WHEN ATTRIBUTION IS NOT REPAIR: RESPONSIBILITY AND INTERVENTION IN LLM MULTI- AGENT SYSTEMS

Debugging tools for LLM multi-agent systems usually assume that finding where an error entered a trace tells us where to fix it. We test this assumption directly. A failed trace exhibits source–repair mismatch (SRM) when some logged action would repair the final answer but none of those actions lies at an annotated error source. On 116 repairable failures, two independent blinded Source annotations give SRM rates of 0.543 and 0.733, and 0.388 of traces stay mismatched even when every event marked by either annotator counts as a source. As a consequence, a policy restricted to source events can recover at most 61.2% of candidate-oracle logged repairs (71/116 repairable traces), corresponding to 31.7% absolute Repair@1 on the 224-failure cohort, however accurate its localization. We release a benchmark that pairs six-role event responsibility labels, a 1,600-item human-adjudicated test set for verifier and contract roles, and checker-scored single-intervention repair. We also introduce RAISER, which ranks an agent system’s own logged answers with standardized responsibility evidence and passes the same evidence to a frozen verifier over a three-item shortlist. On 196 failures held out from development, aligned graph and role channels improve ranking NDCG over a matched local ranker (Holm p=0.007), permuting them within each trace erases the gain, and the full system raises Repair@1 from 65.3% to 70.9% of failures (p=0.027). On the development and validation cohorts, the same final system recovers 86.8% and 85.6% of candidate-oracle repairs; its margins over the matched verifier controls are +1.5 and +4.4 oracle points, respectively. A preregistered decomposition on 1,200 further failures locates the remaining headroom in recognizing a correct answer that is already shortlisted. Code: https://anonymous.4open.science/r/Trace-R. Data: https://anonymous-hf.com/a/psa97qn014rw/.