Mac Computer Use
To3akaRin/mac-computer-use
操作 macOS 桌面应用,探测窗口和自动化接口、截图、读取或修改辅助功能元素、执行鼠标键盘动作,以及通过 CDP 操作内嵌 Chromium 页面。适用于桌面应用自动化与界面验收;普通网页任务优先使用已有浏览器工具。
“Control a connected desktop”
$ npx skills add vellum-ai/vellum-assistant --skill computer-use -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install vellum-ai/vellum-assistant computer-use --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/vellum-ai/vellum-assistant.git skills-src && mkdir -p .claude/skills && cp -r skills-src/assistant/src/config/bundled-skills/computer-use .claude/skills/computer-use && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "computer-use" agent skill from https://github.com/vellum-ai/vellum-assistant/tree/main/assistant/src/config/bundled-skills/computer-use into .claude/skills/computer-use/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "computer-use", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/vellum-ai/vellum-assistant/tree/main/assistant/src/config/bundled-skills/computer-useType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add vellum-ai/vellum-assistant --skill computer-use -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install vellum-ai/vellum-assistant computer-use --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/vellum-ai/vellum-assistant.git skills-src && mkdir -p .agents/skills && cp -r skills-src/assistant/src/config/bundled-skills/computer-use .agents/skills/computer-use && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "computer-use" agent skill from https://github.com/vellum-ai/vellum-assistant/tree/main/assistant/src/config/bundled-skills/computer-use into .agents/skills/computer-use/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "computer-use", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add vellum-ai/vellum-assistant --skill computer-use -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install vellum-ai/vellum-assistant computer-use --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/vellum-ai/vellum-assistant.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/assistant/src/config/bundled-skills/computer-use .cursor/skills/computer-use && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "computer-use" agent skill from https://github.com/vellum-ai/vellum-assistant/tree/main/assistant/src/config/bundled-skills/computer-use into .cursor/skills/computer-use/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "computer-use", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/vellum-ai/vellum-assistant.git --path assistant/src/config/bundled-skills/computer-use--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add vellum-ai/vellum-assistant --skill computer-use -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install vellum-ai/vellum-assistant computer-use --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/vellum-ai/vellum-assistant.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/assistant/src/config/bundled-skills/computer-use .gemini/skills/computer-use && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "computer-use" agent skill from https://github.com/vellum-ai/vellum-assistant/tree/main/assistant/src/config/bundled-skills/computer-use into .gemini/skills/computer-use/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "computer-use", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install vellum-ai/vellum-assistant computer-useInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add vellum-ai/vellum-assistant --skill computer-use -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/vellum-ai/vellum-assistant.git skills-src && mkdir -p .github/skills && cp -r skills-src/assistant/src/config/bundled-skills/computer-use .github/skills/computer-use && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "computer-use" agent skill from https://github.com/vellum-ai/vellum-assistant/tree/main/assistant/src/config/bundled-skills/computer-use into .github/skills/computer-use/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "computer-use", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add vellum-ai/vellum-assistant --skill computer-use -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install vellum-ai/vellum-assistant computer-use --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/vellum-ai/vellum-assistant.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/assistant/src/config/bundled-skills/computer-use .opencode/skills/computer-use && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "computer-use" agent skill from https://github.com/vellum-ai/vellum-assistant/tree/main/assistant/src/config/bundled-skills/computer-use into .opencode/skills/computer-use/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "computer-use", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
computer-useComputer Use is a skill in vellum-ai/vellum-assistant (1.4k stars). Its SKILL.md is about 1.5k tokens, with 13 other files in the folder. Licence: MIT.
Read from SKILL.md and the folder at commit 844117a. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Ships script files (TypeScript), which the agent can run.
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Designed for Vellum personal assistants
From compatibility in the SKILL.md frontmatter.
Computer Use loads about 1.5k tokens when it runs. Until then it costs about 10 tokens; SKILL.md has 829 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from vellum-ai/vellum-assistant at commit 844117a, republished under its MIT licence (© vellum-ai). 829 words, ~1,511 tokens.
