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Mac Use

CommunityPopular
polyuiislab
mac-use

Control macOS GUI apps visually — take screenshots, click, scroll, type. Use when the user asks to interact with any Mac desktop application's graphical interface.

Overview

Publisherpolyuiislab
RepositoryinfiAgent
Skill namemac-use
Stars
1.2K
Forks
47
Bundled files
2
LicenseGPL-3.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by polyuiislab on GitHub. Read the source before you install it.

Installation

Install the Mac Use AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/polyuiislab/infiAgent/tree/main/skills/mac-use
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/polyuiislab/infiAgent.git /tmp/infiAgent
mkdir -p .claude/skills
cp -r /tmp/infiAgent/skills/mac-use .claude/skills/mac-use
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Mac Use in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Mac Use on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Mac Use is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Mac Use

Control any macOS GUI application through a screenshot → pick element → click → verify loop.

Setup

Platform: macOS only (requires Apple Vision framework for OCR)

System binaries (pre-installed on macOS):

  • python3 — via Homebrew (brew install python)
  • screencapture — built-in macOS utility

Python packages — install from the skill directory:

bash
pip3 install --break-system-packages -r {baseDir}/requirements.txt

How It Works

The screenshot command captures a window, uses Apple Vision OCR to detect all text elements, draws numbered annotations on the image, and returns both:

  1. Annotated image at /tmp/mac_use.png — numbered green boxes around each detected text
  2. Element list in JSON — [{num: 1, text: "Submit", at: [500, 200]}, {num: 2, text: "Cancel", at: [600, 200]}, ...] where at is the center point [x, y] on the 1000x1000 canvas (origin at top-left)

You receive both by calling Bash (gets JSON with element list) and then Read on /tmp/mac_use.png (gets the visual). Always do both so you can cross-reference the numbers with what you see.

Quick Reference

bash
# List all visible windows
python3 {baseDir}/scripts/mac_use.py list

# Screenshot + annotate (returns image + numbered element list)
python3 {baseDir}/scripts/mac_use.py screenshot <app> [--id N]

# Click element by number (primary click method)
python3 {baseDir}/scripts/mac_use.py clicknum <N>

# Click at canvas coordinates (fallback for unlabeled icons)
python3 {baseDir}/scripts/mac_use.py click --app <app> [--id N] <x> <y>

# Scroll inside a window
python3 {baseDir}/scripts/mac_use.py scroll --app <app> [--id N] <direction> <amount>

# Type text (uses clipboard paste — supports all languages)
python3 {baseDir}/scripts/mac_use.py type [--app <app>] "text here"

# Press key or combo
python3 {baseDir}/scripts/mac_use.py key [--app <app>] <combo>

Workflow

  1. Open the target app with open -a "App Name" (optionally with a URL or file path)
  2. Wait for it to load: sleep 2
  3. Screenshot the app:
    bash
    python3 {baseDir}/scripts/mac_use.py screenshot <app> [--id N]
    This returns JSON with file (image path) and elements (numbered text list).
  4. Read the annotated image at /tmp/mac_use.png to see the numbered elements visually
  5. Decide which element to interact with:
    • Prefer clicknum N — pick the number of a detected text element
    • Fallback click --app <app> x y — only for unlabeled icons (arrows, close buttons, cart icons) that have no text and therefore no number
  6. Act using clicknum, type, key, or scroll
  7. Screenshot again to verify the result
  8. Repeat from step 3

Commands

list

Show all visible app windows.

bash
python3 {baseDir}/scripts/mac_use.py list

Returns JSON array: [{"app":"Google Chrome","title":"Wikipedia","id":4527,"x":120,"y":80,"w":1200,"h":800}, ...]

screenshot

Capture a window, detect text elements via OCR, annotate with numbered markers, and return the element list. The target window is automatically raised to the top before capture, so overlapping windows are handled.

bash
python3 {baseDir}/scripts/mac_use.py screenshot chrome
python3 {baseDir}/scripts/mac_use.py screenshot chrome --id 4527
  • <app>: fuzzy, case-insensitive match (e.g. "chrome" matches "Google Chrome")
  • --id N: target a specific window ID (required when multiple windows of the same app exist)
  • Returns JSON with:
    • file: path to annotated screenshot (/tmp/mac_use.png)
    • id, app, title, scale: window metadata
    • elements: array of {num, text, at} — the numbered clickable text elements, where at is [x, y] center coordinates on the 1000x1000 canvas (origin at top-left)
  • If multiple windows match, returns a list of windows instead — pick one and retry with --id
  • The image is 1000x1000 pixels with green bounding boxes and blue number badges
  • Element map is saved to /tmp/mac_use_elements.json for clicknum

clicknum

Click on a numbered element from the last screenshot. This is the primary click method.

