Individual skill

performance-analysis

Measure before optimizing. Profile startup time, latency, throughput, memory, or bundle size, find the dominant cost with evidence, and propose the smallest change that moves the number. Use for "slow", "takes N seconds", "high CPU or memory", and performance regressions.

src/skills/builtin/performance-analysis/SKILL.md

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# Analyze performance with numbers

Optimizing without a measurement changes the code without changing the
outcome. Every step below produces a number you can show.

## Establish the baseline

1. Define the metric and the scenario exactly: what is slow, from which event
   to which, on what input size, on what machine. Ask if unclear.
2. Measure it three times with the tools the project already has (timers,
   `--profile` flags, `time`, `hyperfine`, language profilers, `--cpu-prof`,
   heap snapshots, bundle analyzers). Record median and spread.
3. Record the environment: load average, CPU count, disk free, network,
   concurrent processes. A loaded machine invalidates comparisons.