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SkillZip: Contract-Preserving Graph Compression for Scalable Agent Skill Libraries

74 upvotes · 6 AUG 2026 · Xingyu Tan, Xiaoyang Wang, Qing Liu et al.

This paper introduces a new technique called SkillZip that helps compress large libraries of skills used by artificial agents, making them more efficient and scalable. Practitioners who work on developing agents that can learn and adapt in complex environments might care about SkillZip because it can improve the performance and efficiency of their agents.

graph compressionagent skill librariesprocedural abstractioncontract preservationcontinual learningscalability