What problem does it solve? Building interactive data applications on Databricks requires navigating scaffolding commands, plugin manifests, data access patterns, and platform constraints that are easy to get wrong, leading to failed deployments and broken apps. ## Core Features & Use Cases - Guided Scaffolding: Derives the correct databricks apps init command from the live databricks apps manifest output, including plugin features and required resource bindings. - Data Access Decision Gate: Helps choose between Lakebase synced tables for low-latency lookups and SQL warehouse analytics for dashboards before writing any code. - Framework Coverage: Supports AppKit (React/TypeScript) plus Streamlit, FastAPI, Flask, Gradio, Dash, and Next.js with platform-specific port, auth, and deployment rules. - Use Case: A user asks for an internal tool that lets analysts search orders and trigger an ETL job; the skill evaluates storage needs, scaffolds an AppKit app with analytics and jobs plugins, generates typed SQL queries, and validates before deployment. ## Quick Start Use the databricks-apps skill to scaffold and deploy a Databricks App that displays sales KPIs from my Unity Catalog tables.