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.
npx skills add IceWhaleTech/ZimaOS-Blue --skill computer_usegit clone --depth 1 https://github.com/IceWhaleTech/ZimaOS-BlueWrote 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.
[](https://agentmods.dev/skills/icewhaletech/zimaos-blue/computer_use)<a href="https://agentmods.dev/skills/icewhaletech/zimaos-blue/computer_use"><img src="https://agentmods.dev/badge/skills/icewhaletech/zimaos-blue/computer_use.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00099 | $0.01694 |
| Opus 5 | $0.00049 | $0.00847 |
| Sonnet 5 | $0.00020 | $0.00339 |
| Haiku 4.5 | $0.00010 | $0.00169 |
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 7d 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.
How it starts
The opening of the file, as written. The whole thing — 158 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Computer Use
Use the built-in computer_use tool for live UI work on desktop apps, native windows, and accessibility-backed browser flows.
Setup
No external CLI is required.
For host-window actions:
- macOS: Accessibility permission may be required.
- Windows: UI Automation / WinEvent-backed inspection must be available.
If the user only wants to edit a workspace artifact such as .docx, .xlsx, .pptx, or .pdf, use the native document tools instead of driving the app UI.
Task Routing
| User Intent | Action |
|---|---|
| Focus the right app or window | blue computer_use action=focus ... |
| Inspect interactive host UI before acting | blue computer_use action=snapshot_interactive ... |
| Read the full accessibility tree for debugging | blue computer_use action=snapshot ... |
| Send a chat message in a known conversation | blue computer_use action=message ... |
| Switch to a conversation/list row/item without typing | blue computer_use action=select ... |
| Type into the likely composer/input without exposing refs | blue computer_use action=type ... |
| Click a named control or toggle a named setting | blue computer_use action=click ... / toggle ... |
| Scroll, press keys, or capture evidence | blue computer_use action=scroll ..., key ..., screenshot ... |
| Run a multi-step CUA desktop task | blue computer_use action=task goal="..." |
| Use CUA action aliases | open_app, input_text, Click, RightSingle, move_mouse, scroll_up/down, Hotkey, multi_Hotkey, record_info, done |
| User goal is still ambiguous and you truly need low-level control | blue computer_use action=act params... |
Command Usage
Fast Path
blue computer_use action=message app_name="Feishu,Lark" conversation="Orca" value="hello"
blue computer_use action=type app_name="Feishu,Lark" conversation="Orca" value="draft only"
blue computer_use action=select app_name="Feishu,Lark" conversation="Orca"
blue computer_use action=click window_title="Settings" control="Open Network"
blue computer_use action=toggle window_title="Settings" setting="Enable notifications"
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.
- 7d ago First seen · 158 lines · 99 tokens per session scan A ce9f0f25224f
computer_use is a skill published in the GitHub repository IceWhaleTech/ZimaOS-Blue (25 stars, last pushed 4mo ago), licensed MIT. It adds 99 tokens to every session and 1,694 once invoked, about $0.0005 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.
Other skills, from other repositories
credential-setup-with-computer-use
Guides n8n credential setup through Computer Use browser tools. Use when a user needs OAuth apps, API keys, client IDs, client secrets, or other credential values from an external service console.
defuddle
Extract clean markdown content from web pages using Defuddle CLI, removing clutter and navigation to save tokens. Use instead of WebFetch when the user provides a URL to read or analyze, for online documentation, articles, blog posts, or any standard web page. Do NOT use for URLs ending in .md — those are already…
browser-harness-skill
Drive the user's real Chrome over raw CDP by writing Python against browser-harness helpers - screenshot, coordinate clicks, JS evaluation, form fill, tabs. For tasks needing full freedom or the user's own logins.
browser-skill
Interactive browser automation - navigate, click, type, fill forms, take screenshots, get accessibility snapshots. Supports system Chrome/Edge via auto-detection.
nearby-places-skill
Search for nearby places like restaurants, cafes, stores, and services using Google Places API. Find places by type and location.
unbrowse
One-call web access for agents with cache-first API replay and browser capture on misses. Unbrowse passively learns first-party route DAGs while browsing, independently validates replay, and keeps remote sharing consented and fail-closed. Prefer it over WebFetch, curl, and browser loops.