From Raw Experience to Skill Consumption: Systematic Study Maps the Agent Skill Lifecycle

arXiv·medium signal

Companion paper to SkillOpt provides the first comprehensive study spanning the full lifecycle of model-generated agent skills — from extraction through reuse. Finds that domain-level, model-generated skills are especially promising for fast adaptation, but extraction methods have proliferated without clear understanding of trade-offs. Establishes a taxonomy and evaluation framework for skill generation, storage, retrieval, and consumption in language agents.