Model Picker Tool

Let the agent pick between several models per turn.

Overview

The model picker tool gives an agent the ability to dynamically choose which model to use for each turn of the conversation. This is useful when you want the agent to route different types of requests to different models — for example, using a fast, inexpensive model for simple queries and a more capable model for complex reasoning tasks.

Configuration

toolsets:
  - type: model_picker
    models:
      - openai/gpt-5-mini
      - anthropic/claude-sonnet-4-5
      - openai/gpt-5

Options

Property	Type	Required	Description
`models`	array[string]	✓	List of model references the agent can choose from. Use `provider/model` format.

How It Works

When the model picker toolset is enabled, the agent gets a pick_model tool it can call to switch to a different model for the next turn. The agent decides which model to use based on the complexity of the task, cost considerations, or other factors you describe in its instruction.

Example

agents:
  root:
    model: openai/gpt-5-mini  # Default model
    instruction: |
      You are a helpful assistant. For simple questions, use gpt-5-mini.
      For complex reasoning or coding tasks, switch to claude-sonnet-4-5 or gpt-5.
    toolsets:
      - type: model_picker
        models:
          - openai/gpt-5-mini
          - anthropic/claude-sonnet-4-5
          - openai/gpt-5

💡 Cost optimization

The model picker tool is particularly useful for cost optimization: let the agent use a cheap model by default and only escalate to expensive models when necessary.

Tool Interface

The toolset exposes a single tool, pick_model, with one parameter:

Parameter	Type	Required	Description
`model`	string	✓	The model to use for the next turn. Must be one of the configured models.

The model switch takes effect on the next turn — the current turn continues with the model that was active when pick_model was called.