Skip to content
Back to skills

Interfaces Md

ASecurity

"Run trained SchNetPack models through ASE calculators, ensemble

  • 247 stars
  • 0 votes
  • 0 copies
  • 1 view
  • Added September 9, 2026
toolspythondatabase

Works with

  • cli

Security analysis

A100/100

Pro scans all 6 files and shows the line behind each finding

Scanned September 9, 2026

npx -y skills add VectorSpaceLab/AREX-Skill --skill interfaces-md --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of Interfaces Md?

Add the live security badge to your README. It updates with every re-scan.

Security grade badge for Interfaces Md
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/vectorspacelab-interfaces-md/badge)](https://www.skillsdirectory.com/skills/vectorspacelab-interfaces-md)

More formats (shields.io, HTML) on the badges page. Keep it an A: scan every change in CI with Pro.

Download with Pro
SKILL.md
---
name: interfaces-md
description: "Run trained SchNetPack models through ASE calculators, ensemble
  uncertainty, molecular dynamics configs, TorchScript deployment, and LAMMPS
  interface guidance."
disable-model-invocation: true
metadata:
  disco-role: operating
license: NOASSERTION
---

# SchNetPack Interfaces and Molecular Dynamics

Use this sub-skill when the task starts from an already trained SchNetPack model and asks to run, relax, deploy, or simulate atomistic systems.

## Route Here For

- ASE calculators with `SpkCalculator`, `AtomsConverter`, `AseInterface`, `SpkEnsembleCalculator`, `AbsoluteUncertainty`, or `RelativeUncertainty`.
- Single-point energy/force/stress prediction, ASE optimization, normal modes, short ASE MD, or batchwise relaxation planning.
- `spkmd` command construction, Hydra MD config files, checkpoint/restart handling, thermostat/barostat/integrator choices, RPMD, and CPU fallback.
- TorchScript deployment for the SchNetPack LAMMPS pair style with `scripts/deploy_for_lammps.py`.
- LAMMPS interface advice, including `pair_style schnetpack`, `pair_coeff` atom-type mapping, cutoff metadata, and build-risk warnings.

## Route Elsewhere

- Model architecture, output modules, response-force/stress training, and model checkpoints: `../models-atomistic/SKILL.md`.
- Training runs, Hydra training configs, callbacks, and checkpoint selection: `../training-configs/SKILL.md`.
- Dataset creation, ASE databases, property units, and unit conversion before training: `../data-pipelines/SKILL.md`.
- External LAMMPS compilation, source-tree patching, or cluster build-system changes: provide guidance only unless the user explicitly authorizes environment mutation.

## Fast Decision Guide

- For a Python workflow using ASE `Atoms`: start with [ASE interface](references/ase-interface.md).
- For production-style MD from CLI/config: start with [MD CLI](references/md-cli.md).
- For LAMMPS deployment: read [LAMMPS deployment](references/lammps.md), then use `scripts/deploy_for_lammps.py` only after checking model compatibility.
- For failures or unsafe requests: use [troubleshooting](references/troubleshooting.md).

## Safety Defaults

- Prefer `device="cpu"` for examples and dry runs unless the user confirms CUDA availability.
- Keep MD examples bounded; do not launch long MD, GPU workloads, dataset downloads, native tests, or LAMMPS builds by default.
- Treat SchNetPack's upstream LAMMPS patch helper as reference-only because it mutates an external LAMMPS source tree and build files.

Files in this skill

  • SKILL.md2.5 KB
  • references/ase-interface.md7.9 KB
  • references/lammps.md5.9 KB
  • references/md-cli.md7.6 KB
  • references/troubleshooting.md6.3 KB
  • scripts/deploy_for_lammps.py2.8 KB

Attribution

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.

Comments

Loading comments…

Newsletter

Get the weekly list of safe new skills, and the ones we pulled.