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Agent skill

Mat Lammps Md

by learningmatter-mit in learningmatter-mit/AtomisticSkills

Build and run LAMMPS molecular dynamics with isolated MLIP-specific binaries (MACE, MatGL/CHGNet, FairChem) to avoid Python and Torch stack conflicts.

MITAuto-check passedResearch & Science

Install Mat Lammps Md

skills CLI
$ npx skills add learningmatter-mit/AtomisticSkills --skill mat-lammps-md -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install learningmatter-mit/AtomisticSkills mat-lammps-md --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/learningmatter-mit/AtomisticSkills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/mat-lammps-md .claude/skills/mat-lammps-md && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
mat-lammps-md
GitHub stars
175
Token cost
~1.2k tokens
SKILL.md length
424 words
Files
14 (incl. scripts)
Skills in repo
129
Repo updated
First seen
Licence
MIT

At a glance

Build and run LAMMPS molecular dynamics with isolated MLIP-specific binaries (MACE, MatGL/CHGNet, FairChem) to avoid Python and Torch stack conflicts.

  • Works in 3 steps: Select the MLIP backend and model family… → Check system prerequisites. → Identify GPU compute capability and set…
  • Tasks that involve Physical and earth sciences
  • SKILL.md covers Goal, Instructions, Examples and Constraints, plus 1 more section
  • Runs Shell and Python scripts from its folder; calls bash and cmake

What it does

Mat Lammps Md is an agent skill from learningmatter-mit/AtomisticSkills. Build and run LAMMPS molecular dynamics with isolated MLIP-specific binaries (MACE, MatGL/CHGNet, FairChem) to avoid Python and Torch stack conflicts.

Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 19 other files, including scripts (for example `examples/fairchem/README.md`, `examples/fairchem/run_fairchem_co_cu111_adsorption.sh` and `examples/mace/README.md`).

It sits in Research & Science, covering Physical and earth sciences. It works with Python and CUDA. The repository describes itself as: Integrating AtomisticSkills into Agentic IDEs (Cursor, Claude Code, Codex, Google Antigravity, Hermes Agent, etc). The licence is MIT.

When your agent uses it

  • Tasks that involve Physical and earth sciences

Example prompts

  • “/mat-lammps-md”

Requirements

  • Python 3
  • A Bash shell

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. Select the MLIP backend and model family first using the foundation-potential guide
  2. Check system prerequisites.
  3. Identify GPU compute capability and set Kokkos arch flag.

What it can do on your machine

Read from SKILL.md and the folder at commit 7f2d86d. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 3 files in scripts/ (Shell and Python), which the agent can run.

    Shell commands in SKILL.md call:

    • bash
    • cmake

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • arxiv.org
    • doi.org
    • docs.lammps.org
    • fair-chem.github.io
    • github.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Mat Lammps Md loads about 1.2k tokens when it runs. Until then it costs about 41 tokens; SKILL.md has 424 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~41
When it runs · the whole SKILL.md, loaded when a task matches
~1.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from learningmatter-mit/AtomisticSkills at commit 7f2d86d, republished under its MIT licence (© learningmatter-mit). 424 words, ~1,187 tokens.

Download SKILL.mdSave it as .claude/skills/mat-lammps-md/SKILL.md (or your agent's skills folder). This skill also uses 13 other files; get the full folder from GitHub.
name
mat-lammps-md
description
Build and run LAMMPS molecular dynamics with isolated MLIP-specific binaries (MACE, MatGL/CHGNet, FairChem) to avoid Python and Torch stack conflicts.
metadata.category
materials
metadata.venv
fairchem, mlip

LAMMPS Molecular Dynamics with MLIPs

Goal

Run GPU-accelerated LAMMPS molecular dynamics with MLIP backends using three isolated binaries (MACE, MatGL/CHGNet, FairChem) so Python embedding through ML-IAP/mliappy remains stable and reproducible.

Instructions

  1. Select the MLIP backend and model family first using the foundation-potential guide:

    • ml-foundation-potentials
    • This determines which environment (mlip for MACE and MatGL, fairchem for FairChem) and which LAMMPS binary you must use.

