AN

android-compose-performance

A toolkit for diagnosing and fixing performance bottlenecks in Jetpack Compose applications, focusing on rendering and state stability.

Install

mkdir -p .claude/skills/android-compose-performance && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/16632" && unzip -o skill.zip -d .claude/skills/android-compose-performance && rm skill.zip

Installs to .claude/skills/android-compose-performance

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

Profile and improve Compose recomposition, layout, scrolling, startup, and rendering performance in Android apps.
113 charsno explicit “when” trigger
Intermediate

Key capabilities

  • Profile Compose recomposition hotspots
  • Optimize LazyColumn performance
  • Improve app startup jank
  • Enhance layout rendering efficiency
  • Stabilize list identity in Compose
  • Move heavy work out of composition

How it works

The skill identifies performance bottlenecks in Compose UI, such as excessive recomposition or slow scrolling, and provides remediation examples to optimize rendering.

Inputs & outputs

You give it
Android app with Compose UI
You get back
improved Compose recomposition, layout, scrolling, startup, and rendering performance

When to use android-compose-performance

  • Fix excessive recomposition in Compose
  • Optimize LazyColumn performance
  • Profile app startup jank
  • Improve layout rendering efficiency

About this skill

Android Compose Performance

When To Use

  • Use this skill when the request is about: compose performance issue, recomposition too much android, slow lazycolumn compose.
  • Primary outcome: Profile and improve Compose recomposition, layout, scrolling, startup, and rendering performance in Android apps.
  • Handoff skills when the scope expands:
  • android-performance-observability
  • android-testing-ui

Workflow

  1. Identify whether the target surface is Compose, View system, or a mixed interoperability screen.
  2. Select the lowest-friction UI pattern that satisfies responsiveness, accessibility, and performance needs.
  3. Build the UI around stable state, explicit side effects, and reusable design tokens.
  4. Exercise edge cases such as long text, font scaling, RTL, and narrow devices in the fixture apps.
  5. Validate with unit, UI, and screenshot-friendly checks before handing off.

Guardrails

  • Optimize for stable state and predictable rendering before adding animation or abstraction.
  • Respect accessibility semantics, contrast, focus order, and touch target guidance by default.
  • Do not mix Compose and View system ownership without an explicit interoperability boundary.
  • Prefer measured performance work over premature micro-optimizations.

Anti-Patterns

  • Embedding navigation or business logic directly in leaf UI components.
  • Using fixed dimensions that break on localization or dynamic text.
  • Ignoring semantics and announcing only visual changes.
  • Porting XML patterns directly into Compose without adapting the mental model.

Remediation Examples

Stabilize list identity

LazyColumn {
    items(tasks, key = { it.id }) { task ->
        TaskRow(task)
    }
}

Move heavy work out of composition

@Composable
fun TaskBoard(tasks: List<TaskUiModel>) {
    val visibleTasks = remember(tasks) { tasks.sortedBy { it.title } }
    LazyColumn { items(visibleTasks, key = { it.title }) { TaskRow(it) } }
}

Avoid broad scroll-driven recomposition

Box(
    modifier = Modifier.offset {
        IntOffset(0, scrollState.value)
    }
)

Examples

Happy path

  • Scenario: Profile the Compose task list for unnecessary recomposition hotspots.
  • Command: cd examples/orbittasks-compose && ./gradlew :app:testDebugUnitTest

Edge case

  • Scenario: Evaluate long lists, filter chips, and snackbar churn under repeated state changes.
  • Command: cd examples/orbittasks-compose && ./gradlew :app:assembleDebug

Failure recovery

  • Scenario: Separate performance requests from generic Compose or observability prompts.
  • Command: python3 scripts/eval_triggers.py --skill android-compose-performance

Done Checklist

  • The implementation path is explicit, minimal, and tied to the right Android surface.
  • Relevant example commands and benchmark prompts have been exercised or updated.
  • Handoffs to adjacent skills are documented when the request crosses boundaries.
  • Official references cover the chosen pattern and the main migration or troubleshooting path.

Official References

When not to use it

  • When the issue is not related to Compose performance
  • When the issue is about `play release notes only`
  • When the issue is about `room migration only`

Limitations

  • The skill focuses on profiling and improving Compose performance in Android apps
  • The skill addresses recomposition, layout, scrolling, startup, and rendering performance
  • The skill does not cover `permission denied ui only` or `rxjava migration only`

How it compares

This skill provides specific code examples and workflows for optimizing Compose performance, directly addressing issues like unstable list identity or heavy work in composition, unlike general Android performance advice.

Compared to similar skills

android-compose-performance side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
android-compose-performance (this skill)04moReviewIntermediate
mobile-android-design1012moNo flagsIntermediate
mobile_engineer02moNo flagsAdvanced
mobile-architect-agent01moNo flagsIntermediate

Try saying

Example prompts that trigger this skill in your AI assistant.

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