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flutter-performance

Skill16 starsChanged 2 months agoBSD-3-ClauseView on GitHub

Profile and improve Flutter runtime performance using profile-mode evidence, DevTools, frame analysis, rebuild inspection, memory, and app-size tools. Use for jank, slow startup, excessive work, leaks, or size regressions; route production logs, errors, and traces to flutter-observability.

3 other projects use a version of this.

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The file

We split this skill into the rules it gives an agent

1 rule. About 0 are common, 1 is distinctive, and 0 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈1

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Prefer removing or moving work over caching everything.

    line 23

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Flutter Performance

Measure a reproducible flow before changing code. Debug-mode timing is not release-performance evidence. A cause or fix named in the request is a hypothesis: confirm it with a measurement first.

Establish evidence

Record the target device, Flutter version, build mode, flow, dataset, and metric. Reproduce in profile mode on representative hardware when the issue is user-facing.

Diagnose by symptom

  • Frame jank: inspect UI/raster timing, expensive build/layout/paint, shader or image work.
  • Excess rebuilds: inspect state subscription scope and widget identity before adding const mechanically.
  • Slow startup: trace initialization and defer work not required for first useful frame.
  • Memory growth: compare repeated-flow snapshots and find retained ownership, listeners, controllers, or caches.
  • Large binaries: use Flutter's app-size analysis and compare like-for-like release artifacts.
  • CPU-heavy Dart: use timeline/CPU profiling and consider isolates only after locating the work.

Prefer removing or moving work over caching everything. Bound caches and preserve correctness.

Load profile and frame analysis for frame, CPU, image, rebuild, or web-rendering investigations. Load memory, startup, and size for retention, first-useful-frame, or artifact-size work.

Verification

Repeat the same scenario after the change and report before/after evidence with variance. Run correctness tests because performance changes often alter lifecycle or caching behavior.

Sources

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