💭 technically that could be done by parsing into json, using some form of embedding and basic ml, but that wouldnt be able to give any interpretable feedback. Could auto/llm generate interpretable input measures and use those instead. Maybe some model where you can predict each input from all the other inputs and directly see how in-distribution each input or combination of inputs is