Evaluating and Improving Agent Skills with MLflow
Summary
MLflow enables evaluation-driven development for AI agent skills by combining traces, evaluation datasets, custom evaluators, and experiment tracking to treat agent capabilities like testable software components. Instead of grading only final outputs, teams can use execution traces to systematically measure critical behaviors such as tool sequencing, policy compliance, and execution efficiency across skill iterations.
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