macos-computer-use

macos-computer-use is a skill for Claude Code, Codex from humanerd-drew/opencode-drewgent. It costs 60 tokens per session (1,865 once invoked), scanned A, a copy of macos-computer-use, MIT.

A skill for controlling a macOS desktop in the background using screenshots, mouse actions, keyboard input, scrolling, and dragging. It is designed to avoid taking control of the user’s cursor, keyboard focus, or desktop space.

In plain words
What is it for?
Use it to inspect and operate macOS applications, including clicking controls, entering text, scrolling, and dragging items. It works with models that can use tools.
Why use it?
It lets a tool-capable coding agent interact with Mac applications while the user continues working. The skill uses screenshots and named interface elements to guide actions.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions OpenCode.

Good fit Use it to inspect and operate macOS applications, including clicking controls, entering text, scrolling, and dragging items. It works with models that can use tools.

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Install with agentmods
npx agentmods add skills/humanerd-drew/opencode-drewgent/macos-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 humanerd-drew/opencode-drewgent --skill macos-computer-use
Clone the repo
git clone --depth 1 https://github.com/humanerd-drew/opencode-drewgent

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 macos-computer-use

README.md
[![agentmods](https://agentmods.dev/badge/skills/humanerd-drew/opencode-drewgent/macos-computer-use/github.svg)](https://agentmods.dev/skills/humanerd-drew/opencode-drewgent/macos-computer-use)
Your own site
<a href="https://agentmods.dev/skills/humanerd-drew/opencode-drewgent/macos-computer-use"><img src="https://agentmods.dev/badge/skills/humanerd-drew/opencode-drewgent/macos-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 macos-computer-use

Your own site · 80×15
<a href="https://agentmods.dev/skills/humanerd-drew/opencode-drewgent/macos-computer-use"><img src="https://agentmods.dev/badge/skills/humanerd-drew/opencode-drewgent/macos-computer-use.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 60 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,865 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. ✓ AI security review Sonnet 5 · 6 Sept 2026 📄 Read the review
Origin 89% copy Near-identical to another mod 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 $0.00060 $0.01865
Opus 5.5 $0.00024 $0.00746
Sonnet 5.5 $0.00012 $0.00373
Haiku 4.5 $0.00006 $0.00186

Measured 1mo ago against content hash 2ee295ec65ed, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

macos-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 1mo ago.

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.

Origin

This is a copy

89% identical to macos-computer-use — 406 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/apple/macos-computer-use/SKILL.md · 206 lines

How it starts

The opening of the file, as written. The whole thing — 206 lines — stays where its author put it; the contents beside it link to each section on GitHub.

macOS Computer Use (universal, any-model)

You have a computer_use tool that drives the Mac in the background. Your actions do NOT move the user's cursor, steal keyboard focus, or switch Spaces. The user can keep typing in their editor while you click around in Safari in another Space. This is the opposite of pyautogui-style automation.

Everything here works with any tool-capable model — Claude, GPT, Gemini, or an open model running through a local OpenAI-compatible endpoint. There is no Anthropic-native schema to learn.

The canonical workflow

Step 1 — Capture first. Almost every task starts with:

computer_use(action="capture", mode="som", app="Safari")

Returns a screenshot with numbered overlays on every interactable element AND an AX-tree index like:

#1  AXButton 'Back' @ (12, 80, 28, 28) [Safari]
#2  AXTextField 'Address and Search' @ (80, 80, 900, 32) [Safari]
#7  AXLink 'Sign In' @ (900, 420, 80, 24) [Safari]
...

Step 2 — Click by element index. This is the single most important habit:

computer_use(action="click", element=7)

Much more reliable than pixel coordinates for every model. Claude was trained on both; other models are often only reliable with indices.

Step 3 — Verify. After any state-changing action, re-capture. You can save a round-trip by asking for the post-action capture inline:

computer_use(action="click", element=7, capture_after=True)

Capture modes

mode Returns Best for
som (default) Screenshot + numbered overlays + AX index Vision models; preferred default
vision Plain screenshot When SOM overlay interferes with what you want to verify
ax AX tree only, no image Text-only models, or when you don't need to see pixels

Actions

capture           mode=som|vision|ax   app=…  (default: current app)
click             element=N     OR     coordinate=[x, y]
double_click      element=N     OR     coordinate=[x, y]
right_click       element=N     OR     coordinate=[x, y]
middle_click      element=N     OR     coordinate=[x, y]
drag              from_element=N, to_element=M        (or from/to_coordinate)
scroll            direction=up|down|left|right   amount=3 (ticks)
type              text="…"
key               keys="cmd+s" | "return" | "escape" | "ctrl+alt+t"
wait              seconds=0.5
list_apps
focus_app         app="Safari"  raise_window=false   (default: don't raise)

Read the full file on GitHub · 206 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. 1mo ago First seen · 206 lines · 60 tokens per session scan F 2ee295ec65ed

Subscribe to this mod's changes

macos-computer-use is a skill published in the GitHub repository humanerd-drew/opencode-drewgent (3 stars, last pushed 3mo ago), licensed MIT. It adds 60 tokens to every session and 1,865 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 89% identical to macos-computer-use, differing in 406 lines, and is treated as a copy.

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