Cluster and Portfolio Analysis
fastskill analyze helps you evaluate quality at system level, not only case level.
1) Cluster analysis
Group skills by semantic similarity to detect taxonomy health:- Very large clusters: broad or overlapping skill definitions
- Too many tiny clusters: fragmented naming or inconsistent scope
- Unexpected cluster members: missing or unclear skill descriptions
2) Similarity matrix
Inspect relationship density:3) Duplicate detection
Detect likely redundancy:Recommended cadence
- On every PR affecting skill content: duplicates + smoke evals
- Weekly: cluster + matrix review
- Before release: full eval suite + duplicate cleanup pass
Cluster quality checklist
- Cluster distribution looks balanced for current catalog size
- High-severity duplicates are resolved or justified
- New skills do not overlap existing core skills above threshold