matchms
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.
88
86%
Does it follow best practices?
Impact
88%
4.63xAverage score across 3 eval scenarios
Advisory
Suggest reviewing before use
Security
1 medium severity finding. This skill can be installed but you should review these findings before use.
W011: Third-party content exposure detected (indirect prompt injection risk)
What this means
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
Why it was flagged
Third-party content exposure detected (high risk: 0.80). The skill explicitly loads spectra from public repositories via load_from_usi (references/importing_exporting.md) and fetches structure annotations from PubChem via derive_annotation_from_compound_name (references/filtering.md), meaning it ingests untrusted, user-generated third‑party content (e.g., GNPS/USI entries) that is parsed and used to drive processing and matching decisions.
- Repository
- K-Dense-AI/claude-scientific-skills
- Commit
b58ad7e
- Audited
- Security analysis
Is this your skill?
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