收录解读
This paper addresses a practical bottleneck in skill-based agents: skill artifacts are often text-heavy documents whose invocation rules, execution structure, side effects, and risk evidence remain entangled.
It proposes a Scheduling-Structural-Logical representation that separates when a skill should be used, what execution structure it contains, and which logic/action/resource details matter for review.
The representation improves skill discovery and risk assessment over text-only baselines, making skill libraries more searchable, inspectable, and operationally usable.
For the separate agent-memory/capability theme inside the formal collection, this is valuable because it turns skills from opaque prose into structured machine-operable capability objects.