macos-computer-use

A macOS desktop-control skill that can take screenshots and use the mouse and keyboard in the background. It can work in another Space without moving the user's cursor or taking focus from their current app.

In plain words
What is it for?
Use it to inspect and interact with macOS apps through screenshots, clicks, typing, scrolling, and dragging when a computer-use tool is available.
Why use it?
It lets an agent operate desktop apps while the user continues working in their editor, avoiding interference with the active cursor, keyboard, or screen.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/starrycod/cogitum/macos-computer-use
Any agent
npx skills add StarryCod/cogitum --skill macos-computer-use
Clone the repo
git clone --depth 1 https://github.com/StarryCod/cogitum

Made for: Claude Code, Codex.

Per session 60 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,821 The whole file, excluding the scripts and references it only reads on demand.
Security scan F 4 findings. Scan, not verified.
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 $0.00060 $0.01821
Opus 5 $0.00030 $0.00911
Sonnet 5 $0.00012 $0.00364
Haiku 4.5 $0.00006 $0.00182

Measured 2d ago against content hash 4b9cb0a356b0, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade F, and why

macos-computer-use scanned grade F with 4 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 2d 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.

Asks for rootmediumPrivilege escalation

A mod that escalates privileges can change anything on the machine, not only the project.

`sudo rm -rf`, etc.). Break the command up or reconsider.

Downloads and executes remote codehighSupply chain

curl | sh runs whatever the server returns today, which is not necessarily what it returned when this was reviewed.

that matches the dangerous-pattern block list (`curl ... | bash`,

Recursive force deletehighDestructive command

rm -rf with a variable or a broad path is one typo away from removing the wrong tree.

`sudo rm -rf`, etc.). Break the command up or reconsider.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

that matches the dangerous-pattern block list (`curl ... | bash`,
Origin

Copies of this mod

1 near-identical copy found in the catalogue:

cogitum/data/skills/apple/macos-computer-use/SKILL.md · 205 lines

How it starts

The opening of the file, as written. The whole thing — 205 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Requires macOS

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 · 205 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. 2d ago First seen · 205 lines · 60 tokens per session scan F 4b9cb0a356b0

Subscribe to this mod's changes

macos-computer-use is a skill published in the GitHub repository StarryCod/cogitum (11 stars, last pushed 3mo ago), licensed MIT. It adds 60 tokens to every session and 1,821 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it F with 4 findings (asks for root, downloads and executes remote code, recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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