benchmark
Performance regression detection using the browse daemon. Establishes baselines for page load times, Core Web Vitals, and resource sizes. Compares before/after on every PR.
Best use case
benchmark is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Performance regression detection using the browse daemon. Establishes baselines for page load times, Core Web Vitals, and resource sizes. Compares before/after on every PR.
Teams using benchmark should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/benchmark/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How benchmark Compares
| Feature / Agent | benchmark | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Performance regression detection using the browse daemon. Establishes baselines for page load times, Core Web Vitals, and resource sizes. Compares before/after on every PR.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
<!-- Regenerate: bun run gen:skill-docs -->
## Voice
**Tone:** direct, concrete, sharp, never corporate, never academic. Sound like a builder, not a consultant. Name the file, the function, the command. No filler, no throat-clearing.
**Writing rules:** No em dashes (use commas, periods, "..."). No AI vocabulary (delve, crucial, robust, comprehensive, nuanced, etc.). Short paragraphs. End with what to do.
## Repro
1. {step}
## What would make this a 10
{one sentence}
**Date:** {YYYY-MM-DD} | **Version:** {version} | **Skill:** /{skill}
```
Slug: lowercase hyphens, max 60 chars. Skip if exists. Max 3/session. File inline, don't stop.
## FOUNDERCLAW REVIEW REPORT
| Review | Trigger | Why | Runs | Status | Findings |
|--------|---------|-----|------|--------|----------|
| CEO Review | \`plan-ceo-review\` | Scope & strategy | 0 | — | — |
| Codex Review | \`codex review\` | Independent 2nd opinion | 0 | — | — |
| Eng Review | \`plan-eng-review\` | Architecture & tests (required) | 0 | — | — |
| Design Review | \`plan-design-review\` | UI/UX gaps | 0 | — | — |
**VERDICT:** NO REVIEWS YET — run \`autoplan\` for full review pipeline, or individual reviews above.
\`\`\`
**PLAN MODE EXCEPTION — ALWAYS RUN:** This writes to the plan file, which is the one
file you are allowed to edit in plan mode. The plan file review report is part of the
plan's living status.
# benchmark — Performance Regression Detection
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.
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.
## User-invocable
When the user types `benchmark`, run this skill.
## Arguments
- `benchmark <url>` — full performance audit with baseline comparison
- `benchmark <url> --baseline` — capture baseline (run before making changes)
- `benchmark <url> --quick` — single-pass timing check (no baseline needed)
- `benchmark <url> --pages /,/dashboard,/api/health` — specify pages
- `benchmark --diff` — benchmark only pages affected by current branch
- `benchmark --trend` — show performance trends from historical data
## Instructions
### Phase 1: Setup
### Phase 2: Page Discovery
Same as canary — auto-discover from navigation or use `--pages`.
If `--diff` mode:
```bash
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
```
### Phase 3: Performance Data Collection
For each page, collect comprehensive performance metrics:
```bash
open browser to <page-url>
$B perf
```
Then gather detailed metrics via JavaScript:
```bash
$B eval "JSON.stringify(performance.getEntriesByType('navigation')[0])"
```
Extract key metrics:
- **TTFB** (Time to First Byte): `responseStart - requestStart`
- **FCP** (First Contentful Paint): from PerformanceObserver or `paint` entries
- **LCP** (Largest Contentful Paint): from PerformanceObserver
- **DOM Interactive**: `domInteractive - navigationStart`
- **DOM Complete**: `domComplete - navigationStart`
- **Full Load**: `loadEventEnd - navigationStart`
Resource analysis:
```bash
$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))"
```
Bundle size check:
```bash
$B eval "JSON.stringify(performance.getEntriesByType('resource').filter(r => r.initiatorType === 'script').map(r => ({name: r.name.split('/').pop().split('?')[0], size: r.transferSize})))"
$B eval "JSON.stringify(performance.getEntriesByType('resource').filter(r => r.initiatorType === 'css').map(r => ({name: r.name.split('/').pop().split('?')[0], size: r.transferSize})))"
```
Network summary:
```bash
$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])})})()"
```
### Phase 4: Baseline Capture (--baseline mode)
Save metrics to baseline file:
```json
{
"url": "<url>",
"timestamp": "<ISO>",
"branch": "<branch>",
"pages": {
"/": {
"ttfb_ms": 120,
"fcp_ms": 450,
"lcp_ms": 800,
"dom_interactive_ms": 600,
"dom_complete_ms": 1200,
"full_load_ms": 1400,
"total_requests": 42,
"total_transfer_bytes": 1250000,
"js_bundle_bytes": 450000,
"css_bundle_bytes": 85000,
"largest_resources": [
{"name": "main.js", "size": 320000, "duration": 180},
{"name": "vendor.js", "size": 130000, "duration": 90}
]
}
}
}
```
Write to `.founderclawbenchmark-reports/baselines/baseline.json`.
