Best fit
- このスキルを使用して、パフォーマンスベースラインを測定し、PR前後の回帰を検出し、スタック代替案を比較します。
affaan-m/ECC
benchmark
このスキルを使用して、パフォーマンスベースラインを測定し、PR前後の回帰を検出し、スタック代替案を比較します。
66Collecting
See how to use itView GitHub source
npx skills add https://github.com/affaan-m/ECC --skill "docs/ja-JP/skills/benchmark"Automated source guide
Source checked Jul 28, 2026·Refresh due Oct 26, 2026
Reorganized from the pinned upstream SKILL.md
Turn benchmark's source instructions into a guide you can follow
According to the pinned SKILL.md from affaan-m/ECC: このスキルを使用して、パフォーマンスベースラインを測定し、PR前後の回帰を検出し、スタック代替案を比較します。
npx skills add https://github.com/affaan-m/ECC --skill "docs/ja-JP/skills/benchmark"Bring this context
- A concrete task that matches the documented purpose of benchmark.
- The files, examples, or context the task depends on.
- Your constraints, target environment, and definition of done.
Expected outputs
- A result that follows the pinned benchmark instructions.
- A concise record of assumptions, inputs used, and unresolved questions.
- A final check against the source workflow and relevant permission signals.
Key source sections
Read benchmark through these 5 source sections
Sections are extracted automatically from the pinned SKILL.md and link back to the source.
使用時期
PR前後にパフォーマンスへの影響を測定
PR前後にパフォーマンスへの影響を測定プロジェクトのパフォーマンスベースラインを設定ユーザーが「遅く感じる」と報告したとき
動作方法
ブラウザMCPを介してリアルブラウザメトリクスを測定：
ブラウザMCPを介してリアルブラウザメトリクスを測定：/benchmark baseline 現在のメトリクスを保存
モード1：ページパフォーマンス
ブラウザMCPを介してリアルブラウザメトリクスを測定：
ブラウザMCPを介してリアルブラウザメトリクスを測定：
モード2：APIパフォーマンス
Review the “モード2：APIパフォーマンス” section in the pinned source before continuing.
Review and apply the “モード2：APIパフォーマンス” source section.
モード3：ビルドパフォーマンス
Review the “モード3：ビルドパフォーマンス” section in the pinned source before continuing.
Review and apply the “モード3：ビルドパフォーマンス” source section.
SkillSignal prompt templates
Provide the task, context, and acceptance criteria
These prompts were written by SkillSignal from the source structure; they are not upstream text.
Task-start prompt
Confirm source fit, inputs, and outputs before acting.
Use benchmark to help me with: [specific task]. Context: [files, data, or background]. Constraints: [environment, scope, and prohibited actions]. Before acting, check the pinned SKILL.md and explain which sections apply, what inputs are still missing, and what you will deliver.
Source-guided execution
Make the Agent explicitly follow the key extracted sections.
Apply the pinned benchmark source to [task]. Pay particular attention to these source sections: “使用時期”, “動作方法”, “モード1：ページパフォーマンス”, “モード2：APIパフォーマンス”, “モード3：ビルドパフォーマンス”. Preserve the important decision at each step. Mark facts not covered by the source as “needs confirmation” instead of inventing them. Then verify the result against my acceptance criteria: [criteria].
Result-review prompt
Check omissions, permissions, and source drift before delivery.
Review the current benchmark result: (1) does it satisfy the original task; (2) were any applicable steps or limits in the pinned SKILL.md missed; (3) did it perform any unauthorized file, command, network, or data action; and (4) which conclusions remain unverified? List issues first, then fix only what the source or user authorization supports.
Output checklist
Verify each item before delivery
The task matches the purpose documented in the SKILL.md.
The source section “使用時期” has been checked.
The source section “動作方法” has been checked.
The source section “モード1：ページパフォーマンス” has been checked.
The source section “モード2：APIパフォーマンス” has been checked.
Inputs, constraints, and acceptance criteria are explicit.
Unverified facts, compatibility, and outcome claims are clearly marked.
Any file, command, network, or data action has been reviewed.
Choose a different workflow
When another Skill is the better fit
benchmark
Use this skill to measure performance baselines, detect regressions before/after PRs, and compare stack alternatives.
A separate implementation from affaan-m/ECC; compare its source, maintenance signals, and permission requirements.
Open source detailbenchmark
使用此技能测量性能基线，检测PR前后的回归，并比较堆栈替代方案。
A separate implementation from affaan-m/ECC; compare its source, maintenance signals, and permission requirements.
Open source detailab-testing
When the user wants to plan, design, or implement an A/B test or experiment, or build a growth experimentation program. Also use when the user mentions "A/B test," "split test," "experiment," "test this change," "variant copy," "multivariate test," "hypothesis," "should I test this," "which version is better," "test two versions," "statistical significance," "how long should I run this test," "growth experiments," "experiment velocity," "experiment backlog," "ICE score," "experimentation program
A separate implementation from coreyhaines31/marketingskills; compare its source, maintenance signals, and permission requirements.
