What problem does it solve?
Web pages contain large, noisy DOMs that make automated scraping and interaction brittle and expensive for AI agents. This Skill reduces context size by using AI-optimized accessibility-tree snapshots and stable element references so agents can navigate, fill forms, click controls, and extract data reliably.
Core Features & Use Cases
- AI-optimized snapshots with element refs: produce compact accessibility trees that replace full DOM dumps with stable refs (e.g., @e1) for deterministic actions.
- Full browser control: navigation (open, back, forward, reload, close), interaction (click, fill, type, press, hover, select, check), and information extraction (get text, html, value, attrs, title, url).
- Session and workflow management: isolated sessions for parallel tasks, session state save/load, multi-session swarm workflows for coordinated scraping or testing.
- Integration and automation: screenshot support, snapshot flags for interactive-only or compact output, MCP tool namespacing (browser/*), memory storage and hooks for pre/post task orchestration.
- Use cases: automated login and form submission, product data extraction from listings, end-to-end UI smoke tests, and authenticated multi-session scraping.
Quick Start
Open a URL, take an interactive snapshot, and extract product names and prices using the element refs from the snapshot.