| name | matchms |
| description | Spectral similarity and compound identification for metabolomics. Use for comparing mass spectra, computing similarity scores (cosine, modified cosine), and identifying unknown compounds from spectral libraries. Best for metabolite identification, spectral matching, library searching. For full LC-MS/MS proteomics pipelines use pyopenms. |
| source_skill_id | k-dense-ai-scientific-agent-skills-scientific-skills-matchms-skill-md |
| category | Science, research & data analysis |
| source_mirror | ../../../../../skills/by-category/science-research-data-analysis/latest-release-community/matchms/SKILL.md |
| benchmark_status | artifact_gated |
matchms
Use this skill when the task matches the description above or the source path clearly applies. Start with this concise entrypoint; open ../../../../../skills/by-category/science-research-data-analysis/latest-release-community/matchms/SKILL.md only when implementation details, commands, assets, or references are needed.
Workflow
- Confirm the task matches this skill's scope.
- Read the local source mirror if more detail is required.
- Follow repository-level
AGENTS.md; use one AI session only.
- Keep claims tied to files, commands, citations, or benchmark artifacts.
Verification
- Source mirror:
../../../../../skills/by-category/science-research-data-analysis/latest-release-community/matchms/SKILL.md
- Source commit:
eb20fb0dcb0b1dadaa3db2737188f0755bbc4770
- Static benchmark results: see
docs/benchmark-results.md
- Runtime artifacts recorded by this entrypoint:
0
- Assigned scenarios:
skill-proof-k-dense-ai-scientific-agent-skills-scientific-skills-matchms-skill-md, science-research-and-data-analysis-cellxgene-census, science-research-and-data-analysis-chembl, science-research-and-data-analysis-ome-ngff-samples
Do not claim this skill passed a runtime benchmark until a validated artifact exists.
