An Empirical Study of Agent Skills for Healthcare: Practice, Gaps, and Governance
Healthcare automation is shaped by local procedures and organizational constraints, so agent capabilities rarely transfer unchanged across settings. Agent skills, self-contained directories that package reusable procedures for AI agents, are emerging as a procedural layer for adapting healthcare agents across diverse healthcare settings. We present the first empirical analysis of healthcare agent skills, drawing on 557 healthcare-related skills filtered from 58,159 public skills on ClawHub and annotated along ten dimensions covering function, deployment context, autonomy, and safety. We find that public healthcare skills emphasize patient-facing workflow automation and monitoring rather t...
| Authors | Gelei Xu, Ningzhi Tang, Xueyang Li et al. |
|---|---|
| Primary category | cs.AI |
| Published | 4 May 2026 |
| Last updated at source | 4 May 2026 |
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