SkillEvolver: Skill Learning as a Meta-Skill
Agent skills today are static artifact: authored once -- by human curation or one-shot generation from parametric knowledge -- and then consumed unchanged, with no mechanism to improve from real use. We propose \textbf{SkillEvolver}, a lightweight, plug-and-play solution for online skill learning, in which a single meta-skill iteratively authors, deploys, and refines domain-specific skills. The learning target of SkillEvolver is the skill's prose and code, not model weights, so that the resultin
Record details
Published: 11 May 2026
Source: arXiv
Category: Research
Topics: Agents & autonomy
Retrieved: 14 July 2026
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ethics.ai (11 May 2026), “SkillEvolver: Skill Learning as a Meta-Skill,” evidence record 4557, https://ethics.ai/record/4557 (originally published by arXiv).
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