
MN
Mitsuhiro Nakayama, Toshiaki Sota, Takehiko Yamaguchi, Michiaki Tatsubori
· 1 min read
ResearcharXiv cs.AI
Separation of Skilling Context for Standard Operating Procedure-based Agents
arXiv:2611.11348v1 Announce Type: new
Abstract: Standard Operating Procedures (SOPs) are kept concise for human readability, so LLM agents that generate executable skills from them lack the tacit knowledge and implementation details needed for automation. Human intervention fills these gaps, but must be repeated as SOPs evolve---a problem we call \textit{SOP-skill drift}. We propose managing SOPs and Contextual Knowledge (CK) separately, together with a \textit{contract-aware} evaluation that distinguishes genuine violations from CK-resolved differences. On eight Indeed-derived workflows (single LLM), it raises the functional-equivalence rate from 12\% to 58\%. Under three SOP-revision perturbations, previously extracted CK already covers 79.5\% of newly introduced automation gaps.
Original source
This story was published by arXiv cs.AI and written by Mitsuhiro Nakayama, Toshiaki Sota, Takehiko Yamaguchi, Michiaki Tatsubori. SyncAI.news shows a preview; the complete article is on the publisher's site.
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