Vision-driven iOS automation using natural language commands and screenshot analysis.
Works with
Operates entirely from screenshots without requiring DOM access or accessibility labels; can interact with any visible UI element regardless of technology stack
Requires a configured vision model (Gemini, Qwen, Doubao, or similar) via environment variables for AI-powered screen understanding and action execution
Follows a synchronous workflow: connect device, take screenshot, execute actions via nat
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionios-device-automationExecute the skills CLI command in your project's root directory to begin installation:
Fetches ios-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 ios-device-automation. Access via /ios-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 iOS devices using npx @midscene/ios@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 iOS, Midscene can tap, double-tap, long-press, type, clear text, scroll, drag items, zoom with two fingers, press keys, and use system navigation such as Home or the app switcher 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/ios@1 connect
Use the built-in launch capability when you want to start from a known app or route before the rest of the task. Give it the most specific target you have, such as a bundle ID, web URL, deep link, or phone/mail link. Typical targets include com.apple.Preferences, https://www.apple.com, myapp://profile/user/123, and tel:+1234567890.
Use this when the task needs lower-level device control instead of a normal visible UI interaction:
npx @midscene/ios@1 runwdarequest --method GET --endpoint /wda/screen
This does not run an ADB command. On iOS, the underlying operation is an HTTP request to WebDriverAgent, typically GET http://<wdaHost>:<wdaPort>/session/<sessionId>/wda/screen.
npx @midscene/ios@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/ios@1 act --prompt "type hello world in the search field and press Enter"
npx @midscene/ios@1 act --prompt "tap Delete, then confirm in the alert dialog"
# or target-driven instructions
npx @midscene/ios@1 act --prompt "open Settings and navigate to Wi-Fi, 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/ios@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/ios@1 disconnect
Since CLI commands are stateless between invocations, follow this pattern:
act to perform the desired action or target-driven instructions."the Settings icon in the top-right corner" instead of "the icon"."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 check the connected network" 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 — Alert dialog interaction:
npx @midscene/ios@1 act --prompt "tap the Delete button and confirm in the alert dialog"
npx @midscene/ios@1 take_screenshot
Example — Form interaction:
npx @midscene/ios@1 act --prompt "fill in the username field with 'testuser' and the password field with 'pass123', then tap the Login button"
npx @midscene/ios@1 take_screenshot
Symptom: Connection refused or timeout errors. Solution:
Symptom: No device detected or connection errors. Solution:
Symptom: Authentication or model errors. Solution:
.env file contains MIDSCENE_MODEL_API_KEY=<your-key>.@midscene/* Dependency Version OutdatedSymptom: Unexpected behavior, missing features, or version mismatch errors. Solution:
npm ls @midscene/ios @midscene/core @midscene/shared (or pnpm why @midscene/ios).npm view @midscene/ios version, npm view @midscene/core version, npm view @midscene/shared version.npm i @midscene/ios@latest @midscene/core@latest @midscene/shared@latest.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
Useful defaults in ios-device-automation — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
ios-device-automation fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
ios-device-automation is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Useful defaults in ios-device-automation — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
I recommend ios-device-automation for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Keeps context tight: ios-device-automation is the kind of skill you can hand to a new teammate without a long onboarding doc.
Registry listing for ios-device-automation matched our evaluation — installs cleanly and behaves as described in the markdown.
Solid pick for teams standardizing on skills: ios-device-automation is focused, and the summary matches what you get after install.
We added ios-device-automation from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Keeps context tight: ios-device-automation is the kind of skill you can hand to a new teammate without a long onboarding doc.
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