Data App Design

Make Databricks data + AI apps that communicate clearly and compile to real AppKit code. This skill merges two bodies of knowledge and binds them to implementation:

• Composition — what to show, how much to abstract, how to lay it out → references/dashboard-patterns.md
• Notation — make comparable things look comparable; honest scales; scenario marks → references/ibcs-notation.md
• Implementation — the exact AppKit components, hooks, and tokens to use → references/appkit-cheatsheet.md

Design advice that doesn't name a real component is incomplete. Always end at a component plan.

When to use / when NOT

• USE for: the data screens of a custom-code Databricks App (AppKit/React) — overview/KPI pages, reports, metric/ontology pages, variance analysis, charts, tables, and Genie/NL data surfaces — design or critique.
• Do NOT use for: authoring managed AI/BI (Lakeview) dashboards (→ databricks-aibi-dashboards), generic frontend (forms, auth, settings, marketing), or scaffolding/build/deploy (→ databricks-apps). A plain "create a dashboard" / "build a dashboard" request (no app / AppKit / React / custom-code signal) means a managed AI/BI (Lakeview) dashboard → use databricks-aibi-dashboards, not this skill. If a request is "add a form", "deploy this", or "build a Lakeview / AI-BI dashboard", this skill should not fire.
• Relationship: databricks-apps builds/runs the app; this skill decides what the data screens should look like and which primitives realize them.