Best use case
Mobile Performance Profiling is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Mobile app performance analysis and optimization
Teams using Mobile Performance Profiling should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/mobile-perf/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How Mobile Performance Profiling Compares
| Feature / Agent | Mobile Performance Profiling | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Mobile app performance analysis and optimization
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Mobile Performance Profiling Skill
## Overview
This skill provides mobile app performance analysis and optimization capabilities. It enables profiling with Xcode Instruments, Android Profiler, Flipper, and Flutter DevTools to identify and fix performance issues.
## Allowed Tools
- `bash` - Execute profiling tools and build commands
- `read` - Analyze performance reports and profiles
- `write` - Generate optimization configurations
- `edit` - Update performance-related code
- `glob` - Search for performance files
- `grep` - Search for patterns
## Capabilities
### Xcode Instruments
1. **Time Profiler**
- Profile CPU usage
- Identify hot paths
- Analyze call trees
- Measure function durations
2. **Allocations**
- Track memory allocations
- Identify memory leaks
- Analyze retain cycles
- Monitor heap growth
3. **Core Animation**
- Profile rendering performance
- Identify offscreen renders
- Measure frame rates
- Detect layer issues
### Android Profiler
4. **CPU Profiler**
- Record method traces
- Analyze thread activity
- Identify CPU bottlenecks
- Profile startup time
5. **Memory Profiler**
- Track allocations
- Capture heap dumps
- Identify memory leaks
- Analyze GC events
6. **Network Profiler**
- Monitor requests
- Analyze response times
- Profile bandwidth usage
### React Native
7. **Flipper Performance**
- Monitor React renders
- Profile JavaScript thread
- Analyze bridge communication
- Track native modules
8. **Hermes Profiler**
- Profile Hermes engine
- Analyze bytecode execution
- Optimize bundle size
### Flutter DevTools
9. **Performance Overlay**
- Monitor frame rendering
- Identify jank
- Profile widget rebuilds
- Analyze timeline
### Metrics
10. **App Startup**
- Cold start optimization
- Warm start measurement
- Hot start profiling
- Deferred initialization
11. **Memory Management**
- Peak memory usage
- Memory warnings handling
- Image caching strategies
- Object pooling
12. **Rendering Performance**
- Frame rate maintenance
- Scroll performance
- Animation smoothness
- Layout optimization
## Target Processes
- `mobile-performance-optimization.js` - Performance tuning
- `mobile-testing-strategy.js` - Performance testing
- `jetpack-compose-ui.js` - Compose optimization
- `swiftui-app-development.js` - SwiftUI optimization
## Dependencies
- Xcode Instruments
- Android Studio Profiler
- Flipper
- Flutter DevTools
## Usage Examples
### Instruments Command Line
```bash
# Record Time Profiler trace
xcrun xctrace record --device "iPhone 15 Pro" \
--template "Time Profiler" \
--attach "MyApp" \
--time-limit 30s \
--output ~/Desktop/profile.trace
# Export trace data
xcrun xctrace export --input ~/Desktop/profile.trace \
--xpath '/trace-toc/run/tracks/track[@name="Time Profiler"]' \
--output ~/Desktop/profile_data.xml
```
### Android Profiler Commands
```bash
# Capture CPU trace
adb shell am profile start com.example.myapp /data/local/tmp/profile.trace
# Stop and pull trace
adb shell am profile stop com.example.myapp
adb pull /data/local/tmp/profile.trace ./profile.trace
# Capture heap dump
adb shell am dumpheap com.example.myapp /data/local/tmp/heap.hprof
adb pull /data/local/tmp/heap.hprof ./heap.hprof
```
### React Native Performance Optimization
```typescript
// Optimize list rendering
import { FlashList } from '@shopify/flash-list';
const OptimizedList = () => {
const renderItem = useCallback(({ item }) => (
<MemoizedListItem item={item} />
), []);
return (
<FlashList
data={items}
renderItem={renderItem}
estimatedItemSize={100}
keyExtractor={item => item.id}
/>
);
};
// Memoize expensive components
const MemoizedListItem = memo(({ item }) => {
return (
<View style={styles.item}>
<Text>{item.title}</Text>
</View>
);
}, (prev, next) => prev.item.id === next.item.id);
// Optimize images
import FastImage from 'react-native-fast-image';
const OptimizedImage = ({ uri }) => (
<FastImage
source={{ uri, priority: FastImage.priority.normal }}
resizeMode={FastImage.resizeMode.cover}
style={styles.image}
/>
);
```
### SwiftUI Performance
```swift
// Optimize view updates
struct OptimizedView: View {
@State private var items: [Item] = []
var body: some View {
List {
ForEach(items) { item in
ItemRow(item: item)
.equatable() // Prevent unnecessary redraws
}
}
}
}
// Use Equatable for custom views
struct ItemRow: View, Equatable {
let item: Item
static func == (lhs: ItemRow, rhs: ItemRow) -> Bool {
lhs.item.id == rhs.item.id
}
var body: some View {
Text(item.title)
}
}
// Lazy loading
struct LazyImageView: View {
let url: URL
var body: some View {
AsyncImage(url: url) { phase in
switch phase {
case .empty:
ProgressView()
case .success(let image):
image.resizable().aspectRatio(contentMode: .fit)
case .failure:
Image(systemName: "photo")
@unknown default:
EmptyView()
}
}
}
}
```
### Compose Performance
```kotlin
// Optimize recomposition
@Composable
fun OptimizedList(items: List<Item>) {
LazyColumn {
items(
items = items,
key = { it.id }
) { item ->
// Stable key prevents unnecessary recomposition
ItemCard(item = item)
}
}
}
// Use derivedStateOf for computed values
@Composable
fun SearchableList(items: List<Item>, query: String) {
val filteredItems by remember(items, query) {
derivedStateOf {
items.filter { it.title.contains(query, ignoreCase = true) }
}
}
LazyColumn {
items(filteredItems, key = { it.id }) { ItemCard(it) }
}
}
// Use remember for expensive calculations
@Composable
fun ExpensiveView(data: ComplexData) {
val processedData = remember(data) {
expensiveCalculation(data)
}
Text(processedData.result)
}
```
## Quality Gates
- App startup < 2s (cold), < 1s (warm)
- Frame rate >= 60fps (120fps for ProMotion)
- Memory usage within platform limits
- No memory leaks detected
- Scroll performance smooth
## Related Skills
- `mobile-testing` - Performance testing
- `react-native-dev` - RN optimization
- `flutter-dart` - Flutter optimization
- `kotlin-compose` - Compose optimization
## Version History
- 1.0.0 - Initial releaseRelated Skills
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