Agent Desktop

OrganizationPopular

superagent-ai

agent-desktop

Use the built-in `Computer` sub-agent with `agent-desktop` for macOS desktop automation. Apply when a task needs application launching, accessibility snapshots, stable element refs, window focusing, semantic clicks/typing, or visual confirmation outside the browser sandbox.

Overview

Publisher	superagent-ai
Repository	`grok-cli`
Skill name	`agent-desktop`
Stars	3.5K
Forks	423
Bundled files	Instructions only
License	MIT
Links	Skill source Repository

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.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by superagent-ai on GitHub. Read the source before you install it.

Installation

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

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/superagent-ai/grok-cli/tree/main/.agents/skills/agent-desktop
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.

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/superagent-ai/grok-cli.git /tmp/grok-cli
mkdir -p .claude/skills
cp -r /tmp/grok-cli/.agents/skills/agent-desktop .claude/skills/agent-desktop

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Agent Desktop 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 Agent Desktop 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 Agent Desktop 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.

agent-desktop

Use this skill when the task involves the host macOS desktop rather than repository files, shell output, or browser-only verification.

This project uses agent-desktop on the host. Prefer the built-in Computer sub-agent for these tasks instead of trying to drive the desktop with plain shell commands.

When to use it

The user wants to inspect or interact with a native macOS application.
The task needs app launch, window focus, accessibility snapshots, semantic element refs, clicks, typing, keypresses, or scrolling.
A browser-only workflow is not enough, or the target is not a web page.

Requirements

agent-desktop must be installed and its native binary available.
On macOS, the terminal app running grok needs Accessibility permission.
Refs from computer_snapshot are only valid until the next snapshot.

Preferred flow

Delegate to task with agent: "computer" unless the current agent already has the computer_* tools and the task is tiny.
Use computer_launch, computer_list_windows, or computer_focus_window to get the target app/window ready.
Start with computer_snapshot.
Pick one ref-based action.
After any UI transition, snapshot again before reusing refs.

Tool guidance

computer_snapshot: primary observation tool; prefer interactive_only.
computer_click: use ref values from the latest snapshot whenever possible.
computer_type: requires a target ref and is preferred over coordinate typing.
computer_press: use for shortcuts and special keys such as Enter, Tab, cmd+space, or cmd+k.
computer_scroll: pass an element ref, not raw coordinates.
computer_get: read text, value, bounds, role, or states from a ref.
computer_screenshot: use for visual confirmation or when the accessibility tree is not enough.

Reliability rules

Use a snapshot -> act -> snapshot loop.
Prefer refs over coordinates.
Refs go stale after the next snapshot; do not reuse them blindly.
Keep actions reversible and low risk unless the user explicitly asked for something destructive.
If the accessibility tree is poor or ambiguous, use computer_screenshot for confirmation and explain the limitation.

Blockers

Stop and report clearly if:

Accessibility permission is missing.
agent-desktop is unavailable or its native binary is missing.
The target app/window cannot be found.
Refs are stale or ambiguous after a UI transition.
The requested action could be destructive and the user did not explicitly ask for it.

Frequently asked questions

What does the Agent Desktop AI skill do?

Why use Agent Desktop on TypingMind?

Because you install it once and use it with any model. Agent Desktop 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 Agent Desktop in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/superagent-ai/grok-cli/tree/main/.agents/skills/agent-desktop. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Agent Desktop?

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 Agent Desktop?

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

Is the Agent Desktop AI skill free?

Yes. It is published on GitHub by superagent-ai under the MIT 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

agent-desktop

When to use it

Requirements

Preferred flow

Tool guidance

Reliability rules

Blockers

Frequently asked questions

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