  2. Check system prerequisites.

bash
nvidia-smi
nvcc --version
g++ --version
cmake --version
mpicxx --version
  1. Identify GPU compute capability and set Kokkos arch flag.
bash
nvidia-smi --query-gpu=name,compute_cap --format=csv,noheader
  • Example mapping:
    • 8.0 -> Kokkos_ARCH_AMPERE80
    • 8.6 -> Kokkos_ARCH_AMPERE86
    • 8.9 -> Kokkos_ARCH_ADA89
    • 9.0 -> Kokkos_ARCH_HOPPER90
    • 10.0 -> Kokkos_ARCH_BLACKWELL100
    • 12.0, 12.1 (e.g. GB10 / DGX Spark) -> Kokkos_ARCH_BLACKWELL120 (Kokkos 4.6 has no 12.1 target; it runs, with a performance warning)

  1. Build the environment-matched LAMMPS binary (choose one of the three paths below). Builds go to $LAMMPS_ROOT (default ~/.cache/atomisticskills/lammps) and need the environment to run natively on the host.

    Path A: MACE (ACEsuit's LAMMPS fork with ML-MACE, linked against the mlip environment's libtorch)

bash
bash ${CLAUDE_SKILL_DIR}/scripts/build_lammps_mace.sh
  • Binary: ~/.cache/atomisticskills/lammps/mace/lmp
  • Runtime env: mlip+lammps
  • Needs a CUDA toolkit (CUDA_HOME) at least as new as the environment's torch build (12.6 for cu126, 13.0 for cu130); PyTorch's CMake config refuses an older one.

Path B: MatGL/CHGNet (Kokkos with CUDA, ML-IAP with the Python coupling, embedding the mlip environment's Python)

bash
KOKKOS_ARCH_FLAG=Kokkos_ARCH_AMPERE80 \
bash ${CLAUDE_SKILL_DIR}/scripts/build_lammps_matgl.sh
  • Binary: ~/.cache/atomisticskills/lammps/matgl/lmp
  • Runtime env: mlip+lammps
  • LAMMPS_REF defaults to stable_22Jul2025_update4, whose Kokkos knows current GPU architectures.

Path C: FairChem (no build: the lammps extra installs the LAMMPS wheel and fairchem-lammps)

bash
${CLAUDE_SKILL_DIR}/../../venv/run fairchem+lammps lmp_fc --help
  • Binaries: lmp and lmp_fc in the fairchem+lammps environment
  1. Run the selected binary in its matching environment.
bash
# (example; switch environment/binary pair as needed)
${CLAUDE_SKILL_DIR}/../../venv/run mlip+lammps ~/.cache/atomisticskills/lammps/mace/lmp -h
  1. Launch MD with the same binary-environment pair used during build; do not cross-run binaries between MLIP stacks.
Show full SKILL.md (160 more words)Show less

Examples

See scripts/three-backends-build-check/README.md for a minimal build/verification matrix across MACE, MatGL, and FairChem. See the respective README.md files under examples/mace/, examples/matgl/, and examples/fairchem/ for model-specific run scripts.

Constraints

  • Strict binary-env pairing: each LAMMPS binary must run only in the environment it was built against (venv/run mlip+lammps or venv/run fairchem+lammps).
  • No stack mixing: never run the MACE or MatGL binary in the fairchem environment, or lmp_fc in mlip.
  • GPU arch alignment: choose KOKKOS_ARCH_* from actual compute_cap output.
  • Python-coupled mode: this workflow targets ML-IAP/mliappy usage.

References

  • Thompson et al., "LAMMPS - A flexible simulation tool for particle-based materials modeling at the atomic, meso, and continuum scales", Computer Physics Communications, 2022. DOI
  • LAMMPS Manual, ML-IAP package documentation. Link
  • Batatia et al., "MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields". arXiv
  • Deng et al., "CHGNet as a pretrained universal neural network potential for charge-informed atomistic modelling". arXiv
  • FairChem documentation and model zoo. Link

Author: Jurģis Ruža Contact: GitHub @JurgisR

© learningmatter-mit, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 13 other files (scripts) in skills/mat-lammps-md of learningmatter-mit/AtomisticSkills.

