Audits web page performance by ranking hot paths from Chrome traces and network waterfalls.
npx skills add https://github.com/celeroncoder/skills --skill flame-audit-celeroncoder
Please help me install this Agent Skill. Skill: flame-audit Source: https://github.com/celeroncoder/skills/tree/main/flame-audit Command: npx skills add https://github.com/celeroncoder/skills --skill flame-audit-celeroncoder
High-intent search queries and answers about installing and using this skill.
Capture a Chrome Performance trace of a cold load or interaction, then rank the widest stack frames by cost—long tasks, script evaluation, layout, and LCP phases. Fix the fattest exclusive leaf frames first rather than applying generic optimizations.
Use navigate_page to load the URL, then performance_start_trace with autoStop and reload to capture a cold-load trace. Follow up with list_network_requests to analyze transfer sizes and waterfall delays as a second flame graph.
Yes. Provide a flame graph image, speedscope export, .cpuprofile, or trace JSON and the widest frames are identified visually or structurally, then mapped to likely code fixes. Findings are labeled as profile interpretation rather than live measurements.
LCP is good under 2.5s and poor above 4s; INP is good under 200ms and poor above 500ms. TBT should stay under 200ms, CLS under 0.1, and TTFB under 800ms for a good rating.
Skip optimization when all metrics are green with no long tasks, or when a frame is thin—deep stacks and small leaves are rarely the real cost. Avoid recommending memoization, image compression, or CDNs unless the measured hot path actually points there.
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