Agent Scripts is a repository of shared instructions, reusable skills, helper scripts, and local safeguards for coding-agent workflows across multiple workspaces. It is for maintaining common agent behavior and portable development utilities between repositories.
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 skills add steipete/agent-scripts --skill native-app-performancegit clone --depth 1 https://github.com/steipete/agent-scriptsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/steipete/agent-scripts/native-app-performance)<a href="https://agentmods.dev/skills/steipete/agent-scripts/native-app-performance"><img src="https://agentmods.dev/badge/skills/steipete/agent-scripts/native-app-performance/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/steipete/agent-scripts/native-app-performance"><img src="https://agentmods.dev/badge/skills/steipete/agent-scripts/native-app-performance.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What 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 5.1 | $0.00020 | $0.00502 |
| Opus 5.5 | $0.00008 | $0.00201 |
| Sonnet 5.5 | $0.00004 | $0.00100 |
| Haiku 4.5 | $0.00002 | $0.00050 |
Grade A, and why
native-app-performance 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 1mo 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.
What it actually says
Native App Performance (CLI-only)
Goal: record Time Profiler via xctrace, extract samples, symbolicate, and propose hotspots without opening Instruments.
Quick start (CLI)
- Record Time Profiler (attach):
# Start app yourself, then attach
xcrun xctrace record --template 'Time Profiler' --time-limit 90s --output /tmp/App.trace --attach <pid>
- Record Time Profiler (launch):
xcrun xctrace record --template 'Time Profiler' --time-limit 90s --output /tmp/App.trace --launch -- /path/App.app/Contents/MacOS/App
- Extract time samples:
scripts/extract_time_samples.py --trace /tmp/App.trace --output /tmp/time-sample.xml
- Get load address for symbolication:
# While app is running
vmmap <pid> | rg -m1 "__TEXT" -n
- Symbolicate + rank hotspots:
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 recordandxcrun xctrace help exportshow 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
__TEXTload address fromvmmap. - If using a new build, update the
--binarypath; symbols must match the trace. - CLI-only flow: no need to open Instruments if stacks are symbolicated via
atos.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 64 lines · 20 tokens per session scan A 0c8a67d976b2
native-app-performance is a skill published in the GitHub repository steipete/agent-scripts (7,379 stars, last pushed yesterday), licensed MIT. It adds 20 tokens to every session and 502 once invoked, about $0.0001 per session on Opus 5.5. 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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