Individual skill

atlas-databricks

Databricks specifics for Atlas: the extended binary and login, connection URLs and scope (catalog vs schema), the dev catalog (no Docker), Delta table properties, managed and external tables, partitioning and liquid clustering, generated and identity columns, defaults and column mapping, renames, informational keys and checks, collations, column masks and row filters, views, metric views, and materialized views, SQL and Python functions, procedures, Unity Catalog grants, no transactions and no locks, partial failures, schema and migration tests, and custom lint rules. Use with the atlas skill whenever Atlas manages a Databricks database. For Databricks Lakebase, use atlas-lakebase.

skills/atlas-databricks/SKILL.md

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# Atlas for Databricks

What is specific to Databricks when Atlas manages the schema. The `atlas` skill covers the workflows and
commands; this skill covers the rules, edge cases, and answers that differ on Databricks. Atlas connects
through a SQL warehouse and manages Unity Catalog objects: schemas, Delta tables, views, materialized
views, functions, procedures, and grants.

Databricks Lakebase is a managed PostgreSQL service, not a Unity Catalog database: Atlas manages it with
the `postgres` driver, so use the `atlas-lakebase` skill instead, with `atlas-postgres`
(https://atlasgo.io/guides/postgres/databricks-lakebase).

## Files

This skill is `SKILL.md` plus seven reference files under `references/`, each served at
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