Vision-driven Android automation from screenshots, no DOM access required.
Works with
Operates entirely from device screenshots using AI visual understanding; interacts with any visible UI element regardless of underlying technology stack
Supports taps, swipes, text input, app launches, and complex multi-step interactions via natural language commands
Requires pre-configured vision model (Gemini, Qwen, Doubao, or similar) with API credentials in environment variables
Commands run synchronous
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionandroid-device-automationExecute the skills CLI command in your project's root directory to begin installation:
Fetches android-device-automation from web-infra-dev/midscene-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate android-device-automation. Access via /android-device-automation in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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CRITICAL RULES — VIOLATIONS WILL BREAK THE WORKFLOW:
- Never run midscene commands in the background. Each command must run synchronously so you can read its output (especially screenshots) before deciding the next action. Background execution breaks the screenshot-analyze-act loop.
- Run only one midscene command at a time. Wait for the previous command to finish, read the screenshot, then decide the next action. Never chain multiple commands together.
- Allow enough time for each command to complete. Midscene commands involve AI inference and screen interaction, which can take longer than typical shell commands. A typical command needs about 1 minute; complex
actcommands may need even longer.- Always report task results before finishing. After completing the automation task, you MUST proactively summarize the results to the user — including key data found, actions completed, screenshots taken, and any relevant findings. Never silently end after the last automation step; the user expects a complete response in a single interaction.
Automate Android devices using npx @midscene/android@1. Each CLI command maps directly to an MCP tool — you (the AI agent) act as the brain, deciding which actions to take based on screenshots.
act Can DoInside a single act call on Android, Midscene can tap, double-tap, long-press, type, clear text, scroll or swipe in any direction, pull to refresh, drag items, zoom with two fingers, press keys, and use system navigation such as Back, Home, or recent apps while working from the current visible screen.
Midscene requires models with strong visual grounding capabilities. The following environment variables must be configured — either as system environment variables or in a .env file in the current working directory (Midscene loads .env automatically):
MIDSCENE_MODEL_API_KEY="your-api-key"
MIDSCENE_MODEL_NAME="model-name"
MIDSCENE_MODEL_BASE_URL="https://..."
MIDSCENE_MODEL_FAMILY="family-identifier"
Example: Gemini (Gemini-3-Flash)
MIDSCENE_MODEL_API_KEY="your-google-api-key"
MIDSCENE_MODEL_NAME="gemini-3-flash"
MIDSCENE_MODEL_BASE_URL="https://generativelanguage.googleapis.com/v1beta/openai/"
MIDSCENE_MODEL_FAMILY="gemini"
Example: Qwen 3.5
MIDSCENE_MODEL_API_KEY="your-aliyun-api-key"
MIDSCENE_MODEL_NAME="qwen3.5-plus"
MIDSCENE_MODEL_BASE_URL="https://dashscope.aliyuncs.com/compatible-mode/v1"
MIDSCENE_MODEL_FAMILY="qwen3.5"
MIDSCENE_MODEL_REASONING_ENABLED="false"
# If using OpenRouter, set:
# MIDSCENE_MODEL_API_KEY="your-openrouter-api-key"
# MIDSCENE_MODEL_NAME="qwen/qwen3.5-plus"
# MIDSCENE_MODEL_BASE_URL="https://openrouter.ai/api/v1"
Example: Doubao Seed 2.0 Lite
MIDSCENE_MODEL_API_KEY="your-doubao-api-key"
MIDSCENE_MODEL_NAME="doubao-seed-2-0-lite"
MIDSCENE_MODEL_BASE_URL="https://ark.cn-beijing.volces.com/api/v3"
MIDSCENE_MODEL_FAMILY="doubao-seed"
Commonly used models: Doubao Seed 2.0 Lite, Qwen 3.5, Zhipu GLM-4.6V, Gemini-3-Pro, Gemini-3-Flash.
If the model is not configured, ask the user to set it up. See Model Configuration for supported providers.
npx @midscene/android@1 connect
npx @midscene/android@1 connect --deviceId emulator-5554
Use the dedicated launch step when you want a deterministic starting point before the rest of the task:
npx @midscene/android@1 launch --uri https://www.ebay.com
npx @midscene/android@1 launch --uri com.android.settings
npx @midscene/android@1 launch --uri com.android.settings/.Settings
Use this when the task needs lower-level device control that is not best expressed as a visible UI interaction:
npx @midscene/android@1 runadbshell --command "dumpsys battery"
This is forwarded to adb shell on the connected device. In practice, the underlying command is adb -s <deviceId> shell dumpsys battery and some environments may also include the default ADB server port, such as adb -P 5037 -s <deviceId> shell dumpsys battery.
npx @midscene/android@1 take_screenshot
After taking a screenshot, read the saved image file to understand the current screen state before deciding the next action.
