ios-ettrace-performance
Capture and interpret iOS Simulator ETTrace profiles. Use when profiling launch or runtime latency, comparing traces, or finding CPU-heavy stacks.
Savant verdict: Review advised
SkillSpector or the source hub flagged patterns to review before use.
Live evaluation
55overall
57quality
39compliance
76grounding
61actionability
49efficiency
Why this score may understate the skillThe live evaluation is a chat-only run: the model follows the skill's instructions but can't execute its scripts, call tools or reach the network.
- Ships 2 scripts the live run can't execute; outputs describe those steps rather than perform them.
0 pass · 2 investigate · 5 fail across 7 cases. Jev accepted 7 of 17 LLM-drafted cases. Drafted and run by nvidia/nemotron-3-super-120b-a12b, validated and scored by jev-latest.
- Measure the CPU cost of tapping the 'Refresh' button in my news app's feed screen to see if JSON parsing is blocking the main thread for more than 16ms.positive case · fail
- Run ETTrace on my app to find any performance issues.edge case · fail
- Use ETTrace to profile my iOS app on a physical device to check for battery drain during GPS usage.negative case · investigate
- Generate a flamegraph for my Android app's startup time using ETTrace.negative case · investigate
- Measure the CPU cost of switching from the drafts list to the editor screen in my note-taking app to see if Core Data saving is blocking the main thread during the transition.positive case · fail
- Profile the launch of my iOS app in the simulator using ETTrace to see why it feels slow, but I don't have a built .app file yet and I'm not sure if I should build for simulator or device.edge case · fail
- Capture an ETTrace trace of my app's login flow in the simulator, but I'm not sure whether to use --launch or just start ETTrace manually after navigating to the login screen.edge case · fail
Safety (NVIDIA SkillSpector)
Risk score
34/100
Recommendation
CAUTION
Severity
MEDIUM
Savant decision
Review advised
SkillSpector rated it CAUTION with a risk score of 20/100 or more; review the findings before use. SkillSpector 2.12.0, static analysis.
7 patterns found
- Tool Misuse: rm -rf "$RUN_DIR/ETTrace-iphonesimulator.xcarchive"high · SKILL.md:63 · Tool parameters are crafted to achieve unintended or unsafe behavior. Parameter abuse can bypass intended safety checks (e.g. shell=True, --force, dangerous glob patterns).
- Rogue Agent: Plistmedium · SKILL.md:120 · Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.
- Rogue Agent: Plistmedium · scripts/collect_ios_dsyms.sh:104 · Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.
- Rogue Agent: plistmedium · SKILL.md:120 · Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.
- Rogue Agent: plistmedium · SKILL.md:138 · Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.
- Rogue Agent: plistmedium · scripts/collect_ios_dsyms.sh:103 · Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.
- Rogue Agent: plistmedium · scripts/collect_ios_dsyms.sh:104 · Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.
Structure
- Ships 2 executable scriptsscripts/analyze_flamegraph_json.py, scripts/collect_ios_dsyms.sh. Review what they do before enabling the skill for agents with tool access.
- No license declaredConfirm you may reuse this skill before importing it into your repository.
SKILL.md
---
name: ios-ettrace-performance
description: Capture and interpret iOS Simulator ETTrace profiles. Use when profiling launch or runtime latency, comparing traces, or finding CPU-heavy stacks.
---
# iOS ETTrace Performance
Use this skill to capture a focused, symbolicated ETTrace profile from an iOS simulator app. Pair it with `../ios-debugger-agent/SKILL.md` when the task also needs simulator build, install, launch, UI driving, logs, or screenshots.
## Core Workflow
1. Pick one focused flow and write down the expected start and stop points.
2. Build the exact simulator app that will be installed and profiled.
3. Temporarily link ETTrace into that app target for simulator/debug profiling.
4. Collect UUID-matched dSYMs for the app executable and embedded dynamic frameworks.
5. Capture one launch or runtime trace.
6. Preserve the processed flamegraph JSON immediately after the run.
7. Analyze only the processed JSON and report the flow, artifacts, hotspots, and caveats.
Avoid broad "use the app for a while" captures. One trace should correspond to one user-visible flow.
