web-perf

name	web-perf
description	Analyzes web performance using Chrome DevTools MCP. Measures Core Web Vitals and related lab metrics (FCP, LCP, INP/TBT, CLS, Speed Index), identifies render-blocking resources, network dependency chains, layout shifts, caching issues, and accessibility gaps. Use when asked to audit, profile, debug, or optimize page load performance, Lighthouse scores, or site speed.

Web Performance Audit

Audit web page performance using Chrome DevTools MCP tools. This skill focuses on Core Web Vitals, network optimization, and high-level accessibility gaps.

FIRST: Verify MCP Tools Available

Run this before starting. Try calling navigate_page or performance_start_trace. If unavailable, STOP—the chrome-devtools MCP server isn't configured.

Ask the user to add this to their MCP config:

"chrome-devtools": {
  "type": "local",
  "command": ["npx", "-y", "chrome-devtools-mcp@latest"]
}

Key Guidelines

• Be assertive: Verify claims by checking network requests, DOM, or codebase—then state findings definitively.
• Verify before recommending: Confirm something is unused before suggesting removal.
• Quantify impact: Use estimated savings from insights. Don't prioritize changes with 0ms impact.
• Account for variance: Prefer multiple traces for important conclusions, or state when findings are from a single run.
• Skip non-issues: If render-blocking resources have 0ms estimated impact, note but don't recommend action.
• Be specific: Say "compress hero.png (450KB) to WebP" not "optimize images".
• Prioritize ruthlessly: A site with 200ms LCP and 0 CLS is already excellent—say so.
• Separate mobile and desktop: Note the tested viewport/device conditions and avoid generalizing across them without evidence.

Quick Reference

Task	Tool Call
Load page	navigate_page(url: "...")
Start trace	performance_start_trace(autoStop: true, reload: true)
Analyze insight	performance_analyze_insight(insightSetId: "...", insightName: "...")
List requests	list_network_requests(resourceTypes: ["Script", "Stylesheet", ...])
Request details	get_network_request(reqid: <id>)
A11y snapshot	take_snapshot(verbose: true)

Workflow

Copy this checklist to track progress:

Audit Progress:
- [ ] Phase 1: Performance trace (navigate + record)
- [ ] Phase 2: Core Web Vitals analysis (includes CLS culprits)
- [ ] Phase 3: Network analysis
- [ ] Phase 4: Accessibility snapshot
- [ ] Phase 5: Codebase analysis (skip if third-party site)

Phase 1: Performance Trace

1. Navigate to the target URL:

   navigate_page(url: "<target-url>")
   

2. Start a performance trace with reload to capture cold-load metrics:

   performance_start_trace(autoStop: true, reload: true)
   

3. Wait for trace completion, then retrieve results.

Troubleshooting:

• If trace returns empty or fails, verify the page loaded correctly with navigate_page first
• If insight names don't match, inspect the trace response to list available insights

Phase 2: Core Web Vitals Analysis

Use performance_analyze_insight to extract key metrics.

Note: Insight names may vary across Chrome DevTools versions. If an insight name doesn't work, check the insightSetId from the trace response to discover available insights.

Common insight names:

Metric	Insight Name	What to Look For
LCP	LCPBreakdown	Time to largest contentful paint; breakdown of TTFB, resource load, render delay
CLS	CLSCulprits	Elements causing layout shifts (images without dimensions, injected content, font swaps)
Render Blocking	RenderBlocking	CSS/JS blocking first paint
Document Latency	DocumentLatency	Server response time issues
Network Dependencies	NetworkRequestsDepGraph	Request chains delaying critical resources

Example:

performance_analyze_insight(insightSetId: "<id-from-trace>", insightName: "LCPBreakdown")

Key thresholds (good/needs-improvement/poor):

• TTFB: < 800ms / < 1.8s / > 1.8s
• FCP: < 1.8s / < 3s / > 3s
• LCP: < 2.5s / < 4s / > 4s
• INP: < 200ms / < 500ms / > 500ms
• TBT: < 200ms / < 600ms / > 600ms
• CLS: < 0.1 / < 0.25 / > 0.25
• Speed Index: < 3.4s / < 5.8s / > 5.8s

Phase 3: Network Analysis

List all network requests to identify optimization opportunities:

list_network_requests(resourceTypes: ["Script", "Stylesheet", "Document", "Font", "Image"])

Look for:

1. Render-blocking resources: JS/CSS in <head> without async/defer/media attributes
2. Network chains: Resources discovered late because they depend on other resources loading first (e.g., CSS imports, JS-loaded fonts)
3. Missing preloads: Critical resources (fonts, hero images, key scripts) not preloaded
4. Caching issues: Missing or weak Cache-Control, ETag, or Last-Modified headers
5. Large payloads: Uncompressed or oversized JS/CSS bundles
6. Unused preconnects: If flagged, verify by checking if ANY requests went to that origin. If zero requests, it's definitively unused—recommend removal. If requests exist but loaded late, the preconnect may still be valuable.
7. Third-party resources: Do not recommend removal without confirming ownership, business purpose, and measured impact. Prefer defer, consent-gate, async, or lazy-load recommendations when removal is not clearly safe.

For detailed request info:

get_network_request(reqid: <id>)

Phase 4: Accessibility Snapshot

Take an accessibility tree snapshot:

take_snapshot(verbose: true)

Flag high-level gaps:

• Missing or duplicate ARIA IDs
• Elements with poor contrast ratios (check against WCAG AA: 4.5:1 for normal text, 3:1 for large text)
• Focus traps or missing focus indicators
• Interactive elements without accessible names

Phase 5: Codebase Analysis

Skip if auditing a third-party site without codebase access.

Analyze the codebase to understand where improvements can be made.

Detect Framework & Bundler

Search for configuration files to identify the stack:

Tool	Config Files
Webpack	webpack.config.js, webpack.*.js
Vite	vite.config.js, vite.config.ts
Rollup	rollup.config.js, rollup.config.mjs
esbuild	esbuild.config.js, build scripts with esbuild
Parcel	.parcelrc, package.json (parcel field)
Next.js	next.config.js, next.config.mjs
Nuxt	nuxt.config.js, nuxt.config.ts
SvelteKit	svelte.config.js
Astro	astro.config.mjs

Also check package.json for framework dependencies and build scripts.

Tree-Shaking & Dead Code

• Webpack: Check for mode: 'production', sideEffects in package.json, usedExports optimization
• Vite/Rollup: Tree-shaking enabled by default; check for treeshake options
• Look for: Barrel files (index.js re-exports), large utility libraries imported wholesale (lodash, moment)

Unused JS/CSS

• Check for CSS-in-JS vs. static CSS extraction
• Look for PurgeCSS/UnCSS configuration (Tailwind's content config)
• Identify dynamic imports vs. eager loading

Polyfills

• Check for @babel/preset-env targets and useBuiltIns setting
• Look for core-js imports (often oversized)
• Check browserslist config for overly broad targeting

Compression & Minification

• Check for terser, esbuild, or swc minification
• Look for gzip/brotli compression in build output or server config
• Check for source maps in production builds (should be external or disabled)

Output Format

Present findings as:

1. Core Web Vitals Summary - Table with metric, value, and rating (good/needs-improvement/poor)
2. Top Issues - Prioritized list of problems with estimated impact (high/medium/low)
3. Recommendations - Specific, actionable fixes with code snippets or config changes
4. Codebase Findings - Framework/bundler detected, optimization opportunities (omit if no codebase access)