Agent Operation Recovery
A benchmark designed to test AI agents' failure-recovery capabilities in scenarios where operation-confirmation receipts are lost. It contains 24 synthetic cases across four business domains—ticketing, inspection, appointment, and inventory deduction—evaluating an agent's ability to avoid repeating non-idempotent operations while continuing to advance business processes safely.
Timeline (last 90 days)
A developer designed a benchmark called 'Agent Operation Recovery' and attempted to submit it to the Kaggle Benchmark Challenge.
The benchmark contains 24 synthetic cases covering scenarios including in-flight operations, missing confirmation receipts, unknown execution results, legitimate new intents, authorization changes, and goal-binding changes.
Of the 24 cases, 17 require advancing business progress and 7 require returning unknown, blocked, or pending results, so simply refusing all operations cannot pass the test.
New write operations in the test are deliberately designed to be non-idempotent, and the simulator does not mask unsafe duplicate dispatches through automatic deduplication.
Each model was run twice across all 24 cases, i.e., 48 episodes per model and 96 episodes in total, each time using a fresh conversation and simulator state with caching disabled.
Once final JSON parsing fails, subsequent semantic checks are skipped entirely, which is the technical root cause of the 'task completed yet zero score' phenomenon.
The developer publicly released the full96-v1 version, containing cases, scorers, manifests, all 96 episode records, and fixed reproduction source code.
This research is built on a small-scale synthetic contract, involves only two models from the same family and a single vendor, and cannot demonstrate production environment safety or general equivalence across models.
All Facts (8)
This research is built on a small-scale synthetic contract, involves only two models from the same family and a single vendor, and cannot demonstrate production environment safety or general equivalence across models.
50%UnverifiedThe benchmark contains 24 synthetic cases covering scenarios including in-flight operations, missing confirmation receipts, unknown execution results, legitimate new intents, authorization changes, and goal-binding changes.
50%UnverifiedOf the 24 cases, 17 require advancing business progress and 7 require returning unknown, blocked, or pending results, so simply refusing all operations cannot pass the test.
50%UnverifiedNew write operations in the test are deliberately designed to be non-idempotent, and the simulator does not mask unsafe duplicate dispatches through automatic deduplication.
50%UnverifiedEach model was run twice across all 24 cases, i.e., 48 episodes per model and 96 episodes in total, each time using a fresh conversation and simulator state with caching disabled.
50%UnverifiedOnce final JSON parsing fails, subsequent semantic checks are skipped entirely, which is the technical root cause of the 'task completed yet zero score' phenomenon.
50%UnverifiedThe developer publicly released the full96-v1 version, containing cases, scorers, manifests, all 96 episode records, and fixed reproduction source code.
50%UnverifiedA developer designed a benchmark called 'Agent Operation Recovery' and attempted to submit it to the Kaggle Benchmark Challenge.
50%