GuideSkill: Evolving Executable LLM Agent Skills for Guideline-Grounded Clinical Reasoning
Clinical practice guidelines (CPGs) encode diagnostic criteria, but LLM systems typically retrieve guideline text or absorb it through training rather than execute its rules. We introduce GuideSkill, an external reasoning layer that compiles disease-specific criteria into executable functions returning ordinal diagnostic-support scores. GuideSkill-Zero is initialized from guidelines, while GuideSkill-Evo uses case--diagnosis pairs to refine covered skills and add missing diagnoses. At inference, an LLM proposes a differential diagnosis, grounds the features required by each matched skill, and fuses its ranking with the executed skill scores. Across four benchmarks and four backbones, Guid...
| Authors | Lang Cao, Yuhao Shen, Tianyang Luo et al. |
|---|---|
| Primary category | cs.AI |
| Published | 28 July 2026 |
| Last updated at source | 28 July 2026 |
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