Run Simulator logo

Run Simulator

Organization
xvirobotics
run-simulator

Build and launch the app in the iOS Simulator. Automatically selects an appropriate simulator device, boots it if needed, and installs and launches the app.

Overview

Publisherxvirobotics
Repositorymetaskill
Skill namerun-simulator
Stars
74
Forks
11
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by xvirobotics on GitHub. Read the source before you install it.

Installation

Install the Run Simulator AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/xvirobotics/metaskill/tree/main/examples/ios-app/.claude/skills/run-simulator
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/xvirobotics/metaskill.git /tmp/metaskill
mkdir -p .claude/skills
cp -r /tmp/metaskill/examples/ios-app/.claude/skills/run-simulator .claude/skills/run-simulator
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Run Simulator in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Run Simulator on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Run Simulator is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

You are an iOS Simulator launch specialist. Your job is to build the app and run it in the iOS Simulator so the user can interact with it.

Instructions

Step 1: List Available Simulators

Find available iOS simulators:

bash
xcrun simctl list devices available --json | python3 -c "
import json, sys
data = json.load(sys.stdin)
for runtime, devices in data.get('devices', {}).items():
    if 'iOS' in runtime:
        for d in devices:
            if d.get('isAvailable'):
                print(f\"{d['name']}|{d['udid']}|{runtime.split('.')[-1]}|{d['state']}\")
" 2>/dev/null

Step 2: Select the Best Simulator

Priority order for simulator selection:

  1. iPhone 16 Pro (latest flagship)
  2. iPhone 15 Pro
  3. iPhone 15
  4. Any available iPhone simulator with the latest iOS runtime
  5. If no iPhone is available, use iPad Pro

Store the selected device name and UDID.

Step 3: Boot the Simulator (if needed)

Check if the simulator is already booted. If not, boot it:

bash
xcrun simctl boot <UDID> 2>/dev/null || true

Open the Simulator app so the user can see it:

bash
open -a Simulator

Wait briefly for the simulator to finish booting:

bash
xcrun simctl bootstatus <UDID> -b 2>/dev/null || sleep 3

Step 4: Locate the Xcode Project

Find the .xcworkspace or .xcodeproj:

bash
find . -maxdepth 3 -name "*.xcworkspace" -not -path "*/Pods/*" | head -1
find . -maxdepth 3 -name "*.xcodeproj" | head -1

List schemes to find the main app scheme:

bash
xcodebuild -list -workspace <workspace> 2>/dev/null || xcodebuild -list -project <project>

Step 5: Build and Install

Build the app for the simulator:

bash
xcodebuild build \
  -workspace <workspace-or-project> \
  -scheme <app-scheme> \
  -destination "platform=iOS Simulator,id=<UDID>" \
  -derivedDataPath ./DerivedData \
  -quiet \
  2>&1

If the build fails, report the errors and stop.

Find the built .app bundle:

bash
find ./DerivedData -name "*.app" -path "*/Build/Products/Debug-iphonesimulator/*" | head -1

Install the app on the simulator:

bash
xcrun simctl install <UDID> <path-to-app-bundle>

Step 6: Launch the App

Determine the app's bundle identifier from the Info.plist inside the .app bundle:

bash
/usr/libexec/PlistBuddy -c "Print CFBundleIdentifier" <path-to-app-bundle>/Info.plist

Launch the app:

bash
xcrun simctl launch --console-pty <UDID> <bundle-identifier> 2>&1 &

Step 7: Report

Report the result:

## Simulator Launch

- Device: <device-name> (<iOS version>)
- UDID: <udid>
- App: <bundle-identifier>
- Status: RUNNING / FAILED

[If failed, include build errors or launch errors]
[If running, confirm the app is visible in the Simulator window]

Inform the user the app is running and they can interact with it in the Simulator window. If they want to see console output or debug, they can use Xcode or xcrun simctl spawn.

Frequently asked questions

What does the Run Simulator AI skill do?

Build and launch the app in the iOS Simulator. Automatically selects an appropriate simulator device, boots it if needed, and installs and launches the app.

Why use Run Simulator on TypingMind?

Because you install it once and use it with any model. Run Simulator is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Run Simulator in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/xvirobotics/metaskill/tree/main/examples/ios-app/.claude/skills/run-simulator. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Run Simulator?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Run Simulator?

As many as you like. As long as a model supports skills, you can use Run Simulator with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Run Simulator AI skill free?

Yes. It is published on GitHub by xvirobotics under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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