lycorp-jp/sim-use is a command-line tool that lets AI agents observe and control iOS simulators, Android emulators, and devices through accessibility information and input actions. It helps agents test mobile applications by reading compact screen descriptions and interacting with named elements, while the catalogue skills and instructions teach agents how to use those capabilities.
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 lycorp-jp/sim-use --skill sim-usegit clone --depth 1 https://github.com/lycorp-jp/sim-useWrote 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/lycorp-jp/sim-use/sim-use)<a href="https://agentmods.dev/skills/lycorp-jp/sim-use/sim-use"><img src="https://agentmods.dev/badge/skills/lycorp-jp/sim-use/sim-use/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/lycorp-jp/sim-use/sim-use"><img src="https://agentmods.dev/badge/skills/lycorp-jp/sim-use/sim-use.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
SkillSpector: 1 finding, up to low
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- low Excessive Agency · line 108 Skill's behavior or capabilities extend beyond its stated purpose. Scope creep allows an agent to perform actions unrelated to its documented functionality, increasing the attack surface.Fix: Limit the skill's scope to its documented purpose. Remove instructions that enable the agent to perform actions outside its stated functionality.
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 | $0.00062 | $0.03504 |
| Opus 5.5 | $0.00025 | $0.01402 |
| Sonnet 5.5 | $0.00012 | $0.00701 |
| Haiku 4.5 | $0.00006 | $0.00350 |
Grade A, and why
sim-use 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 7d 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 — 177 lines — stays where its author put it; the contents beside it link to each section on GitHub.
0. Preflight
Before first interaction with a device, run the preflight check:
python3 scripts/preflight.py --device <UDID>
This verifies sim-use is installed and compatible with the skill, the device is reachable, and the daemon is healthy. If you don't have the script, do the checks manually:
sim-use --version— confirm sim-use is on PATH and supports the skill's documented commands.sim-use devices— confirm the target device is listed and booted/connected.sim-use ui --device <UDID>— confirm you can read the screen.
A WARN UI content line still passes preflight: the read works, but the outline can miss app controls. See the Pitfalls index.
--device is optional when only one simulator is booted or one daemon is running. For Android, run sim-use android init --device <serial> once to install the bridge APK. Attached physical iPhones/iPads appear in sim-use devices with kind physical and route through the top-level verbs too — but only ui, selector-based tap and screenshot; every other verb rejects on that target. See Physical iOS devices below before driving one. A Linux build of sim-use drives Android only: sim-use ios …, record-video / stream-video, viewer and init are absent there, every verb needs --device <serial>, and sim-use devices lists Android devices only.
1. The observe-act loop
Every interaction follows the same cycle: observe → act → verify.
Observe
sim-use ui --device <UDID>
Read the outline. Each element has an @N alias and optionally a #<id> identifier. List cells carry #N (dominant list) or #N@M (scoped).
Frames in the JSON output (--json: entries[].frame, screen) are in platform-native units — iOS points, Android pixels. Key off the envelope's platform field before doing math on coordinates across platforms. Always pair --json with --no-raw — see Keeping output small below.
Act
Pick a selector, in order of preference:
What ships with it
5 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.
- 7d ago Changed · +1 lines 1db81cb3bdeb
- 8d ago Changed 7a8bb04e189d
- 15d ago Changed · +3 lines b056e9d130cc
- 1mo ago Changed 4027d3b9c361
- 1mo ago Changed db8e72866ea7
- 1mo ago First seen · 173 lines · 62 tokens per session scan A 567eb039f992
sim-use is a skill published in the GitHub repository lycorp-jp/sim-use (1,425 stars, last pushed today), licensed Apache-2.0. It adds 62 tokens to every session and 3,504 once invoked, about $0.0002 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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