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performance-investigation

performance-investigation

github.com/sveltejsDevelopment88.5k151 installsUpdated today
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About performance-investigation

A repository-specific skill for comparing benchmark performance across branches and investigating regressions with reports and CPU profiles. It guides developers through targeted reruns and runtime tests.

Key features

  1. 01Branch-to-branch benchmark comparison
  2. 02Regression reports and raw results
  3. 03CPU profile summaries and diffs
  4. 04Targeted benchmark runs
  5. 05Runtime regression test guidance

Use cases

  1. 01Check whether a branch regresses against main
  2. 02Find hotspots behind a benchmark delta
  3. 03Rerun selected reactivity benchmarks
  4. 04Validate performance changes with tests

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/sveltejs/svelte --skill performance-investigation

After installing, type/performance-investigationin Claude Code to confirm it loaded.

Details

From the project README

Quick start

  1. Start from a branch you want to measure (for example foo).
  2. Run:
pnpm bench:compare main foo

If you pass one branch, bench:compare automatically compares it to main.

Where outputs go

  • Summary report: benchmarking/compare/.results/report.txt
  • Raw benchmark numbers:
    • benchmarking/compare/.results/main.json
    • benchmarking/compare/.results/<your-branch>.json
  • CPU profiles (per benchmark, per branch):
    • benchmarking/compare/.profiles/main/*.cpuprofile
    • benchmarking/compare/.profiles/main/*.md
    • benchmarking/compare/.profiles/<your-branch>/*.cpuprofile
    • benchmarking/compare/.profiles/<your-branch>/*.md

The .md files are generated summaries of the CPU profile and are usually the fastest way to inspect hotspots.

Suggested investigation flow

  1. Open benchmarking/compare/.results/report.txt and identify largest regressions first.
  2. For each high-delta benchmark, compare:
    • benchmarking/compare/.profiles/main/<benchmark>.md
    • benchmarking/compare/.profiles/<branch>/<benchmark>.md
  3. Look for changes in self/inclusive hotspot share in runtime internals (runtime.js, reactivity/batch.js, reactivity/deriveds.js, reactivity/sources.js).
  4. Make one optimization change at a time, then re-run targeted benches before re-running full compare.

Fast benchmark loops

Run only selected reactivity benchmarks by substring:

pnpm bench kairo_mux kairo_deep kairo_broad kairo_triangle
pnpm bench repeated_deps sbench_create_signals mol_owned

Tests to run after perf changes

Runtime reactivity regressions are most likely in runes runtime tests:

pnpm test runtime-runes

Helpful script

For quick cpuprofile hotspot deltas between two branches:

node benchmarking/compare/profile-diff.mjs kairo_mux_owned main foo

This prints top function sample-share deltas for the selected benchmark.

Practical gotchas

  • bench:compare checks out branches while running. Avoid uncommitted changes (or stash them) so branch switching is safe.
  • Each bench:compare run rewrites benchmarking/compare/.results and benchmarking/compare/.profiles.

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