According to AlphaMoat, as of 2026-09, Native App Performance has 3,140 downloads and 5 stars — ranked #3,628 of 5,078 AI skills overall, and #461 of 577 in Development.
| Platform | Installs | Downloads | Stars | Comments |
|---|---|---|---|---|
| ClawHub ↗ | 99 | 3.0K | 5 | - |
| SkillHub ↗ | 129 | 3.1K | 5 | — |
Platforms count differently and update at different times.
The workflow uses xctrace to record Instruments traces, extract samples, and symbolicate results to identify performance hotspots without opening the Instruments UI. Traces and symbolication output may expose app internals, file paths, and performance details. Profile only apps and processes you are authorized to inspect, and do not share these artifacts outside approved contexts.
Profile published 2026-10-29
Generated from the skill’s documentation as examples; not results of actual runs.
The counting method changed in 2026-09: skills with the same name are now counted separately by author, and the full catalog is covered. Dashed lines show months before the change; they are not compared with later months, and no growth is computed across the change.
| Month | Downloads | MoM | Stars |
|---|---|---|---|
| 2026-09 | 3.1K | — | 5 |
| 2026-08 | 2.9K | +3.5% | 5 |
| 2026-07 | 2.8K | +7.4% | 5 |
| 2026-06 | 2.6K | +4.5% | 5 |
| 2026-05 | 2.5K | — | 5 |
| 2026-03 | 2.2K | — | 5 |
The author’s original file, shown as plain text without edits or review by AlphaMoat. Links are not clickable; check commands before running them. Fetched 2026-10-23.
--- name: native-app-performance description: 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. --- # 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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Data month: 2026-09 · Downloads, stars and installs are aggregated monthly from public skill registries (ClawHub, SkillHub). See methodology.