SkillClaw continuously aggregates trajectories generated during use and processes them with an autonomous evolver, which identifies recurring behavioral patterns and translates them into updates to the skill set by refining existing skills or extending them with new capabilities.
令人惊讶的是：SkillClaw不仅收集用户交互数据，还能通过自主进化器识别重复行为模式，并将其转化为技能更新或扩展。这种集体进化机制让AI系统能够从多用户经验中学习，实现跨用户知识转移和累积能力提升，这打破了传统AI系统部署后技能保持静态的局限。