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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.

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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.

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Install for OpenClaw

Quick setup
  1. Download the package from Yavira.
  2. Extract the archive and review SKILL.md first.
  3. Import or place the package into your OpenClaw setup.

Requirements

Target platform
OpenClaw
Install method
Manual import
Extraction
Extract archive
Prerequisites
OpenClaw
Primary doc
SKILL.md

Package facts

Download mode
Yavira redirect
Package format
ZIP package
Source platform
Tencent SkillHub
What's included
SKILL.md, references/google-computer-use.md, scripts/computer_use_agent.py

Validation

  • Use the Yavira download entry.
  • Review SKILL.md after the package is downloaded.
  • Confirm the extracted package contains the expected setup assets.

Install with your agent

Agent handoff

Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.

  1. Download the package from Yavira.
  2. Extract it into a folder your agent can access.
  3. Paste one of the prompts below and point your agent at the extracted folder.
New install

I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.

Upgrade existing

I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.

Trust & source

Release facts

Source
Tencent SkillHub
Verification
Indexed source record
Version
1.0.0

Documentation

ClawHub primary doc Primary doc: SKILL.md 5 sections Open source page

Quick start

Source the env file and set your API key: cp env.example env.sh $EDITOR env.sh source env.sh Create a virtual environment and install dependencies: python -m venv .venv source .venv/bin/activate pip install google-genai playwright playwright install chromium 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)

Capture a screenshot and send the user goal + screenshot to the model. Parse function_call actions in the response. Execute each action in Playwright. If a safety_decision is require_confirmation, prompt the user before executing. Send function_response objects containing the latest URL + screenshot. 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

Category context

Code helpers, APIs, CLIs, browser automation, testing, and developer operations.

Source: Tencent SkillHub

Largest current source with strong distribution and engagement signals.

Package contents

Included in package
2 Docs1 Scripts
  • SKILL.md Primary doc
  • references/google-computer-use.md Docs
  • scripts/computer_use_agent.py Scripts