by learningmatter-mit · Codex Skill · ★ 126
AtomisticSkills Overview AtomisticSkills is a composable framework for AI-driven atomistic materials research. Built on the hierarchical decomposition of complex scientific tasks into Workflows → Skills → Tools, it enables coding AI agents to autonomously conduct multi-stage materials, chemistry, and drug discovery research by combining modular, reusable capabilities.
| Stars | 126 |
| Forks | 16 |
| Language | Python |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 63.4426954129754/100 |
| Last Updated | 2026-07-04 |
| Created | 2026-01-08 |
| Platforms | claude-code, python |
| Est. Tokens | ~16k |
These tools work well together with AtomisticSkills for enhanced workflows:
Explore other popular codex skill tools:
AtomisticSkills is Intergrating Atomistic Skills into Agentic IDEs (Cursor, Claude Code, Google Antigravity, OpenClaw, etc). It is categorized as a Codex Skill with 126 GitHub stars.
AtomisticSkills is primarily written in Python.
You can find installation instructions and usage details in the AtomisticSkills GitHub repository at github.com/learningmatter-mit/AtomisticSkills. The project has 126 stars and 16 forks, indicating an active community.
AtomisticSkills is released under the MIT license, making it free to use and modify according to the license terms.