computer-use

computer-use is a skill for Claude Code, Codex from zavora-ai/computer-use-mcp. It costs 37 tokens per session (1,195 once invoked), scanned A, original, MIT.

A desktop automation skill for controlling native macOS and Windows applications through screenshots, accessibility controls, or scripts.

In plain words
What is it for?
Use it to inspect app interfaces, fill forms, click controls, paste long text, and run scripts while targeting a specific application window.
Why use it?
It helps with tasks that can only be completed inside a desktop app, such as installers, dialogs, and applications without a usable command-line or web interface.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to inspect app interfaces, fill forms, click controls, paste long text, and run scripts while targeting a specific application window.

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Install with agentmods
npx agentmods add skills/zavora-ai/computer-use-mcp/computer-use
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add zavora-ai/computer-use-mcp --skill computer-use
Clone the repo
git clone --depth 1 https://github.com/zavora-ai/computer-use-mcp

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for computer-use

README.md
[![agentmods](https://agentmods.dev/badge/skills/zavora-ai/computer-use-mcp/computer-use/github.svg)](https://agentmods.dev/skills/zavora-ai/computer-use-mcp/computer-use)
Your own site
<a href="https://agentmods.dev/skills/zavora-ai/computer-use-mcp/computer-use"><img src="https://agentmods.dev/badge/skills/zavora-ai/computer-use-mcp/computer-use/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for computer-use

Your own site · 80×15
<a href="https://agentmods.dev/skills/zavora-ai/computer-use-mcp/computer-use"><img src="https://agentmods.dev/badge/skills/zavora-ai/computer-use-mcp/computer-use.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 37 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,195 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00037 $0.01195
Opus 5.5 $0.00015 $0.00478
Sonnet 5.5 $0.00007 $0.00239
Haiku 4.5 $0.00004 $0.00120

Measured today against content hash 5e567e994349, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

computer-use scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/computer-use/SKILL.md · 54 lines

How it starts

The opening of the file, as written. The whole thing — 54 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Computer Use (desktop automation)

When to use

  • Native desktop apps, installers, modal dialogs, simulators
  • Apps that draw their own UI (Unreal, Blender, games): OCR route below
  • UI-only workflows with no API/CLI

When NOT to use

  • Prefer the app's own API or MCP server, connectors, shell, filesystem, or browser automation (Playwright) first

Mandatory first steps

If the app ID is unknown, first use discover_applications({query, include_capabilities: true}). Use its targetApp when present; do not assume a desktop registration ID is a process target.

  1. get_tool_guide({ task_description }) — pick scripting vs accessibility vs OCR vs coordinates
  2. get_app_capabilities({ bundle_id }) — is the app scriptable? accessibility: { nodes, hasControls } says whether its tree has real controls (accessible means hasControls); a handful of nodes means it draws its own UI
  3. Route order: run_script → accessibility (fill_form, click_element) → OCR (read_window_text, click_text) → coordinates (click, type, key) last

Route for apps that draw their own UI (macOS)

Unreal, Blender, games and Electron canvases expose an empty accessibility tree. Do not call get_ui_tree, find_element or list_menu_bar on them.

  1. list_windows (kinds: main, document, dialog, panel, toast) to pick the window
  2. read_window_text with a region (keeps it to a few dozen tokens): lines with box in window points; screen point = screen_origin + box. On-device, works on covered windows, activates nothing
  3. click_text to press a label by what it says (match: exact | contains | regex, nth); wait_for_text (appears, or gone: true) or wait_for_stable after the click instead of sleeping
  4. screenshot / zoom only when text is not enough (icons, 3D viewports); mouse_drag for orbit/pan These OCR tools exist on macOS only; on Windows and Linux they are not listed.

Hard rules

  • Always set target_app (bundle ID macOS / process name Windows) or target_window_id — or call set_target once and omit it afterwards (get_target shows it; an explicit target on a call wins)
  • One click {coordinate, button: left|right|middle, count: 1|2|3}; left_click, double_click and the rest are aliases of it
  • Do not screenshot every step: use get_ui_tree / find_element where the app has accessibility, read_window_text where it does not; screenshot with a target captures that window (full_screen: true for the whole screen)
  • Wait with wait_for_window, wait_for_text, wait_for_stable, not wait plus a screenshot loop
  • Long text: write_clipboard + paste shortcut, not type
  • On focus failure, follow suggestedRecovery (activate_window, unhide_app, open_application)
  • Use focus_strategy: "prepare_display" only after a focus race

Read the full file on GitHub · 54 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. today Changed 5e567e994349
  2. 12d ago Changed 512d1795c725
  3. 15d ago Changed · +23 lines · +1 tokens per session 13a6e3a86e74
  4. 1mo ago Changed · +1 lines ecbab29544c7
  5. 1mo ago First seen · 30 lines · 36 tokens per session scan A 4228d8fa8a4f

Subscribe to this mod's changes

computer-use is a skill published in the GitHub repository zavora-ai/computer-use-mcp (86 stars, last pushed today), licensed MIT. It adds 37 tokens to every session and 1,195 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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