Validate LLM Structured Output Against a Schema
Check whether model JSON, tool-call arguments, or agent output actually matches the contract your app expects.
Why this workflow matters
A response can be valid JSON and still fail your integration because keys are missing, types drifted, or extra fields slipped in. Schema validation catches those contract failures before production code does.
What success looks like
- Confirm whether the model output is structurally safe to consume.
- Catch missing keys, wrong types, and extra properties quickly.
- Turn vague prompt failures into concrete validation feedback.
Best tools for this job
LLM JSON Output Validator
Repair and validate model JSON output against a schema
Валидатор JSON Schema
Проверка по схеме
Починка JSON
Исправление типичных ошибок
Structured Output Schema Builder
Generate OpenAI, Anthropic, MCP, or plain JSON Schema wrappers from sample output
Recommended workflow
- 1
Paste the model output and the expected schema into LLM JSON Output Validator.
- 2
Enable repair first when the output is malformed but still close to valid JSON.
- 3
Use Structured Output Schema Builder or JSON Schema Validator when you need to tighten the contract before rerunning the check.
Related guides and examples
Start with LLM JSON Output Validator
This workflow is anchored on LLM JSON Output Validator. Open it first, then move through the supporting steps only if the payload, request, or output still needs more work.
Open LLM JSON Output Validator