// Audits database data quality (nulls, duplicates, orphans, invalid ranges) and produces a short findings report with remediation queries. Use when debugging data issues, validating migrations, or verifying analytics correctness.
Diagnoses and fixes slow database queries using explain plans, statistics, and targeted indexes or rewrites. Use when an endpoint is slow, a query regresses, cpu spikes, or timeouts appear.
Inspects database schema and metadata (tables, columns, indexes, constraints, relationships). Use when exploring an unfamiliar database, writing joins, debugging query behavior, or documenting schema.
Plans and executes safe database migrations with low-downtime patterns, verification, and rollback. Use when changing schema, backfilling data, adding constraints, or creating indexes in production.
| name | data-quality-audit |
| description | Audits database data quality (nulls, duplicates, orphans, invalid ranges) and produces a short findings report with remediation queries. Use when debugging data issues, validating migrations, or verifying analytics correctness. |
Goal: find correctness issues quickly and return a small, actionable report.
SELECT COUNT(*) AS null_count
FROM your_table
WHERE important_col IS NULL;
SELECT key_col, COUNT(*) AS c
FROM your_table
GROUP BY key_col
HAVING COUNT(*) > 1
ORDER BY c DESC
LIMIT 50;
SELECT COUNT(*) AS orphan_count
FROM child c
LEFT JOIN parent p ON p.id = c.parent_id
WHERE c.parent_id IS NOT NULL
AND p.id IS NULL;
SELECT COUNT(*) AS bad_count
FROM your_table
WHERE amount < 0;
SELECT COUNT(*) AS bad_count
FROM your_table
WHERE created_at > NOW();
count(*) + targeted where clauseslimit when inspecting example rows## data quality audit
### scope
- tables:
- time window:
### findings
- [severity] issue: evidence
### likely impact
- user impact:
- analytics impact:
### remediation
- step 1:
- step 2:
### verification
- query checks: