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AutoMD-GROMACS — 技能工具

v5.0.0

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

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by @billwanttobetop (Billwanttobetop)·MIT-0
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License
MIT-0
最后更新
2026/4/11
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OpenClaw
安全
high confidence
The skill's files, instructions, and required tools are coherent with an AI-oriented GROMACS automation toolkit; nothing in the package demands unrelated credentials or hidden endpoints, but review before executing network/publish actions.
评估建议
This package is coherent with an AI-friendly GROMACS automation toolkit and appears to be what it claims. Before running anything: (1) ensure gmx and python3 come from trusted installs (conda-forge or upstream), (2) inspect any scripts that auto-download resources or call pip/git before executing them, (3) avoid running publish/push/remote-upload commands (clawhub, git push, scp) from untrusted hosts or without reviewing authorship, and (4) if you want to test, run scripts in a sandboxed environ...
详细分析 ▾
✓ 用途与能力
Name/description (AutoMD-GROMACS) match the included scripts, analyses, and docs. Declared required binaries (gmx, python3) and runtime needs (PyYAML) are appropriate for the stated MD workflows. The large set of scripts and documentation aligns with the claimed capabilities (workflows, enhanced sampling, analysis, visualization).
ℹ 指令范围
SKILL.md and many scripts instruct the agent/user to run local scripts (scripts/*), use gmx and python3, and consult references/*. They also include explicit publish/upload steps (git, clawhub, scp) and automatic downloads (forcefields, martinize) in some scripts — these actions are expected for this domain but have side effects (network access, file writes). The instructions do not request unrelated system secrets or arbitrary file exfiltration, but they do encourage operations that can publish or upload the repository if executed.
✓ 安装机制
No opaque binary download URLs are embedded; SKILL.md suggests installing GROMACS via conda-forge or following the official manual, and PyYAML via pip. Where scripts auto-download forcefields or tools, the documentation references known project resources (MARTINI, martinize). There is a minor inconsistency between the registry-level 'no install spec' note and the SKILL.md's install guidance, but the install recommendations themselves are proportional and use mainstream sources.
✓ 凭证需求
The skill declares no required environment variables or credentials and only needs gmx/python3. Some workflows mention interactive login steps (clawhub login, git push) but do not require secrets be provided to the skill. No unexpected credentials or config paths are requested by the skill metadata or documentation.
✓ 持久化与权限
always is false and autonomous invocation is allowed (platform default). The skill does not request persistent platform-wide privileges or to modify other skills' configs. Several included docs give instructions for publishing the repository (git/clawhub) — these are user-driven actions, not automatic privileges embedded in the skill.
安全有层次，运行前请审查代码。

License

MIT-0

可自由使用、修改和再分发，无需署名。

运行时依赖

无特殊依赖

版本

latestv5.0.02026/4/8

Add decision layer with method-selector, canonical target map, V5 public packaging cleanup, and publishable release workflow.

● 无害

安装命令 点击复制

官方npx clawhub@latest install automd-gromacs
镜像加速npx clawhub@latest install automd-gromacs --registry https://cn.clawhub-mirror.com

技能文档

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

  • Read references/SKILLS_INDEX.yaml
  • If the method is not chosen yet, use scripts/decision/method-selector.py
  • Run the recommended script under scripts/
  • 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

数据来源：ClawHub ↗ · 中文优化：龙虾技能库
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