I tokenized these and they seem to use around 20% less tokens than the original JSONs. Which makes me think a schema like this might optimize latency and costs in constrained LLM decoding.

I know that LLMs are very familiar with JSON, and choosing uncommon schemas just to reduce tokens hurts semantic performance. But a schema that is sufficiently JSON-like probably won't disrupt model path/patterns that much and prevent unintended bias.