  • SKILL.md
  • examples/fairchem/README.md
  • examples/fairchem/in.relax_adsorption_fairchem
  • examples/fairchem/run_fairchem_co_cu111_adsorption.sh
  • examples/mace/README.md
  • examples/mace/generate_na2si3o7_structure.py
  • examples/mace/in.na2si3o7_quench_mace
  • examples/mace/run_mace_na2si3o7_quench.sh
  • examples/matgl/README.md
  • examples/matgl/in.cu_phase_transition_matgl
  • examples/matgl/run_matgl_cu_phase_transition.sh
  • scripts/build_lammps_mace.sh
  • scripts/build_lammps_matgl.sh
  • scripts/three-backends-build-check/README.md

Open the folder on GitHubat commit 7f2d86d

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Works with

Categories

Questions about Mat Lammps Md

What does Mat Lammps Md do?

Build and run LAMMPS molecular dynamics with isolated MLIP-specific binaries (MACE, MatGL/CHGNet, FairChem) to avoid Python and Torch stack conflicts. Mat Lammps Md is an agent skill from learningmatter-mit/AtomisticSkills. Build and run LAMMPS molecular dynamics with isolated MLIP-specific binaries (MACE, MatGL/CHGNet, FairChem) to avoid Python and Torch stack conflicts.

When should I use Mat Lammps Md?

Mat Lammps Md fits situations like: tasks that involve Physical and earth sciences.

How do I install Mat Lammps Md in Claude Code?

Run `npx skills add learningmatter-mit/AtomisticSkills --skill mat-lammps-md -a claude-code`. Or copy the skill folder (skills/mat-lammps-md in learningmatter-mit/AtomisticSkills) into .claude/skills/mat-lammps-md in your project. Claude Code loads it when a task matches its description.

How do I install Mat Lammps Md in Codex?

Run `npx skills add learningmatter-mit/AtomisticSkills --skill mat-lammps-md -a codex`. Or copy the skill folder (skills/mat-lammps-md in learningmatter-mit/AtomisticSkills) into .agents/skills/mat-lammps-md in your project. Codex loads it when a task matches its description.

Can I use Mat Lammps Md in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add learningmatter-mit/AtomisticSkills --skill mat-lammps-md -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/mat-lammps-md, .gemini/skills/mat-lammps-md, .github/skills/mat-lammps-md and .opencode/skills/mat-lammps-md in your project.

What does Mat Lammps Md need to run?

Going by SKILL.md and its folder, Mat Lammps Md needs a shell and Python for the scripts in its folder and the command-line tools its instructions call (bash and cmake). Our summary lists: Python 3; A Bash shell.

Does Mat Lammps Md access the network?

SKILL.md names 5 domains. As links in the text: arxiv.org, doi.org, docs.lammps.org, fair-chem.github.io and github.com. This is read from the text; nothing was executed.

Is Mat Lammps Md safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Mat Lammps Md use?

Mat Lammps Md is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Mat Lammps Md use?

About 1.2k tokens (SKILL.md is roughly 4.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Mat Lammps Md?

Skills that share tags, products or a category with Mat Lammps Md: Nvmolkit Usage (NVIDIA-BioNeMo/bionemo-agent-toolkit, 478 stars), Pixi Environment Builder (xuzhougeng/wisp-science, 1k stars), Nvmolkit Usage (NVIDIA/skills, 3.5k stars) and Astropy (zLanqing/codex-claude-academic-skills, 4.6k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Mat Lammps Md?

learningmatter-mit (a GitHub organization) maintains it in learningmatter-mit/AtomisticSkills, which has 175 GitHub stars. The repository holds 129 skills in this directory. The repository was last updated on October 6, 2026.

Source: learningmatter-mit/AtomisticSkills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.