Anything2Skill: Compiling External Knowledge into Reusable Skills for Agents

The paper introduces Anything2Skill, a framework that compiles external knowledge into reusable skills for agents, enhancing retrieval-augmented generation (RAG) capabilities. It employs a skill-tree prior for skill extraction from heterogeneous knowledge records, converting them into structured skill contracts that detail invocation conditions and workflows. Experiments demonstrate that Anything2Skill, when combined with RAG, achieves success rates of 98.85% and 94.10% on qsv and GitHub-CLI tasks, respectively, indicating significant improvements in agent performance by enabling procedural knowledge reuse.