agentmods.dev

computer-use

A tool guide for controlling real desktop applications through DeepChat's built-in computer-control features. It supports starting a session, finding an application, and carrying out GUI actions.

In plain words
What is it for?
Use it to automate or inspect native applications, navigate their windows, and perform tasks through their visible user interfaces.
Why use it?
It gives developers a defined way to inspect and operate desktop software when a task cannot be completed through text or code alone.

Skill for Claude CodeCodex

6.3k +9 yesterday A scan 40 tokens original Apache-2.0
View the source file ThinkInAIXYZ/deepchat
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/thinkinaixyz/deepchat/computer-use
Any agent
npx skills add ThinkInAIXYZ/deepchat --skill computer-use
Clone the repo
git clone --depth 1 https://github.com/ThinkInAIXYZ/deepchat

Made for: Claude Code, Codex.

Per session 40 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,638 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 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 $0.00040 $0.02638
Opus 5 $0.00020 $0.01319
Sonnet 5 $0.00008 $0.00528
Haiku 4.5 $0.00004 $0.00264

Measured 3d ago against content hash 89ec0e98e13c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, 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 3d 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.

plugins/cua/skills/computer-use/SKILL.md · 201 lines

How it starts

The opening of the file, as written. The whole thing — 201 lines — stays where its author put it; the contents beside it link to each section on GitHub.

computer-use

Use DeepChat's plugin-provided Computer Use tools as the only action surface for this skill. Do not ask the user to install cua-driver, configure an external server, or put anything on PATH for the bundled DeepChat plugin.

Runtime Context

  • Plugin id: ${OWNER_PLUGIN_ID}.
  • Plugin root: ${PLUGIN_ROOT}.
  • Process arch: ${PROCESS_ARCH}.
  • Supported targets: darwin/arm64, darwin/x64, win32/x64, win32/arm64, linux/x64.
  • Unsupported targets: linux/arm64.
  • macOS runtime bundle: packaged builds prefer DeepChat.app/Contents/Helpers/DeepChat Computer Use.app; the plugin-local fallback is ${PLUGIN_ROOT}/runtime/darwin/${PROCESS_ARCH}/DeepChat Computer Use.app.
  • Windows helper binary: ${PLUGIN_ROOT}/runtime/win32/${PROCESS_ARCH}/cua-driver.exe.
  • Linux helper binary: ${PLUGIN_ROOT}/runtime/linux/${PROCESS_ARCH}/cua-driver.

Required Loop

  1. Declare one stable run identity with start_session({ session, capture_scope: "auto" }). Reuse that session value for every state and action call whose advertised schema declares it. Omit cursor_theme during normal session setup.
  2. Resolve the app with list_apps. Match localized names, English names, romanized names, bundle identifiers, executable names, and common abbreviations. Prefer stable identifiers when a result provides them.
  3. Start or reuse the target with launch_app. Use the returned pid when available.
  4. Inspect windows with list_windows({ pid }) when the launch result lacks a usable window.
  5. Snapshot before every UI action with get_window_state({ pid, window_id, session }). Pass include_screenshot: true for the initial view, sparse or ambiguous accessibility trees, pixel actions, and visual verification. Pass include_screenshot: false for a routine cheap re-index when the accessibility target is already unambiguous.
  6. Act with the matching DeepChat tool: click, right_click, double_click, drag, scroll, type_text, press_key, hotkey, set_value, set_window_frame, invoke_menu, or launch_app with URLs/files when supported by the platform. Follow WEB_APPS.md for browser page content.
  7. When an ActionResult-contract tool appends ## CUA action result, read it. Delivery describes dispatch, not effect or task completion. Do not continue as if the action succeeded when effect is partial, unverifiable, suspected_noop, or refused. Legacy lifecycle/app tools without this projection still require postcondition verification.
  8. Verify after each action. Use verify_state for an exact-window postcondition expressible as window existence/bounds or a trusted native element's existence/value/enabled/selected state. Otherwise take a fresh get_window_state, get_browser_state, or get_desktop_state and inspect the relevant visible evidence.
  9. Call end_session({ session }) after the run, including orderly error cleanup.

Read the full file on GitHub · 201 lines

Files

What ships with it

4 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. 3d ago First seen · 201 lines · 40 tokens per session scan A 89ec0e98e13c

Subscribe to this mod's changes

computer-use is a skill published in the GitHub repository ThinkInAIXYZ/deepchat (6,302 stars, last pushed yesterday), licensed Apache-2.0. It adds 40 tokens to every session and 2,638 once invoked, about $0.0002 per session on Opus 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.

Browser automationProductivityaiai-assistantchatgptcross-platformllm-clientopenai-client
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