Use act to interact with the device and get the result. It autonomously handles all UI interactions internally — tapping, typing, scrolling, swiping, waiting, and navigating — so you should give it complex, high-level tasks as a whole rather than breaking them into small steps. Describe what you want to do and the desired effect in natural language:
# specific instructions
npx @midscene/android@1 act --prompt "type hello world in the search field and press Enter"
npx @midscene/android@1 act --prompt "long press the message bubble and tap Delete in the popup menu"
# or target-driven instructions
npx @midscene/android@1 act --prompt "open Settings and navigate to Wi-Fi settings, tell me the connected network name"
When the user provides a screenshot, icon, logo, or reference image and wants an exact visual match, prefer tap --locate instead of a generic act --prompt. Pass --locate as JSON. The prompt describes the target, images supplies named reference images, and convertHttpImage2Base64: true is useful when the image URL may not be directly accessible to the model.
npx @midscene/android@1 tap --locate '{
"prompt": "tap the area contains the image",
"images": [
{
"name": "target image",
"url": "https://github.githubassets.com/assets/GitHub-Mark-ea2971cee799.png"
}
],
"convertHttpImage2Base64": true
}'
The same locate JSON shape also works for other commands that accept a locate parameter.
npx @midscene/android@1 disconnect
Since CLI commands are stateless between invocations, follow this pattern:
act to perform the desired action or target-driven instructions.adb shell am start -n <package/activity>) before invoking any midscene commands. Then take a screenshot to confirm the app is actually in the foreground. Only after visual confirmation should you proceed with UI automation using this skill. ADB commands are significantly faster than using midscene to navigate to and open apps."the Wi-Fi toggle switch on the right side" instead of "the toggle"."the search icon at the top right", "the third item in the list").act command: When performing consecutive operations within the same app, combine them into one act prompt instead of splitting them into separate commands. For example, "open Settings, tap Wi-Fi, and toggle it on" should be a single act call, not three. This reduces round-trips, avoids unnecessary screenshot-analyze cycles, and is significantly faster.tap --locate when a reference image is provided: If the user shares a screenshot, icon, or logo and wants that exact visual target, use tap --locate with a multimodal locate JSON object such as { "prompt": "...", "images": [...] } instead of relying only on act --prompt.Example — Popup menu interaction:
npx @midscene/android@1 act --prompt "long press the message bubble and tap Delete in the popup menu"
npx @midscene/android@1 take_screenshot
Example — Form interaction:
npx @midscene/android@1 act --prompt "fill in the username field with 'testuser' and the password field with 'pass123', then tap the Login button"
npx @midscene/android@1 take_screenshot
| Problem | Solution |
|---|---|
| ADB not found | Install Android SDK Platform Tools: brew install android-platform-tools (macOS) or download from developer.android.com. |
| Device not listed | Check USB connection, ensure USB debugging is enabled in Developer Options, and run adb devices. |
| Device shows "unauthorized" | Unlock the device and accept the USB debugging authorization prompt. Then run adb devices again. |
| Device shows "offline" | Disconnect and reconnect the USB cable. Run adb kill-server && adb start-server. |
| Command timeout | The device screen may be off or locked. Wake the device with adb shell input keyevent KEYCODE_WAKEUP and unlock it. |
| API key error | Check .env file contains MIDSCENE_MODEL_API_KEY=<your-key>. See Model Configuration. |
@midscene/* dependency version is outdated |
Check local versions with npm ls @midscene/android @midscene/core @midscene/shared (or pnpm why @midscene/android). Compare with latest versions using npm view @midscene/android version, npm view @midscene/core version, and npm view @midscene/shared version. Upgrade as needed (npm i @midscene/android@latest @midscene/core@latest @midscene/shared@latest). |
| Wrong device targeted | If multiple devices are connected, use --deviceId <id> flag with the connect command. |
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
mattpocock/skills
android-device-automation reduced setup friction for our internal harness; good balance of opinion and flexibility.
Registry listing for android-device-automation matched our evaluation — installs cleanly and behaves as described in the markdown.
android-device-automation fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Keeps context tight: android-device-automation is the kind of skill you can hand to a new teammate without a long onboarding doc.
I recommend android-device-automation for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Keeps context tight: android-device-automation is the kind of skill you can hand to a new teammate without a long onboarding doc.
I recommend android-device-automation for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
android-device-automation has been reliable in day-to-day use. Documentation quality is above average for community skills.
We added android-device-automation from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
android-device-automation fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
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