AI RESEARCH
SkillPager: Query-Adaptive Intra-Skill Navigation via Semantic Node Retrieval
arXiv CS.AI
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ArXi:2606.00822v1 Announce Type: cross Skill-based LLM agents increasingly rely on long procedural documents, but full-document prompting wastes tokens and dilutes information critical to execution. We study this setting as intra-skill retrieval, where the goal is to select a minimal, execution-sufficient context from a known skill document given a query. We present SkillPager, a two-stage framework that parses each Markdown skill into typed semantic nodes offline and leverages Maximal Marginal Relevance (MMR) to perform global, query-conditioned node selection online.