agent-browser

Automate browser interactions for navigation, form filling, and data extraction.

Updated Aug 27, 2026

Search Tags:#automation #cli #web-testing #ai-agents #data-extraction #browser-automation

Ready to run

npx skills add https://github.com/TheBoomerDev/feedback_proyect --skill agent-browser-theboomerdev

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: agent-browser
Source: https://github.com/TheBoomerDev/feedback_proyect/tree/main/.agents/skills/agent-browser
Command: npx skills add https://github.com/TheBoomerDev/feedback_proyect --skill agent-browser-theboomerdev

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

AI agents often struggle with interacting with web pages in an automated, reliable way. This Skill provides a CLI tool to drive browser actions, capture structure, and extract data, enabling deterministic automation without manual scripting.

Core Features & Use Cases

Open URLs and navigate pages for automated testing and data collection.
Snapshot-based element refs (@e1, @e2, etc.) to reduce prompt size and increase reliability.
Form interaction and data extraction across web apps, dashboards, and SaaS platforms.
Session management and authentication patterns including state persistence and auth vaults to reuse credentials securely.
Templates and references for rapid workflow creation and deep learning guidance.

Quick Start

Open a website, snapshot the page to obtain element refs, then fill and submit a form.

Frequently Asked Questions about agent-browser

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I automate browser tasks with a CLI for AI agents?▼

Browser automation for AI agents is handled through a CLI tool that drives page navigation, form filling, element clicking, and data extraction. It applies to automated web testing and QA validation across dynamic web apps.

What is snapshot-based element referencing in web testing automation?▼

Snapshot-based element refs (@e1, @e2) capture page structure to reduce prompt size and increase reliability. This mechanism allows AI agents to deterministically target elements for form interaction and data extraction.

How do I manage authentication and sessions for automated browser data extraction?▼

Session management and authentication patterns provide state persistence and auth vaults to securely reuse credentials. This enables AI agents to maintain authenticated sessions across multiple browser automation workflows.

Does CLI browser automation work for filling and submitting forms on dynamic web apps?▼

CLI browser automation supports form interaction and data extraction across dynamic web apps, dashboards, and SaaS platforms. You can open URLs, snapshot pages to obtain element refs, then fill and submit forms automatically.

Are there templates available for rapid browser automation workflow creation?▼

Templates and references are included for rapid workflow creation and deep learning guidance. These templates help structure common browser automation patterns like navigation, form interaction, and data extraction tasks.

What are the limitations of using CLI-driven browser automation for QA validation?▼

CLI-driven browser automation provides deterministic execution without manual scripting, but complex dynamic web apps may require careful snapshot management. The tool focuses on navigation, form filling, and data extraction tasks rather than visual regression testing.