Besides standard Pydantic features, you can also use a special ToolConfig class to customize tool behavior within the framework:

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Available ToolConfig Parameters

Currently, the following parameters are supported:

NameTypeDescriptionWhen to UseDefault Value
one_call_at_a_timeboolPrevents concurrent execution for a specific tool. To prevent the agent from executing any tools concurrently, set parallel_tool_calls=False in the Agent class.Use for database operations, API calls with rate limits, or actions that depend on previous results.False
strictboolEnables strict mode, which ensures the agent will always provide perfect tool inputs that 100% match your schema. Has limitations. See OpenAI Docs.Use for mission-critical tools or tools that have nested Pydantic model schemas.False
async_modestrWhen set to “threading,” executes this tool in a separate thread.Use when your agent needs to execute multiple tools or the same tool multiple times in a single message to decrease latency. Beware of resource allocation.None
output_as_resultboolForces the output of this tool as the final message from the agent that called it.Only recommended for very specific use cases and only if you know what you’re doing.False

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Usage

To use one of the available parameters, simply add a class ToolConfig block to your tool class:

class MyCustomTool(BaseTool):
    # ...

    class ToolConfig:
        one_call_at_a_time = True
        strict = False
        async_mode = "threading"
        output_as_result = True

    def run(self):
        # ...