skill-agent-browser

OpenClaw skill for agent-browser — The best browser automation CLI for AI agents.

Why This Is Better

Deterministic Refs (Game-Changer for AI)

Traditional browser automation uses CSS selectors or coordinates that break constantly. agent-browser uses deterministic refs from accessibility trees:

# Get snapshot — each element gets a stable ref
agent-browser snapshot -i --json
# Output: - button "Submit" [ref=e2]

# Use that ref — it NEVER changes for that element
agent-browser click @e2

Why this matters:

• CSS selectors break when websites update
• Coordinates fail on responsive layouts
• Vision-based automation is slow and expensive
• Refs just work — point to the exact element from your snapshot

Built for AI Agents (Not Developers)

	Traditional Tools	agent-browser
Element targeting	Fragile selectors	Deterministic refs
Page understanding	Raw HTML soup	Semantic accessibility tree
Output	Text logs	Structured JSON
Speed	Slow per command	Fast daemon architecture
Designed for	Human developers	AI agents

Fast Architecture

• Rust CLI — Native binary for instant command parsing
• Node.js Daemon — Browser stays warm between commands
• First launch: ~2 seconds
• Subsequent commands: ~100 milliseconds

Installation

Prerequisites

npm install -g agent-browser
agent-browser install  # Downloads Chromium (~30 seconds)

Install the Skill

cd ~/.openclaw/skills  # or ~/clawd/skills
git clone https://github.com/clawdbrunner/skill-agent-browser.git agent-browser

The AI Workflow

The pattern that makes agent-browser shine:

# 1. Navigate
agent-browser open example.com

# 2. Get structured snapshot (AI "sees" the page)
agent-browser snapshot -i --json

# 3. AI picks refs, executes actions
agent-browser click @e1
agent-browser fill @e2 "user@example.com"

# 4. Verify state changed
agent-browser snapshot -i --json

# 5. Done
agent-browser close

Quick Reference

Essential Commands

# Navigation
agent-browser open <url> [--json] [--headed]

# Snapshot (the killer feature)
agent-browser snapshot [-i] [-c] [--json]              # Interactive, compact, JSON

# Interaction with refs
agent-browser click @e1
agent-browser fill @e2 "text"
agent-browser type @e2 "text"                          # Without clearing
agent-browser press Enter

# State checks
agent-browser get text @e1
agent-browser get url
agent-browser is visible @e2

# Session management
agent-browser --session <name> open <url>            # Isolated session
agent-browser --profile <path> open <url>            # Persistent cookies
agent-browser close

Snapshot Options (Control What AI Sees)

Flag	Purpose
-i	Interactive elements only — recommended
-c	Compact (remove empty elements)
-d <n>	Limit tree depth
-s <sel>	Scope to CSS selector
--json	Machine-readable JSON — essential for AI

Best for AI: agent-browser snapshot -i -c --json

Selector Strategies (Ranked)

1. Refs (Best): agent-browser click @e2
2. Semantic: agent-browser find role button click --name "Submit"
3. CSS: agent-browser click "#submit"
4. Text/XPath (Last resort): agent-browser click "text=Submit"

Example: Complex Form Automation

# Open billing portal
agent-browser open https://portal.aeronetpr.com

# Login flow using refs from snapshot
agent-browser fill @e1 "username"
agent-browser fill @e2 "password"
agent-browser click @e3

# Wait for navigation, get new state
sleep 2
agent-browser snapshot -i --json

# Add credit card
agent-browser click @e24                                    # "Add new credit card"
agent-browser fill @e10 "John Smith"                       # Name on card
agent-browser fill @e11 "4111111111111111"                 # Card number (test)
agent-browser fill @e12 "12/2030"                          # Expiration
agent-browser fill @e13 "123"                              # CVV
agent-browser fill @e14 "123 Main Street"                  # Address
agent-browser fill @e260 "San Juan"                        # City
agent-browser fill @e322 "00907"                           # ZIP
agent-browser click @e324                                  # Submit

# Verify
agent-browser snapshot -i --json

# Cleanup
agent-browser close

Documentation

See SKILL.md for complete documentation including:

• Detailed comparison to other tools
• All commands and options
• Tips for AI agents
• When to use this vs built-in browser tools

Comparison to Alternatives

Tool	agent-browser Advantage
Puppeteer/Playwright	Purpose-built for AI, deterministic refs vs brittle selectors
Selenium	10x faster, modern architecture
browser-use	Better refs system, faster CLI
Vision-based	100x cheaper, 10x faster, no API calls
OpenClaw browser	Better for complex multi-step flows

When to Use This

Use agent-browser for:

• Multi-step web workflows
• Complex form filling
• Reliable, repeatable automation
• Dynamic/modern web apps
• Cost-sensitive operations (no vision APIs)

Use OpenClaw's built-in browser tool for:

• Simple single-page checks
• Quick screenshots
• Already-authenticated Chrome sessions

Links

• Upstream project: https://github.com/vercel-labs/agent-browser
• This skill: https://github.com/clawdbrunner/skill-agent-browser
• Releases: https://github.com/clawdbrunner/skill-agent-browser/releases

License

MIT