K-Dense-AI/scientific-agent-skills
matchms
Processes, cleans, compares, and searches tandem mass spectra with matchms. Use for MS/MS file I/O, metadata harmonization, peak filtering, spectral similarity, library matching, score matrices, and molecular-similarity networks. Use pyopenms instead for LC-MS feature detection or proteomics pipelines.
Before you install
- Last update
- Files in folder
- 8
- Scripts
- Contains scripts. Review them before running.
- SKILL.md size
- 13 KB (about 3,205 tokens of context each time it loads)
- License
- MIT
- Source on GitHub
- K-Dense-AI/scientific-agent-skills
Skills are plain text instructions the agent follows, sometimes with scripts. Check the source, prefer repositories with many installs and stars, and read any script it ships.
Install
npx skills add K-Dense-AI/scientific-agent-skills@matchmsRuns in a terminal with Node.js 18 or newer. Add -y to skip the prompts and -g to install for every project instead of this one.
Install for your agent
npx skills add K-Dense-AI/scientific-agent-skills@matchms --agent claude-code -y- Project install writes to
.claude/skills/matchms- Global install writes to
~/.claude/skills/matchms
Start a new session afterwards so the agent picks the skill up. In Claude Code you can also call it directly with /matchms.
What it does
Matchms Purpose and Scope Matchms is a Python package for importing, cleaning, processing, and comparing tandem mass spectra. This skill targets matchms 0.33.1, released 2026-06-08, verified again on 2026-10-01. Older tutorials can use removed names; see the migration reference. Use matchms for: - MS/MS library search and query-versus-reference scoring - Metadata harmonization, adduct/precursor handling, and peak filtering - Cosine, modified-cosine, neutral-loss, approximate, and entropy scoring - Structured score matrices, top-hit extraction, and spectral networks - MGF, MSP, mzML, mzXML,…
Excerpt from the skill's own SKILL.md. Read the full file on GitHub before installing: skills run with your agent's permissions.
Categories
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