Function Calling and Tool Use — LLMs as Real-World Orchestrators

An LLM generates text. With function calling, it generates actions. The model calls a calendar API with parameters. No parsing — structured output directly from the model.

How It Works¶

You define tools as JSON schemas. The model returns a structured function call with arguments. The application executes it and returns the result to the model.

Design Principles¶

• Clear descriptions: The model decides based on the description
• Atomic functions: One tool = one action
• Input validation: Never trust parameters without validation
• Idempotence: A double call must not cause problems

Security¶

Prompt injection can trigger unauthorized API calls. Add a confirmation step for destructive actions, an allow-list, and rate limiting.

Production¶

A tool-use agent for helpdesk: 8 tools. After 3 months: 60% of tickets resolved without human intervention.

Function Calling Is the Bridge Between AI and Action¶

Invest in tool design the same way you invest in API design — it’s equally important.