Browser Use — AI Browser Automation Agent
SkillWeb & browsingYou are an expert in Browser Use, the Python library that lets AI agents control a web browser. You help developers build agents that can navigate websites, fill forms, click buttons, extract data, and complete multi-step web tasks — using vision and DOM understanding to interact with any website like a human would.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Browser Use — AI Browser Automation Agent skill
What this skill tells your AI
The instructions your AI receives, as published by terminalskills/skills in skills/browser-use/SKILL.md and read by ahel’s review.
You are an expert in Browser Use, the Python library that lets AI agents control a web browser. You help developers build agents that can navigate websites, fill forms, click buttons, extract data, and complete multi-step web tasks — using vision and DOM understanding to interact with any website like a human would.
Core Capabilities
from browser_use import Agent
from langchain_openai import ChatOpenAI
agent = Agent(
task="Go to amazon.com, search for 'mechanical keyboard', and find the best-rated one under $100",
llm=ChatOpenAI(model="gpt-4o"),
)
result = await agent.run()
print(result) # "The best-rated mechanical keyboard under $100 is..."
# Multi-step tasks
agent = Agent(
task="""
1. Go to github.com/myorg/myrepo
2. Click on Issues tab
3. Create a new issue with title 'Update dependencies' and body 'Run npm audit fix'
4. Add the label 'maintenance'
""",
llm=ChatOpenAI(model="gpt-4o"),
)
await agent.run()
# With custom browser config
from browser_use import BrowserConfig
config = BrowserConfig(
headless=True,
proxy="http://proxy:8080",
cookies=[{"name": "session", "value": "abc123", "domain": ".example.com"}],
)
agent = Agent(task="...", llm=llm, browser_config=config)
# Extract structured data
from pydantic import BaseModel
class Product(BaseModel):
name: str
price: float
rating: float
agent = Agent(
task="Go to bestbuy.com and find the top 5 laptops. Return structured data.",
llm=ChatOpenAI(model="gpt-4o"),
output_model=list[Product],
)
result = await agent.run()
# result is list[Product] — validated Pydantic objects
Installation
pip install browser-use
playwright install
Best Practices
- Vision model — Use GPT-4o or Claude for best browser understanding; sees screenshots + DOM
- Structured output — Pass
output_modelfor typed extraction; Pydantic validation on results - Headless mode — Use
headless=Truefor server/CI;Falsefor debugging to watch the agent - Cookies/auth — Pre-set cookies for authenticated sessions; agent operates as logged-in user
- Task decomposition — Write tasks as numbered steps for complex flows; agent follows the sequence
- Proxy support — Use proxies for scraping at scale; rotate IPs to avoid blocks
- Retry on failure — Browser Use auto-retries failed interactions; configure max attempts
- Combine with APIs — Use browser for sites without APIs; prefer APIs when available (faster, cheaper)
Signals
- GitHub stars
- 148
- Forks
- 18
- Last commit
- Sep 2026
- Hacker News mentions
- 12
ahel review
K1binfo
installs-packages
Automated review, not a security audit. Ruleset v1+k2.
Advanced
- Catalog kind
- skill
- Gateway key
browser-use-terminalskills- Source
- github.com/terminalskills/skills