iOS Simulator Skill for Claude Code is a collection of scripts that helps coding agents build, test, and interact with iOS apps through Xcode and simulator tools. It is intended for developers and agents working on iOS projects, and the catalogue entries provide its plugin, instruction, and skill workflows.
Borrowing it
Nothing to install: this file belongs to conorluddy/ios-simulator-skill. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/conorluddy/ios-simulator-skill/main/AGENTS.mdgit clone --depth 1 https://github.com/conorluddy/ios-simulator-skillWrote 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/instructions/conorluddy/ios-simulator-skill/agents-md)<a href="https://agentmods.dev/instructions/conorluddy/ios-simulator-skill/agents-md"><img src="https://agentmods.dev/badge/instructions/conorluddy/ios-simulator-skill/agents-md/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/instructions/conorluddy/ios-simulator-skill/agents-md"><img src="https://agentmods.dev/badge/instructions/conorluddy/ios-simulator-skill/agents-md.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 | $0.02910 | $0.02910 |
| Opus 5.5 | $0.01164 | $0.01164 |
| Sonnet 5.5 | $0.00582 | $0.00582 |
| Haiku 4.5 | $0.00291 | $0.00291 |
Grade A, and why
ios-simulator-skill AGENTS.md 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 10d 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.
This is a copy
97% identical to ios-simulator-skill CLAUDE.md — 266 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 266 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AGENTS.md - Developer Guide
Canonical guidance for AI coding agents (Codex, Claude Code, and others) and developers working
with this repository. CLAUDE.md only imports this file - edit here, not there.
Project Overview
iOS Simulator Skill is a production-ready Agent Skill providing 30 scripts for iOS app building, testing, and automation. It wraps Apple's xcrun simctl and Facebook's idb tools with semantic interfaces designed for AI agents and developers.
Key Statistics:
- 30 production scripts
- 7 script categories (Build, Device State, Navigation, Testing, Permissions, Simulator Discovery, Lifecycle)
- 7 shared utility modules (~2,400 lines)
- 100% token-optimized default output
- Unit tests under
tests/(runpytest tests/)
Principles
Every script is a tool an agent calls in a loop, so these rules beat convenience. New code and reviews are checked against them.
- Low noise, high signal. An agent-facing message is one line that says what happened and,
on failure, what to do next. No usage dumps, tracebacks or prose. Default output is 3-5 lines;
--verboseand--jsongive more. Cap lists (IOS_SIM_MAX_ELEMENTS) and end them with "... and N more". - Never claim an effect you didn't get. Say how an action was done ("(accessibility press)") and warn when its effect can't be confirmed, e.g. a coordinate tap on a toggle. A wrong "Tapped" costs an agent more than an honest failure.
- Act only on an unambiguous target. idb markers are substring, first-match: only use one when nothing else on screen contains it, otherwise fall back to the safer path.
- Verify against a live simulator before relying on idb behaviour. Upstream publishes no changelog and the docs drift from reality. Ship only what you saw working, and record what you dropped and why.
- Gate features by trying, not by version. Run the command and fall back (or hint at an
upgrade) on failure. Don't add
--helpprobes to hot paths: each costs ~0.35s. - simctl first. It's Apple-maintained, with no companion to break. Use idb only for what simctl can't do (UI interaction, notification list/clear, photos clear).
- Don't change the device silently. Device-wide side effects (e.g. axbridge's automation mode)
sit behind an explicit flag like
--deep, and tests restore whatever they change. - Semantic over pixels. Find elements by meaning via the accessibility tree; coordinates are the last resort.
- One helper per repeated agent-facing message. Shared wording lives in
common/(e.g.with_idb_upgrade_hint) once it appears a third time (AHA), so messages can't drift apart. - Destructive operations need
--yes. Anything that deletes data the user can't easily recreate (erasing or deleting a simulator, uninstalling an app, clearing the photo library) refuses without--yesin one line that says what would be lost, so the agent asks the user first. Never prompt interactively: an agent has no one to answer.
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.
- 10d ago Changed · +8 lines · +462 tokens per session 66fc787a5a14
- 11d ago First seen · 258 lines · 2,448 tokens per session scan A 64d77492d331
ios-simulator-skill AGENTS.md is an instructions file published in the GitHub repository conorluddy/ios-simulator-skill (1,302 stars, last pushed 10d ago), licensed MIT. It adds 2,910 tokens to every session, about $0.0116 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 97% identical to ios-simulator-skill CLAUDE.md, differing in 266 lines, and is treated as a copy.
Other instructions, from other repositories
vscode buildNext.instructions.md
Working notes and architecture documentation for the new esbuild-based build system in build/next. Use when making changes to the new build pipeline (transpile/bundle commands, NLS plugin, source-map handling, resource copying, or self-hosting watch tasks).
next.js AGENTS.md
AGENTS.md instructions for vercel/next.js, covering next.js development guide, codebase structure, monorepo overview, core package: packages/next and other important packages.
vscode oss-third-party-notices.instructions.md
Instructions for microsoft/vscode, covering vs code oss third-party-notices pipeline, architecture, pipeline flow in ci, cache eligibility and rollout and applying the notice (cutover).
langchain AGENTS.md
AGENTS.md instructions for langchain-ai/langchain, covering global development guidelines for the langchain monorepo, corridor security analysis, project architecture and context, monorepo structure and development tools & commands.
vscode copilot-instructions.md
Copilot instructions for microsoft/vscode, covering vs code copilot instructions, project overview, root folders, core architecture (src/ folder) and built-in extensions (extensions/ folder).
deepseek-harness AGENTS.md
AGENTS.md instructions for deepseek-ai/deepseek-harness, covering agents.md, pre-stable apis and released session data, repository layout, commands and host sandbox failures.