ios-device-automation
web-infra-dev/midscene-skills
Vision-driven iOS device automation using natural language commands and screenshots.
What is ios-device-automation?
Automate iOS devices entirely from screenshots using Midscene CLI, with no DOM or accessibility labels required. Control iPhones and iPads by describing actions in natural language, and verify app behavior through visual assertions. Use this for end-to-end testing, QA validation, and app automation across any iOS app regardless of technology stack.
- Tap, swipe, type, and scroll on iOS devices using natural language commands
- Take screenshots and analyze current screen state before deciding next actions
- Perform complex multi-step interactions like opening apps, navigating menus, and filling forms
- Assert that the screen matches expected conditions for QA and validation
- Launch apps, URLs, and deep links to start automation from known states
- Send low-level WebDriverAgent requests for advanced device control
How to install ios-device-automation
npx skills add https://github.com/web-infra-dev/midscene-skills --skill ios-device-automation- WebDriverAgent running on the iOS device or simulator
- Vision-capable AI model configured via environment variables (Gemini, Qwen, Doubao, or Zhipu GLM)
- API key and model configuration for the chosen provider (MIDSCENE_MODEL_API_KEY, MIDSCENE_MODEL_NAME, MIDSCENE_MODEL_BASE_URL, MIDSCENE_MODEL_FAMILY)
- Node.js and npx available in the environment
How to use ios-device-automation
- 1.Set up environment variables for your AI model (API key, model name, base URL, family)
- 2.Run `npx -y @midscene/ios@1 connect` to establish a WebDriverAgent session with the iOS device
- 3.Take a screenshot with `npx -y @midscene/ios@1 take_screenshot` to see the current screen state
- 4.Use `npx -y @midscene/ios@1 act --prompt "<action>"` to perform interactions (tap, type, scroll, navigate)
- 5.Use `npx -y @midscene/ios@1 assert --prompt "<condition>"` to verify the screen matches expected state
- 6.Repeat screenshot → analyze → act cycle until the task is complete, then report results to the user
Use cases
- End-to-end testing of iOS apps across different device states and user flows
- Visual verification and QA checks to confirm app behavior matches requirements
- Automated app navigation and data entry for testing login, forms, and workflows
- Screenshot-based regression testing to detect visual or functional changes
- Testing app behavior on different iOS versions or device types
- QA engineers and testers validating iOS app functionality
- Mobile app developers automating integration and end-to-end tests
- CI/CD pipelines requiring visual verification of iOS apps
- Teams needing screenshot-based testing without modifying app code
ios-device-automation FAQ
Midscene works with vision-capable models including Gemini-3-Flash, Gemini-3-Pro, Qwen 3.5, Doubao Seed 2.0 Lite, and Zhipu GLM-4.6V. Any model configured with a compatible API endpoint can be used.
Yes. Midscene operates entirely from screenshots and can interact with any visible element on screen, regardless of the app's technology stack or whether accessibility labels are present.
Most commands take about 1 minute due to AI inference and screen interaction. Complex `act` commands may take longer. Commands must run synchronously so you can read the screenshot before deciding the next action.
No. Each command must run synchronously and complete before the next one starts. Running commands in the background or chaining them breaks the screenshot-analyze-act loop that Midscene relies on.
The `act` command can tap, double-tap, long-press, type, clear text, scroll, drag items, zoom with two fingers, press keys, and use system navigation like Home or the app switcher — all from a single natural language instruction.
Full instructions (SKILL.md)
Source of truth, from web-infra-dev/midscene-skills.
name: ios-device-automation description: | Vision-driven iOS device automation using Midscene CLI. Operates entirely from screenshots — no DOM or accessibility labels required. Can interact with all visible elements on screen regardless of technology stack. Control iOS devices with natural language commands via WebDriverAgent.
Triggers: ios, iphone, ipad, ios app, tap on iphone, swipe, mobile app ios, ios device, ios testing, iphone automation, ipad automation, ios screen, ios navigate, test ios app, verify on iphone, QA on ipad, check the app on ios, test on ios device, see if the app works on iphone, end-to-end test on ios, visual verification on ios
Powered by Midscene.js (https://midscenejs.com) allowed-tools:
- Bash
iOS Device Automation
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 -y @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.
What act Can Do
Inside 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.
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 -y @midscene/ios@1 connect
If WebDriverAgent is already running and the session was created outside Midscene, pass the WDA endpoint and external session ID together:
npx -y @midscene/ios@1 connect --wda-host 127.0.0.1 --wda-port 8100 --session-id <sessionId>
Use the same --wda-host, --wda-port, and --session-id options on later
commands when you want them to operate through that existing WDA session.
