Agent skill
ios-instruments-performance-cli
Use Xcode Instruments command line tools to analyze iOS app performance, detect memory leaks, optimize launch times, monitor CPU usage, and identify performance bottlenecks for the iOS project
Install this agent skill to your Project
npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/development/ios-instruments-performance-cli
SKILL.md
iOS Instruments Performance CLI
Instructions
When helping with iOS app performance optimization using Instruments command line tools:
1. Setup Analysis Environment
CRITICAL: Always use device UUID, never device names
- Get device UUID:
xcrun simctl list devices available | grep "iPhone" - Device names like "iPhone 17 Pro" are ambiguous and will fail
- Use UUID format:
F464E766-555C-4B95-B8CC-763702A70791
Clean installation state (REQUIRED)
- Always uninstall app before profiling:
xcrun simctl uninstall $DEVICE_UUID <bundle id> - Multiple app installations cause "process is ambiguous" errors
- Alternative: Completely erase simulator for cleanest state
Build configuration
- Build in Release mode for accurate performance measurements
2. Choose Appropriate Instrument Template
Use xcrun xctrace list templates to see available templates:
- App Launch - Essential for launch time optimization (most common)
- Time Profiler - CPU performance analysis
- Allocations - Memory usage tracking
- Leaks - Memory leak detection
- Network - API calls and network activity
- Animation Hitches - UI performance issues
3. Run Performance Analysis
Standard workflow:
DEVICE_UUID="F464E766-555C-4B95-B8CC-763702A70791" # this is sample uuid, run command line to get exist uuid
xcrun simctl uninstall $DEVICE_UUID <bundle id>
xcrun simctl install $DEVICE_UUID /path/to/<app name>.app
sleep 2
xcrun xctrace record --template "App Launch" --device $DEVICE_UUID \
--launch -- /path/to/<app name>.app 2>&1
Important notes:
- Trace files auto-generate names like
Launch_<app name>.app_2025-10-30_3.55.40 PM_39E6A410.trace --outputparameter may be ignored; accept auto-generated names- Wait 2 seconds after installation before profiling
- Use
2>&1to capture all output - Recording duration: 10-30s for launch, 2-5m for other analyses
4. Analyze Results
Finding trace files:
ls -lt *.trace | head -1 # Most recent trace
find . -name "*.trace" -type d -mmin -5 # Files from last 5 minutes
Analysis approaches:
-
CLI export often fails - "trace is malformed" errors are common
-
Recommended: Open in Instruments.app GUI for reliable analysis
bashopen -a Instruments.app Launch_<app name>*.trace -
Parse signpost markers for performance metrics
-
Identify bottlenecks in launch sequence, memory allocations, CPU hotspots
5. Common Optimization Patterns
Based on successful optimizations:
- Lazy initialization - Defer expensive dependency resolution
- Background operations - Move non-critical setup off main thread
- Deferred bindings - Set up subscriptions after UI appears
- Font loading - Register fonts asynchronously
- Method swizzling - Only essential swizzles during launch
Critical Pitfalls to Avoid
❌ Using device names instead of UUIDs ❌ Skipping clean installation step ❌ Building in Debug mode ❌ Trying to export trace immediately after recording ❌ Assuming --output path will be used ❌ Not waiting between installation and profiling
Reference Documentation
See examples in this skill directory for:
- Detailed command examples with correct syntax
- Complete troubleshooting guide with solutions
- Real-world lessons learned
- Production-ready workflow scripts
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