.claude/skills/computer-use/SKILL.md (or your agent's skills folder). This skill also uses 13 other files; get the full folder from GitHub.This skill provides the computer_use_* action tools for controlling a connected desktop. CU tools run through the main agent loop via HostCuProxy.
The skill is internally preactivated for conversations with a connected desktop client.
Tools in this skill are proxy tools. Execution is forwarded to a connected desktop client or handled by the assistant's virtual desktop.
Every computer-use step returns the accessibility tree. Every action also
returns a screenshot taken after it ran (one at the end of a
computer_use_sequence), so check it to see what your action did. An
observation comes with a screenshot on a desktop's first look, when it is
window-scoped, or when you pass include_screenshot: true. Ask for one whenever
the tree is not enough to act on: a canvas, a game, a custom-drawn view, few or
unlabeled controls, or a layout question.
The tree is walked to a limited depth to keep steps fast, and says when it was
cut off. If the element you need is not in it, call computer_use_observe with
full_tree: true.
Prefer element IDs from the latest observation. Click, scroll and drag coordinates are screen points, not screenshot pixels. For a desktop screenshot, use the per-axis conversion in its observation metadata. If you crop or resize the image, map back to the original screenshot first. Observe again after the layout changes; an older image is not a current target.
During live editing, use the app's zoom and track-height controls, then inspect the fresh screenshot. Avoid installing image libraries or repeatedly cropping and measuring screenshot pixels just to locate a UI control or waveform. Reserve scripted image or media analysis for tasks that actually require it. If an action does not produce the expected visible result, check focus and the coordinate mapping before repeating it.
Waveform pixels do not reveal spoken words. If an edit depends on audio you cannot hear or a boundary you cannot see, ask for a timestamp, a user-positioned playhead, or the source media. Do not guess the cut point or claim an edit succeeded without observing its result.
Reach for computer_use_run_applescript first when an app can be driven by
script. It does not take the cursor.
Try the app's own scripting dictionary before anything else. Ask it for the state you want, not for the clicks that would produce that state. Finder, Mail, Music, Notes, Safari, Terminal and many third-party apps have one, and where there is a dictionary the whole task is usually a sentence with no window to open, no tree to read and nothing to click:
tell application "Finder"
set target of front window to desktop
set current view of front window to list view
set sort column of list view options of front window to name column
end tellSystem Events menu clicking is the fallback, for apps with no dictionary
entry for what you need: click menu item "Split Clip" of menu "Modify" of menu bar 1 inside tell application "System Events" to tell process "iMovie". It is
UI automation in a script's clothes: it still depends on the menu sitting where
you expect and on the app being frontmost. A menu item that needs a selection or
a playhead position does nothing when that context is missing, so set it up
first, and read enabled of menu item when unsure.
Click and type for everything a script cannot reach. host_bash is for shell
commands, not for driving apps.
Pressing enter in a chat, email or form usually sends or submits it, and that cannot be taken back. Send only when the user asked you to send, post or submit. When they asked you to type, write or draft something, type it and stop before pressing enter; tell them it is ready to send.
When you already know the next few actions and none depends on seeing the
result of the one before, send them as one computer_use_sequence call, for
example opening a new window, typing a URL and pressing enter. Act one step at
a time whenever the next action depends on what the screen shows.
computer_use_observe accepts optional capture_window_id, a native macOS
CGWindowID (not a browser tab ID or accessibility element ID). Obtain the ID
from a current native window inventory before using it; never guess one.
The native helper captures that window and its accessibility tree without
including secondary windows, even when another app covers the selected window.
A missing window must not be replaced with a desktop capture.
This is a single observation, not a session-wide privacy boundary: normal
click/type/scroll and other action tools still observe the whole desktop. Do not promise app-only capture for a whole control session.
The desktop must explicitly advertise host_cu_window_capture support on its
connection; the daemon rejects older or unsupported clients before requesting
any capture. Other desktop platforms reject this option.
The screenshot is window-relative, while action coordinates are screen points; do not scale it using full-display dimensions. Prefer accessibility element IDs and ensure the intended window is focused before a later action. Window-scoped observation does not focus the window or confine subsequent input to that app.
© vellum-ai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 13 other files in assistant/src/config/bundled-skills/computer-use of vellum-ai/vellum-assistant.
