{"id":77125,"plugin_id":"plugins_6ab424ad5b448191b8fede2ebf569333","kind":"skill","collection_source":"plugin_package","comparison_source":null,"observed_at":"2026-11-03T00:12:27.482Z","digest":"b40075c24304da88bf839a789018dde5a4e196650cb069dacc73dd17f03db304","against":null,"payload":{"description":"Review SQL data-model grain, key uniqueness, fact/dimension joins, slowly changing dimensions and metric definitions.","included_files":[],"name":"review-data-model","skill_md_contents":"---\nname: review-data-model\ndescription: Review SQL data-model grain, key uniqueness, fact/dimension joins, slowly changing dimensions and metric definitions.\n---\n\n\n# Model grain, semantics and correctness\n**Trigger:** Double-counted metrics, ambiguous keys, wrong joins, SCD, star schema, business metric design or data contract review.\n\n1. Identify intended business entity and grain of **each** input/output table. Mark primary/foreign keys, nullable keys and one-to-many relationships.\n2. Establish metric denominator, event time, valid-time/system-time and semantic definitions; use actual domain definitions, not guesses.\n3. Test join cardinality and fan-out before aggregate measures. Reduce child tables to agreed grain before joining; don't use DISTINCT to conceal root causes.\n4. For SCD type 2, define effective ranges, overlapping current rows, late corrections, surrogate keys and point-in-time joins.\n5. Check NULL semantics, time zones, currency, cancellation/refund treatment and missing/duplicate rows.\n6. Return model specification, sample reconciliation SQL and a regression checklist for BI consumers.\n\nRead `../../references/schema-contracts.md`, `../../references/warehouse-dbt.md`, `../../templates/model-contract.md`.\n"},"changes":[],"summary":"First saved snapshot. No earlier version is available for comparison.","summary_kind":"deterministic","summary_metadata":{}}