Comparison
Structured Output vs Tool Use
Structured Output and Tool Use are both common AI/LLM terms but cover different ideas. Here is a quick side-by-side.
When you would reach for Structured Output
Any time you need to programmatically parse model output — extraction, function arguments, classification, multi-step pipelines.
OpenAI Structured Outputs with a Pydantic / JSON Schema.
When you would reach for Tool Use
Tool Use comes up when the question is fundamentally about agents & tools.
Calling get_weather(city) and getting back JSON the model interprets.
Frequently asked
What is the difference between Structured Output and Tool Use?
Structured Output: Structured output constrains an LLM to emit text matching a schema — usually JSON. The model can be guaranteed to produce valid output that your code can parse without retries. Tool Use: Tool use is when an LLM can call external functions — APIs, code interpreters, databases, web fetchers — and read their results. The mechanism that turns chat into action.
When should I use Structured Output vs Tool Use?
Any time you need to programmatically parse model output — extraction, function arguments, classification, multi-step pipelines. Tool Use applies when you are focused on agents & tools.
Are Structured Output and Tool Use the same thing?
No. Structured Output is inference; Tool Use is agents & tools. They are related but address different parts of the AI stack.