Databricks Apps Development

FIRST: Use the parent databricks-core skill for CLI basics, authentication, and profile selection.

Is this even a Databricks App? Don't assume an app is the only way to show data. For a simple "dashboard with a few charts" and no app-specific need, the managed AI/BI (Lakeview) dashboard is the simpler path → use the databricks-aibi-dashboards skill, not this one. Reach for a custom Databricks App only when the user needs something AI/BI can't give them — bespoke interactivity/components, write-back, embedded or auth-gated workflows, a Genie/chat surface inside the app — or explicitly asks for an app. If it's genuinely ambiguous, surface both options (managed AI/BI dashboard vs custom app) and let the user choose instead of defaulting to an app. Once an app is the right call, it's fine for this skill to favor an app-based dashboard, and databricks-app-design covers building it well.

For data UI design (required for any data-displaying app): once you've confirmed the user wants a custom-code app (not a managed AI/BI dashboard — see above), if the app shows ANY data — a KPI/overview page, report, chart, table, query results, OR a conversational / chat / Genie natural-language assistant — you MUST use the databricks-app-design skill (alongside this one) to decide layout, charts, KPIs, semantic color, required states, and AI-result trust, and map them to AppKit components. This includes chat/Genie apps, not just static data views — if in doubt, use it.

Build apps that deploy to Databricks Apps platform.

Required Reading by Phase

Phase	READ BEFORE proceeding
Scaffolding	⚠️ STOP — review the State Storage Guidance and complete the Data Access Decision Gate below before scaffolding. Parent databricks-core skill (auth, warehouse discovery); then run databricks apps manifest + databricks apps init with --features and --set (see AppKit section below)
Writing SQL queries	SQL Queries Guide