Open the folder on GitHubat commit 844117a
Computer Use next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Computer Use this skillvellum-ai/vellum-assistant | 1.4k | — | ~1.5k | Automated safety check: Pass | MIT | |
| Mac Computer UseTo3akaRin/mac-computer-use | 1.1k | — | ~495 | Automated safety check: Pass | MIT | |
| Verify Reelrselbach/reel | 118 | — | ~2k | Automated safety check: Pass | Unlicense | |
| Steerdisler/mac-mini-agent | 272 | — | ~2.1k | Automated safety check: Pass | None | |
| Computer Usekunpengtalk/PeakCode | 166 | — | ~2.5k | Automated safety check: Pass | MIT | |
| Openbridge DebugAFK-surf/OpenBridge | 430 | — | ~2.2k | Automated safety check: Pass | MIT |
To3akaRin/mac-computer-use
操作 macOS 桌面应用,探测窗口和自动化接口、截图、读取或修改辅助功能元素、执行鼠标键盘动作,以及通过 CDP 操作内嵌 Chromium 页面。适用于桌面应用自动化与界面验收;普通网页任务优先使用已有浏览器工具。
rselbach/reel
Verify Reel, the macOS menu-bar screen recorder, by launching a disposable app bundle and driving its real UI with Computer Use.
disler/mac-mini-agent
macOS GUI automation CLI. An agent skill from disler/mac-mini-agent.
kunpengtalk/PeakCode
Drive a macOS app through the computer tool — read its accessibility tree, act on elements, and use real input only when the tree cannot reach the target.
AFK-surf/OpenBridge
Debug and validate OpenBridge on a real macOS desktop through mini-machine plus full VNC computer-use.
clacky-ai/openclacky
Drive the desktop — macOS, or the Windows desktop through WSL — when a task needs a native app, dialog, menu bar, file picker or anything the terminal and browser tools cannot reach.
vellum-ai/vellum-assistant
Create and configure a GitHub App so the assistant can push commits, open PRs, and comment under its own bot identity.
vellum-ai/vellum-assistant
Connect a Discord bot to the assistant via the Discord Gateway with guided application creation and intent configuration
vellum-ai/vellum-assistant
Create and configure a Sentry internal integration so the assistant can manage issues, alerts, and releases under its own identity
vellum-ai/vellum-assistant
Ingest a large dataset into memory as a skimmed map. An agent skill from vellum-ai/vellum-assistant.
vellum-ai/vellum-assistant
A skill your agent uses when the user wants to build, scaffold, ship, or edit a Vellum plugin that bundles multiple surfaces (hooks, tools, skills, and more) into one installable package.
vellum-ai/vellum-assistant
Connect a Slack app to the Vellum Assistant via Socket Mode.
Works with
Categories
Run `npx skills add vellum-ai/vellum-assistant --skill computer-use -a claude-code`. Or copy the skill folder (assistant/src/config/bundled-skills/computer-use in vellum-ai/vellum-assistant) into .claude/skills/computer-use in your project. Claude Code loads it when a task matches its description.
Run `npx skills add vellum-ai/vellum-assistant --skill computer-use -a codex`. Or copy the skill folder (assistant/src/config/bundled-skills/computer-use in vellum-ai/vellum-assistant) into .agents/skills/computer-use in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add vellum-ai/vellum-assistant --skill computer-use -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/computer-use, .gemini/skills/computer-use, .github/skills/computer-use and .opencode/skills/computer-use in your project.
Going by SKILL.md and its folder, Computer Use needs TypeScript for the scripts in its folder. Compatibility (from SKILL.md): Designed for Vellum personal assistants.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Computer Use is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 1.5k tokens (SKILL.md is roughly 6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Computer Use: Mac Computer Use (To3akaRin/mac-computer-use, 1.1k stars), Verify Reel (rselbach/reel, 118 stars), Steer (disler/mac-mini-agent, 272 stars) and Computer Use (kunpengtalk/PeakCode, 166 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
vellum-ai (a GitHub organization) maintains it in vellum-ai/vellum-assistant, which has 1,400 GitHub stars. The repository holds 108 skills in this directory. The repository was last updated on October 9, 2026.
Source: vellum-ai/vellum-assistant on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.