supabase

To navigate the Supabase schema, you can explore core tables and their relationships to accelerate data modeling. This provides quick schema awareness, allowing you to trace connections from storytellers to transcripts and analysis results.

You can query published stories with associated transcripts by applying optimized SQL join patterns across the Empathy Ledger tables. This supports generating cultural impact reports by retrieving storytellers, stories, and AI analysis results.

The best way to discover table relationships is by tracing join paths between core tables like storytellers, stories, and transcripts. This approach helps developers and analysts understand structural connections for performant data retrieval.

Yes, this Supabase schema navigation tool supports performant data retrieval across tenants. It is designed for developers, data analysts, and researchers who need to query tenant-specific storytellers, stories, and analysis results.

Knowing SQL is beneficial because the Skill provides example SQL patterns and reference materials for querying the Empathy Ledger database. It helps you write and optimize queries to fetch stories, transcripts, and themes.

The Skill focuses on schema discovery, relationship tracing, and providing example SQL patterns for AI analysis results. It does not perform the AI analysis itself, but rather helps you retrieve and navigate existing analysis data stored in the Supabase database.