ai-core/structured-outputs

To get typed JSON from LLM chat responses, this skill applies Zod schemas to chat sessions, converting outputs into strongly typed JSON objects via schema validation. It translates outputSchema declarations into provider-specific response formats automatically.

Yes, structured LLM output validation supports ArkType and Valibot schemas alongside Zod. The adapter translates these schemas into each provider's response format, ensuring typed inference without manual provider-specific settings.

Provider-agnostic schema handling for LLM structured outputs works by translating outputSchema declarations into each provider's response format. This centralizes configuration, forcing chat sessions to emit validated JSON objects without provider-specific setup.

The best way to extract structured company data from transcripts is using schema enforcement during chat LLM calls. This skill parses conversation transcripts with schemas and returns validated, typed JSON objects for immediate downstream logic.

No, you do not need to manually configure response formats for different LLM providers. The adapter handles provider-specific response format translation automatically based on your declared outputSchema, keeping structured output configuration centralized.

To convert schema definitions to JSON schema for LLM chat outputs, use the provided convertSchemaToJsonSchema() utility. This allows manual schema conversions when multi-library support via Zod, ArkType, or Valibot requires explicit JSON schema formatting.