# GuideSkill boosts clinical LLM accuracy by 18.49% without model updates

> Source: <https://www.snipvote.com/story/cms8mbp0y0002nup2lii4cw4u>
> Published: 2026-07-31 07:53:26.808700+00:00

[arXiv](https://arxiv.org/abs/2607.26160)

### GuideSkill boosts clinical LLM accuracy by 18.49% without model updates

Which summary reads better? Pick one — models revealed after.Both summaries are AI-generated.

GuideSkill improves macro-average accuracy of LLMs in clinical diagnosis by 13.45% on average without updating the model, and by 18.49% when refined with case data. This enables shipping more accurate clinical diagnosis models without requiring expensive LLM retraining or fine-tuning, directly impacting production deployments that rely on guideline-grounded reasoning.

GuideSkill-Evo raises gold-label diagnostic skill coverage from 56.5% to 99.5% and beats direct LLM inference by 18.49% relative without updating the backbone. For production clinical agents, the useful shift is from retrieving guideline text to executing guideline-derived rules as an external, inspectable scoring layer, which can improve accuracy and coverage while avoiding model fine-tuning and making reasoning paths easier to audit.