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browser-use/docs/customize/tools/response.mdx
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2025-08-26 18:13:11 -07:00

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---
title: "Tool Response"
description: ""
icon: "arrow-turn-down-left"
mode: "wide"
---
Tools return results using `ActionResult` or simple strings.
## Return Types
```python
@tools.action('My tool')
def my_tool() -> str:
return "Task completed successfully"
@tools.action('Advanced tool')
def advanced_tool() -> ActionResult:
return ActionResult(
extracted_content="Main result",
long_term_memory="Remember this info",
error="Something went wrong",
is_done=True,
success=True,
attachments=["file.pdf"],
)
```
## ActionResult Properties
- `extracted_content` (default: `None`) - Main result passed to LLM, this is equivalent to returning a string.
- `include_extracted_content_only_once` (default: `False`) - Set to `True` for large content to include it only once in the LLM input.
- `long_term_memory` (default: `None`) - This is always included in the LLM input for all future steps.
- `error` (default: `None`) - Error message, we catch exceptions and set this automatically. This is always included in the LLM input.
- `is_done` (default: `False`) - Tool completes entire task
- `success` (default: `None`) - Task success (only valid with `is_done=True`)
- `attachments` (default: `None`) - Files to show user
- `metadata` (default: `None`) - Debug/observability data
## Why `extracted_content` and `long_term_memory`?
With this you control the context for the LLM.
### 1. Include short content always in context
```python
def simple_tool() -> str:
return "Hello, world!" # Keep in context for all future steps
```
### 2. Show long content once, remember subset in context
```python
return ActionResult(
extracted_content="[500 lines of product data...]", # Shows to LLM once
include_extracted_content_only_once=True, # Never show full output again
long_term_memory="Found 50 products" # Only this in future steps
)
```
We save the full `extracted_content` to files which the LLM can read in future steps.
### 3. Dont show long content, remember subset in context
```python
return ActionResult(
extracted_content="[500 lines of product data...]", # The LLM never sees this because `long_term_memory` overrides it and `include_extracted_content_only_once` is not used
long_term_memory="Saved user's favorite products", # This is shown to the LLM in future steps
)
```
## Terminating the Agent
Set `is_done=True` to stop the agent completely. Use when your tool finishes the entire task:
```python
@tools.action(description='Complete the task')
def finish_task() -> ActionResult:
return ActionResult(
extracted_content="Task completed!",
is_done=True, # Stops the agent
success=True # Task succeeded
)
```