
from asi16
Mass-spectrometry processing library: import/export mzML/MGF/MSP, harmonize metadata, apply filters, and compute spectral similarity for metabolomics workflows.
matchms adds robust mass-spectrometry data processing and similarity scoring to an agent's toolkit. It supports importing common formats (mzML, MGF, MSP, JSON), standardizing and harmonizing metadata, applying peak and quality filters, building reproducible processing pipelines, and calculating spectral similarity (cosine, modified cosine, and variants). Typical outputs include cleaned spectra, similarity scores, and processed libraries ready for downstream analysis or visualization.
Use this skill when an agent needs to ingest raw MS files, clean and normalize spectra, run quality-control filters, compare query spectra to reference libraries, or construct batch processing workflows for metabolomics or small-molecule MS analyses. It is appropriate for automated library searches, spectral matching, QC pipelines, and converting between common MS formats.
This is a Python-centered skill and is most useful for agents that can run Python code or orchestrate Python environments (Copilot/Codex/GitHub Actions runners, Python-capable assistant runtimes). It complements tools that handle data I/O and plotting for result visualization.
Documentation-only skill for the matchms Python library (mass spectrometry data processing). No scripts bundled — purely reference content with code examples for importing/exporting MS data, filtering, spectral similarity, and pipeline building. SKILL.md is well-structured with clear sections and pointers to a references/ directory, but entirely static with no executable logic or output contracts.
Clean, benign skill — just documentation for a specialized scientific Python library. No security concerns whatsoever. Low usefulness score reflects the extremely narrow audience (mass spectrometry / metabolomics researchers).