Every LLM evaluation framework today invents its own test case format, its own grader definitions, and its own results schema. DeepEval, Promptfoo, Inspect AI, and lm-evaluation-harness all solve the same core problem (checking whether a model's output is correct) but none of them can read each other's eval datasets. That means every time a team wants to compare frameworks, or move from a notebook prototype to a production eval pipeline, they end up hand-rewriting the same test cases over and...