Diagnose why a page is slow with a Lighthouse-style trace
When to use: A page feels sluggish and you want Claude to run a trace and point at the actual bottleneck instead of guessing.
Prerequisites
- Target URL loads without login (or you handle auth first) — Use
navigate_pagewith a URL; for auth-gated pages, first log in via chrome-devtools click/type tools
Flow
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Run a performance traceOpen https://example.com/product/123. Run a performance trace with CPU throttling 4x and a slow-3G network profile. Tell me the LCP, CLS, and TBT.✓ Copied→ Three metric numbers plus a trace summary
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Find the top culpritWhat single asset or script contributes most to the LCP delay? Show the request timing.✓ Copied→ Specific URL identified, with timing breakdown (DNS/connect/TTFB/download)
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Propose a concrete fixWhat's the cheapest fix that would move LCP under 2.5s? Propose one change (preconnect, preload, defer, lazy, or bundle-split) with specific lines to add.✓ Copied→ Actionable HTML/JS diff, not a generic list
Outcome: A perf regression with a named cause and a specific fix, verifiable by re-running the trace after you apply it.
Pitfalls
- Trace varies run-to-run — one-off numbers mislead — Run the trace 3x and take the median before concluding anything
- Local/dev builds differ from production — Trace against a production URL or a CDN-served preview, not localhost with no compression