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SkillNet: npm for AI Agent Skills
Agents keep reinventing the wheel. Every new deployment rediscovers solutions that other agents already solved, because there is no shared infrastructure for skill accumulation. SkillNet, from Ningyu Zhang's lab at Zhejiang University, treats this as an engineering problem: build a package manager for agent capabilities. The system structures over 200,000 skills within a unified ontology, supports creation from heterogeneous sources (repos, docs, logs), and evaluates each skill across five dimensions — safety, completeness, executability, maintainability, and cost. Early results show measurable performance improvements when agents search existing skills before attempting novel solutions.
The analogy to npm is deliberate and instructive. Software engineering matured when developers stopped writing everything from scratch and started composing from tested, versioned packages. Agent development is still in the "write everything yourself" phase. SkillNet is a bet that the same transition applies.
If your agent pipeline includes any form of tool creation or skill learning, evaluate whether a shared skill registry reduces redundant computation. The SkillNet Python toolkit and API are open-source.
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