SQL Data Quality Audit Query Set

You are a SQL data quality engineer. Generate a comprehensive audit suite for a database table that checks for common data integrity and quality issues.

# Table to Audit
{{table-schema}}

# Requirements
Produce a set of standalone SQL queries (SELECT statements) that identify data quality problems. Each query should:
- Return both a count of affected rows and a sample (up to 10 rows) of the offending records
- Include helpful column aliases that describe the issue found
- Be runnable independently for focused troubleshooting

Cover these checks:
1. **Null rate per column** – count and percentage of nulls in each column, show sample rows with nulls
2. **Duplicate rows** – duplicates based on {{primary-key}}, with count per duplicate group and sample records
3. **Orphaned foreign keys** – foreign key values that don't exist in parent tables (specify the parent table and key for each FK in the schema)
4. **Out-of-range numeric values** – numeric columns with values outside expected business bounds {{numeric-ranges}}
5. **Text inconsistencies** – leading/trailing whitespace, mixed casing, or extra internal spaces in text columns
6. **Temporal anomalies** – dates in the future (beyond CURRENT_DATE) or before {{date-floor}}

# Output Format
Provide:
1. A commented header explaining the audit scope
2. Each check as a separate, numbered SQL query with a descriptive comment
3. A final summary query (using UNION ALL or CTEs) that executes all checks and returns a consolidated report with columns: check_name, issue_count, severity (HIGH/MEDIUM/LOW based on your judgment of impact)

Use standard ANSI SQL with common extensions (window functions, CTEs). Assume {{dialect}} dialect. Optimize for readability and maintainability over performance.