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预测分子的临界密度
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
Use this skill when user wants to view one or multiple PDB / SDF files in the 3D structure viewer. Trigger when user mentions: open pdb, open sdf, 3D structure, view protein, view molecule, or provides local .pdb/.sdf file(s) to view. Supports viewing multiple files simultaneously by chaining path parameters with '&'.
When the service is deployed on a cloud server, use this skill when the user provide a file path and ask to download to their personal computer. This skill upload a file to Alibaba Cloud OSS and generate a shareable preview link for users to download easily. Trigger especially when user mentions: download file, upload to OSS, cloud storage upload, view image, preview image, generate share link, preview file via URL, or provides a local file path that needs to be shared online.
输入PDB ID，获取相应的PDB文件
预测化合物的admet性质
Build the final collection report in two steps: model writes a report template, then script injects each paper's Brief Conclusion and abs URL from summary.md by arXiv-id placeholders.
Tool-only paper processing skill with a manual language parameter: supports batch artifact download for many papers or single-paper download, then the model manually reads source/PDF and writes summary.md in the selected language. Use when per-paper comprehension should be model-driven instead of script-generated.
| name | critical-density-predict |
| description | 预测分子的临界密度 |
| license | Proprietary. LICENSE.txt has complete terms |
When given a compound, predict its critical density.
| 参数名 | 类型 | 必填 | 描述 |
|---|---|---|---|
smiles | string | 是 | SMILES字符串或包含SMILES的文件路径（通过标准输入传递） |
output | string | 否 | 输出文件路径，不指定时：单条SMILES输出到终端，CSV文件写回原文件 |
smiles-column | string | 否 | CSV文件中SMILES列的名称，不指定时自动检测 |
batch-size | integer | 否 | 推理批处理大小，默认32 |
device | string | 否 | 推理设备：auto, cpu, cuda，默认auto |
cd skills/critical_density && python critical_density_predict.py
运行后输入 SMILES 字符串或文件路径。
# 直接预测单个SMILES的临界密度
echo "CCO" | cd skills/critical_density && python critical_density_predict.py
# 批量预测CSV文件中所有SMILES的临界密度
echo "path/to/smiles.csv" | cd skills/critical_density && python critical_density_predict.py
cd skills/critical_density && python critical_density_predict.py [--smiles-column COLUMN] [--batch-size SIZE] [--device {auto,cpu,cuda}] [--output OUTPUT_FILE]
# 直接预测CCO的临界密度
echo "CCO" | python critical_density_predict.py
# 从csv文件批量预测临界密度（相对路径）
echo "../../critical_density.csv" | python critical_density_predict.py
# 从csv文件批量预测临界密度（绝对路径）
echo "D:/PythonProjects/skills_test/critical_density.csv" | python critical_density_predict.py
# 指定输出文件
echo "smiles.csv" | python critical_density_predict.py --output predictions.csv