JSON Schema Validates Structure, Not Accuracy — A Gap That Matters in Production AI

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A developer building ShapeCraft, an open-source Node.js structured output library, found that JSON Schema validation does not guarantee the factual correctness of data extracted by large language models. An LLM can return a perfectly valid, schema-compliant JSON response that still contains wrong or hallucinated values, such as an incorrect invoice total. The author distinguishes between structural validation, which JSON Schema handles well, and semantic validation, which checks whether extracted values are accurate and grounded in the source document. Major AI providers including OpenAI, Groq, Ollama, and Anthropic each enforce structured outputs differently, offering varying levels of guarantee that are often not transparent to developers. ShapeCraft was built to expose these differences by surfacing a guarantee level — native, constrained, or best-effort — for each provider response.

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