computer-use

computer-use is a skill for Codex from QwenLM/qwen-code. It costs 33 tokens per session (3,322 once invoked), scanned A, original, Apache-2.0.

A way to operate local desktop applications through their user interface, using computer-control commands when a dedicated connector or command-line tool is unavailable.

In plain words
What is it for?
Use it to read information from or perform actions in local desktop apps, following the required computer-control setup and interaction method.
Why use it?
It lets the coding assistant work with applications that do not expose a suitable API or command-line interface.

Skill for Codex ✓ vendor

Written for Codex: agents/openai.yaml present. Also seen: mentions Codex.

Good fit Use it to read information from or perform actions in local desktop apps, following the required computer-control setup and interaction method.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/qwenlm/qwen-code/computer-use
About the project

Qwen Code is an open-source AI coding agent that runs in a terminal and helps developers work with code through language models. It supports multiple model providers and can also be used through IDEs, desktop software, SDKs, and messaging bots.

QwenLM/qwen-code · 28,586 stars · on GitHub · qwenlm.github.io

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 QwenLM/qwen-code --skill computer-use
Clone the repo
git clone --depth 1 https://github.com/QwenLM/qwen-code

Made for: 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/qwenlm/qwen-code/computer-use/github.svg)](https://agentmods.dev/skills/qwenlm/qwen-code/computer-use)
Your own site
<a href="https://agentmods.dev/skills/qwenlm/qwen-code/computer-use"><img src="https://agentmods.dev/badge/skills/qwenlm/qwen-code/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/qwenlm/qwen-code/computer-use"><img src="https://agentmods.dev/badge/skills/qwenlm/qwen-code/computer-use.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 33 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,322 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. Third-party audits
  • Snyk pass 7 Sept 2026
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00033 $0.03322
Opus 5.5 $0.00013 $0.01329
Sonnet 5.5 $0.00007 $0.00664
Haiku 4.5 $0.00003 $0.00332

Measured 21d ago against content hash 0f8742eb4b42, 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 21d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (SKILL.test.ts), 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.

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.

packages/core/src/skills/bundled/computer-use/SKILL.md · 296 lines

How it starts

The opening of the file, as written. The whole thing — 296 lines — stays where its author put it; the contents beside it link to each section on GitHub.

node_repl + @qwen-code/cua-sdk (Computer Use)

  • Use node_repl (JavaScript) for all Computer Use actions.
  • If both servers are available, use node_repl from the desktop-node-repl MCP server; the regular server runs on the Qwen Code host.
  • Do not use other technologies besides node_repl for computer interactions, unless specifically requested by the user (e.g. AppleScript, osascript, JXA, System Events, synthesized input).
  • Prefer a dedicated plugin or skill when it can complete the task; use Computer Use for app interactions that are not exposed through a more specific interface.
  • node_repl state is persistent across calls.
  • For text output, use nodeRepl.write(...). It takes a string; use JSON.stringify(...) only for textual metadata. For an observation, write its .text and emit its screenshots as images; do not stringify an observation or driver result containing image bytes.
  • Omit yield_time_ms for ordinary UI calls to use the default 10-second wait. A shorter yield does not speed up the action and can add a node_repl_wait round. Use a shorter yield only when you need control back before completion; if a cell is still running, collect its result with node_repl_wait before issuing dependent actions.

Forwarding results in Codex code mode

When calling node_repl through tools.* inside Codex's outer functions.exec, forward each returned content block by its type. nodeRepl.emitImage(...) produces an MCP image block; the outer script must pass that block to image() for the model to receive an image. Prefer the desktop relay tool when it is present; otherwise use the regular node-repl server:

// A code-mode `tools` object throws on an unknown key, so probe with `in`:
// reading an unbound tool would abort the script before any fallback ran.
const DESKTOP_NODE_REPL = 'mcp__desktop_node_repl__node_repl';
const nodeReplTool =
  DESKTOP_NODE_REPL in tools
    ? tools[DESKTOP_NODE_REPL]
    : tools.mcp__node_repl__node_repl;
const result = await nodeReplTool({ code });
for (const block of result.content ?? []) {
  if (block.type === 'text') {
    text(block.text);
  } else if (block.type === 'image') {
    image(block);
  }
}

Read the full file on GitHub · 296 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. 21d ago Changed · +13 lines 0f8742eb4b42
  2. 26d ago Changed · -42 lines a346c2807c61
  3. 1mo ago Changed 260a9df7cf08
  4. 1mo ago Changed · +21 lines 924c67a46c9e
  5. 1mo ago Changed · +217 lines ac4c290fd8a7
  6. 1mo ago Changed · -152 lines 3f79f147b0a9
  7. 1mo ago Changed 1cfee453132a
  8. 1mo ago Changed · +73 lines 39379c284042
  9. 1mo ago Changed · -64 lines 77f5e17bebd1
  10. 1mo ago First seen · 230 lines · 33 tokens per session scan A fcfac31c91cf

Subscribe to this mod's changes

computer-use is a skill published in the GitHub repository QwenLM/qwen-code (28,586 stars, last pushed today), licensed Apache-2.0. It adds 33 tokens to every session and 3,322 once invoked, about $0.0001 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 2026-08-30.

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