Borrowing it
Nothing to install: this file belongs to ZimoLiao/scholaraio. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/ZimoLiao/scholaraio/main/.claude/skills/gromacs/SKILL.mdgit clone --depth 1 https://github.com/ZimoLiao/scholaraioWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/zimoliao/scholaraio/gromacs)<a href="https://agentmods.dev/skills/zimoliao/scholaraio/gromacs"><img src="https://agentmods.dev/badge/skills/zimoliao/scholaraio/gromacs/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/zimoliao/scholaraio/gromacs"><img src="https://agentmods.dev/badge/skills/zimoliao/scholaraio/gromacs.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium analysis-evasion · line 1 Suspicious Unicode normalization or mixed-script contentFix: Review the flagged content for security risks. Ensure no credentials, secrets, or sensitive data are exposed.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00039 | $0.01813 |
| Opus 5 | $0.00019 | $0.00907 |
| Sonnet 5 | $0.00008 | $0.00363 |
| Haiku 4.5 | $0.00004 | $0.00181 |
Grade A, and why
gromacs scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 156 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GROMACS 分子动力学
用 GROMACS 做分子动力学模拟:从体系搭建、平衡、产出 MD 到轨迹分析和结合自由能评估。
本 skill 故意保持轻量:
- 它负责告诉 agent 什么时候该用 GROMACS、标准工作流是什么、哪些科学规范不能踩
- 它不充当完整命令手册
- 具体命令行选项、
.mdp参数、子命令语法统一去查scholaraio toolref
Agent 默认协议(toolref-first)
对 GROMACS 问题,agent 默认按这个顺序工作:
- 先判断问题属于哪一层:
gmx子命令、.mdp参数、分析工具、力场/拓扑流程 - 写
.mdp前先查 thermostat、barostat、constraints、cutoff、输出频率这类高风险参数 - 对用户自然语言说法,先
search再show - 如果
toolref已经能回答,就不要在 skill 中重复堆参数表 - 如果
toolref缺页或命中不理想,agent 应先完成任务,并明确这是toolref覆盖缺口,而不是用户需要自己手动适配
这意味着:
- 普通用户不需要自己打磨 GROMACS 参数映射
- agent 应优先自己把
Parrinello-Rahman、v-rescale thermostat、constraints h-bonds等问法映射到参数页 skill负责路线和规范,toolref负责参数与接口
前置条件
# 安装
conda install -c conda-forge gromacs
# 配体参数化
conda install -c conda-forge acpype ambertools
# 结合自由能
pip install gmx-MMPBSA
# 可视化(可选)
conda install -c conda-forge pymol-open-source
验证:gmx --version 应显示版本号和 GPU 支持信息。
何时使用
适合:
- 蛋白-配体结合、蛋白构象变化、膜蛋白、溶液中生物大分子
- 需要标准 MD 流程、轨迹分析、MM/PBSA 估算
不适合:
- 需要量子化学精度时,转 DFT / QM/MM
- 配体参数化来源不明、力场体系不一致时,不要直接推进
Toolref 优先
当 agent 不确定子命令、选项、.mdp 参数含义时,先查 toolref。
常用查法:
scholaraio toolref search gromacs "temperature coupling"
scholaraio toolref show gromacs mdp integrator
scholaraio toolref show gromacs mdp pcoupl
scholaraio toolref show gromacs mdp tau-t
scholaraio toolref show gromacs mdp ref-t
推荐习惯:
- 写
.mdp前,先逐项查核心参数 - 不靠记忆拼写 thermostat/barostat 选项
- 对“这项参数在当前版本是否还推荐”这类问题,优先相信
toolref而不是旧教程
如果遇到覆盖缺口:
- 先继续使用 GROMACS 官方文档完成任务
- 在输出中点明这里超出了当前
toolref覆盖 - 不要把补齐
toolref当成普通用户的前置工作
核心流程
知识库协作模式
这是本 skill 与普通 GROMACS 教程的核心区别。在任何模拟开始前:
- 用
scholaraio usearch "<体系关键词>"检索知识库中的相关论文 - 从论文中提取:力场选择依据、模拟参数(温度、压力、时长)、验证基准数据
- 在
.mdp文件注释中标注参数来源(如 "# 300 K, per Homeyer et al. 2014 JCTC") - 模拟完成后,将结果与论文数据定量对比
建议工作流:
- 读论文,确定力场、温压条件、盐浓度、模拟时长和验证指标
- 准备蛋白/配体结构与拓扑
- 构建溶剂盒并加离子
- 能量最小化
- NVT / NPT 平衡
- 产出 MD
- 轨迹分析
- 必要时做 MM/PBSA,并和文献/实验对比
典型输出:
- RMSD / RMSF / 氢键 / 回旋半径
- 关键构象快照或轨迹动画
- 结合自由能及误差条
- 对应文献基准的对比图
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 156 lines · 39 tokens per session scan A 499f7e1f4d34
gromacs is a skill published in the GitHub repository ZimoLiao/scholaraio (570 stars, last pushed 12d ago), licensed MIT. It adds 39 tokens to every session and 1,813 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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