matchms

Process, clean, compare, and search 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.

Quality

93%

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Securityby

Passed

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Quality

Content

86%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is action-oriented with executable code and a well-sequenced workflow that includes validation checkpoints and a checklist, supported by a clean one-level reference structure; only minor conciseness and feedback-loop gaps keep it from top marks.

Suggestions

Tighten the Citing section and the similarity-method bullet list to lift conciseness toward fully lean.

Add an explicit validate->fix->retry loop (e.g., for processing_report errors or empty score outputs) to reach the top workflow-clarity anchor.

Consider moving the full similarity-class catalog detail into references/similarity.md and keeping only the decision guidance inline.

Dimension	Reasoning	Score
Conciseness	The body is dense and assumes Claude's competence (no basic explanations of mass spectrometry or cosine scoring), but a few sections such as the citation block and the long similarity-method list could be trimmed, fitting the 'efficient with minor over-explanation' anchor rather than fully lean.	4 / 5
Actionability	Provides copy-paste-ready code (Quick Start, Pair Scoring, Large Comparisons, Spectrum Objects) and a fully-flagged CLI invocation covering common cases, matching the fully-executable anchor.	5 / 5
Workflow Clarity	The 8-step Operating Workflow is clearly sequenced with validation-relevant steps (estimate pair count, drop invalid spectra, validate top hits) plus a Non-Negotiable Checks checklist, but explicit validate->fix->retry feedback loops are only weakly present, placing it just below the top anchor.	4 / 5
Progressive Disclosure	A clear overview with well-signaled one-level-deep references to six real reference files (filtering, importing_exporting, migration, similarity, sources, workflows) and the bundled scripts/library_search.py, all verified to exist, matching the clear-overview anchor.	5 / 5
	Total	18 / 20 Passed

Description

100%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is concrete, comprehensive, and gives explicit trigger phrases plus a clear boundary against pyopenms, answering both what and when with minimal conflict risk.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions ('Process, clean, compare, and search tandem mass spectra') plus a comprehensive enumeration (file I/O, metadata harmonization, peak filtering, spectral similarity, library matching, score matrices, molecular-similarity networks), matching the comprehensive-coverage anchor.	5 / 5
Completeness	Explicitly states what it does ('Process, clean, compare, and search tandem mass spectra with matchms') and when to use it ('Use for MS/MS file I/O, ...'), plus a clear boundary clause, satisfying the explicit what-and-when anchor.	5 / 5
Trigger Term Quality	Covers natural domain terms a user would say ('tandem mass spectra', 'MS/MS', 'spectral similarity', 'library matching', 'score matrices', 'molecular-similarity networks', 'proteomics') with synonyms (MS/MS and tandem mass spectra), matching the comprehensive synonym coverage anchor.	5 / 5
Distinctiveness Conflict Risk	Occupies a clear niche (tandem mass spectra / matchms) and explicitly disambiguates from a neighboring tool ('Use pyopenms instead for LC-MS feature detection or proteomics pipelines'), giving minimal conflict risk.	5 / 5
	Total	20 / 20 Passed

Validation

100%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository: K-Dense-AI/scientific-agent-skills
Path: skills/matchms/SKILL.md
Commit: 49c6e97

Reviewed: 9 days ago

Table of Contents

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