Claude Agent Skill · by Am Will

Gemini Computer Use

Install Gemini Computer Use skill for Claude Code from am-will/codex-skills.

Install
Terminal · npx
$npx skills add https://github.com/am-will/codex-skills --skill gemini-computer-use
Works with Paperclip

How Gemini Computer Use fits into a Paperclip company.

Gemini Computer Use drops into any Paperclip agent that handles this kind of work. Assign it to a specialist inside a pre-configured PaperclipOrg company and the skill becomes available on every heartbeat — no prompt engineering, no tool wiring.

S
SaaS FactoryPaired

Pre-configured AI company — 18 agents, 18 skills, one-time purchase.

$27$59
Explore pack
Source file
SKILL.md63 lines
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---name: gemini-computer-usedescription: Build and run Gemini 2.5 Computer Use browser-control agents with Playwright. Use when a user wants to automate web browser tasks via the Gemini Computer Use model, needs an agent loop (screenshot → function_call → action → function_response), or asks to integrate safety confirmation for risky UI actions.--- # Gemini Computer Use ## Quick start 1. Source the env file and set your API key:    ```bash   cp env.example env.sh   $EDITOR env.sh   source env.sh   ``` 2. Create a virtual environment and install dependencies:    ```bash   python -m venv .venv   source .venv/bin/activate   pip install google-genai playwright   playwright install chromium   ``` 3. Run the agent script with a prompt:    ```bash   python scripts/computer_use_agent.py \     --prompt "Find the latest blog post title on example.com" \     --start-url "https://example.com" \     --turn-limit 6   ``` ## Browser selection - Default: Playwright's bundled Chromium (no env vars required).- Choose a channel (Chrome/Edge) with `COMPUTER_USE_BROWSER_CHANNEL`.- Use a custom Chromium-based executable (e.g., Brave) with `COMPUTER_USE_BROWSER_EXECUTABLE`. If both are set, `COMPUTER_USE_BROWSER_EXECUTABLE` takes precedence. ## Core workflow (agent loop) 1. Capture a screenshot and send the user goal + screenshot to the model.2. Parse `function_call` actions in the response.3. Execute each action in Playwright.4. If a `safety_decision` is `require_confirmation`, prompt the user before executing.5. Send `function_response` objects containing the latest URL + screenshot.6. Repeat until the model returns only text (no actions) or you hit the turn limit. ## Operational guidance - Run in a sandboxed browser profile or container.- Use `--exclude` to block risky actions you do not want the model to take.- Keep the viewport at 1440x900 unless you have a reason to change it. ## Resources - Script: `scripts/computer_use_agent.py`- Reference notes: `references/google-computer-use.md`- Env template: `env.example`