A CLI-first approach to profiling macOS and iOS application performance using xctrace and automated symbolication scripts.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install native-app-performance
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install native-app-performance using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Native App Performance Profiling?
This skill empowers developers to perform deep performance analysis of native Apple applications directly from the terminal. By leveraging the power of Openclaw Skills, you can automate the recording of Time Profiler traces via xctrace, bypass the heavy Instruments UI, and programmatically extract and symbolicate stack traces to identify performance bottlenecks in real-time. It is specifically designed for developers who need to optimize code execution without the overhead of manual GUI interaction.
Native App Performance Profiling Use Cases
- Investigating UI hangs or slow main thread execution in macOS applications.
- Automated performance regression testing within development pipelines using Openclaw Skills.
- Profiling production-intent builds where GUI access is restricted or inefficient.
- Identifying CPU-intensive hotspots in complex iOS application logic and system frameworks.
How Native App Performance Profiling Works
- Initialize the profiling process by either attaching to a running PID or launching the target binary directly using the xctrace utility.
- Record system-level performance data for a specified duration or until a specific interaction is complete to capture the problematic execution path.
- Export the raw .trace file data into a parseable XML format using the included extraction scripts.
- Retrieve the runtime memory load address (ASLR) using vmmap to ensure accurate symbolication of the binary.
- Process the extracted samples through the symbolication engine to map memory addresses back to human-readable source code frames and rank the top hotspots.
Native App Performance Profiling Setup
Ensure you have the Xcode Command Line Tools installed on your macOS environment. You can verify this by running:
xcode-select --install
xcrun xctrace list templates
Integrate the provided scripts into your project to enable Openclaw Skills automation for performance monitoring:
# Example of recording a launch trace
xcrun xctrace record --template 'Time Profiler' --output /tmp/App.trace --launch -- /path/to/YourApp.app/Contents/MacOS/YourApp
Native App Performance Profiling Data Schema & Taxonomy
The skill manages performance data through the following schema:
| Data Component | Description | Format |
|---|---|---|
| Instruments Trace | Raw recording containing system-wide or process-specific events. | .trace package |
| XML Samples | Normalized time-sample data extracted for script processing. | .xml |
| Hotspot Analysis | Symbolicated report ranking the most intensive function calls. | Markdown/Text |
| Memory Maps | Runtime __TEXT segment load addresses for ASLR compensation. | Hex/Text |
Native App Performance Profiling Advanced Features
- Headless profiling support for automated environment integrations using Openclaw Skills.
- Precise time-limit controls to minimize trace file size while capturing critical hotspots.
- Dual-mode operation supporting both active process attachment and clean-launch profiling.
- Direct symbolication using local binaries and dSYM files via the atos utility for maximum accuracy.
SKILL.md
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