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Python library skill for importing, filtering, and comparing mass spectra (mzML/MGF/MSP); builds reproducible preprocessing pipelines and computes spectral simi
Adds mass-spectrometry data processing capabilities: import/export mzML, MGF, MSP, JSON; harmonize metadata; apply filters and QC; compute spectral similarity (cosine, modified cosine, fingerprint-based); and build reproducible processing pipelines. Useful for metabolomics, library matching, and large-scale spectral comparisons.
Use this skill when you need to preprocess mass spectrometry datasets, clean and harmonize metadata, filter noisy peaks, match unknown spectra against reference libraries, or compute spectral similarity scores for annotation and clustering. It fits workflows that ingest mzML/MGF/MSP files, run standardized filters, and output processed libraries for downstream analysis.
Primarily useful for code-capable agents that can run or author Python: Copilot/Codex/GPT-code-style agents, Claude Code, and other agents able to produce/run Python data-science workflows.
Matchms skill provides documentation for the open-source Python library for mass spectrometry data processing. No scripts included — purely a reference/documented skill. SKILL.md is well-organized with clear sections, code examples, and progressive disclosure to references/. No security concerns whatsoever. Very niche audience (metabolomics/MS researchers) limits broad usefulness.
Clean documentation-only skill. No executable code, no security issues. Well-structured following skill spec conventions with references/ for deeper docs. Low usefulness score reflects niche domain, not quality issues.