Agent Browser

What This Skill Does

The Agent Browser skill is a high-performance, Rust-based headless browser automation tool designed specifically for AI agents. It serves as the primary interface between an OpenClaw agent and the web. By providing a structured command-line interface, the tool allows agents to navigate complex websites, parse the Document Object Model (DOM) into simplified reference-based representations, and execute precise interactions like clicking, typing, and form submission. Unlike standard browser automation tools that require heavy scripting, this skill provides a stateless, command-driven approach that minimizes overhead and maximizes the reliability of agent-led tasks.

Installation

To integrate this skill into your OpenClaw environment, use the CLI provided by the platform:

clawhub install openclaw/skills/skills/thesethrose/agent-browser

Once installed, ensure your system meets the requirements for the underlying engine. It is recommended to run the post-installation dependency command to ensure the headless environment is correctly configured:

agent-browser install --with-deps

Use Cases

• Autonomous Web Research: Agents can use the browser to visit research papers, documentation sites, or news portals, using snapshot -i to identify relevant links or data points.
• Form Automation and Data Entry: Automate repetitive web-based tasks by filling in input fields via @refs and triggering submission buttons accurately.
• Dynamic Content Monitoring: Easily check page states, verify element presence, or scrape specific data points like product prices or status updates from dynamic dashboards.
• Headless Testing: Integrate the agent into a CI/CD pipeline to verify UI states or confirm functional paths within a web application without needing manual intervention.

Example Prompts

1. "Open https://github.com/trending, take an interactive snapshot, and tell me the name of the top repository in the list."
2. "Go to the login page, fill in the email field with '[email protected]', enter the password, and click the submit button."
3. "Navigate to the target website, count how many articles appear on the home page, and get the text of the first one."

Tips & Limitations

• Use Interactive Snapshots: Always prefer snapshot -i over a full snapshot. It limits output to interactable elements, significantly reducing the context size for the AI and preventing 'token soup'.
• Reference Stability: The @ref tokens (e.g., @e1) are valid for the current state. If you navigate to a new page, always run a fresh snapshot to get valid references for the new DOM.
• Performance: While Rust-based, heavy page loads or complex JavaScript-rendered sites may cause slight delays. Use get count or get attr to minimize the data returned to the agent context.
• Limitations: This is a headless environment; certain web elements like complex canvas-based graphics or highly specific CAPTCHAs may pose challenges for standard interaction commands.