---
title: AI Agent Tool node documentation
description: Learn how to use the AI Agent Tool node in n8n. Follow technical documentation to integrate the AI Agent Tool node into your workflows.
contentType: [integration, reference]
priority: high
---

# AI Agent Tool node

The AI Agent Tool node allows a root-level [agent](/glossary.md#ai-agent) in your workflow to call other agents as tools to simplify multi-agent orchestration.

The [primary agent](/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.agent/tools-agent.md) can supervise and delegate work to AI Agent Tool nodes that specialize in different tasks and knowledge. This allows you to use multiple agents in a single workflow without the complexity of managing context and variables that sub-workflows require. You can nest AI Agent Tool nodes into multiple layers for more complex multi-tiered use cases.

On this page, you'll find the node parameters for the AI Agent Tool node, and links to more resources.

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## Node parameters

Configure the AI Agent Tool node using these parameters:

* **Description**: Give a description to the LLM of this agent's purpose and scope of responsibility. A good, specific description tells the parent agent when to delegate tasks to this agent for processing.
* **Prompt (User Message)**: The prompt to the LLM explaining what actions to perform and what information to return.
* **Require Specific Output Format**: Whether you want the node to require a specific output format. When turned on, n8n prompts you to connect one of the output parsers [described on the main agent page](/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.agent/tools-agent.md#require-specific-output-format).
* **Enable Fallback Model**: Whether to enable a fallback model. When enabled, n8n prompts you to connect a backup chat model to use in case the primary model fails or isn't available.

## Node options

Refine the AI Agent Tool node's behavior using these options:

* **System Message**: A message to send to the agent before the conversation starts.
* **Max Iterations**: The maximum number of times the model should run to generate a response before stopping.
* **Return Intermediate Steps**: Whether to include intermediate steps the agent took in the final output.
* **Automatically Passthrough Binary Images**: Whether binary images should be automatically passed through to the agent as image type messages.
* **Batch Processing**: Whether to enable the following batch processing options for rate limiting:
	* **Batch Size**: The number of items to process in parallel. This helps with rate limiting but may impact the log output ordering.
	* **Delay Between Batches**: The number of milliseconds to wait between batches.

## Templates and examples

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## Dynamic parameters for tools with `$fromAI()`

To learn how to dynamically populate parameters for app node tools, refer to [Let AI specify tool parameters with `$fromAI()`](/advanced-ai/examples/using-the-fromai-function.md).