// Predict and visualize MS/MS spectra from a single SMILES using the fioRa online app. Use when the user wants a mass spectrum, MGF/MSP output, or a plotted stick spectrum from SMILES, with optional custom Name, precursor type, collision energy, and instrument settings.
Extract structured chemical compound characterization data from chemistry supplementary material documents (PDF/Markdown). 从化学论文补充材料(PDF/Markdown)中提取结构化化合物表征数据。 Use when Kimi needs to extract compound properties including NMR spectra, HRMS, HPLC data, melting points, optical rotation, and yield information from chemistry research papers or supplementary materials. 支持提取NMR谱图、HRMS、HPLC数据、熔点、旋光度、产率等信息。 Supports both single compound extraction and batch extraction of all compounds. 支持单个化合物提取和批量提取所有化合物。
Convert Gaussian gjf input files to XYZ format. 将Gaussian gjf输入文件转换为XYZ格式。 Use when agent needs to convert molecular structure files from Gaussian input format (.gjf) to XYZ format for visualization or use with other computational chemistry software. 当智能体需要将Gaussian输入格式(.gjf)的分子结构文件转换为XYZ格式用于可视化或其他计算化学软件时使用。
Convert PDF files to Markdown using MinerU API. 使用MinerU API将PDF文件转换为Markdown格式。 Use when Kimi needs to extract structured text, images, tables, and formulas from PDF documents while preserving document layout and formatting. 适用于需要提取结构化文本、图片、表格和公式并保留文档布局的场景。 Supports batch conversion and outputs full.md with images/, JSON metadata, and other extracted assets. 支持批量转换，输出full.md、images/目录、JSON元数据等。 Now supports large PDFs (600+ pages) by automatic splitting and merging. 现已支持大文件(600+页)自动拆分和合并处理。
Extract DFT calculation coordinates from PDF files and generate Gaussian gjf files. 从PDF文件中提取DFT计算坐标并生成Gaussian gjf输入文件。 Supports batch processing with separate output folders for each PDF. 支持批量处理，每个PDF单独生成输出文件夹。
Predict liquid-phase ¹H and ¹³C NMR chemical shifts from a SMILES string using NMRNet (deep learning, SE(3)-Transformer). Outputs per-atom shift values (ppm) and Lorentzian-broadened spectrum PNG files.
使用半经验方法 (xTB) 对分子三维结构进行几何优化，支持 SMILES 自动转 3D、XYZ 文件输入，输出优化后坐标、能量、收敛状态。
| name | ms-spectra-simulation |
| description | Predict and visualize MS/MS spectra from a single SMILES using the fioRa online app. Use when the user wants a mass spectrum, MGF/MSP output, or a plotted stick spectrum from SMILES, with optional custom Name, precursor type, collision energy, and instrument settings. |
Use this skill when the user provides a SMILES string and wants:
--name (optional, default: mol1)--precursor (optional, default: [M+H]+)--ce (optional, default: 20)--instrument (optional, default: HCD)--output-stem (optional, default: predicted_ms)--plot / --no-plot (optional, default: plot enabled)--show-title / --no-show-title (optional, default: no title on the plot)/tmp/chemclaw/predicted_ms.msp/tmp/chemclaw/predicted_ms.mgf/tmp/chemclaw/predicted_ms.pngIf --output-stem mol1 is used, the outputs become:
/tmp/chemclaw/mol1.msp/tmp/chemclaw/mol1.mgf/tmp/chemclaw/mol1.pngWhen returning results to the user, include the generated spectrum image directly in the response when a PNG was created.
https://apps.bam.de/shn01/fioRa/.conda create -n fiora-online python=3.10 pip -y
conda activate fiora-online
cd ms-spectra-simulation
python -m pip install -r requirements.txt
python -m playwright install chromium
python ms_spectra_simulation.py CCO
cd ms-spectra-simulation
python ms_spectra_simulation.py CCO
This uses:
name=mol1precursor=[M+H]+ce=20instrument=HCDcd ms-spectra-simulation
python ms_spectra_simulation.py "CCO" \
--name mol1 \
--precursor "[M+H]+" \
--ce 20 \
--instrument HCD
cd ms-spectra-simulation
python ms_spectra_simulation.py "CCO" --no-plot
cd ms-spectra-simulation
python ms_spectra_simulation.py "CCO" --show-title