Bowen Deng, Bohan Li, Matthew Cox, Hoje Chun, Juno Nam, Artur Lyssenko, Sathya Edamadaka, Jurgis Ruza, Xiaochen Du, Nofit Segal, Jesus Diaz Sanchez, Mingrou Xie, Ty Perez, Yu Yao, Miguel Steiner, Sauradeep Majumdar, Charles B. Musgrave III, Anirban Chandra, Abhirup Patra, Detlef Hohl, Connor W. Coley, Ju Li, Rafael Gómez-Bombarelli (2026)
Highlighted by Jan Jensen
AtomisticSkills is a hierarchical research framework in which skills encode reusable, mid-level scientific workflows, while tools provide low-level, type-checked computational operations that agents can reliably call to execute those workflows. While LLMs can in principle assemble such workflows from package documentation and first principles, in practice their performance degrades as context length grows. Put another way, trying to keep the manuals and execution details for RDKit, ORCA, and related tools in context at the same time is likely to increase hallucinations in the proposed workflow. Instead, complicated workflows are distilled by experts into SKILL.md files that outline how the tools are to be used, and these can be loaded into general-purpose coding agents such as Claude Code and Codex.
I especially like this last point. AtomisticSkills lets researchers use a tool they may already be familiar with, but apply it to new scientific problems. It looks like an interesting way to share robust workflows with non-experts. Take, for example, the installation of AtomisticSkills itself: it basically amounts to downloading the repository and telling Codex to “Install AtomisticSkills according to its docs/setup.md guide,” after which the agent interactively guides the user through comparatively complicated steps such as creating environments, configuring API keys, and registering MCP servers.
For example, while we have made the xTB version of our EsNuEl workflow available through a web server, making the DFT versions available there was not practical. Installing it locally from the repo is of course possible, but perhaps a little intimidating for the target group of synthetic chemists. An approach like this might be more palatable: package the workflow as a skill, provide tested scripts and examples, and let a general-purpose coding agent guide the user through local setup and execution.
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