web-perf

Web Performance Audit

Your knowledge of web performance metrics, thresholds, and tooling APIs may be outdated. Prefer retrieval over pre-training when citing specific numbers or recommendations.

Retrieval Sources

Source	How to retrieve	Use for
web.dev	https://web.dev/articles/vitals	Core Web Vitals thresholds, definitions
Chrome DevTools docs	https://developer.chrome.com/docs/devtools/performance	Tooling APIs, trace analysis
Lighthouse scoring	https://developer.chrome.com/docs/lighthouse/performance/performance-scoring	Score weights, metric thresholds

FIRST: Verify MCP Tools Available

Discover available browser and performance tools before starting. Use the capabilities available for the requested audit. If trace tools are unavailable, continue any useful source or network analysis and state which measurements could not be collected.

If the user wants Chrome DevTools MCP setup, consult its installation guide and use the latest package version. Only change MCP configuration when setup is within the user's authorized scope; otherwise ask first. For clients using command and args, an example server entry is:

"chrome-devtools": {
  "command": "npx",
  "args": ["-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.
• 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.

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.

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)