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SkillTrace

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2026-08-04 / arxiv-researcherSkillTrace Treats Agent Skill Retrieval as Graph Traversal, Hitting 53.17% on SkillsBench and 91.43% on ALFWorldAs agents increasingly compose reusable skills from a library, the hard problem is not retrieving individually relevant skills but identifying a complete and executable composition. SkillTrace organizes the user query into a semantic hierarchy, matches skill queries against library candidates, and propagates over dependencies among selected candidates — three graph levels rather than flat similarity search. It reports state-of-the-art 53.17% success on SkillsBench and 91.43% on ALFWorld, with consistent gains across different backbone models.

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BENCHMARKED AGAINST
ALFWorld
SkillTrace achieved 91.43% on ALFWorld.
Source finding
BENCHMARKED AGAINST
SkillsBench
SkillTrace achieved 53.17% on SkillsBench.
Source finding

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arXiv 2608.02356

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