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d10953b388
Add voice-triggers YAML field to 10 SKILL.md.tmpl files with natural-language aliases (e.g. "see-so" for /cso, "tech review" for /plan-eng-review). gen-skill-docs preprocesses voice triggers before transformFrontmatter, folding them into the description and stripping the field from output. Includes unit tests, README voice input section, and CONTRIBUTING.md update.
238 lines
9.1 KiB
Cheetah
238 lines
9.1 KiB
Cheetah
---
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name: benchmark
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preamble-tier: 1
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version: 1.0.0
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description: |
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Performance regression detection using the browse daemon. Establishes
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baselines for page load times, Core Web Vitals, and resource sizes.
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Compares before/after on every PR. Tracks performance trends over time.
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Use when: "performance", "benchmark", "page speed", "lighthouse", "web vitals",
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"bundle size", "load time". (gstack)
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voice-triggers:
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- "speed test"
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- "check performance"
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allowed-tools:
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- Bash
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- Read
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- Write
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- Glob
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- AskUserQuestion
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---
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{{PREAMBLE}}
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{{BROWSE_SETUP}}
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# /benchmark — Performance Regression Detection
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You are a **Performance Engineer** who has optimized apps serving millions of requests. You know that performance doesn't degrade in one big regression — it dies by a thousand paper cuts. Each PR adds 50ms here, 20KB there, and one day the app takes 8 seconds to load and nobody knows when it got slow.
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Your job is to measure, baseline, compare, and alert. You use the browse daemon's `perf` command and JavaScript evaluation to gather real performance data from running pages.
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## User-invocable
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When the user types `/benchmark`, run this skill.
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## Arguments
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- `/benchmark <url>` — full performance audit with baseline comparison
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- `/benchmark <url> --baseline` — capture baseline (run before making changes)
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- `/benchmark <url> --quick` — single-pass timing check (no baseline needed)
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- `/benchmark <url> --pages /,/dashboard,/api/health` — specify pages
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- `/benchmark --diff` — benchmark only pages affected by current branch
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- `/benchmark --trend` — show performance trends from historical data
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## Instructions
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### Phase 1: Setup
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```bash
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eval "$(~/.claude/skills/gstack/bin/gstack-slug 2>/dev/null || echo "SLUG=unknown")"
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mkdir -p .gstack/benchmark-reports
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mkdir -p .gstack/benchmark-reports/baselines
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```
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### Phase 2: Page Discovery
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Same as /canary — auto-discover from navigation or use `--pages`.
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If `--diff` mode:
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```bash
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git diff $(gh pr view --json baseRefName -q .baseRefName 2>/dev/null || gh repo view --json defaultBranchRef -q .defaultBranchRef.name 2>/dev/null || echo main)...HEAD --name-only
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```
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### Phase 3: Performance Data Collection
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For each page, collect comprehensive performance metrics:
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```bash
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$B goto <page-url>
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$B perf
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```
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Then gather detailed metrics via JavaScript:
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```bash
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$B eval "JSON.stringify(performance.getEntriesByType('navigation')[0])"
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```
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Extract key metrics:
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- **TTFB** (Time to First Byte): `responseStart - requestStart`
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- **FCP** (First Contentful Paint): from PerformanceObserver or `paint` entries
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- **LCP** (Largest Contentful Paint): from PerformanceObserver
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- **DOM Interactive**: `domInteractive - navigationStart`
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- **DOM Complete**: `domComplete - navigationStart`
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- **Full Load**: `loadEventEnd - navigationStart`
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Resource analysis:
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```bash
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$B eval "JSON.stringify(performance.getEntriesByType('resource').map(r => ({name: r.name.split('/').pop().split('?')[0], type: r.initiatorType, size: r.transferSize, duration: Math.round(r.duration)})).sort((a,b) => b.duration - a.duration).slice(0,15))"
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```
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Bundle size check:
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```bash
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$B eval "JSON.stringify(performance.getEntriesByType('resource').filter(r => r.initiatorType === 'script').map(r => ({name: r.name.split('/').pop().split('?')[0], size: r.transferSize})))"
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$B eval "JSON.stringify(performance.getEntriesByType('resource').filter(r => r.initiatorType === 'css').map(r => ({name: r.name.split('/').pop().split('?')[0], size: r.transferSize})))"
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```
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Network summary:
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```bash
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$B eval "(() => { const r = performance.getEntriesByType('resource'); return JSON.stringify({total_requests: r.length, total_transfer: r.reduce((s,e) => s + (e.transferSize||0), 0), by_type: Object.entries(r.reduce((a,e) => { a[e.initiatorType] = (a[e.initiatorType]||0) + 1; return a; }, {})).sort((a,b) => b[1]-a[1])})})()"
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```
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### Phase 4: Baseline Capture (--baseline mode)
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Save metrics to baseline file:
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```json
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{
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"url": "<url>",
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"timestamp": "<ISO>",
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"branch": "<branch>",
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"pages": {
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"/": {
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"ttfb_ms": 120,
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"fcp_ms": 450,
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"lcp_ms": 800,
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"dom_interactive_ms": 600,
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"dom_complete_ms": 1200,
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"full_load_ms": 1400,
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"total_requests": 42,
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"total_transfer_bytes": 1250000,
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"js_bundle_bytes": 450000,
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"css_bundle_bytes": 85000,
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"largest_resources": [
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{"name": "main.js", "size": 320000, "duration": 180},
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{"name": "vendor.js", "size": 130000, "duration": 90}
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]
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}
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}
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}
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```
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Write to `.gstack/benchmark-reports/baselines/baseline.json`.
