{"id":77118,"plugin_id":"plugins_6ab424ad5b448191b8fede2ebf569333","kind":"skill","collection_source":"plugin_package","comparison_source":null,"observed_at":"2026-11-03T00:12:27.191Z","digest":"ba7660c209c9e6fe4e5830363e00b90bd55a519f0d01f07fb358b7ee59eb93ed","against":null,"payload":{"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"},"changes":[],"summary":"First saved snapshot. No earlier version is available for comparison.","summary_kind":"deterministic","summary_metadata":{}}