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BytesAgain β€Ί Skills β€Ί Automd Gromacs
πŸ¦€ ClawHub

Automd Gromacs

by @billwanttobetop

AutoMD-GROMACS: AI-friendly molecular dynamics automation for GROMACS with workflow, enhanced sampling, special-system simulation, advanced analysis, and pub...

Versionv5.3.3
Downloads1,304
Stars⭐ 2
#crypto-defi#legal#automation
TERMINAL
clawhub install automd-gromacs

πŸ“– About This Skill

name: automd-gromacs description: "AutoMD-GROMACS: AI-friendly molecular dynamics automation for GROMACS with workflow, enhanced sampling, special-system simulation, advanced analysis, and publication-ready visualization. Built-in troubleshooting and token-optimized execution. Part of the AutoMD series." metadata: openclaw: emoji: "🧬" category: science requires: bins: - gmx - python3 install: - id: conda kind: conda channel: conda-forge package: gromacs bins: - gmx label: Install GROMACS via conda - id: manual kind: manual url: https://manual.gromacs.org/current/install-guide/index.html label: Install GROMACS from source - id: pyyaml kind: manual url: https://pyyaml.org/wiki/PyYAMLDocumentation label: Install PyYAML for the decision layer (pip install pyyaml)

AutoMD-GROMACS

AutoMD-GROMACS is an AI-oriented automation toolkit for GROMACS. It packages decision-layer routing, end-to-end simulation workflows, enhanced sampling, special-system simulation, advanced analysis, and publication-ready visualization into a public OpenClaw skill with troubleshooting references.

Project metadata:

  • Version: 5.0.0
  • Author: Guo Xuan
  • Organization: Hong Kong University of Science and Technology (Guangzhou)
  • Homepage: https://github.com/Billwanttobetop/automd-gromacs

    • Scope

  • Decision layer: method routing before execution via method-selector
  • Core workflow: setup, equilibration, production, preprocessing, utilities
  • Enhanced sampling: umbrella, free energy, replica exchange, metadynamics, steered MD, enhanced sampling, accelerated MD
  • Special systems: membrane, ligand, coarse-grained, electric field, non-equilibrium, QM/MM
  • Validation and analysis: trajectory, binding, property, membrane, scattering, free-energy, protein-focused analyses
  • Visualization: publication-ready plotting and structure/trajectory rendering

    • Quick Start

    1. Read references/SKILLS_INDEX.yaml 2. If the method is not chosen yet, use scripts/decision/method-selector.py 3. Run the recommended script under scripts/ 4. If something fails, read references/troubleshoot/-errors.md

    Example:

    python3 scripts/decision/method-selector.py \
  --goal "binding free energy from a docked complex" \
  --system-type protein-ligand \
  --target-observable binding-free-energy \
  --pretty

    Design

  • Decision -> execution -> validation as the public product stack
  • Executable workflows over tutorial prose
  • Layered disclosure for low token overhead
  • Embedded domain knowledge from GROMACS practice
  • Auto-repair and troubleshooting guidance by default

    • Project Info

  • Version: 5.0.0
  • Based on: GROMACS 2026.1
  • Runtime needs: python3, PyYAML, gmx
  • License: MIT
  • Homepage: https://github.com/Billwanttobetop/automd-gromacs

    • Get started: read references/SKILLS_INDEX.yaml

    πŸ’‘ Examples

    1. Read references/SKILLS_INDEX.yaml 2. If the method is not chosen yet, use scripts/decision/method-selector.py 3. Run the recommended script under scripts/ 4. If something fails, read references/troubleshoot/-errors.md

    Example:

    python3 scripts/decision/method-selector.py \
  --goal "binding free energy from a docked complex" \
  --system-type protein-ligand \
  --target-observable binding-free-energy \
  --pretty