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am-will/codex-skills1.2k installs

gemini-computer-use

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.

How do I install this agent skill?

npx skills add https://github.com/am-will/codex-skills --skill gemini-computer-use
view source ↗

Is this agent skill safe to install?

  • Gen Agent Trust Hubpass

    This skill implements a browser automation agent using Gemini Computer Use. It is vulnerable to indirect prompt injection from malicious content on websites visited by the agent.

  • Socketpass

    No alerts

  • Snykwarn

    Risk: MEDIUM · 1 issue

  • Runlayerwarn

    4/4 files flagged

  • ZeroLeakspass

    Score: 93/100 · 2 sections analyzed

What does this agent skill do?

Gemini Computer Use

Quick start

  1. Source the env file and set your API key:

    cp env.example env.sh
    $EDITOR env.sh
    source env.sh
    
  2. Create a virtual environment and install dependencies:

    python -m venv .venv
    source .venv/bin/activate
    pip install google-genai playwright
    playwright install chromium
    
  3. Run the agent script with a prompt:

    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

Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.

<a href="https://skillzs.dev/skills/am-will/codex-skills/gemini-computer-use">View gemini-computer-use on skillZs</a>