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Computer Use

OrganizationPopular
ai4s-research
computer-use

Use when a task needs an app on the user's own screen — a native desktop application (instrument control software, Origin, GraphPad, ImageJ, a reference manager, a spreadsheet), or a desktop browser window that needs window-level control. Read before the first `computer` call. Covers the observe-act-observe loop, why element indexes go stale, which action to prefer for which control, what "unverified" means and why it must never be reported as success, and the recovery for each error code. Not for page-level web automation (use the browser connector) and not for anything that can be done from the shell.

Overview

Publisherai4s-research
Repositoryopen-science
Skill namecomputer-use
Stars
1.7K
Forks
201
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by ai4s-research on GitHub. Read the source before you install it.

Installation

Install the Computer 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.
  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/ai4s-research/open-science.git /tmp/open-science
mkdir -p .claude/skills
cp -r /tmp/open-science/runtime/skills/core/computer-use .claude/skills/computer-use
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Computer 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 Computer 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 Computer 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.

Computer use

computer reads an app's accessibility tree and acts on the numbered elements in it. The tree is the interface; a screenshot is confirmation. This design, and most of the rules below, come from Orca (MIT).

Before anything else

Use this only when there is no better route. A file is read with read, a computation is run in the shell, a web page is driven by the browser connector. Reach for computer when the capability lives in a desktop app and nowhere else.

The user sees a permission prompt on the first call of a session. Say what you intend to do before you make it.

Never push, submit a form, send a message, buy, delete, or change an account setting unless the user asked for that exact thing. If an app holds content the user did not ask about, read only what the task needs.

The loop

computer(action: "list_apps")
computer(action: "get_state", app: "com.spotify.client")
computer(action: "click", app: "com.spotify.client", elementIndex: 42)
computer(action: "get_state", app: "com.spotify.client")

Observe, act once, observe again. Every action already returns the new state, so the reply to an action is also the next thing you read.

Element indexes go stale

The numbers in the tree are valid for that snapshot of that window. Navigation, scrolling, a focus change, a dialog, an app re-render, or simply a few seconds passing can invalidate them.

  • Re-read the tree after anything that changes the UI.
  • Indexes are sparse — noisy sections are omitted. Never infer a valid index from the element count, and never guess one that is not printed.
  • One window at a time: once you pick windowId (or windowIndex), pass the same one to every later call until you mean to change window.

Picking the app

Prefer the bundle id from list_apps; a name is fine when unambiguous; pid:<number> only when neither is. app names a desktop application, never a website — Gmail is com.google.Chrome, not "Gmail".

When an app has several windows, run list_windows first. Use windowId when the listed id is not null, windowIndex otherwise.

Which action

  • Editable fieldset_value. It writes the value and can usually read it back, which is the only way to prove the text landed.
  • Button, link, checkbox, menu itemclick.
  • An action the tree explicitly lists on an elementperform_action with that exact name.
  • type_text only after a field is focused and the tree confirms a focused text receiver. Synthetic keystrokes go into the void; they are never verified.
  • press_key for one key (Return, Escape, Tab, arrows). hotkey for one modifier chord plus one key (CmdOrCtrl+A). Prefer CmdOrCtrl+… so the same call works on every platform.
  • Modifier-click is click with modifiers. Never send separate modifier-down/modifier-up calls: an interruption between them leaves a modifier logically held down on the user's machine.
  • paste_text for a long or exact body, into a field you have confirmed has focus.

Verified vs. unverified

Every action reports whether its effect could be read back:

ReportWhat it means
verified <property>The changed value was read back. It happened.
unverified (accessibility action unasserted)The call succeeded; nothing checked the result.
unverified (synthetic input)Input was fired at the OS. Unverifiable in principle.
unverified (clipboard paste)Same, through the clipboard.
no verification at allTreat as unverified.

An unverified action is not a completed action. Read the state back before telling the user it worked, and if the action could have sent, submitted, bought or deleted something, say plainly that the effect is unproven.

Screenshots

Off by default: the tree is what you act on, and an image you did not need is pure cost. Pass screenshot: true when pixels are the answer — confirming something visually, reading a chart or canvas the tree cannot describe, or picking coordinates.

