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Agent Workflows · By learningmatter-mit
Skills
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| # | Skill | Repository | Stars | Used in | Tokens | Auto-check | Licence | Updated |
|---|---|---|---|---|---|---|---|---|
| 1 | Set up, check or troubleshoot how AtomisticSkills runs on this machine -- creating its Python environments, connecting its MCP servers, choosing uv or a container runtime, and configuring API keys. | learningmatter-mit/ | 176 | — | ~1.2k | Automated safety check: Notes | MIT | yesterday |
| 2 | Query Materials Project database for crystal structures, computed properties, elastic/magnetic data, and structurally similar materials using the MP API. | learningmatter-mit/ | 176 | — | ~3k | Automated safety check: Pass | MIT | yesterday |
| 3 | Simulate long-time kinetics using rejection-free kinetic Monte Carlo (KMC) with event catalog construction, rate assignment via TST/Arrhenius, detailed-balance validation, superbasin handling, and… | learningmatter-mit/ | 176 | — | ~3.8k | Automated safety check: Pass | MIT | yesterday |
| 4 | Iteratively optimize expensive black-box objectives — such as materials properties, experimental yields, or simulation outputs — by learning from past evaluations to select the most promising next… | learningmatter-mit/ | 176 | — | ~2.3k | Automated safety check: Pass | MIT | yesterday |
| 5 | train a Cluster Expansion (CE) for lattice-based Monte Carlo simulation of disordered materials. | learningmatter-mit/ | 176 | — | ~2.1k | Automated safety check: Pass | MIT | yesterday |
| 6 | Hierarchically decompose high-level scientific workflows (from literature or user-proposed) into executable sequences of existing SKILLs and MCP tools for the research plan. | learningmatter-mit/ | 176 | — | ~936 | Automated safety check: Pass | MIT | yesterday |