**System tools** enable your assistant to update the internal state of a conversation. Unlike [webhook tools](/guides/elevenagents-customization-tools-webhook-tools) or [client tools](/guides/elevenagents-customization-tools-client-tools), system tools don't make external API calls or trigger client-side functions—they modify the internal state of the conversation without making external calls.

## Overview

Some applications require agents to control the flow or state of a conversation.
System tools provide this capability by allowing the assistant to perform actions related to the state of the call that don't require communicating with external servers or the client.

### Available system tools

#### [End call](/guides/elevenagents-customization-tools-system-tools-end-call)

Let your agent automatically terminate a conversation when appropriate conditions are met.

#### [Language detection](/guides/elevenagents-customization-tools-system-tools-language-detection)

Enable your agent to automatically switch to the user's language during conversations.

#### [Agent transfer](/guides/elevenagents-customization-tools-system-tools-agent-transfer)

Seamlessly transfer conversations between AI agents based on defined conditions.

#### [Transfer to number](/guides/elevenagents-customization-tools-system-tools-transfer-to-number)

Transfer calls to external phone numbers or SIP URIs.

#### [Skip turn](/guides/elevenagents-customization-tools-system-tools-skip-turn)

Enable the agent to skip their turns if the LLM detects the agent should not speak yet.

#### [Play keypad touch tone](/guides/elevenagents-customization-tools-system-tools-play-keypad-touch-tone)

Enable agents to play DTMF tones to interact with automated phone systems and navigate menus.

#### [Voicemail detection](/guides/elevenagents-customization-tools-system-tools-voicemail-detection)

Enable agents to automatically detect voicemail systems and optionally leave messages.

#### [Update state](/guides/elevenagents-customization-tools-system-tools-update-state)

Let your agent update dynamic variables mid-conversation using expressions.

## Implementation

When creating an agent via API, you can add system tools to your agent configuration. Here's how to implement both the end call and language detection tools:

## Custom LLM integration

When using a custom LLM with ElevenLabs agents, system tools are exposed as function definitions that your LLM can call. Each system tool has specific parameters and trigger conditions:

### Available system tools

#### End call

**Purpose**: Automatically terminate conversations when appropriate conditions are met.

**Trigger conditions**: The LLM should call this tool when:

- The main task has been completed and user is satisfied
- The conversation reached natural conclusion with mutual agreement
- The user explicitly indicates they want to end the conversation

**Parameters**:

- `reason` (string, required): The reason for ending the call
- `message` (string, optional): A farewell message to send to the user before ending the call

**Function call format**:

```json
{
  "type": "function",
  "function": {
    "name": "end_call",
    "arguments": "{\"reason\": \"Task completed successfully\", \"message\": \"Thank you for using our service. Have a great day!\"}"
  }
}
```

**Implementation**: Configure as a system tool in your agent settings. The LLM will receive detailed instructions about when to call this function.

Learn more: [End call tool](/guides/elevenagents-customization-tools-system-tools-end-call)

#### Language detection

**Purpose**: Automatically switch to the user's detected language during conversations.

**Trigger conditions**: The LLM should call this tool when:

- User speaks in a different language than the current conversation language
- User explicitly requests to switch languages
- Multi-language support is needed for the conversation

**Parameters**:

- `reason` (string, required): The reason for the language switch
- `language` (string, required): The language code to switch to (must be in supported languages list)

**Function call format**:

```json
{
  "type": "function",
  "function": {
    "name": "language_detection",
    "arguments": "{\"reason\": \"User requested Spanish\", \"language\": \"es\"}"
  }
}
```

**Implementation**: Configure supported languages in agent settings and add the language detection system tool. The agent will automatically switch voice and responses to match detected languages.

Learn more: [Language detection tool](/guides/elevenagents-customization-tools-system-tools-language-detection)

#### Agent transfer

**Purpose**: Transfer conversations between specialized AI agents based on user needs.

**Trigger conditions**: The LLM should call this tool when:

- User request requires specialized knowledge or different agent capabilities
- Current agent cannot adequately handle the query
- Conversation flow indicates need for different agent type

**Parameters**:

- `reason` (string, optional): The reason for the agent transfer
- `agent_number` (integer, required): Zero-indexed number of the agent to transfer to (based on configured transfer rules)

**Function call format**:

```json
{
  "type": "function",
  "function": {
    "name": "transfer_to_agent",
    "arguments": "{\"reason\": \"User needs billing support\", \"agent_number\": 0}"
  }
}
```

**Implementation**: Define transfer rules mapping conditions to specific agent IDs. Configure which agents the current agent can transfer to. Agents are referenced by zero-indexed numbers in the transfer configuration.

Learn more: [Agent transfer tool](/guides/elevenagents-customization-tools-system-tools-agent-transfer)

#### Transfer to number

**Purpose**: Seamlessly hand off conversations to human operators when AI assistance is insufficient.

**Trigger conditions**: The LLM should call this tool when:

- Complex issues requiring human judgment
- User explicitly requests human assistance
- AI reaches limits of capability for the specific request
- Escalation protocols are triggered

**Parameters**:

- `reason` (string, optional): The reason for the transfer
- `transfer_number` (string, required): The phone number to transfer to (must match configured numbers)
- `client_message` (string, required): Message read to the client while waiting for transfer
- `agent_message` (string, required): Message for the human operator receiving the call

**Function call format**:

```json
{
  "type": "function",
  "function": {
    "name": "transfer_to_number",
    "arguments": "{\"reason\": \"Complex billing issue\", \"transfer_number\": \"+15551234567\", \"client_message\": \"I'm transferring you to a billing specialist who can help with your account.\", \"agent_message\": \"Customer has a complex billing dispute about order #12345 from last month.\"}"
  }
}
```

**Implementation**: Configure transfer phone numbers and conditions. Define messages for both customer and receiving human operator. Works with both Twilio and SIP trunking.