The reply carries the image and its path. If it reports a scale other than 1, convert before using pixel coordinates:

x = screenshot_pixel_x / scale
y = screenshot_pixel_y / scale

Coordinates are window-local, and only valid for the window that screenshot came from. Prefer an element index whenever one exists.

On Linux and Windows a screenshot may come from the visible desktop region, so another window can cover the target. Pass restoreWindow: true when the pixels matter; when you cannot take focus, trust the tree over the pixels.

App notes

Browsers. Set the address field directly with set_value, then press_key: "Return" — do not assume typed text reached the address bar. Use restoreWindow: true when the browser is not frontmost. A large tab strip is deliberately compacted to the active tab plus an "inactive browser tabs omitted" marker; work on the current page unless the user asked about tabs.

Forms inside a browser page (a compose window, a web app) expose accessibility actions without necessarily moving DOM focus. After each field action, check which element actually has focus; if it did not move, Tab from a known field or fall back to window-local coordinates from a fresh screenshot.

Instrument and analysis software often renders its plots as one opaque element. Read the controls from the tree, and take a screenshot for the plot.

Shallow trees. Some apps draw their own interface and expose almost nothing. Two different things look the same from here:

  • The state report says the tree is being built — that is an app whose accessibility is switched on the moment you read it. Read again in a few seconds; the real tree arrives. Do not go to coordinates.
  • The tree really is empty, and stays empty on a second read. Then take a screenshot, work from coordinates, and say in your answer that you are working from pixels, because that path cannot be verified.

Errors

Each is a named recovery, not a retry.

  • app_not_found — run list_apps, use the bundle id. For a web app, target the browser app, not the site name.
  • app_blocked — stop. That app is deliberately out of reach.
  • window_not_found / window_stale — run list_windows, take a current selector, read state again.
  • window_not_focused — retry once with restoreWindow: true. If it says restore was already requested, stop retrying and ask the user to bring the app forward. For editable fields prefer set_value, which often works unfocused. On a coordinate click the message names what was in front instead: another app's window over that point, or nothing frontmost at all. Move that window out of the way rather than retrying the same click.
  • element_not_found — the index is stale. Read state again.
  • element_not_clickable — no actionable frame. Use a parent or child element that has one, or coordinates from a fresh screenshot.
  • action_not_supported — read the element's listed actions and use one of those, or fall back to click / set_value.
  • value_not_settable — the element refuses direct writes. Focus it and use keyboard input, and inspect the result.
  • unsupported_capability — this platform's provider cannot do it. Use a different verb, or tell the user. On Linux this can also mean a missing desktop dependency, which the message names.
  • invalid_argument — fix the arguments. Do not send the same call again.
  • action_timeout — read the state before retrying, then use a simpler action.
  • screenshot_failed — the tree may still be enough. If the message names Screen Recording, the user grants it in Settings → Computer Use. Note it is granted to Open Science itself, not to the helper that Accessibility is granted to — macOS attributes screen capture to the app that started the request.
  • permission_denied / accessibility_error — on macOS, Accessibility has not been granted to Open Science Computer Use. Tell the user to open Settings → Computer Use and grant it; you cannot grant it for them.

An empty tree with no screenshot usually means the app has no visible window, is minimized, or the permission is missing.

Frequently asked questions

What does the Computer Use AI skill do?

Use when a task needs an app on the user's own screen — a native desktop application (instrument control software, Origin, GraphPad, ImageJ, a reference manager, a spreadsheet), or a desktop browser window that needs window-level control. Read before the first `computer` call. Covers the observe-act-observe loop, why element indexes go stale, which action to prefer for which control, what "unverified" means and why it must never be reported as success, and the recovery for each error code. Not for page-level web automation (use the browser connector) and not for anything that can be done fr...

Why use Computer Use on TypingMind?

Because you install it once and use it with any model. Computer 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 Computer Use in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ai4s-research/open-science/tree/master/runtime/skills/core/computer-use. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Computer 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 Computer Use?

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

Is the Computer Use AI skill free?

It is published on GitHub by ai4s-research. Check the repository for licensing terms. 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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