Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/steipete/agent-scripts/instruments-profilingnpx skills add steipete/agent-scripts --skill instruments-profilinggit clone --depth 1 https://github.com/steipete/agent-scriptsWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00025 | $0.00954 |
| Opus 5 | $0.00013 | $0.00477 |
| Sonnet 5 | $0.00005 | $0.00191 |
| Haiku 4.5 | $0.00003 | $0.00095 |
Grade A, and why
instruments-profiling scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Instruments Profiling (macOS/iOS)
Use this skill when the user wants performance profiling or stack analysis for native apps.
Focus: Time Profiler, xctrace CLI, and picking the correct binary/app instance.
Quick Start (CLI)
- List templates:
xcrun xctrace list templates - Record Time Profiler (launch):
xcrun xctrace record --template 'Time Profiler' --time-limit 60s --output /tmp/App.trace --launch -- /path/To/App.app
- Record Time Profiler (attach):
- Launch app yourself, get PID, then:
xcrun xctrace record --template 'Time Profiler' --time-limit 60s --output /tmp/App.trace --attach <pid>
- Open trace in Instruments:
open -a Instruments /tmp/App.trace
Note: xcrun xctrace --help is not a valid subcommand. Use xcrun xctrace help record.
Picking the Correct Binary (Critical)
Gotcha: Instruments may profile the wrong app (e.g., one in /Applications) if LaunchServices resolves a different bundle.
Use these rules:
- Prefer direct binary path for deterministic launch:
xcrun xctrace record ... --launch -- /path/App.app/Contents/MacOS/App
- If launching
.app, ensure it’s the intended bundle:open -n /path/App.app- Verify with
ps -p <pid> -o comm= -o command=
- If both
/Applications/App.appand a local build exist, explicitly target the local build path. - After launch, confirm the process path before trusting the trace.
Command Arguments (xctrace)
--template 'Time Profiler': template name fromxctrace list templates.--launch -- <cmd>: everything after--is the target command (binary or app bundle).--attach <pid|name>: attach to running process.--output <path>:.traceoutput. If omitted, file saved in CWD.--time-limit 60s|5m: set capture duration.--device <name|UDID>: required for iOS device runs.--target-stdout -: stream launched process stdout to terminal (useful for CLI tools).
Exporting Stacks (CLI)
- Inspect trace tables:
xcrun xctrace export --input /tmp/App.trace --toc
- Export raw time-profile samples:
xcrun xctrace export --input /tmp/App.trace --xpath '/trace-toc/run[@number="1"]/data/table[@schema="time-profile"]' --output /tmp/time-profile.xml
- Post-process in a script (Python/Rust) to aggregate stacks.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 90 lines · 25 tokens per session scan A 7b6bdce32c89
instruments-profiling is a skill published in the GitHub repository steipete/agent-scripts (6,590 stars, last pushed today), licensed MIT. It adds 25 tokens to every session and 954 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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