Databricks Apps Development

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

Package manager — resolve this before any install or command below:

Databricks Apps officially supports npm and pnpm only.

1. Detect the project's manager, in priority order: project instructions → package.json's packageManager field → lockfile (pnpm-lock.yaml → pnpm, package-lock.json → npm).
2. If signals conflict, or if an unsupported manager (yarn, bun, etc.) is detected, stop and ask the user which manager to use before proceeding.
3. Only if none is established, default to pnpm.

Throughout this skill and its guides, substitute what you resolved:

• <pm> → that manager, for installs and package scripts (<pm> install, <pm> run typegen).

<pm> is a documentation placeholder, not a shell variable — expand it, don't type it.

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.