Harnessing AtomisticSkills for Agentic Atomistic Research
Computational materials science and chemistry span vast knowledge domains and fractured software ecosystems. Although large language models (LLMs) have demonstrated research capabilities, scaling monolithic agents to manage the rigor and complexity of atomistic research remains a challenge. Here, we introduce AtomisticSkills, an open-source harness framework that empowers general-purpose AI coding agents to conduct atomistic research across materials science, chemistry, and drug discovery. By hierarchically decomposing scientific workflows into agent skills and tools, AtomisticSkills provides agents with modular, extensible, and plug-and-play research capabilities. The framework integrate...
| Authors | Bowen Deng, Bohan Li, Matthew Cox et al. |
|---|---|
| Primary category | physics.chem-ph |
| Published | 18 May 2026 |
| Last updated at source | 18 May 2026 |
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