browser-use--browser-use/skills/open-source/references/tools.md

Tools & Custom Actions

Table of Contents

• Quick Example
• Adding Custom Tools
• Injectable Parameters
• Available Default Tools
• Removing Tools
• Tool Response (ActionResult)

---

Quick Example

from browser_use import Tools, ActionResult, BrowserSession

tools = Tools()

@tools.action('Ask human for help with a question')
async def ask_human(question: str, browser_session: BrowserSession) -> ActionResult:
    answer = input(f'{question} > ')
    return ActionResult(extracted_content=f'The human responded with: {answer}')

agent = Agent(task='Ask human for help', llm=llm, tools=tools)

Warning: Parameter MUST be named browser_session: BrowserSession, not browser: Browser. Agent injects by name matching — wrong name fails silently.

Adding Custom Tools

@tools.action(description='Fill out banking forms', allowed_domains=['https://mybank.com'])
async def fill_bank_form(account_number: str) -> ActionResult:
    return ActionResult(extracted_content=f'Filled form for account {account_number}')

Decorator parameters:

• description (required): What the tool does — LLM uses this to decide when to call
• allowed_domains: Domains where tool can run (default: all)

Pydantic Input

from pydantic import BaseModel, Field

class Car(BaseModel):
    name: str = Field(description='Car name, e.g. "Toyota Camry"')
    price: int = Field(description='Price in USD')

@tools.action(description='Save cars to file')
def save_cars(cars: list[Car]) -> str:
    with open('cars.json', 'w') as f:
        json.dump([c.model_dump() for c in cars], f)
    return f'Saved {len(cars)} cars'

Browser Interaction in Custom Tools

@tools.action(description='Click submit button via CSS selector')
async def click_submit(browser_session: BrowserSession):
    page = await browser_session.must_get_current_page()
    elements = await page.get_elements_by_css_selector('button[type="submit"]')
    if not elements:
        return ActionResult(extracted_content='No submit button found')
    await elements[0].click()
    return ActionResult(extracted_content='Clicked!')

Injectable Parameters

The agent fills function parameters by name. These special names are auto-injected:

Parameter Name	Type	Description
browser_session	BrowserSession	Current browser session (CDP access)
cdp_client		Direct Chrome DevTools Protocol client
page_extraction_llm	BaseChatModel	The LLM passed to agent
file_system	FileSystem	File system access
available_file_paths	list[str]	Files available for upload/processing
has_sensitive_data	bool	Whether action contains sensitive data

Page Methods (via browser_session)

page = await browser_session.must_get_current_page()

# CSS selector
elements = await page.get_elements_by_css_selector('button.submit')

# LLM-powered (natural language)
element = await page.get_element_by_prompt("login button", llm=page_extraction_llm)
element = await page.must_get_element_by_prompt("login button", llm=page_extraction_llm)  # raises if not found

Available Default Tools

Source: tools/service.py

Navigation & Browser Control

• search — Search queries (DuckDuckGo, Google, Bing)
• navigate — Navigate to URLs
• go_back — Go back in history
• wait — Wait for specified seconds

Page Interaction

• click — Click elements by index
• input — Input text into form fields
• upload_file — Upload files
• scroll — Scroll page up/down
• find_text — Scroll to specific text
• send_keys — Send keys (Enter, Escape, Tab, etc.)

JavaScript

• evaluate — Execute custom JS (shadow DOM, selectors, extraction)

Tab Management

• switch — Switch between tabs
• close — Close tabs

Content Extraction

• extract — Extract data using LLM

Visual

• screenshot — Request screenshot in next browser state

Form Controls

• dropdown_options — Get dropdown values
• select_dropdown — Select dropdown option

File Operations

• write_file — Write to files
• read_file — Read files
• replace_file — Replace text in files

Task Completion

• done — Complete the task (always available)

Removing Tools

tools = Tools(exclude_actions=['search', 'wait'])
agent = Agent(task='...', llm=llm, tools=tools)

Tool Response

Simple Return

@tools.action('My tool')
def my_tool() -> str:
    return "Task completed successfully"

ActionResult (Full Control)

@tools.action('Advanced tool')
def advanced_tool() -> ActionResult:
    return ActionResult(
        extracted_content="Main result",
        long_term_memory="Remember this for all future steps",
        error="Something went wrong",
        is_done=True,
        success=True,
        attachments=["file.pdf"],
    )

ActionResult Fields

Field	Default	Description
extracted_content	None	Main result passed to LLM
include_extracted_content_only_once	False	Show large content only once, then drop
long_term_memory	None	Always included in LLM input for all future steps
error	None	Error message (auto-caught exceptions set this)
is_done	False	Tool completes entire task
success	None	Task success (only with is_done=True)
attachments	None	Files to show user
metadata	None	Debug/observability data

Context Control Strategy

1. Short content, always visible: Return string
2. Long content shown once + persistent summary: extracted_content + include_extracted_content_only_once=True + long_term_memory
3. Never show, just remember: Use long_term_memory alone