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Vision-driven browser automation using Midscene. Operates from screenshots — no DOM or…
Vision-driven Android device automation using Midscene. Operates entirely from screenshots — no DOM or accessibility labels required. Can interact with all visible elements on screen regardless of technology stack. Control Android devices with natural language commands via ADB.
$ npx -y skills add web-infra-dev/midscene-skills --skill android-automation --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/android-automationContext preview
The summary Claude sees to decide when to auto-load this skill.
Vision-driven Android device automation using Midscene. Operates entirely from screenshots — no DOM or accessibility labels required. Can interact with all visible elements on screen regardless of technology stack. Control Android devices with natural language commands via ADB.
name: android-device-automation description: > Vision-driven Android device automation using Midscene. Operates entirely from screenshots — no DOM or accessibility labels required. Can interact with all visible elements on screen regardless of technology stack. Control Android devices with natural language commands via ADB. Perform taps, swipes, text input, app launches, screenshots, and more. Trigger keywords: android, phone, mobile app, tap, swipe, install app, open app on phone, android device, mobile automation, adb, launch app, mobile screen, test android app, verify mobile app, QA on phone, check the app on android, test on device, see if the app works on phone, end-to-end test on android, visual verification on mobile Powered by Midscene.js (https://midscenejs.com) allowed-tools: - Bash
> **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 -y @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.
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.
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](https://midscenejs.com/model-common-config) for supported providers.
Use these flags on commands that create or use the Android agent, such as `connect`, `take_screenshot`, `act`, `assert`, and `tap`:
npx -y @midscene/android@1 connect npx -y @midscene/android@1 connect --device-id emulator-5554 npx -y @midscene/android@1 connect --device-id emulator-5554 --use-scrcpy
Use the dedicated launch step when you want a deterministic starting point before the rest of the task:
npx -y @midscene/android@1 launch --uri https://www.ebay.com npx -y @midscene/android@1 launch --uri com.android.settings npx -y @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 -y @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 -y @midscene/android@1 take_screenshot npx -y @midscene/android@1 take_screenshot --device-id emulator-5554 --use-scrcpy
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 a
Vision-driven cross-platform automation Natural-language driven UI control Built on Midscene.js's vision-based automation capabilities — Operates entirely from screenshots, making cross-platform support reliable This repository contains Skills for the
Repo: web-infra-dev/midscene-skills
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