## Setup
Use a writable run folder for each profiling session:
```bash
if [ -z "${RUN_DIR:-}" ]; then
RUN_DIR="$(mktemp -d "${TMPDIR:-/tmp}/codex-ios-ettrace.XXXXXX")"
fi
mkdir -p "$RUN_DIR"
```
Install the ETTrace runner CLI if it is not already available:
```bash
brew install emergetools/homebrew-tap/ettrace
```
`ettrace` is the host-side macOS runner. The app must also link an `ETTrace.xcframework` for the iOS Simulator architecture.
This workflow is validated for ETTrace v1.1.0 processed `output_<thread>.json` files with top-level `nodes`.
## Link ETTrace Into The App
Wire ETTrace into the exact app target being profiled. Keep the integration in a clearly temporary patch and remove it when the profiling task is done unless the user explicitly asks to keep it.
Preferred options:
- Reuse an existing simulator-compatible `ETTrace.xcframework` if the repo already vendors one.
- If none exists, build a simulator-only copy into `RUN_DIR` from the upstream ETTrace package.
- Link the framework directly into the app target, not only into tests, resources, data files, or a nested launcher target.
- Confirm launch logs print `Starting ETTrace`.
- Profile only one ETTrace-instrumented simulator app at a time because simulator mode listens on a fixed localhost port.
Build a simulator framework when needed:
```bash
ETTRACE_TAG="${ETTRACE_TAG:-v1.1.0}" # Override to match the installed runner when Homebrew updates.
ETTRACE_SRC="$RUN_DIR/ETTrace-src"
if [ ! -d "$ETTRACE_SRC" ]; then
git clone --depth 1 --branch "$ETTRACE_TAG" https://github.com/EmergeTools/ETTrace "$ETTRACE_SRC"
fi
rm -rf "$RUN_DIR/ETTrace-iphonesimulator.xcarchive" "$RUN_DIR/ETTrace.xcframework"
pushd "$ETTRACE_SRC" >/dev/null
xcodebuild archive \
-scheme ETTrace \
-archivePath "$RUN_DIR/ETTrace-iphonesimulator.xcarchive" \
-sdk iphonesimulator \
-destination 'generic/platform=iOS Simulator' \
BUILD_LIBRARY_FOR_DISTRIBUTION=YES \
INSTALL_PATH='Library/Frameworks' \
SKIP_INSTALL=NO \
CLANG_CXX_LANGUAGE_STANDARD=c++17
xcodebuild -create-xcframework \
-framework "$RUN_DIR/ETTrace-iphonesimulator.xcarchive/Products/Library/Frameworks/ETTrace.framework" \
-output "$RUN_DIR/ETTrace.xcframework"
popd >/dev/null
```
For Bazel apps, a temporary import usually looks like:
```python
load("@rules_apple//apple:apple.bzl", "apple_dynamic_xcframework_import")
package(default_visibility = ["//visibility:public"])
apple_dynamic_xcframework_import(
name = "ETTrace",
xcframework_imports = glob(["ETTrace.xcframework/**"]),
)
```
For Xcode projects, temporarily add the simulator `ETTrace.xcframework` to the app target's Link Binary With Libraries / Embed Frameworks phases for the debug simulator build you are profiling, then remove that wiring after profiling.
## Symbolication Gate
Do not draw conclusions from an unsymbolicated flamegraph. Before every capture, prepare a dSYM folder that includes the app dSYM and any embedded first-party dynamic framework dSYMs.
Collect dSYMs after the final build that produced the installed app:
```bash
SKILL_DIR="<absolute path to this loaded skill folder>"
APP="<path-to-built-simulator-App.app>"
DSYMS="$RUN_DIR/dsyms"
"$SKILL_DIR/scripts/collect_ios_dsyms.sh" \
--app "$APP" \
--out-dir "$DSYMS" \
--search-root "$(dirname "$APP")" \
--search-root "$PWD" \
--extra-dsym "$RUN_DIR/ETTrace-iphonesimulator.xcarchive/dSYMs/ETTrace.framework.dSYM"
```
Add `--require-framework <FrameworkName>` for app-owned dynamic frameworks that must symbolicate; use `--require-all-frameworks` only when every embedded framework is app-owned or expected to have symbols. If the helper reports a missing required app or framework dSYM, rebuild the exact simulator app with dSYM generation before tracing, or add the build output directory that contains those dSYMs as another `--search-root`.
