SkillJuror: Measuring How Agent Skill Organization Changes Runtime Behavior

The article introduces SkillJuror, a framework designed to evaluate the impact of Skill organization on the runtime behavior of large language model (LLM) agents. Through an 82-task SkillsBench study, it demonstrates that using Progressive Disclosure increases the number of distinct Skill resources utilized and effective uptake events, with a notable 4.1% increase in successful outcomes compared to a flat baseline. This research highlights that the organization of procedural knowledge significantly influences agent performance, emphasizing the importance of actionable resources in task-specific contexts.