スキル when-profiling-performance-use-performance-profiler
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when-profiling-performance-use-performance-profiler
安全 🌐
ネットワークアクセス⚡
スクリプトを含む⚙️
外部コマンド📁
ファイルシステムへのアクセス
Profile performance and find bottlenecks
Application performance issues are hard to identify without proper tooling. This skill measures CPU usage, memory allocation, I/O latency, and network requests to pinpoint bottlenecks and generate optimization recommendations.
対応: Claude Codex Code(CC)
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スキルZIPをダウンロード
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Claudeでアップロード
設定 → 機能 → スキル → スキルをアップロードへ移動
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オンにして利用開始
テストする
「when-profiling-performance-use-performance-profiler」を使用しています。 Profile my Node.js API with standard CPU and memory analysis
期待される結果:
- Baseline throughput: 1,247 requests/second
- Hot path: processData() uses 34% CPU (O(n²) algorithm)
- Memory leak: SessionManager grows 2.3 MB/hour
- Recommendation: Replace nested loops with hash map lookup
「when-profiling-performance-use-performance-profiler」を使用しています。 Analyze database performance and find optimization opportunities
期待される結果:
- Slow queries detected: 12 queries exceed 100ms
- Missing index on users.email column
- N+1 pattern in orders listing (45 extra queries)
- Add index: CREATE INDEX idx_users_email ON users(email)
セキュリティ監査
安全v5 • 1/17/2026
All 269 static findings are false positives. The scanner flagged documentation examples, YAML frontmatter, and GraphViz diagram syntax as security issues. No actual malicious code present. This is a legitimate performance profiling skill for Claude Code.
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スキャンされたファイル
4,060
解析された行数
4
検出結果
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総監査数
リスク要因
🌐 ネットワークアクセス (12)
mcp-performance-profiler.json:567 mcp-performance-profiler.json:568 PROCESS.md:317 PROCESS.md:318 PROCESS.md:364 skill-report.json:6 subagent-performance-profiler.md:495 subagent-performance-profiler.md:495 subagent-performance-profiler.md:496 subagent-performance-profiler.md:501 subagent-performance-profiler.md:504 subagent-performance-profiler.md:500
⚡ スクリプトを含む (2)
⚙️ 外部コマンド (173)
PROCESS.md:10-19 PROCESS.md:19-34 PROCESS.md:34-51 PROCESS.md:51-94 PROCESS.md:94-107 PROCESS.md:107-110 PROCESS.md:110-124 PROCESS.md:124-136 PROCESS.md:136-152 PROCESS.md:152-160 PROCESS.md:160-174 PROCESS.md:174-177 PROCESS.md:177-188 PROCESS.md:188-191 PROCESS.md:191-194 PROCESS.md:194-207 PROCESS.md:207-228 PROCESS.md:228-234 PROCESS.md:234-244 PROCESS.md:244-247 PROCESS.md:247-253 PROCESS.md:253-260 PROCESS.md:260-263 PROCESS.md:263-276 PROCESS.md:276-306 PROCESS.md:306-312 PROCESS.md:312-329 PROCESS.md:329-332 PROCESS.md:332-338 PROCESS.md:338-351 PROCESS.md:351-379 PROCESS.md:379-398 PROCESS.md:398-415 PROCESS.md:415-421 PROCESS.md:421-430 PROCESS.md:430-440 PROCESS.md:440-475 PROCESS.md:475-478 PROCESS.md:478-489 PROCESS.md:489-502 PROCESS.md:502-528 PROCESS.md:528-534 PROCESS.md:534-559 PROCESS.md:559-567 PROCESS.md:567-574 PROCESS.md:574-577 PROCESS.md:577-588 PROCESS.md:588-591 PROCESS.md:591-601 PROCESS.md:601-614 PROCESS.md:614-648 PROCESS.md:648-656 PROCESS.md:656-657 PROCESS.md:680-681 PROCESS.md:681-687 PROCESS.md:687-709 PROCESS.md:709-715 PROCESS.md:715-736 PROCESS.md:736-753 PROCESS.md:753-779 PROCESS.md:779-785 PROCESS.md:785-793 PROCESS.md:793-794 PROCESS.md:794-795 PROCESS.md:795-796 PROCESS.md:796-800 PROCESS.md:800-803 PROCESS.md:803-820 PROCESS.md:820-825 PROCESS.md:825-831 README.md:21-39 README.md:39-43 README.md:43-47 README.md:47-51 README.md:51-59 README.md:59-64 README.md:64-181 README.md:181-186 README.md:186-201 README.md:201-204 README.md:204-219 README.md:219-222 README.md:222-237 README.md:237-240 README.md:240-254 README.md:254-259 README.md:259-289 README.md:289-292 README.md:292-303 README.md:303-306 README.md:306-319 README.md:319-325 README.md:325-326 README.md:326-327 README.md:327-328 README.md:328-329 README.md:329-330 README.md:330-331 README.md:331-332 README.md:332-333 README.md:333-334 README.md:334-335 README.md:335-336 README.md:336-337 README.md:337-338 README.md:338-339 README.md:339-340 README.md:340-341 README.md:341-342 README.md:342-343 README.md:343-347 README.md:347-349 README.md:349-391 SKILL.md:75-77 SKILL.md:77-80 SKILL.md:80-82 SKILL.md:82-85 SKILL.md:85-92 SKILL.md:92-138 SKILL.md:138-170 SKILL.md:170-184 SKILL.md:184-186 SKILL.md:186-189 