Structured Outputs: Make the Model Return Data You Can Trust

For production apps, pretty prose is often the wrong output. Learn when to use structured outputs, function calling, and schema validation.

Creators · Tools Literacy · ~27 min read

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Production Apps Want Shapes

A chatbot can answer in paragraphs. A production workflow often needs fields: title, dueDate, riskLevel, citations, lineItems, actions. Structured Outputs make the model follow a JSON schema so downstream code can trust the shape.

Compare the options

Need	Pattern
Model should call your app's code	Function calling
Model should answer with strict JSON	Structured output with text.format
You only need valid JSON, not exact schema	JSON mode, but prefer structured outputs when supported
User request may be unsafe	Handle refusals explicitly

A schema is a contract between the model and your application.

typescript

const response = await client.responses.create({ model: "gpt-5.5", input: "Extract a task from: Email Sam by Friday about the vendor renewal.", text: { format: { type: "json_schema", name: "task", strict: true, schema: { type: "object", additionalProperties: false, required: ["assignee", "due", "topic"], properties: { assignee: { type: "string" }, due: { type: "string" }, topic: { type: "string" } } } } } });

1Keep schemas small at first.
2Require every field you truly need.
3Set additionalProperties to false when strictness matters.
4Log refusals and parse failures as product signals.
5Version schemas when clients depend on them.

Key terms in this lesson

The big idea: structured outputs make model responses easier to integrate, but they are not a substitute for validation, source checking, or user review.

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