computer-use

computer-use is a skill for Claude Code, Codex from CavinHuang/lume. It costs 11 tokens per session (776 once invoked), scanned A, original, MIT.

A workflow for controlling native desktop applications through Lume Computer Use. It covers how to connect to the desktop-control client and use its documented actions.

In plain words
What is it for?
Use it for tasks in desktop software, such as opening applications, interacting with visible controls, and completing actions through the computer interface.
Why use it?
It gives an agent a defined way to work with applications that are not web pages, while keeping browser work in browser-specific tools.

Skill for Claude CodeCodex

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

Good fit Use it for tasks in desktop software, such as opening applications, interacting with visible controls, and completing actions through the computer interface.

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

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/cavinhuang/lume/computer-use/github.svg)](https://agentmods.dev/skills/cavinhuang/lume/computer-use)
Your own site
<a href="https://agentmods.dev/skills/cavinhuang/lume/computer-use"><img src="https://agentmods.dev/badge/skills/cavinhuang/lume/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/cavinhuang/lume/computer-use"><img src="https://agentmods.dev/badge/skills/cavinhuang/lume/computer-use.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 11 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 776 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.
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 $0.00011 $0.00776
Opus 5.5 $0.00004 $0.00310
Sonnet 5.5 $0.00002 $0.00155
Haiku 4.5 $0.00001 $0.00078

Measured 1mo ago against content hash 06b968920193, 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 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.

apps/sidecar/bundled-plugins/computer-use/skills/computer-use/SKILL.md · 68 lines

What it actually says

Computer Use

Use this skill for native desktop applications. Browser pages should use the Browser or Chrome capability when it is available.

Treat connection setup as internal. Do not mention Node REPL, JavaScript sessions, module imports, or sky in user-facing updates unless the user asks about the implementation.

Before the first desktop action in a task, bootstrap the trusted client through mcp__node_repl__js using the absolute path of this plugin's scripts/computer-use-client.mjs:

if (!globalThis.sky) {
  const { setupComputerUseRuntime } = await import("${PLUGIN_DIR}/scripts/computer-use-client.mjs");
  await setupComputerUseRuntime({ globals: globalThis });
}

Then read the runtime guidance, exact API, and confirmation policy once:

globalThis.computerUseGuidance = await sky.documentation("guidance")
globalThis.computerUseApi = await sky.documentation("api")
globalThis.computerUseConfirmations = await sky.documentation("confirmations")
nodeRepl.write(`${computerUseGuidance}\n\n${computerUseApi}\n\n${computerUseConfirmations}`)

The Node tool only returns string values passed to nodeRepl.write. Bare final expressions are invisible; use nodeRepl.write(JSON.stringify(value)) for structured output.

Use the exact snake_case Window2 methods from the API. Start discovery with await sky.list_apps(); do not translate method names to listApplications, focusApplication, or observe.

list_apps() returns application descriptors, not Windows. Select a Window from an application's windows array before calling get_window. Window is plain data and has no methods; every action is a sky.* call. WindowState uses accessibility and plural screenshots, never text or singular screenshot:

globalThis.apps = await sky.list_apps()
// Replace this exact matcher with the application requested by the user.
globalThis.targetApp = apps.find(app => app.displayName === "微信" && app.windows.length === 1)
if (!targetApp || targetApp.windows.length !== 1) {
  nodeRepl.write(JSON.stringify({
    error: "Select one unique application window",
    candidates: apps.filter(app => /微信|wechat|weixin/i.test(`${app.displayName ?? ""} ${app.id}`))
  }))
} else {
  globalThis.targetWindow = targetApp.windows[0]
  targetWindow = await sky.get_window({ id: targetWindow.id, app: targetWindow.app })
  globalThis.state = await sky.get_window_state({ window: targetWindow })
  targetWindow = state.window
  globalThis.screenshot = state.screenshots[0]
}

For a coordinate action, call the client directly and pass the current Window and screenshot ID:

await sky.click({ window: targetWindow, x, y, screenshotId: state.screenshots[0].id })
await sky.type_text({ window: targetWindow, text })
state = await sky.get_window_state({ window: targetWindow })
targetWindow = state.window

Keep reusable top-level bindings such as apps, targetWindow, and state. After every observation, replace the old target with targetWindow = state.window. Never invent or reconstruct a window ID.

If the trusted client or desktop host is unavailable after one retry, stop and report the failure. Do not fall back to PowerShell SendKeys, WScript, pyautogui, ctypes, robotjs, terminal UI automation, or system-key shortcuts.

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 · 68 lines · 11 tokens per session scan A 06b968920193

Subscribe to this mod's changes

computer-use is a skill published in the GitHub repository CavinHuang/lume (3 stars, last pushed 1mo ago), licensed MIT. It adds 11 tokens to every session and 776 once invoked, about $0.0000 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 2026-08-31.

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