Verify important UUIDs before tracing when the report looks suspicious:
```bash
dwarfdump --uuid "$APP/$(/usr/libexec/PlistBuddy -c 'Print :CFBundleExecutable' "$APP/Info.plist")"
find "$DSYMS" -maxdepth 1 -type d -name '*.dSYM' -print -exec dwarfdump --uuid {} \;
```
After ETTrace exits, read its symbolication summary. Treat meaningful first-party "have library but no symbol" lines as a failed trace unless they are tiny noise. Unsymbolicated system-framework or ETTrace internal buckets are usually acceptable.
## Capture
For launch traces:
```bash
cd "$RUN_DIR"
CAPTURE_MARKER="$RUN_DIR/.ettrace-capture-start"
: > "$CAPTURE_MARKER"
find "$RUN_DIR" -maxdepth 1 \( -name 'output.json' -o -name 'output_*.json' \) -delete
ettrace --simulator --launch --verbose --dsyms "$DSYMS"
```
Use `--launch` only when measuring startup or first render. The first launch connection can force quit the app; relaunch from the simulator home screen rather than Xcode if prompted. For first-launch-after-install traces, temporarily set `ETTraceRunAtStartup=YES` in the app Info.plist, then run `ettrace --simulator` and launch from the home screen.
For runtime flow traces:
```bash
cd "$RUN_DIR"
CAPTURE_MARKER="$RUN_DIR/.ettrace-capture-start"
: > "$CAPTURE_MARKER"
find "$RUN_DIR" -maxdepth 1 \( -name 'output.json' -o -name 'output_*.json' \) -delete
ettrace --simulator --verbose --dsyms "$DSYMS"
```
Start from a stable screen, start ETTrace, perform exactly one focused flow, wait until visible work is complete, then stop the runner. For wider attribution, add `--multi-thread`; otherwise start with the main thread.
In Codex, run `ettrace` with a TTY and answer prompts with `write_stdin`. Without a TTY, the runner can exit without a useful trace.
## Preserve Outputs
The next ETTrace run can overwrite processed flamegraph files, so preserve fresh `output_<thread-id>.json` files immediately. Do not analyze a saved `output.json`; ETTrace also serves a viewer route with that name, and raw `emerge-output/output.json` files are not the processed flamegraph artifacts this workflow expects.
```bash
PRESERVED_DIR="$(mktemp -d "$RUN_DIR/run-$(date +%Y%m%d-%H%M%S).XXXXXX")"
: > "$PRESERVED_DIR/summary.txt"
if [ ! -e "$CAPTURE_MARKER" ]; then
echo "error: capture marker missing; start a fresh ETTrace capture before preserving outputs" >&2
exit 1
fi
find "$RUN_DIR" -maxdepth 1 -name 'output_*.json' -newer "$CAPTURE_MARKER" -print | while IFS= read -r json; do
preserved="$PRESERVED_DIR/${json##*/}"
cp "$json" "$preserved"
{
echo "## ${preserved##*/}"
python3 "$SKILL_DIR/scripts/analyze_flamegraph_json.py" "$preserved"
} >> "$PRESERVED_DIR/summary.txt"
done
if [ ! -s "$PRESERVED_DIR/summary.txt" ]; then
echo "error: no fresh processed ETTrace output JSON found in $RUN_DIR" >&2
exit 1
fi
```
Analyze only processed `output_*.json` files in `RUN_DIR`. Ignore `output.json` and raw `emerge-output/output.json` files unless debugging ETTrace itself. If the analyzer rejects the JSON shape, capture again with the Homebrew ETTrace runner and matching app-side `ETTrace.xcframework` tag instead of trying to interpret the rejected file.
## Read The Profile
Start from `run-*/summary.txt`, then inspect processed JSON directly if needed.
Report:
- exact flow, app build, simulator model/runtime, and run count
- processed flamegraph JSON paths
- top active leaves and inclusive first-party stacks with sample weights or percentages
- whether symbols were complete for app-owned binaries
- caveats such as first-run setup, simulator-only cost, network variance, or low sample count
- before/after deltas only when the same flow was captured with comparable setup
## Cleanup
Remove temporary ETTrace app wiring when profiling is complete unless the user asked to keep it. Keep or discard run artifacts based on the active task.