pyopenms
Complete mass spectrometry analysis platform. Use for proteomics workflows feature detection, peptide identification, protein quantification, and complex LC-MS/MS pipelines. Supports extensive file formats and algorithms. Best for proteomics, comprehensive MS data processing. For simple spectral comparison and metabolite ID use matchms.
81
78%
Does it follow best practices?
Impact
77%
1.37xAverage score across 3 eval scenarios
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./scientific-skills/pyopenms/SKILL.mdEvaluation results
76%
19%LC-MS Data Preprocessing Service Script
Signal preprocessing pipeline
pyopenms alias
0%
100%
Parameter pattern
100%
100%
Gaussian smoothing
100%
100%
High-res peak picker
100%
100%
Normalizer method param
0%
100%
Intensity filtering
0%
100%
Profile/centroid check
0%
0%
Original data preserved
100%
0%
MzML output saved
100%
100%
70%
20%Multi-Sample LC-MS Feature Quantification Pipeline
Feature detection and cross-sample linking
pyopenms alias
0%
100%
FeatureFinder centroided
0%
0%
setPrimaryMSRunPath
100%
100%
Pose clustering aligner
100%
100%
QT grouper
100%
100%
ppm MZ unit
0%
100%
ConsensusXML output
100%
100%
DataFrame export
0%
0%
87%
25%Automated Proteomics Identification Post-Processing
Peptide identification FDR and protein inference
pyopenms alias
0%
100%
idXML load pattern
33%
58%
FDR object apply
100%
100%
q-value threshold
0%
46%
BasicProteinInference
53%
100%
IDMapper annotate
76%
100%
idXML store pattern
100%
100%
DecoyGenerator usage
100%
100%
- Repository
- K-Dense-AI/claude-scientific-skills
- Commit
b58ad7e
- Evaluated
- Agent
- Claude Code
- Model
- Claude Sonnet 4.6
Table of Contents
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