다. 94-95% 정확도를 제공하며 vLLM, Hugging Face 또는 Amazon SageMaker를 사용해 배포할 수 있습니다. 이 기술을 사용하여 AI 애플리케이션에 콘텐츠 필터링 및 안전 가드레일을 손쉽게 통합하세요.
이 Claude Skill은 리소스 적정화, 태깅 전략, 지출 분석을 통해 개발자들이 클라우드 비용을 최적화할 수 있도록 지원합니다. AWS, Azure, GCP에서 클라우드 비용을 절감하고 비용 거버넌스를 구현하기 위한 프레임워크를 제공합니다. 인프라 비용을 분석하거나, 리소스를 적정화하거나, 예산 제약을 충족해야 할 때 사용하세요.
이 Claude Skill은 스프레드, 오버/언더, 프로프 베트를 포함한 스포츠 베팅 시장을 분석합니다. 역사적 추이와 상황별 통계를 검토하여 가치 베트를 발견하고, 교육적 목적으로 실행 가능한 권장 사항이 담긴 구조화된 마크다운 결과를 제공합니다. 개발자는 이 기능을 스포츠 베팅 분석 도구에 활용할 수 있으며, 단순히 엔터테인먼트/교육 목적으로만 설계되었음을 유의해야 합니다.
이 스킬은 bitsandbytes를 사용하여 LLM을 8비트 또는 4비트 정밀도로 양자화하며, 최소한의 정확도 손실로 50-75%의 메모리 감소를 달성합니다. 제한된 GPU 메모리에서 더 큰 모델을 실행하거나 추론을 가속화하는 데 이상적이며, INT8, NF4, FP4와 같은 형식을 지원합니다. 이 스킬은 HuggingFace Transformers와 통합되어 QLoRA 학습 및 8비트 옵티마이저를 가능하게 합니다.
