LLM Agent Skill Specifications Lack User Comprehension Anchors

A recent analysis of 878 skill specifications for large language model (LLM) agents in cybersecurity revealed that only 2.3% included all four essential comprehension elements: operational basis, output contract, boundary disclosure, and example demonstration. Although operational basis cues were frequently identified, a mere 19% provided specific examples or expected outcomes. This study utilized rule-based coding methods and is featured on arXiv with the identifier 2605.19362v1. Moreover, an examination of a small DNS/C2 telemetry sample indicated that the absence of practical examples may impede users' ability to implement localized checks, leading to unrealistic expectations regarding skill utilization.