Tool Orchestration for Agents

Tools are what give agents their power. Without tools, an agent is just a chatbot. This lesson covers how to design tool libraries, implement tool selection strategies, handle tool results and errors gracefully, and dynamically register tools at runtime.

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Why Tools Matter

An LLM on its own can only generate text. Tools let agents interact with the real world:

Capability	Without Tools	With Tools
Get current data	Hallucinate or say "I don't know"	Search the web, query a database
Perform calculations	Approximate (often wrong)	Execute exact calculations
Take actions	Describe what to do	Actually do it (send email, create file)
Access private data	Cannot	Query APIs with authentication

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Designing a Tool Library

A well-designed tool library is the foundation of an effective agent.

Tool Definition Structure

from dataclasses import dataclass, field
from typing import Callable, Any

@dataclass
class Tool:
    name: str
    description: str
    parameters: dict          # JSON Schema describing expected args
    function: Callable        # The actual function to execute
    requires_confirmation: bool = False
    tags: list[str] = field(default_factory=list)