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 termio-sh/termio --skill ios-app-analysisgit clone --depth 1 https://github.com/termio-sh/termioWrote 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/termio-sh/termio/ios-app-analysis)<a href="https://agentmods.dev/skills/termio-sh/termio/ios-app-analysis"><img src="https://agentmods.dev/badge/skills/termio-sh/termio/ios-app-analysis/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/termio-sh/termio/ios-app-analysis"><img src="https://agentmods.dev/badge/skills/termio-sh/termio/ios-app-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.01315 |
| Opus 5.5 | $0.00025 | $0.00526 |
| Sonnet 5.5 | $0.00012 | $0.00263 |
| Haiku 4.5 | $0.00006 | $0.00131 |
Grade A, and why
ios-app-analysis scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.
iOS app analysis
Investigate a concrete behavior and carry the finding through to a fix when requested. Distinguish the target iOS app, its Mac companion, and Termio: evidence from one does not establish another's implementation.
Establish the running versions
Read the repository's AGENTS.md and check the working tree before editing.
Discover the device and installed app instead of reusing an old device ID or
application path:
xcrun devicectl list devices --json-output /tmp/ios-analysis-devices.json
xcrun devicectl device info apps --device "$device_id" \
--json-output /tmp/ios-analysis-apps.json
uv tool run --from pymobiledevice3 pymobiledevice3 apps query "$bundle_id"
Use the JSON results, filtered to the requested app. Record its bundle ID,
executable, version, build, signing identity, and bundle location. A
builtByDeveloper flag alone does not establish debugger access: Rex's TestFlight
build reported that flag, while its signing identity was TestFlight distribution.
When no device is available, ask for connection/trust or work from an existing artifact. Check command help for the installed tool version. Prefer the existing pairing; don't replace it merely to get logs.
Choose an accessible source of evidence
- For a supplied
.ipaor.app, inspect the bundle and executable directly. Usefile,otool -L,otool -l,nm,swift-demangle, and targetedstringssearches. Check Mach-O encryption information before promising useful disassembly. A decompiler reconstructs approximate code, not the original Swift source. devicectl device copy fromandpymobiledevice3 apps pullexpose supported file domains, usually app data. An installed bundle path from metadata does not make its executable accessible through those domains. If an executable pull returns not-found or denied, report the limit rather than repeating it with invented paths. Look for a local build, an accessible companion, or a user-supplied artifact.- A Mac companion can reveal shared types and wire messages. Label those as Mac-binary findings. Type and field names suggest architecture; they do not prove control flow. Prefer a live API contract or runtime trace to confirm it.
- Use an available REA/decompiler workflow for a relevant accessible binary. Check its installed tools and instructions first. REA does not by itself provide access to an iPhone's app executable. Avoid installing a large tool stack when a protocol query or targeted inspection answers the question.
What ships with it
2 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.
- 4d ago First seen · 120 lines · 62 tokens per session scan A eebf2dab75cc
ios-app-analysis is a skill published in the GitHub repository termio-sh/termio (751 stars, last pushed yesterday), licensed MIT. It adds 62 tokens to every session and 1,315 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 2026-10-31.
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