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matchms

Process, clean, and compare mass spectrometry (MS/MS) spectra with Matchms; use when you need reproducible spectral filtering and similarity scoring for metabolomics workflows.

60

Quality

70%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

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tessl review fix ./scientific-skills/Data Analysis/matchms/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

53%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 content is substantive and actionable with real bundle files and a runnable example, but it is hurt by a duplicated section structure (boilerplate plus numbered repeats) and a batch workflow that lacks an explicit validation/verification checkpoint.

Suggestions

Remove the duplicated boilerplate sections (the un-numbered When to Use / Key Features / Dependencies / Example Usage / Implementation Details block) and keep only the substantive numbered sections to cut padding.

Add an explicit validation/verification checkpoint to the run plan (e.g., inspect the scores matrix shape, assert non-empty matches, fail fast on zero spectra) so the batch all-vs-all workflow earns a higher workflow_clarity score.

Make the bundled similarity_pipeline.py write or return real score output instead of the demo stub that only prints the matrix shape, so the example usage is fully reproducible end-to-end.

DimensionReasoningScore

Conciseness

The body duplicates its section structure (When to Use, Key Features, Dependencies, Example Usage, Implementation Details each appear twice), with the first set being generic boilerplate ("Use this skill when a data analytics task needs a packaged method instead of ad-hoc freeform output"), which is noticeably padded and unnecessary.

2 / 5

Actionability

A runnable Python example (load_from_mgf, calculate_scores, CosineGreedy) and a real script invoked via `--help` provide mostly executable guidance, but the bundled pipeline's output is demo-only ("simplified for demo", "we might save this to a file"), leaving a minor gap.

4 / 5

Workflow Clarity

The "Example run plan" lists a sequence (confirm inputs, edit CONFIG, run script, review output) but lacks an explicit validation checkpoint or error-recovery loop; per the batch-operation cap, an all-vs-all scoring workflow without validation cannot exceed 3.

3 / 5

Progressive Disclosure

References to references/filtering.md, references/similarity.md, and references/workflows.md are real, one level deep, and clearly signaled, but the duplicated section structure and inline cosine/fingerprint detail keep it just short of the 5 anchor.

4 / 5

Total

13

/

20

Passed

Description

87%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 strong: it pairs a concrete capability statement with an explicit "use when" trigger in a narrow, package-named niche. The only weakness is slightly generic action verbs and missing file-extension/synonym triggers.

DimensionReasoningScore

Specificity

"Process, clean, and compare" names three concrete actions on a specific domain (MS/MS spectra), but the verbs stay somewhat generic and lack the comprehensive concrete-action coverage of the 5 anchor.

4 / 5

Completeness

It explicitly states both what ("Process, clean, and compare ... spectra with Matchms; ... spectral filtering and similarity scoring") and when ("use when you need reproducible spectral filtering and similarity scoring for metabolomics workflows"), matching the 5 anchor's dual concrete-trigger form.

5 / 5

Trigger Term Quality

"mass spectrometry", "MS/MS spectra", "spectral filtering", "similarity scoring", and "metabolomics" give good natural keyword coverage, but file extensions (.mgf/.msp) and common synonyms are absent, so it falls short of the 5 anchor.

4 / 5

Distinctiveness Conflict Risk

The MS/MS metabolomics niche plus the named "Matchms" package create a clear, distinct trigger surface with minimal overlap risk against other skills.

5 / 5

Total

18

/

20

Passed

Validation

93%

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

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository
aipoch/medical-research-skills
Reviewed

Table of Contents

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