Agents
Scientific Agent Skills: A Library of Procedural Knowledge for Research Agents
arXiv:2609.00065v1 Announce Type: cross Abstract: A language-model agent asked to analyse an experiment will usually return working code. Whether the analysis is defensible is a different question. A
arXiv:2609.00065v1 Announce Type: cross Abstract: A language-model agent asked to analyse an experiment will usually return working code. Whether the analysis is defensible is a different question. A defensible analysis depends on procedural choices: which test the field accepts, which identifier namespace is authoritative, and which caveats must accompany a result. We present Scientific Agent Skills, an open library of 163 such procedures in 16 areas of practice, including genomics, cheminformatics, medical imaging, study design and scientific communication. Each skill is a directory built around a versioned, human-readable instruction file. An agent loads the file only when a task calls for it; the directory often also contains reference material and runnable scripts. We report no task-level evaluation and no host selection rate. Openly licensed and available at https://github.com/K-Dense-AI/scientific-agent-skills.
Related
- RESOURCE2SKILL: Distilling Executable Agent Skills from Human-Created Multimodal Resources
- SkillZip: Contract-Preserving Graph Compression for Scalable Agent Skill Libraries
- From Raw Experience to Skill Consumption: A Systematic Study of Model-Generated Agent Skills
- SkillAlchemy: Open-World Agent Skill Creation
Source: arXiv cs.AI | 2026-09-02