android-device-automation

web-infra-dev/midscene-skills · updated Apr 8, 2026

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$npx skills add https://github.com/web-infra-dev/midscene-skills --skill android-device-automation
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summary

Vision-driven Android automation from screenshots, no DOM access required.

  • 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
skill.md

Android Device Automation

CRITICAL RULES — VIOLATIONS WILL BREAK THE WORKFLOW:

  1. 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.
  2. 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.
  3. 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 act commands may need even longer.
  4. 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.

What act Can Do

Inside 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.

Prerequisites

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.

Commands

Connect to Device

npx @midscene/android@1 connect
npx @midscene/android@1 connect --deviceId emulator-5554

Launch an App or URL

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

Run a Raw Android Shell Command

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.

Take Screenshot

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.

Perform 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"

Use a Reference Image for Precise Targeting

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.

Disconnect

npx @midscene/android@1 disconnect

Workflow Pattern

Since CLI commands are stateless between invocations, follow this pattern:

  1. Connect to establish a session
  2. Launch the target app and take screenshot to see the current state, make sure the app is launched and visible on the screen.
  3. Execute action using act to perform the desired action or target-driven instructions.
  4. Disconnect when done
  5. Report results — summarize what was accomplished, present key findings and data extracted during the task, and list any generated files (screenshots, logs, etc.) with their paths

Best Practices

  1. Bring the target app to the foreground before using this skill: For best efficiency, launch the app using ADB (e.g., 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.
  2. Be specific about UI elements: Instead of vague descriptions, provide clear, specific details. Say "the Wi-Fi toggle switch on the right side" instead of "the toggle".
  3. Describe locations when possible: Help target elements by describing their position (e.g., "the search icon at the top right", "the third item in the list").
  4. Never run in background: Every midscene command must run synchronously — background execution breaks the screenshot-analyze-act loop.
  5. Batch related operations into a single 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.
  6. Always report results after completion: After finishing the automation task, you MUST proactively present the results to the user without waiting for them to ask. This includes: (1) the answer to the user's original question or the outcome of the requested task, (2) key data extracted or observed during execution, (3) screenshots and other generated files with their paths, (4) a brief summary of steps taken. Do NOT silently finish after the last automation command — the user expects complete results in a single interaction.
  7. Prefer 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

Troubleshooting

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.
how to use android-device-automation

How to use android-device-automation on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add android-device-automation
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/web-infra-dev/midscene-skills --skill android-device-automation

The skills CLI fetches android-device-automation from GitHub repository web-infra-dev/midscene-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/android-device-automation

Reload or restart Cursor to activate android-device-automation. Access the skill through slash commands (e.g., /android-device-automation) or your agent's skill management interface.

Security & Verification Notice

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 development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

User Story & Requirements Generation

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

Competitive Analysis

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

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

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

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ 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.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.766 reviews
  • Omar Huang· Dec 28, 2024

    android-device-automation reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Nia Khanna· Dec 24, 2024

    Registry listing for android-device-automation matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Yusuf Singh· Dec 16, 2024

    android-device-automation fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Aditi Taylor· Dec 16, 2024

    Keeps context tight: android-device-automation is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Kofi Kim· Dec 12, 2024

    I recommend android-device-automation for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Dhruvi Jain· Dec 8, 2024

    Keeps context tight: android-device-automation is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Benjamin Huang· Dec 4, 2024

    I recommend android-device-automation for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Oshnikdeep· Nov 27, 2024

    android-device-automation has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Ishan Mehta· Nov 19, 2024

    We added android-device-automation from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Benjamin Menon· Nov 15, 2024

    android-device-automation fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

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