A new dataset (AED) for identifying errors and failures in AI agents is introduced, with 50,228 error-diagnosis pairs from various environments and policy models. The dataset aims to support cross-setting failure analysis and re-diagnosis without repeating the original rollout. The authors present a five-stage pipeline for collecting natural failures, generating diagnoses, and checking proposed corrections against recorded evidence.