SKILL.md:189-191 SKILL.md:191-194 SKILL.md:194-196 SKILL.md:196-199 SKILL.md:199-201 SKILL.md:201-206 SKILL.md:206-222 SKILL.md:222-227 SKILL.md:227-254 slash-command-profile.sh:182 slash-command-profile.sh:193 slash-command-profile.sh:194 slash-command-profile.sh:205 slash-command-profile.sh:235-237 slash-command-profile.sh:238-240 slash-command-profile.sh:241-243 slash-command-profile.sh:244-246 slash-command-profile.sh:566 subagent-performance-profiler.md:27-36 subagent-performance-profiler.md:36-41 subagent-performance-profiler.md:41-70 subagent-performance-profiler.md:70-73 subagent-performance-profiler.md:73-161 subagent-performance-profiler.md:161-164 subagent-performance-profiler.md:164-266 subagent-performance-profiler.md:266-269 subagent-performance-profiler.md:269-407 subagent-performance-profiler.md:407-408 subagent-performance-profiler.md:408-417 subagent-performance-profiler.md:417-420 subagent-performance-profiler.md:420-467 subagent-performance-profiler.md:467-500 subagent-performance-profiler.md:500-527 subagent-performance-profiler.md:527-530 subagent-performance-profiler.md:530-555 subagent-performance-profiler.md:555-633 subagent-performance-profiler.md:633-636 subagent-performance-profiler.md:636-652 subagent-performance-profiler.md:652-666 subagent-performance-profiler.md:666-678 subagent-performance-profiler.md:678-699 subagent-performance-profiler.md:699-703 subagent-performance-profiler.md:703-724 subagent-performance-profiler.md:724-728 subagent-performance-profiler.md:728-731 subagent-performance-profiler.md:731-742 subagent-performance-profiler.md:742-746 subagent-performance-profiler.md:746-756 subagent-performance-profiler.md:756-762 subagent-performance-profiler.md:762-779
📁 ファイルシステムへのアクセス (14)
PROCESS.md:105 PROCESS.md:637 PROCESS.md:105 PROCESS.md:637 PROCESS.md:641 skill-report.json:6 slash-command-profile.sh:199 slash-command-profile.sh:206 slash-command-profile.sh:210 slash-command-profile.sh:560 slash-command-profile.sh:567 slash-command-profile.sh:571 subagent-performance-profiler.md:146 subagent-performance-profiler.md:594
監査者: claude 監査履歴を表示 →
品質スコア
38
アーキテクチャ
100
保守性
87
コンテンツ
19
コミュニティ
100
セキュリティ
83
仕様準拠
作れるもの
Debug slow applications
Identify which functions consume the most CPU time and memory so you know where to focus optimization efforts.
Pre-deployment checks
Establish performance baselines before deployments and detect regressions in CI/CD pipelines.
Database optimization
Find slow queries, missing indexes, and N+1 patterns that slow down application response times.
これらのプロンプトを試す
Quick scan
Run a quick 30-second CPU and memory profile on my application at ./src to identify the top bottlenecks.
Deep analysis
Run a deep 5-minute analysis targeting all performance dimensions. Generate flame graphs and find memory leaks.
Database focus
Profile the database queries in my application. Find slow queries, missing indexes, and N+1 patterns. Suggest fixes.
Compare builds
Profile my application in standard mode, save as baseline. Then profile after my changes and compare to show any regressions.
ベストプラクティス
- Profile under realistic production-like load for accurate results
- Use deep mode for complex applications with multiple bottlenecks
- Always benchmark before and after applying optimizations to verify improvement
回避
- Do not optimize based on guesses; always profile first to confirm bottlenecks
- Avoid profiling in production without proper sampling to minimize overhead
- Do not ignore p95/p99 latency metrics; averages can hide performance issues
よくある質問
What profiling modes are available?
Quick (30 seconds), Standard (5 minutes), Deep (30 minutes), and Continuous for long-running monitoring.
Does profiling slow down my application?
Sampling-based profiling adds minimal overhead. Deep instrumentation profiling has higher overhead but more accurate results.
What languages and frameworks are supported?
Node.js, Python, Java, Go, and Ruby. Supports Express, Django, Spring, and other major frameworks.
Can this skill fix performance issues automatically?
It generates optimization recommendations with code examples. You review and apply changes manually for safety.
How are memory leaks detected?
By taking multiple heap snapshots over time and comparing them to identify objects that grow and are not garbage collected.
What output formats are generated?
JSON reports, CPU flame graphs (SVG), heap snapshots, and optimization patch files that can be applied manually.