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agent-browser

Automate browser interactions using compact element references across a 4-phase lifecycle.

Updated Jan 24, 2026
Search Tags:#playwright#ui-testing#browser-automation#agent-browser#llm-context#ref-handling
One-click install
npx skills add https://github.com/pikakit/agent-skills --skill agent-browser-pikakit
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: agent-browser
Source: https://github.com/pikakit/agent-skills/tree/main/.agent/skills/agent-browser
Command: npx skills add https://github.com/pikakit/agent-skills --skill agent-browser-pikakit

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

AI agents often struggle with heavy DOM payloads and unstable selectors during browser tasks. This skill provides an efficient, context-sensitive browser automation layer that uses compact element references to minimize context size while preserving reliability.

Core Features & Use Cases

  • 4-phase lifecycle: Navigate → Snapshot → Interact → Verify, with stable @refs for reliable page interactions.
  • Isolation & security: Each session runs in an isolated browser context, preventing cross-session data leakage.
  • Use cases: Long autonomous browser sessions, web UI testing, automated data collection, and AI-assisted web interactions.

Quick Start

Open a URL, snapshot the page to obtain element references, interact via references, and verify the result.

Frequently Asked Questions about agent-browser

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

FAQPage Schema
How do I reduce context size when automating browser tasks with Playwright?▼

To reduce context size during browser automation, this skill uses compact element references instead of raw DOM payloads, minimizing token load while maintaining reliable page interactions. It snapshots the page to generate stable @refs for deterministic actions.

What is the best way to run long autonomous browser sessions without data leakage?▼

The best way to run long autonomous browser sessions safely is by using isolated browser contexts. This skill executes each session independently, preventing cross-session data leakage while sustaining extended AI-driven web workflows.

How does the 4-phase lifecycle work for AI web interactions?▼

The 4-phase lifecycle works by guiding AI web interactions through Navigate, Snapshot, Interact, and Verify stages. This structured approach ensures observable results by capturing page state, interacting via stable @refs, and validating outcomes.

Can I use this for UI testing across modern web apps?▼

Yes, you can use this for UI testing across modern web apps. The structured @ref system replaces unstable selectors, providing deterministic and observable results that make automated web workflows highly reliable.

Why does my AI agent struggle with heavy DOM payloads during browser automation?▼

AI agents struggle with heavy DOM payloads because they overwhelm the context window and cause unstable selector targeting. This skill solves the problem by implementing a context-sensitive layer that generates compact element references.

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