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From Skill Text to Skill Structure: Scheduling-Structural-Logical Representation for Agent Skills
Peking University researchers published a framework for converting natural-language skill descriptions into executable, hierarchical agent skill structures. Trending on HuggingFace Daily Papers (May 4), the paper introduces a structured representation that decomposes skills into scheduling, structural, and logical components — enabling more reliable skill composition and execution in LLM-based agents. Directly applicable for anyone building agent frameworks with composable skill systems.
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