computer-use

computer-use is a skill for Claude Code, Codex from aivrar/portable-hermes-agent. It costs 13 tokens per session (3,856 once invoked), scanned A, a copy of computer-use, MIT.

A guide for operating a computer desktop in the background without taking over the user's cursor or keyboard focus. It describes a workflow for capturing the screen and using desktop actions.

In plain words
What is it for?
Use it for tasks that require viewing or controlling a desktop application, including browser-based work.
Why use it?
It helps an agent interact with desktop applications while the user continues working in their own windows.

Skill for Claude CodeCodex

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

Good fit Use it for tasks that require viewing or controlling a desktop application, including browser-based work.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/aivrar/portable-hermes-agent/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 aivrar/portable-hermes-agent --skill computer-use
Clone the repo
git clone --depth 1 https://github.com/aivrar/portable-hermes-agent

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/aivrar/portable-hermes-agent/computer-use.svg)](https://agentmods.dev/skills/aivrar/portable-hermes-agent/computer-use)
Your own site
<a href="https://agentmods.dev/skills/aivrar/portable-hermes-agent/computer-use"><img src="https://agentmods.dev/badge/skills/aivrar/portable-hermes-agent/computer-use.svg" alt="Measured on agentmods" height="20"></a>
Per session 13 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,856 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 100% 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 $0.00013 $0.03856
Opus 5 $0.00006 $0.01928
Sonnet 5 $0.00003 $0.00771
Haiku 4.5 $0.00001 $0.00386

Measured 4d ago against content hash e3d11184959b, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, 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 4d 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

100% identical to computer-use — 0 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/autonomous-ai-agents/computer-use/SKILL.md · 340 lines

How it starts

The opening of the file, as written. The whole thing — 340 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Computer Use (universal, any-model, cross-platform)

You have a computer_use tool that drives the user's desktop in the background — your actions do NOT move the user's cursor, steal keyboard focus, or switch virtual desktops / Spaces. The user can keep typing in their editor while you click around in a browser in another window. This is the opposite of pyautogui-style automation.

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

Hermes drives cua-driver under the hood. This wrapper skill teaches the Hermes computer_use workflow and action vocabulary. Call the actions documented below instead of raw cua-driver MCP tools. For driver internals and platform-specific behavior, follow the Cua skill installed by cua-driver skills install. Hermes autodetection is a planned cua-driver follow-up, so currently point Hermes at the resulting ~/.cua-driver/skills/cua-driver directory or symlink it into your skill space.

The canonical workflow

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

computer_use(action="capture", mode="som", app="<the app you're driving>")

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

#1  AXButton 'Back' @ (12, 80, 28, 28) [Chrome]
#2  AXTextField 'Address bar' @ (80, 80, 900, 32) [Chrome]
#7  Link 'Sign In' @ (900, 420, 80, 24) [Chrome]
...

The role names match the host platform's accessibility framework (AXButton on macOS, Button on Windows UIA, push button on Linux AT-SPI) — treat them as labels, not as strict types.

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:

Read the full file on GitHub · 340 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. 4d ago First seen · 340 lines · 13 tokens per session scan F e3d11184959b

Subscribe to this mod's changes

computer-use is a skill published in the GitHub repository aivrar/portable-hermes-agent (215 stars, last pushed yesterday), licensed MIT. It adds 13 tokens to every session and 3,856 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to computer-use, differing in 0 lines, and is treated as a copy.

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