Scientific Agent Skills: A Library of Procedural Knowledge for Research Agents
arXiv:2609.00065v1 Announce Type: new 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.
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[Submitted on 30 Aug 2026]
Title:Scientific Agent Skills: A Library of Procedural Knowledge for Research Agents
View a PDF of the paper titled Scientific Agent Skills: A Library of Procedural Knowledge for Research Agents, by Timothy Kassis and 4 other authors
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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 this https URL.
Subjects:
Computation and Language (cs.CL); Artificial Intelligence (cs.AI)
Cite as: arXiv:2609.00065 [cs.CL]
(or arXiv:2609.00065v1 [cs.CL] for this version)
https://doi.org/10.48550/arXiv.2609.00065
arXiv-issued DOI via DataCite
Submission history
From: Timothy Kassis [view email] [v1] Sun, 30 Aug 2026 15:40:35 UTC (2,386 KB)
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