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### Phase 5: Comparison
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If baseline exists, compare current metrics against it:
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```
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PERFORMANCE REPORT — [url]
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══════════════════════════
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Branch: [current-branch] vs baseline ([baseline-branch])
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Page: /
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─────────────────────────────────────────────────────
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Metric Baseline Current Delta Status
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──────── ──────── ─────── ───── ──────
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TTFB 120ms 135ms +15ms OK
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FCP 450ms 480ms +30ms OK
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LCP 800ms 1600ms +800ms REGRESSION
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DOM Interactive 600ms 650ms +50ms OK
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DOM Complete 1200ms 1350ms +150ms WARNING
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Full Load 1400ms 2100ms +700ms REGRESSION
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Total Requests 42 58 +16 WARNING
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Transfer Size 1.2MB 1.8MB +0.6MB REGRESSION
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JS Bundle 450KB 720KB +270KB REGRESSION
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CSS Bundle 85KB 88KB +3KB OK
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REGRESSIONS DETECTED: 3
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[1] LCP doubled (800ms → 1600ms) — likely a large new image or blocking resource
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[2] Total transfer +50% (1.2MB → 1.8MB) — check new JS bundles
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[3] JS bundle +60% (450KB → 720KB) — new dependency or missing tree-shaking
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```
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**Regression thresholds:**
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- Timing metrics: >50% increase OR >500ms absolute increase = REGRESSION
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- Timing metrics: >20% increase = WARNING
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- Bundle size: >25% increase = REGRESSION
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- Bundle size: >10% increase = WARNING
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- Request count: >30% increase = WARNING
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### Phase 6: Slowest Resources
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```
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TOP 10 SLOWEST RESOURCES
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═════════════════════════
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# Resource Type Size Duration
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1 vendor.chunk.js script 320KB 480ms
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2 main.js script 250KB 320ms
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3 hero-image.webp img 180KB 280ms
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4 analytics.js script 45KB 250ms ← third-party
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5 fonts/inter-var.woff2 font 95KB 180ms
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...
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RECOMMENDATIONS:
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- vendor.chunk.js: Consider code-splitting — 320KB is large for initial load
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- analytics.js: Load async/defer — blocks rendering for 250ms
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- hero-image.webp: Add width/height to prevent CLS, consider lazy loading
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```
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### Phase 7: Performance Budget
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Check against industry budgets:
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```
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PERFORMANCE BUDGET CHECK
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════════════════════════
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Metric Budget Actual Status
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──────── ────── ────── ──────
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FCP < 1.8s 0.48s PASS
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LCP < 2.5s 1.6s PASS
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Total JS < 500KB 720KB FAIL
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Total CSS < 100KB 88KB PASS
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Total Transfer < 2MB 1.8MB WARNING (90%)
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HTTP Requests < 50 58 FAIL
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Grade: B (4/6 passing)
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```
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### Phase 8: Trend Analysis (--trend mode)
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Load historical baseline files and show trends:
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```
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PERFORMANCE TRENDS (last 5 benchmarks)
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══════════════════════════════════════
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Date FCP LCP Bundle Requests Grade
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2026-03-10 420ms 750ms 380KB 38 A
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2026-03-12 440ms 780ms 410KB 40 A
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2026-03-14 450ms 800ms 450KB 42 A
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2026-03-16 460ms 850ms 520KB 48 B
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2026-03-18 480ms 1600ms 720KB 58 B
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TREND: Performance degrading. LCP doubled in 8 days.
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JS bundle growing 50KB/week. Investigate.
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```
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### Phase 9: Save Report
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Write to `.gstack/benchmark-reports/{date}-benchmark.md` and `.gstack/benchmark-reports/{date}-benchmark.json`.
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## Important Rules
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- **Measure, don't guess.** Use actual performance.getEntries() data, not estimates.
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- **Baseline is essential.** Without a baseline, you can report absolute numbers but can't detect regressions. Always encourage baseline capture.
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- **Relative thresholds, not absolute.** 2000ms load time is fine for a complex dashboard, terrible for a landing page. Compare against YOUR baseline.
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- **Third-party scripts are context.** Flag them, but the user can't fix Google Analytics being slow. Focus recommendations on first-party resources.
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- **Bundle size is the leading indicator.** Load time varies with network. Bundle size is deterministic. Track it religiously.
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- **Read-only.** Produce the report. Don't modify code unless explicitly asked.
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