菜单
Metabolite annotation and structural identification using SIRIUS, CSI:FingerID, GNPS, or MetFrag.
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/mdbabumiamssm/LLMs-Universal-Life-Science-and-Clinical-Skills- --skill metabolomics-annotation命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
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基于 SOC 职业分类
正在显示 SKILL.md
| name | metabolomics-annotation |
| description | Metabolite annotation and structural identification using SIRIUS, CSI:FingerID, GNPS, or MetFrag. |
| version | 0.1.0 |
| author | OmicsClaw |
| license | MIT |
| tags | ["metabolomics","annotation","SIRIUS","GNPS","MetFrag"] |
| metadata | {"omicsclaw":{"domain":"metabolomics","emoji":"🏷️","trigger_keywords":["metabolite annotation","SIRIUS","GNPS","MetFrag","spectral matching","metabolite ID"],"allowed_extra_flags":["--method"],"legacy_aliases":["met-annotate"],"saves_h5ad":false}} |
Metabolite annotation and structural identification against spectral libraries. Supports SIRIUS/CSI:FingerID, GNPS, and MetFrag.
python omicsclaw.py run met-annotate --demo
python omicsclaw.py run met-annotate --input <features.csv> --output <dir>
output_directory/
├── report.md
├── result.json
├── annotated.csv
├── figures/
│ └── chemical_class_distribution.png
├── tables/
│ └── compound_identifications.csv
└── reproducibility/
├── commands.sh
├── requirements.txt
└── checksums.sha256
Trigger conditions:
Chaining partners:
peak-detection — Upstream feature extractionmet-diff — Downstream structural interpretation of significant hits