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bioRxiv · 10.64898/2026.02.04.703888

ChromSkills enables interpretable and reproducible agentic chromatin data analysis

Zhang, Y.·Wang, Y.·Tan, Y.
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Abstract

High-throughput assays generate diverse chromatin datasets that require flexible workflows and context-dependent parameter choices. Although large language models (LLMs) can assist analysis, unconstrained LLM-based execution often exhibits unstable behavior and limited reproducibility. We present ChromSkills, a curated library of domain-specific analytical Skills for agentic chromatin data analysis on the Claude Code platform. ChromSkills encodes expert-informed decision logic and parameter-selection rules as modular, human-readable Skills and couples them with structured tool interfaces to enable reproducible execution and interpretable workflow composition from natural-language task descriptions. Across representative chromatin analysis tasks, ChromSkills consistently selected appropriate tools and parameters across repeated runs and improved execution stability and token efficiency when using Model Context Protocol-based tools. Together, ChromSkills provides a practical framework for trustworthy AI-enabled, agentic chromatin data analysis by guiding LLMs with transparent, reusable domain knowledge.

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Zhang, Y., Wang, Y., Tan, Y.. 2026-02-06. ChromSkills enables interpretable and reproducible agentic chromatin data analysis. https://doi.org/10.64898/2026.02.04.703888

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