Learn more: [Transfer to number tool](/guides/elevenagents-customization-tools-system-tools-transfer-to-number)

#### Skip turn

**Purpose**: Allow the agent to pause and wait for user input without speaking.

**Trigger conditions**: The LLM should call this tool when:

- User indicates they need a moment ("Give me a second", "Let me think")
- User requests pause in conversation flow
- Agent detects user needs time to process information

**Parameters**:

- `reason` (string, optional): Free-form reason explaining why the pause is needed

**Function call format**:

```json
{
  "type": "function",
  "function": {
    "name": "skip_turn",
    "arguments": "{\"reason\": \"User requested time to think\"}"
  }
}
```

**Implementation**: No additional configuration needed. The tool simply signals the agent to remain silent until the user speaks again.

Learn more: [Skip turn tool](/guides/elevenagents-customization-tools-system-tools-skip-turn)

#### Play keypad touch tone

**Parameters**:

- `reason` (string, optional): The reason for playing the DTMF tones (e.g., "navigating to extension", "entering PIN")
- `dtmf_tones` (string, required): The DTMF sequence to play. Valid characters: 0-9, \*, #, w (0.5s pause), W (1s pause)

**Function call format**:

```json
{
  "type": "function",
  "function": {
    "name": "play_keypad_touch_tone",
    "arguments": "{"reason": "Navigating to customer service", "dtmf_tones": "2"}"
  }
}
```

Learn more: [Play keypad touch tone tool](/guides/elevenagents-customization-tools-system-tools-play-keypad-touch-tone)

#### Voicemail detection

**Parameters**:

- `reason` (string, required): The reason for detecting voicemail (e.g., "automated greeting detected", "no human response")

**Function call format**:

```json
{
  "type": "function",
  "function": {
    "name": "voicemail_detection",
    "arguments": "{\"reason\": \"Automated greeting detected with request to leave message\"}"
  }
}
```

Learn more: [Voicemail detection tool](/guides/elevenagents-customization-tools-system-tools-voicemail-detection)

#### Update state

**Purpose**: Let the agent update one or more dynamic variables based on the conversation, without calling an external API.

**Trigger conditions**: The LLM should call this tool when:

- The conversation provides information that should be recorded (e.g. an escalation flag, a chosen option, a value the user provided)
- A configured state update depends on a value the LLM must judge or extract from the conversation

**Parameters**:

The function's parameters depend on how the tool is configured. Each configured state update that uses an LLM-extracted value adds one property to the schema, named after that update's dynamic variable and typed as `string`, `number`, or `boolean`. State updates built only from constants or other dynamic variables don't add any parameters.

**Function call format**:

```json
{
  "type": "function",
  "function": {
    "name": "update_state",
    "arguments": "{\"should_escalate\": true}"
  }
}
```

**Implementation**: The agent evaluates every configured expression using the extracted parameters plus the conversation's current dynamic variables, then assigns the results to the corresponding dynamic variables. No external request is made.

Learn more: [Update state tool](/guides/elevenagents-customization-tools-system-tools-update-state)

```python
from elevenlabs import AgentConfig, ConversationalConfig, ElevenLabs

elevenlabs = ElevenLabs(api_key="YOUR_API_KEY")

# Each system tool is keyed by name under built_in_tools.
# Leave "description" blank to use the default, tool-specific prompt.
response = elevenlabs.conversational_ai.agents.create(
    conversation_config=ConversationalConfig(
        agent=AgentConfig(
            prompt={
                "built_in_tools": {
                    "end_call": {
                        "type": "system",
                        "name": "end_call",
                        "description": "",
                        "params": {"system_tool_type": "end_call"},
                    },
                    "language_detection": {
                        "type": "system",
                        "name": "language_detection",
                        "description": "",
                        "params": {"system_tool_type": "language_detection"},
                    },
                }
            },
        ),
    ),
)
```

```javascript
import { ElevenLabsClient } from "@elevenlabs/elevenlabs-js";

const elevenlabs = new ElevenLabsClient({
  apiKey: "YOUR_API_KEY",
});

// Each system tool is keyed by name under builtInTools.
// Leave "description" blank to use the default, tool-specific prompt.
await elevenlabs.conversationalAi.agents.create({
  conversationConfig: {
    agent: {
      prompt: {
        builtInTools: {
          endCall: {
            type: "system",
            name: "end_call",
            description: "",
            params: { systemToolType: "end_call" },
          },
          languageDetection: {
            type: "system",
            name: "language_detection",
            description: "",
            params: { systemToolType: "language_detection" },
          },
        },
      },
    },
  },
});
```

## FAQ

#### Can system tools be combined with other tool types?

Yes, system tools can be used alongside webhook tools and client tools in the same assistant.
This allows for comprehensive functionality that combines internal state management with
external interactions.

```
```

## Related pages

- [Administration](./administration-index.md)
- [API reference](./api-reference-index.md)
- [Changelog](./changelog-index.md)
- [ElevenAgents](./elevenagents-index.md)
- [ElevenAPI](./elevenapi-index.md)
- [ElevenCreative](./elevencreative-index.md)
- [ElevenLabs Documentation Docs](../index.md)
- [General Troubleshooting FAQ](./troubleshooting-index.md)
- [General Website FAQ](./website-index.md)
- [Help Center](./help-center-2-index.md)

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