Open source detailFAQ
What does benchmark do?
このスキルを使用して、パフォーマンスベースラインを測定し、PR前後の回帰を検出し、スタック代替案を比較します。
How do I start using benchmark?
The catalog detected this source-specific install command: npx skills add https://github.com/affaan-m/ECC --skill "docs/ja-JP/skills/benchmark". Inspect the command and pinned source before running it.
Which Agent platforms does it declare?
No dedicated Agent platform is declared in the pinned source record.
Repository stars
234,327
Repository forks
35,711
Quality
66/100
Source repository last pushed
Quality breakdown
Based on traceable docs and repository signals; stars are not treated as quality.
Documentation20/30
Specificity14/25
Maintenance20/20
Trust signals12/25
Compare before choosing
Related Agent Skills and source variants
These links are selected from shared tasks, functions, stacks, platforms, and same-name variants. Compare the source owner, documentation, permissions, and maintenance signals.
benchmark by affaan-m
Use this skill to measure performance baselines, detect regressions before/after PRs, and compare stack alternatives.
benchmark by affaan-m
使用此技能测量性能基线，检测PR前后的回归，并比较堆栈替代方案。
ab-testing by coreyhaines31
When the user wants to plan, design, or implement an A/B test or experiment, or build a growth experimentation program. Also use when the user mentions "A/B test," "split test," "experiment," "test this change," "variant copy," "multivariate test," "hypothesis," "should I test this," "which version is better," "test two versions," "statistical significance," "how long should I run this test," "growth experiments," "experiment velocity," "experiment backlog," "ICE score," "experimentation program
design-intelligence by event4u-app
Grounded design brief from the adopted corpus — style, WCAG-checked color tokens, typography, layout pattern, anti-patterns. Use on ui-design-brief or any which-style/palette/font/chart decision.
existing-ui-audit by event4u-app
Use BEFORE writing or editing any non-trivial UI — inventories components, design tokens, shadcn primitives, and reusable patterns into state.ui_audit. Hard gate for the ui directive set.
View original Skill.mdThis page is parsed directly from the repository SKILL.md without editorial rewriting. Collected: Jul 28, 2026 · about 1 min
ベンチマーク — パフォーマンスベースラインと回帰検出
使用時期
- PR前後にパフォーマンスへの影響を測定
- プロジェクトのパフォーマンスベースラインを設定
- ユーザーが「遅く感じる」と報告したとき
- ローンチ前 — パフォーマンスターゲットを満たしていることを確認
- スタックを代替案と比較
動作方法
モード1：ページパフォーマンス
ブラウザMCPを介してリアルブラウザメトリクスを測定：
1. 各ターゲットURLに移動
2. Core Web Vitalsを測定：
- LCP (Largest Contentful Paint) — ターゲット < 2.5s
- CLS (Cumulative Layout Shift) — ターゲット < 0.1
- INP (Interaction to Next Paint) — ターゲット < 200ms
- FCP (First Contentful Paint) — ターゲット < 1.8s
- TTFB (Time to First Byte) — ターゲット < 800ms
3. リソースサイズを測定：
- 合計ページウェイト（ターゲット < 1MB）
- JSバンドルサイズ（ターゲット < 200KBgzipped）
- CSSサイズ
- 画像ウェイト
- サードパーティスクリプトウェイト
4. ネットワークリクエストをカウント
5. レンダリングブロッキングリソースをチェック
モード2：APIパフォーマンス
APIエンドポイントをベンチマーク：
1. 各エンドポイントに100回ヒット
2. 測定：p50、p95、p99レイテンシ
3. トラック：レスポンスサイズ、ステータスコード
4. ロード下でテスト：10個の同時リクエスト
5. SLAターゲットと比較
モード3：ビルドパフォーマンス
開発フィードバックループを測定：
1. コールドビルド時間
2. ホットリロード時間（HMR）
3. テストスイート期間
4. TypeScriptチェック時間
5. Lint時間
6. Dockerビルド時間
モード4：前後の比較
変更前後に実行して影響を測定：
/benchmark baseline # 現在のメトリクスを保存
# ... 変更を加える ...
/benchmark compare # ベースラインと比較
出力：
| Metric | Before | After | Delta | Verdict |
|--------|--------|-------|-------|---------|
| LCP | 1.2s | 1.4s | +200ms | WARNING: WARN |
| Bundle | 180KB | 175KB | -5KB | ✓ BETTER |
| Build | 12s | 14s | +2s | WARNING: WARN |
出力
.ecc/benchmarks/にJSONとしてベースラインを保存。Gitで追跡されるため、チームはベースラインを共有します。
統合
- CI：すべてのPRで
/benchmark compareを実行 /canary-watchとペアリングしてデプロイ後の監視/browser-qaとペアリングして完全な出荷前チェックリスト
- Source repo
- affaan-m/ECC
- Skill path
- docs/ja-JP/skills/benchmark/SKILL.md
- Commit SHA
- 4e973d3eaf92
- Repository license
- MIT
- Data collected