What problem does it solve? Turning existing MotherDuck data into a coherent, shareable analytics dashboard requires schema discovery, per-section SQL, and Dive composition; this Skill orchestrates that end-to-end workflow so the result is a saved workspace artifact rather than scattered queries. ## Core Features & Use Cases - Schema-first dashboard design: Explores live MotherDuck tables, metrics, dimensions, and date ranges before choosing the dashboard story and sections. - Structured composition defaults: Enforces one story per dashboard with one KPI row, one primary trend chart, optional breakdown chart, and optional detail table, with heavy shaping done in SQL. - Reusable patterns and runnable artifacts: Ships copy-pasteable Sales, Product Analytics, and Operational Metrics Dive templates plus Python and TypeScript example artifacts that produce KPI, trend, breakdown, and detail outputs. - Use Case: Ask for a revenue dashboard over your MotherDuck orders table and receive the dashboard story, validated per-section SQL, a Dive implementation plan, and the save/update path. ## Quick Start Ask the assistant to build a MotherDuck Dive dashboard with KPIs, a monthly trend, and a category breakdown over your existing analytics database.
