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web-perf

web-perf

github.com/elithrarTesting & quality22272 installsUpdated 2w ago
Repository

About web-perf

Web performance investigation is a skill for diagnosing page performance and validating scoped fixes. It guides developers through browser traces or other available evidence, distinguishing measurements from estimates and hypotheses.

Key features

  1. 01Chooses available profiling evidence
  2. 02Tracks device, cache, and network conditions
  3. 03Investigates Core Web Vitals and bottlenecks
  4. 04Compares equivalent conditions after fixes
  5. 05Reports measurements and verification limits

Use cases

  1. 01Investigating a reported page slowdown
  2. 02Auditing performance with available traces
  3. 03Validating a targeted performance fix

MCP support

It prefers Chrome DevTools traces when available and can use other profilers or artifacts if that MCP server is unavailable. It does not require installing an MCP server to continue source-based analysis.

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/elithrar/dotfiles --skill web-perf

After installing, type/web-perfin Claude Code to confirm it loaded.

Bundled filesevals/evals.jsonreferences/devtools.md

Details

From the project README

Web performance investigation

Identify the target page, reported symptom, and relevant device conditions. For audit requests, report findings. For optimization or fix requests, implement the supported changes and validate their effect within the requested scope.

Choose the evidence path

Inspect the available browser and profiling tools before calling them. Prefer Chrome DevTools traces when available; read references/devtools.md for trace and network investigation. Use the installed tool schemas rather than assuming example parameters match the current version.

If that MCP server is unavailable, use existing trace or Lighthouse artifacts, another available profiler, or relevant source code. Complete the analysis those sources support and state what could not be measured. Missing profiling tools do not justify stopping source inspection or forcing an MCP installation.

Diagnose

Record the page/build, viewport, device or emulation, network/CPU throttling, cache state, and interactions relevant to the result. Reloading alone does not establish a cold cache. Keep mobile and desktop observations distinct.

Separate field Core Web Vitals from laboratory measurements. A load-only trace does not establish INP; TBT is a diagnostic lab metric, not a substitute INP measurement. Use the current metric definitions when assigning ratings, and label missing measurements as unavailable.

Follow the bottleneck from trace insight to request, element, or source path. Inspect the relevant LCP phases, layout-shift participants, long tasks, late resource discovery, or cache headers. Confirm ownership and use before recommending removal, especially for third-party scripts or resources used only in later interactions. Zero estimated savings is not evidence of a material problem, but one trace cannot prove a resource is never useful.

Validate and report

Prioritize findings by observed user impact and confidence. Distinguish measured values, tool estimates, and unmeasured hypotheses; avoid promising additive savings from overlapping insights.

For a fix, compare the affected behavior under equivalent conditions. Repeat measurements when variance or the size of the claimed improvement warrants it. Broaden testing only for an unresolved regression risk or a project gate, then finish.

Report the measured symptom, its supported cause, the concrete fix or recommendation, and the relevant verification limit. Add a metric table when several measurements help comparison. Do not expand a performance request into a mandatory accessibility or whole-codebase audit.

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