Tools

Tools extend your agent’s capabilities beyond conversation. They allow the agent to perform real actions during a call — like calling an external API, transferring the call to a human, or ending the call based on specific conditions.

Tool Types

Callem Studio supports three types of tools:

Type	Description	Use Case
HTTP Tool	Calls an external API endpoint with extracted parameters	Booking appointments, CRM lookups, checking inventory
Transfer Call	Transfers the call to another phone number based on conditions	Escalation to human agent, routing to a specialist
End Call	Ends the call based on defined conditions	Hang up when the conversation goal is achieved, or when the caller is abusive

HTTP Tool

HTTP tools leverage the function calling capability of modern LLMs to invoke external APIs during a conversation.

How It Works

Define the tool

Create a tool with a name, description, parameters (JSON Schema), and an API endpoint.

Attach to an agent

Link the tool to one or more agents via the Model tab → Knowledge & Tools section.

LLM decides when to call

During a call, the LLM analyzes the conversation and determines when a tool invocation is appropriate based on its description and the caller’s intent.

Execution

The system calls your API endpoint with the extracted parameters. Your endpoint processes the request and returns a result.

Response integration

The tool’s response is fed back to the LLM, which uses it to continue the conversation naturally (e.g. “I’ve booked your appointment for Tuesday at 3pm”).

HTTP Tool Configuration

Field	Description	Tips
Name	Function name the LLM will reference	Use `snake_case` (e.g. `book_appointment`, `check_stock`). Only letters, digits, underscores and dashes allowed. Max 64 characters.
Description	Explains when and why to use this tool	This is the most important field — the LLM reads it to decide when to invoke the tool. Be explicit about trigger conditions.
Parameters	JSON Schema defining expected inputs	Define every parameter with a type and description. Mark required fields.
Endpoint URL	HTTP endpoint called with the parameters	Must be a valid URL starting with `http://` or `https://`.
Method	HTTP method (GET, POST, etc.)	POST is recommended for actions, GET for lookups.
Headers	Custom headers (e.g. authorization tokens)	Include API keys or auth tokens needed by your endpoint.
Query Params	URL query parameters	For GET requests or additional filtering.
Authentication	Built-in auth configuration	Location (header/query), key name, and value.
Timeout	Maximum time to wait for a response (seconds)	Default: `10s`. Increase for slow APIs.
Async	Execute without waiting for response	Enable for fire-and-forget actions (e.g. logging, notifications) where the agent doesn’t need the result to continue.

Async Mode

When async is enabled, the agent sends the API request but does not wait for the response before continuing the conversation. This is useful for:

Logging events to an external system
Sending notifications (email, SMS, Slack)
Triggering background processes that don’t affect the conversation flow

Writing Effective Descriptions

The tool description is critical — it tells the LLM when to use the tool. Bad description:

“Handles appointments”

Good description:

“Book a new appointment for the caller. Use this tool ONLY when the caller has explicitly confirmed they want to schedule a visit and has provided their name, preferred date, and time. Do NOT use this tool for general questions about availability.”

Parameter Definition (JSON Schema)

Parameters use JSON Schema format. Each parameter needs:

type — data type (string, number, boolean, object, array)
description — what this parameter represents (the LLM reads this to extract the right value from the conversation)

Example: Appointment Booking Tool

{
  "name": "book_appointment",
  "description": "Book an appointment for the caller. Use when the caller explicitly requests to schedule a visit and has provided their name, preferred date, and preferred time.",
  "parameters": {
    "type": "object",
    "properties": {
      "caller_name": {
        "type": "string",
        "description": "Full name of the caller as stated during the conversation"
      },
      "date": {
        "type": "string",
        "description": "Requested appointment date in YYYY-MM-DD format"
      },
      "time": {
        "type": "string",
        "description": "Requested appointment time in HH:MM format (24-hour)"
      },
      "reason": {
        "type": "string",
        "description": "Brief reason for the appointment"
      }
    },
    "required": ["caller_name", "date", "time"]
  }
}

Example: CRM Lookup Tool

{
  "name": "lookup_customer",
  "description": "Look up a customer record in the CRM by phone number. Use at the start of the call to check if the caller is an existing customer.",
  "parameters": {
    "type": "object",
    "properties": {
      "phone_number": {
        "type": "string",
        "description": "Caller's phone number in international format (e.g. +33612345678)"
      }
    },
    "required": ["phone_number"]
  }
}

Transfer Call Tool

The Transfer Call tool lets you define conditions under which the agent should transfer the call to another phone number.

