aidp-data-quality
Run data-quality rule checks on AIDP tables — not-null, uniqueness, allowed ranges/sets, referential integrity, and freshness. Use when the user wants to validate data, check for nulls/duplicates/orphans, assert a column's domain, or gate a pipeline on quality. Expresses each rule as bounded Spark SQL and reports pass/fail with offending counts.
Pinned to revision 4e8964e24a5a, so it is the text this page describes rather than whatever the author pushed since.
Files
- skills/aidp-data-quality/SKILL.md
- skills/aidp-data-quality/LICENSE
- skills/aidp-data-quality/references/dq-rules.md
- skills/aidp-data-quality/references/no-mcp-rest-map.md
- skills/aidp-data-quality/references/oci-raw-request.md
- skills/aidp-data-quality/references/semantic-model.md
- skills/aidp-data-quality/scripts/aidp_sql.py
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