An advanced AI-driven browser automation tool that leverages LLMs to navigate, interact with, and extract structured data from any website using a real Chromium instance.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install alex-browser-use
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install alex-browser-use using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is browser-use?
The browser-use skill is a high-performance automation framework designed for Openclaw Skills that utilizes the browser-use library to drive a real Chromium browser. By integrating LLM agents, this skill can perform complex, multi-step web tasks such as filling forms, clicking elements, and navigating sophisticated UIs just like a human user. It is specifically engineered to handle JavaScript-heavy sites and dynamic content that traditional static scrapers often fail to process.
This skill excels in scenarios where traditional API access is unavailable or restricted. It includes built-in mechanisms for anti-detection, ensuring that automated sessions remain stealthy and avoid being flagged as bots. Whether you are automating account registrations or extracting structured data from complex web interfaces, this tool provides the necessary abstraction to turn natural language instructions into reliable browser actions within the Openclaw Skills ecosystem.
browser-use Use Cases
- Automating end-to-end web workflows including logins and multi-step form submissions.
- Scraping data from dynamic, JavaScript-rendered pages that require real-time user interaction.
- Registering for internet services using the Alex Chen persona for consistent identity management.
- Solving CAPTCHAs and bypassing advanced browser-based security checks using human-like behaviors.
- Extracting structured data from web UIs into machine-readable formats using Pydantic schemas.
- Executing any task that requires the visual context and full interaction capabilities of a real browser.
How browser-use Works
- Initialize the automation environment using the Openclaw Skills framework and the browser-use library.
- Configure a stealth session to harden the Chromium instance against bot detection mechanisms.
- Define the specific task and select a supported LLM such as Google Gemini or Anthropic Claude.
- The agent analyzes the live web page DOM and plans actions like typing, clicking, and scrolling based on visual and structural cues.
- The skill applies human-like behaviors, including random delays and variable typing speeds, to maintain stealth and avoid rate limiting.
- The final result is extracted as structured data or a summary, depending on the user's requirements.
browser-use Setup
To get started with browser-use in your Openclaw Skills environment, ensure you have the necessary dependencies installed. Use the uv package manager to execute your scripts to ensure proper environment management.
uv run python your_script.py
Configure your LLM provider. If using Google Gemini via Cloud Code Assist, ensure your OAuth is authenticated. For Anthropic, set your API key in your environment:
export ANTHROPIC_API_KEY='your-key-here'
Ensure you have Chromium installed and the path set if it is not in the default location:
export CHROMIUM_PATH='/usr/bin/chromium-browser'
Set the headless mode preference if you wish to watch the browser actions locally:
export BROWSER_USE_HEADLESS='false'
browser-use Data Schema & Taxonomy
The skill organizes data through Pydantic models for structured extraction and maintains session state via cookie injection. Below is the metadata and data organization structure used by this skill:
| Feature | Description |
|---|---|
| Output Schema | Uses Pydantic classes to define the exact shape of extracted web data for reliability. |
| Session Cookies | Supports JSON-based cookie lists for pre-authenticated sessions on platforms like X or LinkedIn. |
| Sensitive Data | A secure dictionary mapping for credentials that prevents leaking secrets to the LLM during processing. |
| Identity Profile | Utilizes a default persona (Alex Chen) for consistent registration and interaction workflows. |
browser-use Advanced Features
- Anti-detection hardening via stealth_session() which spoofs navigator.webdriver and hides automation flags.
- Human-like interaction emulation with variable typing delays and randomized action timeouts to bypass bot filters.
- Direct URL navigation capability to bypass honeypot landing pages and complex homepage redirects.
- Multi-model support fully compatible with Gemini 2.5 and Claude 3.5/4.5 for high-reasoning tasks.
- Sensitive data masking allows the agent to handle credentials without them being exposed in the prompt history.
- Support for cookie injection enables the skill to maintain persistent, authenticated sessions across multiple runs.
SKILL.md
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