Configuration

Each Transfer Call tool contains one or more conditions, each with:

Field	Description	Example
Condition	A natural language description of when to transfer	”The caller explicitly asks to speak with a human agent”
Number	The phone number to transfer to	`+33123456789`

You can define multiple conditions with different target numbers:

Condition	Number
”Caller requests technical support”	`+33 1 23 45 67 89`
”Caller wants to speak with sales”	`+33 1 98 76 54 32`
”Caller is upset and asks for a manager”	`+33 1 11 22 33 44`

Write conditions as clearly as possible. The LLM evaluates these conditions against the conversation context to decide when to trigger the transfer.

End Call Tool

The End Call tool lets you define conditions under which the agent should terminate the call.

Configuration

Each End Call tool contains one or more conditions:

Field	Description	Example
Condition	A natural language description of when to end the call	”The caller has confirmed their appointment and has no further questions”

Multiple conditions can be defined:

Condition
”The conversation goal has been achieved and the caller says goodbye"
"The caller is abusive or uses inappropriate language"
"The caller has been silent for an extended period after the reminder”

Linking Tools to an Agent

You can attach tools to agents in the agent’s Model tab → Knowledge & Tools section. Select one or more tools from the dropdown. Tools can be shared across multiple agents.

Tool Invocation During Calls

When a tool is invoked during a call, you can see it in:

Chat sidebar (test mode) — shows tool name, input parameters, and output
Call transcript (call detail view) — logged as part of the conversation flow
Observability (if configured) — traced in Langfuse/Langsmith for debugging

Best Practices

Write precise, condition-specific descriptions

The LLM uses the tool description to decide when to call it. Include explicit trigger conditions and counter-conditions. For example: “Use when X. Do NOT use when Y.”

Return human-readable responses from HTTP tools

Your API endpoint should return clear messages the agent can relay to the caller. Instead of {"status": 200, "id": "apt_123"}, return {"message": "Appointment confirmed for Tuesday March 15 at 3:00 PM."}.

Handle errors gracefully

Return meaningful error messages from HTTP endpoints. The agent will relay these to the caller. Example: {"error": "No available slots on that date. Please suggest an alternative."}.

Use async for fire-and-forget actions

Enable async mode for tools that log events, send notifications, or trigger background processes where the agent doesn’t need to wait for a response.

One tool = one action

Don’t create a “do everything” tool. Split complex workflows into multiple tools with clear responsibilities. The LLM handles orchestration between tools naturally.

Use Transfer Call for escalation paths

Instead of hardcoding transfer numbers in the system prompt, use a Transfer Call tool with explicit conditions. This makes the logic visible, editable, and independent from the prompt.

Test with real scenarios

Call your agent and try to trigger each tool. Verify the parameters are passed correctly and the response is used appropriately in the conversation.

Getting Started

Build

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Settings

Tools

Tools

Tool Types

HTTP Tool

How It Works

HTTP Tool Configuration

Async Mode

Writing Effective Descriptions

Parameter Definition (JSON Schema)

Example: Appointment Booking Tool

Example: CRM Lookup Tool

Transfer Call Tool

Configuration

End Call Tool

Configuration

Linking Tools to an Agent

Tool Invocation During Calls

Best Practices

​Tools

​Tool Types

​HTTP Tool

​How It Works

​HTTP Tool Configuration

​Async Mode

​Writing Effective Descriptions

​Parameter Definition (JSON Schema)

​Example: Appointment Booking Tool

​Example: CRM Lookup Tool

​Transfer Call Tool

​Configuration

​End Call Tool

​Configuration

​Linking Tools to an Agent

​Tool Invocation During Calls

​Best Practices

Tools

Tool Types

HTTP Tool

How It Works

HTTP Tool Configuration

Async Mode

Writing Effective Descriptions

Parameter Definition (JSON Schema)

Example: Appointment Booking Tool

Example: CRM Lookup Tool

Transfer Call Tool

Configuration

End Call Tool

Configuration

Linking Tools to an Agent

Tool Invocation During Calls

Best Practices