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Tool Calling

A mechanism that allows large language models to invoke external functions and APIs by generating structured requests.

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Understanding Tool Calling Master how LLMs invoke external tools — from JSON Schema definitions and model decision-making to agent loops, security, and production monitoring.
Building Your Own Coding Agent Build a code-editing agent from scratch in Python — an LLM, a loop, and three tools in a compact baseline implementation.

lessons

Why Build a Coding Agent? Building Your Own Coding Agent / Getting Started
Managing Conversation State Building Your Own Coding Agent / The Conversation Loop
Your First Tool: read_file Building Your Own Coding Agent / Adding Tools
Inference Is Stateless Context Engineering / Tokens and Inference
The Smart Zone and the Dumb Zone Context Engineering / The Real Size of Your Context Window
Measuring Your Context Budget Context Engineering / The Real Size of Your Context Window
Tool Calls as Memory Allocations Context Engineering / Dynamic Allocation: Tool Calling
Sub-Agents Are Not About Personas Context Engineering / Sub-Agents: Managed Runtimes for AI
Why Compaction Is Dangerous Context Engineering / Context Management Strategies
Better Strategies Context Engineering / Context Management Strategies
What Is Tool Calling? Understanding Tool Calling / Foundations
Defining Tools with JSON Schema Understanding Tool Calling / Foundations
The Tool Selection Process Understanding Tool Calling / How Models Decide
Parsing and Validating Tool Calls Understanding Tool Calling / How Models Decide
Multi-Turn Tool Use Understanding Tool Calling / Advanced Patterns
Parallel and Dependent Tool Calls Understanding Tool Calling / Advanced Patterns
Building an Agent Loop Understanding Tool Calling / Advanced Patterns
Prompt Injection and Tool Safety Understanding Tool Calling / Security and Production
Guardrails and Permissions Understanding Tool Calling / Security and Production
Monitoring and Debugging Understanding Tool Calling / Security and Production

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