Diagnosis is the missing skill in production agents

A lot of agent stacks talk about planning tool use memory and permissions. But the skill I rarely see defined clearly is diagnosis. When an agent fails it is not enough to say “the tool call failed” “the model got confused” “retry the step” A production agent needs to explain the failure in operational terms which assumption was wrong which tool call or output introduced the bad state what state is durable now whether a retry is safe whether a rollback or compensation is needed whether the next step requires human review Without that the system just produces a nicer error message and then repeats the same bad action. I think diagnosis should be treated as a first-class skill separate from observation. Observation answers What happened Diagnosis answers Why is the system in this state and what is safe to do next For production workflows this matters more than making the agent sound smart. The failure path is where trust is either earned or lost. Curious how others are handling this. Do your agents have a separate diagnosis layer or is failure analysis still mixed into logs traces prompts and human debugging