bash
python3 {baseDir}/scripts/mac_use.py clicknum 5
python3 {baseDir}/scripts/mac_use.py clicknum 12
  • N: the element number from the last screenshot output
  • Reads the saved element map, activates the window, and clicks at the element's center
  • Returns JSON with clicked_num, text, canvas coords, and absolute screen coords

click

Click at a position using canvas coordinates. Fallback only — use for unlabeled icons.

bash
python3 {baseDir}/scripts/mac_use.py click --app chrome 500 300
python3 {baseDir}/scripts/mac_use.py click --app chrome --id 4527 500 300
  • Coordinates are canvas positions (0-1000) from the screenshot image
  • x=0 is left, x=1000 is right; y=0 is top, y=1000 is bottom
  • Use this only when Vision OCR didn't detect the element (icon-only buttons, images, etc.)

scroll

Scroll inside an app window.

bash
python3 {baseDir}/scripts/mac_use.py scroll --app chrome down 5
python3 {baseDir}/scripts/mac_use.py scroll --app notes up 10
  • Directions: up, down, left, right
  • Amount: number of scroll clicks (3-5 for moderate, 10+ for fast scrolling)
  • Mouse is moved to the center of the window before scrolling

type

Type text into the currently focused input field.

bash
python3 {baseDir}/scripts/mac_use.py type --app chrome "hello world"
python3 {baseDir}/scripts/mac_use.py type --app chrome "你好世界"
  • --app: activates the app first to ensure keystrokes go to the right window
  • Uses clipboard paste (Cmd+V) for reliable Unicode/CJK support
  • Always click on the target input field first before typing

key

Press a single key or key combination.

bash
python3 {baseDir}/scripts/mac_use.py key --app chrome return
python3 {baseDir}/scripts/mac_use.py key --app chrome cmd+a
python3 {baseDir}/scripts/mac_use.py key --app chrome cmd+shift+s
  • --app: activates the app first
  • Common keys: return, tab, escape, space, delete, backspace, up, down, left, right
  • Modifiers: cmd, ctrl, alt/opt, shift

Important Rules

  • Always screenshot before your first interaction with an app
  • Always screenshot after an action to verify the result
  • Always Read the screenshot image after running the screenshot command — you need both the element list AND the visual
  • Prefer clicknum over click — only use direct coordinates for unlabeled icons
  • Click before typing — ensure the correct input field has focus first
  • Multiple windows: if you get multiple_windows error, use list to see all windows, then pass --id
  • Popup windows (like WeChat mini-program panels) are separate windows with their own IDs — use list to find them and --id to target them
  • Wait after opening apps: use sleep 2-3 after open -a before taking a screenshot
  • Activate the app before screenshot/click: prepend osascript -e 'tell application "AppName" to activate' && sleep 1 when the target app may be behind other windows
  • Do not type passwords or secrets via this tool

Coordinate System (for fallback click only)

Screenshots are rendered onto a 1000x1000 canvas:

  • Origin (0, 0) is at the top-left corner
  • x increases left to right (0 = left edge, 1000 = right edge)
  • y increases top to bottom (0 = top edge, 1000 = bottom edge)
  • The app window is scaled to fit (aspect ratio preserved), centered, with dark gray padding

Example: Order food on Meituan in WeChat

bash
# 1. Open WeChat
open -a "WeChat"
sleep 3

# 2. Screenshot WeChat — find the mini program window
python3 {baseDir}/scripts/mac_use.py list
# → find the mini program window ID

# 3. Screenshot the mini program (annotated + element list)
python3 {baseDir}/scripts/mac_use.py screenshot 微信 --id 41266
# → returns: {"file": "/tmp/mac_use.png", "elements": [{num: 1, text: "搜索", at: [500, 200]}, ...]}
# → Read /tmp/mac_use.png to see annotated image

# 4. Click "搜索" (element #1)
python3 {baseDir}/scripts/mac_use.py clicknum 1

# 5. Type search query
python3 {baseDir}/scripts/mac_use.py type --app 微信 "炸鸡"

# 6. Press Enter
python3 {baseDir}/scripts/mac_use.py key --app 微信 return
sleep 2

# 7. Screenshot to see results
python3 {baseDir}/scripts/mac_use.py screenshot 微信 --id 41266
# → Read /tmp/mac_use.png, pick a restaurant by number

# 8. Click on a restaurant (e.g. element #5)
python3 {baseDir}/scripts/mac_use.py clicknum 5

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Mac Use AI skill do?

Control macOS GUI apps visually — take screenshots, click, scroll, type. Use when the user asks to interact with any Mac desktop application's graphical interface.

Why use Mac Use on TypingMind?

Because you install it once and use it with any model. Mac Use is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Mac Use in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/polyuiislab/infiAgent/tree/main/skills/mac-use. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Mac Use?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Mac Use?

As many as you like. As long as a model supports skills, you can use Mac Use with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Mac Use AI skill free?

Yes. It is published on GitHub by polyuiislab under the GPL-3.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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