A proposed approach called evidence-guided task recovery addresses AI agents that face ambiguous tool outcomes and partial execution when tool timeouts leave an action failed, committed or still in flight while other workflow steps have already completed. The method formulates recovery over approved obligations, provider capabilities and states, according to the source. The work targets a reliability gap for agents running multi-step workflows against external tools.
Tool timeouts can leave AI agents facing ambiguous tool outcomes and partial execution: an action may have failed, committed or remained in flight while other workflow steps have already completed. We formulate evidence-guided task recovery over approved obligations, provider capabilities and states
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