Launch an App, URL, or Deep Link
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.
Send a Direct Device Request
Use this when the task needs lower-level device control instead of a normal visible UI interaction:
npx -y @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.
Take Screenshot
npx -y @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.
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 -y @midscene/ios@1 act --prompt "type hello world in the search field and press Enter"
npx -y @midscene/ios@1 act --prompt "tap Delete, then confirm in the alert dialog"
# or target-driven instructions
npx -y @midscene/ios@1 act --prompt "open Settings and navigate to Wi-Fi, tell me the connected network name"
Assert Current Screen State
Use assert to verify that the current screen satisfies a natural language condition. It does not perform UI actions; it checks the visible screen state and passes only when the assertion is true. Use this for validation, QA checks, and final state verification after act.
npx -y @midscene/ios@1 assert --prompt "there is a login button visible"
npx -y @midscene/ios@1 assert --prompt "the settings screen shows Wi-Fi and Bluetooth options"
By default a failed assertion throws an AI-generated reason. Pass --message to throw a custom error message instead, which is useful for surfacing the intended outcome in QA and CI logs.
npx -y @midscene/ios@1 assert \
--prompt "the order confirmation screen is visible" \
--message "the order should be confirmed after tapping Pay"
When the assertion needs to compare against a reference image (icon, logo, screenshot), pass --image for the URL/path and --image-name for its display name. Each --image may be an http(s) link, a data: URI, or a local file path. Repeat both flags in matching order when you need to attach more than one image. Add --convertHttpImage2Base64 true when the model cannot reach the URL directly. Requires @midscene/ios@1.9.0+.
npx -y @midscene/ios@1 assert \
--prompt "the visible app icon matches the supplied reference image" \
--image "https://github.githubassets.com/assets/GitHub-Mark-ea2971cee799.png" \
--image-name "icon" \
--convertHttpImage2Base64 true
# or with a local file
npx -y @midscene/ios@1 assert \
--prompt "the header on screen matches the local screenshot" \
--image "./fixtures/header.png" \
--image-name "header"
# multiple reference images — pair --image and --image-name by order
npx -y @midscene/ios@1 assert \
--prompt "the screen shows both the app icon and the header" \
--image "./fixtures/icon.png" --image-name "icon" \
--image "./fixtures/header.png" --image-name "header"
Record and Assert Transient UI
Use a recording when the state to verify may disappear before a current-screen assertion runs, such as a toast, loading banner, animation, or transition:
# Terminal 1: keep this foreground command running
npx -y @midscene/ios@1 record start --device-id <udid> \
--output ./submission-observation.json
# Terminal 2, while Terminal 1 records
npx -y @midscene/ios@1 act --device-id <udid> \
--prompt "tap the Submit button"
# Send Ctrl+C to Terminal 1 and wait for the saved-path message, then assert
npx -y @midscene/ios@1 assert --device-id <udid> \
--record ./submission-observation.json \
--prompt "a success toast appeared during submission"
Pass target flags, capture flags, and --output to record start, then wait for Recording. Press Ctrl+C to stop and save. Keep the recorder as a foreground process in its dedicated terminal; never add shell &. Perform the interaction manually or from a second terminal, send Ctrl+C to the recorder, and wait until it prints the saved path before asserting. Recording uses the WDA MJPEG frame source when enabled and otherwise falls back to periodic screenshots. Optional capture flags are --interval-ms, --max-frames, and --watchdog-ms; --max-frames caps sampled frames, and the manifest may contain one additional final representative frame. The default watchdog finalizes and saves the recording after five minutes, while --watchdog-ms 0 disables that safety limit. The output is a JSON manifest plus an adjacent <name>.frames image directory, not an encoded video or archive. The manifest contains relative JPEG/PNG paths and no base64 image bodies. Keep or move the JSON file and image directory together, and pass the JSON path to assert --record. Use ordinary assert without --record when only the current screen matters.
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 -y @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.
Disconnect
npx -y @midscene/ios@1 disconnect
Consume Report Files
The generated HTML report is recommended for human reading first. It includes step-by-step execution details and replay videos for each operation, which makes it much easier to understand what happened and troubleshoot problems.
