Structured Output
Model-side support for producing responses that conform to a declared schema (JSON Schema, Pydantic model, OpenAI's response_format). Reduces brittle string parsing in tool-use pipelines and is a prerequisite for reliable agent execution.
Related terms
- Tool Use
The capability of AI models to invoke external tools, APIs, and systems to accomplish tasks. Modern implementations rely on structured outputs (JSON schemas or function signatures) so the model's tool calls can be parsed and executed reliably. Extends AI beyond text generation into real-world actions.
- Tool Calling
The general pattern where an LLM emits structured output (typically JSON matching a schema) that a runtime interprets as a call to an external function, API, or service. Also called "function calling". MCP standardizes discovery and invocation across providers.
Related on this site
Framework dimensions
Free tools
Whitepapers
Comparisons
Next steps
- Take the assessment— See where you stand
Call this framework and its tools from your own agent via the Model Context Protocol (MCP) server. Works with Claude Desktop, Cursor, Zed, Continue, and the OpenAI Agents SDK.
Where this fits
Structured Output is part of the Agentic AI vocabulary used in the Generative AI Maturity Framework. See the full glossary for the complete set of 149 defined terms, or take the free maturity assessment to see where your organisation stands.