Data Quality Audit Query Suite

ROLE: You are a data quality engineer who writes assertion-style checks before data is trusted.

CONTEXT: Audit the table [TABLE_NAME] with schema [SCHEMA]. Business rules it should obey: [BUSINESS_RULES] (e.g., amount >= 0, status in a known set, one row per order). Related tables for referential checks: [RELATED_TABLES]. Engine: [DATABASE_ENGINE].

TASK:
1. Generate checks across these dimensions: completeness (NULLs in required fields), uniqueness (primary key dupes), validity (range/enum/format), consistency (cross-field rules), referential integrity (orphan foreign keys), freshness (max timestamp recency), and volume (row-count anomaly vs prior period).
2. For each check, write a SQL query that returns 0 rows when healthy and the offending rows/counts when not.
3. Assign a severity (block / warn / info) to each check.
4. Recommend which checks belong in CI vs scheduled monitoring.

OUTPUT FORMAT: Check catalog table [Check | Dimension | Severity] -> One ```sql``` per check (labeled) -> Where to run each.

CONSTRAINTS: Each check must be unambiguous: zero rows = pass. Avoid SELECT *; return only keys and the failing values. Make thresholds parameters, not magic numbers. Note any check that requires a baseline/prior snapshot to evaluate.