Failure Steps Are Not Repair Intents: Measuring Actionable Ambiguity in Multi-Agent System Diagnosis
Do different blamed execution steps imply different repairs?
We study expert-recommended actions from MP-Bench through a prediction-blind, human-audited model-assisted analysis of 96 multi-agent traces and 1,436 actions.
In the primary analysis, 85.1% of traces contain fewer distinct repair intents than blamed steps, while top repair-set alignment reaches 95.7%. The findings show how step-level evaluation can overstate actionable diversity while often preserving the first repair priority.