Update to Data Engineering Copilot

{
  "description": "Design dbt and SQL warehouse incremental models, tests, snapshots, lineage and release gates.",
  "included_files": [],
  "name": "design-warehouse-dbt",
  "skill_md_contents": "---\nname: design-warehouse-dbt\ndescription: Design dbt and SQL warehouse incremental models, tests, snapshots, lineage and release gates.\n---\n\n\n# Warehouse transformations and dbt\n**Trigger:** dbt model, incremental SQL, snapshots, table tests, warehouse optimization, semantic marts or deployment pipeline.\n\n1. Confirm warehouse/dialect, dbt version/adapter, source model and desired grain. Read repository config when available.\n2. Model layers for reusable staged sources, business transforms and consumer-facing marts. Define entities, metrics, freshness and lineage.\n3. For incremental models, specify unique key, source predicate including late-arrival window, strategy (append/merge/insert overwrite), schema changes and full-refresh conditions. Don't assume `unique_key` enforces uniqueness in every warehouse/strategy.\n4. Add tests for not-null, unique, relationships, accepted values, source freshness, grain and business-specific reconciliations. Use tests that return failing rows where practical.\n5. Version changes, compare baseline outputs, test snapshots and historical data and define rollback/backfill steps.\n6. Avoid claims that SQL or dbt ran without executed tool evidence.\n\nUse `../../references/warehouse-dbt.md`, `../../references/schema-contracts.md`.\n"
}