If another skill or tool needs to consume the report, first convert it with report-tool from the same platform CLI package. Prefer Markdown for LLM-based workflows. Use JSON when the report needs to be processed programmatically.
npx -y @midscene/ios@1 report-tool --action to-markdown --htmlPath ./midscene_run/report/.../index.html --outputDir ./output-markdown
npx -y @midscene/ios@1 report-tool --action split --htmlPath ./midscene_run/report/.../index.html --outputDir ./output-data
Workflow Pattern
Since CLI commands are stateless between invocations, follow this pattern:
- Connect to establish a session
- Launch the target app and take screenshot to see the current state, make sure the app is launched and visible on the screen.
- Execute action using
actto perform the desired action or target-driven instructions. Useassertfor the resulting screen state, or keeprecord start --output ...running in a dedicated terminal during transient-state workflows, stop it with Ctrl+C, and then useassert --record. - Disconnect when done
- 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
- Be specific about UI elements: Instead of vague descriptions, provide clear, specific details. Say
"the Settings icon in the top-right corner"instead of"the icon". - 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"). - Never run in background: Every midscene command must run synchronously — background execution breaks the screenshot-analyze-act loop.
- Batch related operations into a single
actcommand: When performing consecutive operations within the same app, combine them into oneactprompt instead of splitting them into separate commands. For example, "open Settings, tap Wi-Fi, and check the connected network" should be a singleactcall, not three. This reduces round-trips, avoids unnecessary screenshot-analyze cycles, and is significantly faster. - Choose the right verification window: Use
assert --prompt "..."for the current screen. For a toast, banner, animation, or transition, runrecord start --output ...in a dedicated terminal, perform the interaction, stop recording with Ctrl+C, wait for the saved-path message, then pass the artifact toassert --record. - 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.
- Prefer
tap --locatewhen a reference image is provided: If the user shares a screenshot, icon, or logo and wants that exact visual target, usetap --locatewith a multimodallocateJSON object such as{ "prompt": "...", "images": [...] }instead of relying only onact --prompt.
Example — Alert dialog interaction:
npx -y @midscene/ios@1 act --prompt "tap the Delete button and confirm in the alert dialog"
npx -y @midscene/ios@1 take_screenshot
Example — Form interaction:
npx -y @midscene/ios@1 act --prompt "fill in the username field with 'testuser' and the password field with 'pass123', then tap the Login button"
npx -y @midscene/ios@1 take_screenshot
Improve Precision (Deep Locate / Deep Think)
Two optional global flags help when Midscene struggles with a task. Put them anywhere in the command (before or after the sub-command); once set, the relevant operations use them by default, so you don't pass a per-call parameter.
--deep-locate— spends an extra round of visual reasoning to pinpoint the target element. Use it when an action interacts with the wrong spot (location drift / offset). It applies to every operation that locates an element, includingtap --locateand the locating that happens insideact.--deep-think— plansactwith deeper reasoning (richer context and sub-goal decomposition). Use it for complex, multi-stepactinstructions; it only affects planning.
Both trade a little speed for better results, and you can combine them.
# more accurate element location (helps act's internal locating too)
npx -y @midscene/ios@1 act --deep-locate --prompt "tap the small back chevron in the top-left corner"
# deeper planning for a complex, multi-step act
npx -y @midscene/ios@1 act --deep-think --prompt "complete the multi-step signup form and submit"
# combine both
npx -y @midscene/ios@1 act --deep-locate --deep-think --prompt "open Settings, go to Display & Brightness, and turn on Dark Mode"
Troubleshooting
WebDriverAgent Not Running
Symptom: Connection refused or timeout errors. Solution:
- Ensure WebDriverAgent is installed and running on the device.
- If another tool created the WDA session, pass that session explicitly with
--session-idplus the matching--wda-hostand--wda-port. - See https://midscenejs.com/usage-ios.html for setup instructions.
Device Not Found
Symptom: No device detected or connection errors. Solution:
- Ensure the device is connected via USB and trusted.
API Key Issues
Symptom: Authentication or model errors. Solution:
- Check
.envfile containsMIDSCENE_MODEL_API_KEY=<your-key>. - See https://midscenejs.com/zh/model-common-config.html for details.
@midscene/* Dependency Version Outdated
Symptom: Unexpected behavior, missing features, or version mismatch errors. Solution:
- Check local versions:
npm ls @midscene/ios @midscene/core @midscene/shared(orpnpm why @midscene/ios). - Check latest versions:
npm view @midscene/ios version,npm view @midscene/core version,npm view @midscene/shared version. - Upgrade dependencies:
npm i @midscene/ios@latest @midscene/core@latest @midscene/shared@latest.
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