Artificial intelligence agent evaluation examines more than a final response. It can score tool selection, action order, exception handling, recovery, policy compliance, cost and the actual business outcome of a task.
Real execution traces provide valuable cases because they contain messy edge conditions absent from simple benchmarks. Strong evaluations retain representative failures and are rerun when models, tools, workflows or prompts change.
