AI & ML
Right Family, Wrong Skill: Evaluating Risk Exposure in Agent Skill Retrieval
arXiv cs.IR0 views
arXiv:2606.10388v4 Announce Type: replace Abstract: A skill can match a task's topic while conflicting with its resource, procedure, or output requirements. We study this as same-capability risk-exposure retrieval and introduce SameCapRisk-Bench: 890 units and 1,314 query cases across five mechanisms and twelve conflict types. Each unit pairs a skill that meets a query requirement with a same-capability skill that violates it, with evidence for that distinction. The evaluation tests source-task requirements and two kinds of paired queries that reverse which skill fits: changing the requested evidence role or exact output interface while holding the skills fixed. To capture both retrieval success and conflicting exposure, Recall tracks helpful hits, harmful sibling rate (HSR) tracks exposure of the conflicting sibling, and CleanHit requires a helpful hit without that exposure. Four public skill retrievers expose conflicting siblings at HSR@3 of 0.737-0.881 on source-task contracts, compared with 0.099-0.12 on controlled source-role queries. Across the fixed mixture of 1,235 held-out queries, their Recall@3 is 0.903-0.944 and HSR@3 is 0.344-0.393. The conflicting sibling ranks first on 24.8-29.2% of source-task queries for these four retrievers. We also examine what the reranker receives: truncating long skills can remove the passages where the two skills' contracts differ. With the same BGE top-20 candidates, increasing the reranker's input budget from 512 to 4,096 tokens reduces source-task sibling-first errors by 8.27 pp, with an uncertain CleanHit gain.
Source:https://arxiv.org/abs/2606.10388PreviousGenerative Spatiotemporal Intent Sequence Recommendation via Implicit Reasoning in AmapNextMERGED: Multimodal Entity Resolution via Generated Expert Reasoning Distillation
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