AI Agent Workflow Collection

Skill for executing ABACUS DFT materials calculations. Help users set up, run, and analyze ABACUS calculations.

Submit and manage computational jobs on Bohrium (bohrium.com) cloud platform using bohr CLI. Recommended for submission methods on Bohrium.

General guideline for MLFF model training. Describes the decision flow for choosing between pre-trained model validation, fine-tuning on available data, and launching a full PFD workflow.

LAMMPS molecular dynamics with DeepMD/DPA machine-learning potentials ONLY. This skill generates LAMMPS input files (in.lammps) using pairstyle deepmd. Classical force fields (Stillinger-Weber, Tersoff, EAM, etc.) are NOT supported and must NEVER be suggested. The default model is the DPA3 pretrained checkpoint frozen with the Omat24 head (from DEEPMDMODELPATH env var), identical to the ase-deepmd skill. A model file is always required — do NOT ask the user whether they want to use a classical potential instead. Bohrium's default DeepMD image (registry.dp.tech/dptech/deepmd-kit) already includes LAMMPS — no separate LAMMPS installation is needed. Covers structure conversion, input generation, Bohrium submission via bohrium skill, and result collection.

A modular Python framework for building and analyzing atomic structures with CLI tools for materials modelling.

Iterative workflow for materials design through candidate generation, property prediction, screening, and refinement.

Query Materials Project data for crystal structures, stability, electronic properties, phase diagrams.

MatterGen is a diffusion-based generative model for inorganic crystal structure generation. Use this skill to understand what MatterGen can do and which sub-skill to load. For generation, fine-tuning, or evaluation tasks, load the appropriate sub-skill.

Iterative workflow for model distillation. Generates a light ML force field from a pre-trained or fine-tuned model via active learning.

Iterative workflow that fine-tunes pre-trained ML force fields using DFT-labeled data via active learning.

Skill for scientific plotting using matplotlib. Generates, executes, and verifies publication-quality plots directly via runpython and runbash.

Web search, content extraction, crawling, and deep research via the Tavily CLI. Use this skill whenever the user wants to search the web, find articles, research a topic, look something up online, extract content from a URL, grab text from a webpage, crawl documentation, download a site's pages, discover URLs on a domain, or conduct in-depth research with citations. Also use when they say "fetch this page", "pull the content from", "get the page at https://", "find me articles about", or reference extracting data from external websites. This provides LLM-optimized web search, content extraction, site crawling, URL discovery, and AI-powered deep research — capabilities beyond what agents can do natively. Do NOT trigger for local file operations, git commands, deployments, or code editing tasks.

Crawl websites and extract content from multiple pages via the Tavily CLI.

Discover and list all URLs on a website without extracting content, via the Tavily CLI. Use this skill when the user wants to find a specific page on a large site, list all URLs, see the site structure, find where something is on a domain, or says "map the site", "find the URL for", "what pages are on", "list all pages", or "site structure". Faster than crawling — returns URLs only. Essential when you know the site but not the exact page. Combine with extract for targeted content retrieval.

Conduct comprehensive AI-powered research with citations via the Tavily CLI.

Skills for VASP DFT calculations — input preparation, remote submission to Bohrium, and result collection.

VASP DFT skills using pymatgen.io.vasp.sets (MPRelaxSet, MPStaticSet, MPNonSCFSet). INCAR is driven by pymatgen MP defaults; the agent only supplies userincarsettings overrides.