cuba_vigia
Analyze knowledge graph health, detect drift, identify communities and bridges, and compute structural centrality metrics for backbone analysis.
Instructions
Knowledge graph analytics: summary (counts + token estimate), health (staleness, entropy, DB size), drift (chi-squared on errors), communities (Leiden), bridges (betweenness centrality). v0.9: 'structural' returns harmonic + closeness + k-core ranking for backbone identification.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| metric | Yes | Metric to compute. v0.9: 'structural' adds harmonic + closeness centrality (Boldi-Vigna 2014, Bavelas 1950) + k-core decomposition (Seidman 1983). |