desktop-computer-automation

安装量: 944
排名: #1394

安装

npx skills add https://github.com/web-infra-dev/midscene-skills --skill desktop-computer-automation

Desktop Computer 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 act commands 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. Control your desktop (macOS, Windows, Linux) using npx @midscene/computer@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. 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 Desktop npx @midscene/computer@1 connect npx @midscene/computer@1 connect --displayId < id

List Displays npx @midscene/computer@1 list_displays Take Screenshot npx @midscene/computer@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 computer and get the result. It autonomously handles all UI interactions internally — clicking, typing, scrolling, 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/computer@1 act --prompt "type hello world in the search field and press Enter" npx @midscene/computer@1 act --prompt "drag the file icon to the Trash"

or target-driven instructions

npx @midscene/computer@1 act
--prompt
"search for the weather in Shanghai using the Chrome browser, tell me the result"
Disconnect
npx @midscene/computer@1 disconnect
Workflow Pattern
Since CLI commands are stateless between invocations, follow this pattern:
Connect
to establish a session
Health check
— observe the output of the
connect
command. If
connect
already performed a health check (screenshot and mouse movement test), no additional check is needed. If
connect
did not perform a health check, do one manually: take a screenshot and verify it succeeds, then move the mouse to a random position (
act --prompt "move the mouse to a random position"
) and verify it succeeds. If either step fails, stop and troubleshoot before continuing. Only proceed to the next steps after both checks pass without errors.
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
act
to perform the desired action or target-driven instructions.
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
Always run a health check first
After connecting, observe the output of the
connect
command. If
connect
already performed a health check (screenshot and mouse movement test), no additional check is needed. If it did not, do one manually: take a screenshot and move the mouse to a random position. Both must succeed (no errors) before proceeding with any further operations. This catches environment issues early.
Bring the target app to the foreground before using this skill
For best efficiency, bring the app to the foreground using other means (e.g.,
open -a
on macOS,
start
on Windows)
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. Avoid using Spotlight, Start menu search, or other launcher-based approaches through midscene — they involve transient UI, multiple AI inference steps, and are significantly slower.
Be specific about UI elements
Instead of vague descriptions, provide clear, specific details. Say
"the red close button in the top-left corner of the Safari window"
instead of
"the close button"
.
Describe locations when possible
Help target elements by describing their position (e.g.,
"the icon in the top-right corner of the menu bar"
,
"the third item in the left sidebar"
).
Never run in background
Every midscene command must run synchronously — background execution breaks the screenshot-analyze-act loop.
Check for multiple displays
If you launched an app but cannot see it on the screenshot, the app window may have opened on a different display. Use
list_displays
to check available displays. You have two options: either move the app window to the current display, or use
connect --displayId
to switch to the display where the app is.
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, "search for X, click the first result, and scroll down to see more details" should be a single
act
call, not three. This reduces round-trips, avoids unnecessary screenshot-analyze cycles, and is significantly faster.
Set up
PATH
before running (macOS)
On macOS, some commands (e.g.,
system_profiler
) may not be found if the
PATH
is incomplete. Before running any midscene commands, ensure the
PATH
includes the standard system directories:
export
PATH
=
"/usr/sbin:/usr/bin:/bin:/sbin:
$PATH
"
This prevents screenshot failures caused by missing system utilities.
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. Example — Context menu interaction: npx @midscene/computer@1 act --prompt "right-click the file icon and select Delete from the context menu" npx @midscene/computer@1 take_screenshot Example — Dropdown menu: npx @midscene/computer@1 act --prompt "open the File menu and click New Window" npx @midscene/computer@1 take_screenshot Troubleshooting macOS: Accessibility Permission Denied Your terminal app does not have Accessibility access: Open System Settings > Privacy & Security > Accessibility Add your terminal app and enable it Restart your terminal app after granting permission macOS: Xcode Command Line Tools Not Found xcode-select --install API Key Not Set Check .env file contains MIDSCENE_MODEL_API_KEY= . macOS: Screenshot Fails with system_profiler Not Found If take_screenshot fails with an error like system_profiler: command not found , the PATH environment variable is likely incomplete. Fix it by running: export PATH = "/usr/sbin:/usr/bin:/bin:/sbin: $PATH " Then retry the screenshot command. AI Cannot Find the Element Take a screenshot to verify the element is actually visible Use more specific descriptions (include color, position, surrounding text) Ensure the element is not hidden behind another window
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