Mode d’emploi
- Copiez la commande et examinez le paquet avant de l’installer dans votre environnement agent.
- Consultez le document original pour les outils, identifiants et environnements requis.
- Décrivez les entrées et le livrable souhaité ; comparez la sortie aux sources.
npx skills add https://github.com/prasad-vennam/awesome-android-ai-agent-skills --skill android-performance-auditAvant de commencer
- L’installation n’inclut ni abonnement au modèle, ni quota API, ni accès aux fichiers.
- Étoiles et installations reflètent l’activité, pas un test indépendant de qualité ou de sécurité.
Rendu depuis le dépôt source en conservant titres, exemples, code, tableaux, liens et images.
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
OutOfMemoryErroror 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
@Stableor@Immutableon 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
LazyorHiltentry points to avoid unnecessary object creation duringApplication.onCreate. - App Startup Library: Utilize
androidx.startupfor organized component initialization.
📦 Memory Management Checklist
- [ ] Context Leaks: Ensure no long-lived references to
Activitycontext (useApplicationContextif possible). - [ ] Bitmap Scaling: Never load full-resolution bitmaps into small
Imageviews. Use Coil withsize()transformations. - [ ] Flow/Coroutine Cleanup: Use
viewModelScopeto 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.




