mobile-use-setup
Walks developers through Minitap SDK setup and validates system prerequisites like Python and required environment tools.
Install
mkdir -p .claude/skills/mobile-use-setup && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/6279" && unzip -o skill.zip -d .claude/skills/mobile-use-setup && rm skill.zipInstalls to .claude/skills/mobile-use-setup
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Interactive setup wizard for Minitap mobile-use SDK. USE WHEN user wants to set up mobile automation, configure mobile-use SDK, connect iOS or Android devices, or create a new mobile testing project.Key capabilities
- →Identify hardware platform requirements (iOS/Android)
- →Configure local versus platform-based LLM settings
- →Validate prerequisite software (Python, Appium, libimobiledevice)
- →Initialize project scaffolding for mobile testing
How it works
It runs a series of diagnostic scripts to check for required binary availability (adb, idevice) and guides the user through the dependency installation process.
Inputs & outputs
When to use mobile-use-setup
- →Set up mobile automation for an app
- →Connect physical iOS or Android devices
- →Configure cloud virtual devices
- →Initialize a new mobile testing project
About this skill
Mobile-Use SDK Setup
Set up mobile-use so the agent runs locally against a selected device.
Gather Requirements
Ask only for information not already provided:
- Target: iOS, Android, or both.
- Device path: local physical device/emulator, BrowserStack, or a Minitap cloud device.
- LLM provider: Minitap API, OpenAI, Anthropic, Google, OpenRouter, a local model, or another supported provider.
Check Prerequisites
python3 --version # Requires 3.12+
which uv
# Android local
which adb
adb devices
# iOS simulator
which idb_companion
xcrun simctl list devices
# iOS physical
which idevice_id
which appium
appium driver list
For missing dependencies, use the device-specific reference files in this skill.
Create The Project
uv init <project-name>
cd <project-name>
uv add minitap-mobile-use python-dotenv
cp llm-config.override.template.jsonc llm-config.override.jsonc
Configure the selected provider in llm-config.override.jsonc and put only the required provider keys in .env. Add .env to .gitignore.
Create The Starter
Generate task code that runs the agent locally:
import asyncio
from dotenv import load_dotenv
from minitap.mobile_use.sdk import Agent
from minitap.mobile_use.sdk.builders import Builders
from minitap.mobile_use.sdk.types import AgentProfile
load_dotenv()
async def main() -> None:
profile = AgentProfile(name="default", from_file="llm-config.override.jsonc")
config = Builders.AgentConfig.with_default_profile(profile).build()
agent = Agent(config=config)
try:
await agent.init()
result = await agent.run_task(goal="Your automation goal", name="first-task")
print(result)
finally:
await agent.clean()
if __name__ == "__main__":
asyncio.run(main())
When selected, extend config with the BrowserStack or for_cloud_device(...) builder API.
Verify
Verify the selected device is visible, then run:
uv run python -c "from minitap.mobile_use.sdk import Agent; print('SDK OK')"
uv run python main.py
Diagnose setup failures from actual command output. Do not silently switch device paths.
When not to use it
- →If the mobile application does not use Minitap SDK
- →When only web-based testing is required
Prerequisites
Limitations
- →Requires administrative access for installing dependencies
- →Limited by the state of local system drivers
How it compares
It automates the environment validation and project scaffolding sequence rather than relying on generic installation manuals.
Compared to similar skills
mobile-use-setup side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| mobile-use-setup (this skill) | 1 | 8mo | Caution | Beginner |
| dev | 2 | 7mo | Review | Advanced |
| examples-auto-run | 2 | 4mo | Review | Intermediate |
| lora-manager-e2e | 1 | 8mo | Review | Advanced |
Try saying
Example prompts that trigger this skill in your AI assistant.
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