What problem does it solve? Manually interacting with websites for testing, scraping, or repetitive form submission is slow and error-prone, and raw DOM parsing consumes excessive context for AI agents. This Skill provides a CLI-driven browser automation workflow where compact element refs replace verbose HTML parsing. ## Core Features & Use Cases - Snapshot-Based Interaction: Capture interactive elements as compact refs (@e1, @e2) and click, fill, select, or check them directly, reducing token usage compared to full DOM parsing. - Session & State Management: Run isolated named sessions in parallel, save and restore authentication state, and persist cookies across runs. - Capture & Verification: Take annotated screenshots, record video, save pages as PDF, and diff snapshots or screenshots to verify changes. - Use Case: An AI agent needs to log into a web app, fill out a multi-field form, and verify the submission succeeded. It opens the login page, snapshots to get refs, fills credentials, saves the auth state, then reuses that state for subsequent automated runs. ## Quick Start Use the agent-browser skill to open https://example.com/login, fill in the email and password fields, click submit, and take a screenshot of the result.