### Phase 5: Comparison
If baseline exists, compare current metrics against it:
```
PERFORMANCE REPORT — [url]
══════════════════════════
Branch: [current-branch] vs baseline ([baseline-branch])
Page: /
─────────────────────────────────────────────────────
Metric Baseline Current Delta Status
──────── ──────── ─────── ───── ──────
TTFB 120ms 135ms +15ms OK
FCP 450ms 480ms +30ms OK
LCP 800ms 1600ms +800ms REGRESSION
DOM Interactive 600ms 650ms +50ms OK
DOM Complete 1200ms 1350ms +150ms WARNING
Full Load 1400ms 2100ms +700ms REGRESSION
Total Requests 42 58 +16 WARNING
Transfer Size 1.2MB 1.8MB +0.6MB REGRESSION
JS Bundle 450KB 720KB +270KB REGRESSION
CSS Bundle 85KB 88KB +3KB OK
REGRESSIONS DETECTED: 3
[1] LCP doubled (800ms → 1600ms) — likely a large new image or blocking resource
[2] Total transfer +50% (1.2MB → 1.8MB) — check new JS bundles
[3] JS bundle +60% (450KB → 720KB) — new dependency or missing tree-shaking
```
**Regression thresholds:**
- Timing metrics: >50% increase OR >500ms absolute increase = REGRESSION
- Timing metrics: >20% increase = WARNING
- Bundle size: >25% increase = REGRESSION
- Bundle size: >10% increase = WARNING
- Request count: >30% increase = WARNING
### Phase 6: Slowest Resources
```
TOP 10 SLOWEST RESOURCES
═════════════════════════
# Resource Type Size Duration
1 vendor.chunk.js script 320KB 480ms
2 main.js script 250KB 320ms
3 hero-image.webp img 180KB 280ms
4 analytics.js script 45KB 250ms ← third-party
5 fonts/inter-var.woff2 font 95KB 180ms
...
RECOMMENDATIONS:
- vendor.chunk.js: Consider code-splitting — 320KB is large for initial load
- analytics.js: Load async/defer — blocks rendering for 250ms
- hero-image.webp: Add width/height to prevent CLS, consider lazy loading
```
### Phase 7: Performance Budget
Check against industry budgets:
```
PERFORMANCE BUDGET CHECK
════════════════════════
Metric Budget Actual Status
──────── ────── ────── ──────
FCP < 1.8s 0.48s PASS
LCP < 2.5s 1.6s PASS
Total JS < 500KB 720KB FAIL
Total CSS < 100KB 88KB PASS
Total Transfer < 2MB 1.8MB WARNING (90%)
HTTP Requests < 50 58 FAIL
Grade: B (4/6 passing)
```
### Phase 8: Trend Analysis (--trend mode)
Load historical baseline files and show trends:
```
PERFORMANCE TRENDS (last 5 benchmarks)
══════════════════════════════════════
Date FCP LCP Bundle Requests Grade
2026-03-10 420ms 750ms 380KB 38 A
2026-03-12 440ms 780ms 410KB 40 A
2026-03-14 450ms 800ms 450KB 42 A
2026-03-16 460ms 850ms 520KB 48 B
2026-03-18 480ms 1600ms 720KB 58 B
TREND: Performance degrading. LCP doubled in 8 days.
JS bundle growing 50KB/week. Investigate.
```
### Phase 9: Save Report
Write to `.founderclawbenchmark-reports/{date}-benchmark.md` and `.founderclawbenchmark-reports/{date}-benchmark.json`.
## Important Rules
- **Measure, don't guess.** Use actual performance.getEntries() data, not estimates.
- **Baseline is essential.** Without a baseline, you can report absolute numbers but can't detect regressions. Always encourage baseline capture.
- **Relative thresholds, not absolute.** 2000ms load time is fine for a complex dashboard, terrible for a landing page. Compare against YOUR baseline.
- **Third-party scripts are context.** Flag them, but the user can't fix Google Analytics being slow. Focus recommendations on first-party resources.
- **Bundle size is the leading indicator.** Load time varies with network. Bundle size is deterministic. Track it religiously.
- **Read-only.** Produce the report. Don't modify code unless explicitly asked.Related Skills
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