prasad-vennam/awesome-android-ai-agent-skills

android-performance-audit

Use when profiling Android apps, debugging memory leaks, optimizing Compose UI, or improving app startup time.

Quelltext ansehen

Verwendung

  1. Installationsbefehl kopieren und das Quellpaket vor der Installation in der eigenen Agentenumgebung prüfen.
  2. Benötigte Werkzeuge, Zugangsdaten und Hosts im Original prüfen.
  3. Eingabe und gewünschtes Ergebnis beschreiben und die Ausgabe mit den Quellen abgleichen.
npx skills add https://github.com/prasad-vennam/awesome-android-ai-agent-skills --skill android-performance-audit

Vor dem Start

  • Die Installation umfasst weder Modellabo noch API-Kontingent oder Dateizugriffsrechte.
  • Sterne und Installationen zeigen Aktivität, keine unabhängige Qualitäts- oder Sicherheitsprüfung.
Originales Skill-Dokument

Aus dem Quell-Repository gerendert; Überschriften, Beispiele, Code, Tabellen, Links und Bilder bleiben erhalten.

Android Performance Auditing 🚀⏱️

Expert strategies for profiling and optimizing Android applications to ensure smooth, responsive, and efficient user experiences.

⚡ When to Use

  • UI Lag: Fixing jank in lists or complex Compose layouts.
  • Memory Issues: Debugging OutOfMemoryError or high memory growth.
  • App Startup: Reducing the time from icon tap to first usable frame.
  • Battery Drain: Identifying excessive network calls or background work.
  • Leak Detection: Investigating persistent objects after activity destruction.

🛠️ Main Tools

1. Android Studio Profiler

  • CPU Profiler: Inspect call stacks and thread activity.
  • Memory Profiler: Capture heap dumps and track allocations.
  • Network Profiler: Analyze traffic and payload sizes.
  • Energy Profiler: Monitor battery impact.

2. LeakCanary

  • Rule: ALWAYS include LeakCanary in debug builds.
  • Use it to detect memory leaks automatically during development.

🎥 Compose Optimization

  • [ ] Recomposition Tracking: Use the "Layout Inspector" in Android Studio to count recompositions.
  • [ ] Stability Rules: Use @Stable or @Immutable on domain models to help the Compose compiler.
  • [ ] Lambda Stability: Avoid pass-through lambdas that capture unstable variables; use method references where possible.
  • [ ] remember & derivedStateOf: Minimize expensive calculations within the composition loop.

🏁 App Startup Optimization

  • Baseline Profiles: Use Baseline Profiles to pre-compile critical code paths (AOT) to improve startup by up to 30%.
  • Lazy Initialization: Use Lazy or Hilt entry points to avoid unnecessary object creation during Application.onCreate.
  • App Startup Library: Utilize androidx.startup for organized component initialization.

📦 Memory Management Checklist

  • [ ] Context Leaks: Ensure no long-lived references to Activity context (use ApplicationContext if possible).
  • [ ] Bitmap Scaling: Never load full-resolution bitmaps into small Image views. Use Coil with size() transformations.
  • [ ] Flow/Coroutine Cleanup: Use viewModelScope to ensure background tasks are canceled with the UI.

🧪 Benchmarking

  • Macrobenchmark: Measure high-level user interactions (Startup, Scrolling).
  • Microbenchmark: Measure isolated code loops or CPU-intensive algorithms.

🔗 Related Resources

Verwandte Aufgaben

aus demselben Repository

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