Benchmark

作者 affaan-mef648e01899ba3e8dc6371642deaaf64b4477775MIT275K 個星標收錄於 2026年10月9日更新於 2026年10月9日儲存庫4 天前更新

Measure performance baselines and detect regressions across browser Core Web Vitals (LCP, INP, CLS, page weight), API endpoint latency percentiles, and build/test feedback times, with before/after comparison stored in git-tracked .ecc/benchmarks JSON. Use when checking page speed, responding to 'it feels slow' reports, verifying launch performance targets, or comparing stack alternatives.

僅含說明Data & Analytics

AI 產生的概覽

量測網頁、API 與建置的效能基準，並透過前後比較偵測效能回歸。

功能: 此技能定義四種量測模式：瀏覽器 Core Web Vitals 與頁面大小、負載下 API 端點的延遲百分位數、建置與測試回饋時間，以及前後比較。它會把基準以 JSON 形式記錄在受 git 追蹤的 .ecc/benchmarks 目錄中，方便團隊共用。比較輸出為包含指標、之前、之後、差值與結論的表格。
適用情境: 適用於在拉取請求前後衡量效能影響、為專案建立效能基準、使用者反映「感覺很慢」、上線前確認是否達到效能目標，或比較不同技術棧的情況。
執行需求: 頁面量測需要瀏覽器 MCP，儲存基準需要 git 儲存庫。此技能不含指令碼，僅為說明文件。

Benchmark — Performance Baseline & Regression Detection

When to Use

Before and after a PR to measure performance impact
Setting up performance baselines for a project
When users report "it feels slow"
Before a launch — ensure you meet performance targets
Comparing your stack against alternatives

How It Works

Mode 1: Page Performance

Measures real browser metrics via browser MCP:

1. Navigate to each target URL2. Measure Core Web Vitals:   - LCP (Largest Contentful Paint) — target < 2.5s   - CLS (Cumulative Layout Shift) — target < 0.1   - INP (Interaction to Next Paint) — target < 200ms   - FCP (First Contentful Paint) — target < 1.8s   - TTFB (Time to First Byte) — target < 800ms3. Measure resource sizes:   - Total page weight (target < 1MB)   - JS bundle size (target < 200KB gzipped)   - CSS size   - Image weight   - Third-party script weight4. Count network requests5. Check for render-blocking resources

1. Navigate to each target URL2. Measure Core Web Vitals:   - LCP (Largest Contentful Paint) — target < 2.5s   - CLS (Cumulative Layout Shift) — target < 0.1   - INP (Interaction to Next Paint) — target < 200ms   - FCP (First Contentful Paint) — target < 1.8s   - TTFB (Time to First Byte) — target < 800ms3. Measure resource sizes:   - Total page weight (target < 1MB)   - JS bundle size (target < 200KB gzipped)   - CSS size   - Image weight   - Third-party script weight4. Count network requests5. Check for render-blocking resources

Mode 2: API Performance

Benchmarks API endpoints:

1. Hit each endpoint 100 times2. Measure: p50, p95, p99 latency3. Track: response size, status codes4. Test under load: 10 concurrent requests5. Compare against SLA targets

1. Hit each endpoint 100 times2. Measure: p50, p95, p99 latency3. Track: response size, status codes4. Test under load: 10 concurrent requests5. Compare against SLA targets

Mode 3: Build Performance

Measures development feedback loop:

1. Cold build time2. Hot reload time (HMR)3. Test suite duration4. TypeScript check time5. Lint time6. Docker build time

1. Cold build time2. Hot reload time (HMR)3. Test suite duration4. TypeScript check time5. Lint time6. Docker build time

Mode 4: Before/After Comparison

Run before and after a change to measure impact:

/benchmark baseline    # saves current metrics# ... make changes .../benchmark compare     # compares against baseline

/benchmark baseline    # saves current metrics# ... make changes .../benchmark compare     # compares against baseline

Output:

| Metric | Before | After | Delta | Verdict ||--------|--------|-------|-------|---------|| LCP | 1.2s | 1.4s | +200ms | WARNING: WARN || Bundle | 180KB | 175KB | -5KB | ✓ BETTER || Build | 12s | 14s | +2s | WARNING: WARN |

| Metric | Before | After | Delta | Verdict ||--------|--------|-------|-------|---------|| LCP | 1.2s | 1.4s | +200ms | WARNING: WARN || Bundle | 180KB | 175KB | -5KB | ✓ BETTER || Build | 12s | 14s | +2s | WARNING: WARN |

Output

Stores baselines in .ecc/benchmarks/ as JSON. Git-tracked so the team shares baselines.

Integration

CI: run /benchmark compare on every PR
Pair with /canary-watch for post-deploy monitoring
Pair with /browser-qa for full pre-ship checklist

來源與署名

來源：affaan-m/ECC位於skills/benchmark提交ef648e0

授權條款： MIT

內容歸原作者所有。SourceWeft 從公開儲存庫中收錄這些內容。

檢舉或申請下架

Benchmark

Benchmark — Performance Baseline & Regression Detection

When to Use

How It Works

Mode 1: Page Performance

Mode 2: API Performance

Mode 3: Build Performance

Mode 4: Before/After Comparison

Output

Integration

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