computer-use

computer-use is a skill for Claude Code, Codex from thewolffish/wolffish-app. It costs 53 tokens per session (6,592 once invoked), scanned C, original, MIT.

A desktop-automation skill for viewing the screen and controlling the mouse and keyboard. It uses screenshots, zoomed views, and click confirmation to target interface elements accurately.

In plain words
What is it for?
Use it to inspect applications, click controls, type text, use keyboard shortcuts, scroll, drag and drop, zoom into small targets, and verify where clicks landed.
Why use it?
It helps avoid clicking the wrong place when screen scaling, multiple monitors, or small controls make coordinates difficult to judge. Each action can be checked against the latest screen image.

Skill for Claude CodeCodex

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

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/thewolffish/wolffish-app/computer-use
Any agent
npx skills add thewolffish/wolffish-app --skill computer-use
Clone the repo
git clone --depth 1 https://github.com/thewolffish/wolffish-app

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/thewolffish/wolffish-app/computer-use.svg)](https://agentmods.dev/skills/thewolffish/wolffish-app/computer-use)
Your own site
<a href="https://agentmods.dev/skills/thewolffish/wolffish-app/computer-use"><img src="https://agentmods.dev/badge/skills/thewolffish/wolffish-app/computer-use.svg" alt="Measured on agentmods" height="20"></a>
Per session 53 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 6,592 The whole file, excluding the scripts and references it only reads on demand.
Security scan C 1 finding. 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 5.1 $0.00053 $0.06592
Opus 5 $0.00026 $0.03296
Sonnet 5 $0.00011 $0.01318
Haiku 4.5 $0.00005 $0.00659

Measured yesterday against content hash 1f5f907cd170, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade C, and why

computer-use scanned grade C with 1 finding 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 yesterday.

The scan reads SKILL.md. This mod also ships 1 executable file (plugin/index.mjs), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

Recursive force deletehighDestructive command

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

- pattern: 'computer_keyboard_type.*(sudo|rm -rf|password|secret|token)'
src/defaults/workspace/brain/cerebellum/computer-use/SKILL.md · 475 lines

How it starts

The opening of the file, as written. The whole thing — 475 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Computer Use — Verified-Aim Desktop Automation

The agent sees and controls the desktop through a closed feedback loop designed for surgical accuracy with any vision-capable model:

  1. One coordinate space, owned by the plugin. Every image the tools return (screenshot, zoom, or click magnifier) becomes the current frame. The model always gives coordinates as pixels read off the latest image; the plugin does all translation to real screen position — screenshot downscaling, Retina/HiDPI scale factors, and multi-monitor offsets. The model never does coordinate math, which removes the entire class of "right target, wrong space" misses.
  2. A crosshair marks the cursor on every returned image, so the model always knows where the pointer actually is. In aiming frames (zooms and magnifiers) thin hairlines additionally run from the image edges through the exact cursor pixel — a fat ring can visually swallow a 16px control that is actually 15px away, while a hairline either passes through the target or visibly does not.
  3. Zoom for small targets. computer_zoom re-captures a chosen region at native resolution (up to 4x magnification). The zoomed image becomes the frame, so tiny controls are clicked in a space where they are dozens of pixels wide. A zoom below 2x is flagged in the result, with the region size that would reach 3x — weak "zooms" of wide regions are where small-target clicks historically missed.
  4. Every click returns proof — including an objective change report. computer_mouse_click captures the screen before and after the press and reports what percentage of pixels changed around the cursor and across the display. "NO visible change" after a click that should have had an immediate local effect (closed a tab, opened a menu) means the click missed, regardless of how the close-up reads. The check samples one display for under half a second, so slow-painting results, cross-display effects, and sub-threshold changes evade it — the model is told to verify with a screenshot before retrying, and never to blindly re-click side-effectful controls. Click, move, and drag also return a 3x-magnified close-up with the crosshair and hairlines on the exact pixel acted on, which becomes the current frame so corrections happen in finer coordinates instead of by re-guessing on the full screenshot.

This mirrors the practices Anthropic uses for Claude's own computer use: act on the latest image only, verify after every action, zoom rather than squint, prefer keyboard shortcuts when they are more reliable than pointing.

Read the full file on GitHub · 475 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. yesterday Changed · +73 lines 1f5f907cd170
  2. 6d ago First seen · 402 lines · 53 tokens per session scan C efd9392c5fd6

Subscribe to this mod's changes

computer-use is a skill published in the GitHub repository thewolffish/wolffish-app (5 stars, last pushed yesterday), licensed MIT. It adds 53 tokens to every session and 6,592 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it C with 1 finding (recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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