databricks-pipelines
Lakeflow Spark Declarative Pipelines Development
FIRST: Use the parent databricks-core skill for CLI basics, authentication, profile selection, and data discovery commands.
Decision Tree
Use this tree to determine which dataset type and features to use. Multiple features can apply to the same dataset — e.g., a Streaming Table can use Auto Loader for ingestion, Append Flows for fan-in, and Expectations for data quality. Choose the dataset type first, then layer on applicable features.
More from databricks/databricks-agent-skills
databricks-apps
Build apps on Databricks Apps platform. Use when asked to create dashboards, data apps, analytics tools, or visualizations. Evaluates data access patterns (analytics vs Lakebase synced tables) before scaffolding. Invoke BEFORE starting implementation.
329databricks-core
Databricks CLI operations: auth, profiles, data exploration, and bundles. Contains up-to-date guidelines for Databricks-related CLI tasks.
317databricks-jobs
Develop and deploy Lakeflow Jobs on Databricks. Use when creating data engineering jobs with notebooks, Python wheels, or SQL tasks. Invoke BEFORE starting implementation.
281databricks-lakebase
Databricks Lakebase Postgres: projects, scaling, connectivity, Lakebase synced tables, and Data API. Use when asked about Lakebase databases, OLTP storage, or connecting apps to Postgres on Databricks.
248databricks-dabs
Create, configure, validate, deploy, run, and manage DABs — Declarative Automation Bundles (formerly Databricks Asset Bundles) — for Databricks resources including dashboards, jobs, pipelines, alerts, volumes, and apps
219databricks
Databricks CLI operations: auth, profiles, data exploration, and bundles. Contains up-to-date guidelines for Databricks-related CLI tasks.
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