Pyopenms

If you're doing proteomics or metabolomics work and need to process LC-MS/MS data, this is the Python interface to OpenMS, which is basically the standard toolkit for computational mass spectrometry. It handles all the usual file formats (mzML, mzXML, mzIdentML), does feature detection across samples, integrates with search engines like Comet and Mascot for peptide identification, and includes the signal processing algorithms you need for quantitative workflows. The API can feel a bit heavy since it's wrapping a large C++ library, but it's comprehensive and battle tested. Export to pandas DataFrames when you need to do custom analysis or ML work downstream.

skills.sh installs: 2K
GitHub stars: 56.6K
last updated: Aug 21, 2026

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Install

$ npx -y skills add k-dense-ai/scientific-agent-skills --skill pyopenms --agent claude-code

Installs into .claude/skills of the current project.

Files

PyOpenMS

Overview

PyOpenMS provides Python bindings to the OpenMS library for computational mass spectrometry, enabling analysis of proteomics and metabolomics data. Use it to read/write MS file formats, process raw spectra, detect and quantify features, identify peptides and proteins, and run end-to-end LC-MS/MS pipelines.

This skill ships ready-to-run scripts in scripts/ covering the most common high-level workflows. Prefer running a script over writing new code—each is a parameterized CLI tool that handles loading, processing, and export. Drop into the Python API (and the references/) only when no script fits.

Installation

uv venv --python 3.13
uv pip install "pyopenms==3.6.0" pandas numpy matplotlib

Verify (note: __version__ works, but the bundled binary prints a one-line memory-status notice on import that is harmless):

import pyopenms as ms
print(ms.__version__)  # 3.6.0

Scripts (start here)

SKILL.md on GitHub

Details

Repository: github.com/k-dense-ai/scientific-agent-skills
Categories: AI & Agent Building, Data Science & ML
First seen: Jun 3, 2026