native-app-performance
Native macOS/iOS app performance profiling via xctrace/Time Profiler and CLI-only analysis of Instruments traces. Use when asked to profile, attach, record, or analyze Instruments .trace files, find hotspots, or optimize native app performance without opening Instruments UI.
Best use case
native-app-performance is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Native macOS/iOS app performance profiling via xctrace/Time Profiler and CLI-only analysis of Instruments traces. Use when asked to profile, attach, record, or analyze Instruments .trace files, find hotspots, or optimize native app performance without opening Instruments UI.
Teams using native-app-performance 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/native-app-performance/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How native-app-performance Compares
| Feature / Agent | native-app-performance | 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?
Native macOS/iOS app performance profiling via xctrace/Time Profiler and CLI-only analysis of Instruments traces. Use when asked to profile, attach, record, or analyze Instruments .trace files, find hotspots, or optimize native app performance without opening Instruments UI.
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
# Native App Performance (CLI-only) Goal: record Time Profiler via `xctrace`, extract samples, symbolicate, and propose hotspots without opening Instruments. ## Quick start (CLI) 1) Record Time Profiler (attach): ```bash # Start app yourself, then attach xcrun xctrace record --template 'Time Profiler' --time-limit 90s --output /tmp/App.trace --attach <pid> ``` 2) Record Time Profiler (launch): ```bash xcrun xctrace record --template 'Time Profiler' --time-limit 90s --output /tmp/App.trace --launch -- /path/App.app/Contents/MacOS/App ``` 3) Extract time samples: ```bash scripts/extract_time_samples.py --trace /tmp/App.trace --output /tmp/time-sample.xml ``` 4) Get load address for symbolication: ```bash # While app is running vmmap <pid> | rg -m1 "__TEXT" -n ``` 5) Symbolicate + rank hotspots: ```bash scripts/top_hotspots.py --samples /tmp/time-sample.xml \ --binary /path/App.app/Contents/MacOS/App \ --load-address 0x100000000 --top 30 ``` ## Workflow notes - Always confirm you’re profiling the correct binary (local build vs /Applications). Prefer direct binary path for `--launch`. - Ensure you trigger the slow path during capture (menu open/close, refresh, etc.). - If stacks are empty, capture longer or avoid idle sections. - `xcrun xctrace help record` and `xcrun xctrace help export` show correct flags. ## Included scripts - `scripts/record_time_profiler.sh`: record via attach or launch. - `scripts/extract_time_samples.py`: export time-sample XML from a trace. - `scripts/top_hotspots.py`: symbolicate and rank top app frames. ## Gotchas - ASLR means you must use the runtime `__TEXT` load address from `vmmap`. - If using a new build, update the `--binary` path; symbols must match the trace. - CLI-only flow: no need to open Instruments if stacks are symbolicated via `atos`.
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