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data-integrity-audit

Assess data integrity across pipelines for schema validity and dbt compliance.

Updated Jan 26, 2026
Search Tags:#dbt#data-integrity#postgres#data-quality#lineage#schema-validation
One-click install
npx skills add https://github.com/l3ocho/mktpl-claude-datasaas --skill data-integrity-audit
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: data-integrity-audit
Source: https://github.com/l3ocho/mktpl-claude-datasaas/tree/main/plugins/data-platform/skills/data-integrity-audit
Command: npx skills add https://github.com/l3ocho/mktpl-claude-datasaas --skill data-integrity-audit

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Data teams need a precise, codified standard for what constitutes valid data. This skill defines the criteria for data integrity across schemas, lineage, and dbt health, and provides guidelines to enforce these standards during sprint execution and audits.

Core Features & Use Cases

  • Schema validity checks (tables exist, correct types, constraints present).
  • dbt project health and tests readiness (parsing, compilation, tests).
  • Lineage integrity and data-traceability checks (no orphaned models, upstream sources exist).
  • Data type consistency and query-safety considerations (dtype alignment, safe queries).
  • PostGIS considerations for spatial datasets (where applicable) and SRID checks.

Quick Start

Start a data integrity audit by running it against your data-platform workspace to validate schemas, models, and lineage during sprint cycles.

Frequently Asked Questions about data-integrity-audit

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I audit data integrity across dbt pipelines and Postgres schemas?▼

Data integrity audits enforce schema validity and dbt compliance by checking table existence, column types, constraints, and test readiness across data pipelines. This ensures your data warehouse maintains correct types and traceable lineage during sprint execution.

What does a dbt health check include for schema validation?▼

A dbt health check validates schema integrity by verifying required tables exist, column data types align correctly, and database constraints are present. It parses and compiles dbt projects to ensure tests are ready and lineage integrity is maintained.

Can I validate dbt lineage to find orphaned models in my data warehouse?▼

Lineage validation checks data traceability to identify orphaned models and verify upstream sources exist. This audit enforces dbt compliance by ensuring all models in your data platform have valid upstream dependencies.

Does this data integrity audit work with PostGIS spatial datasets?▼

The data integrity audit applies PostGIS considerations for spatial datasets, including SRID checks where applicable. This ensures spatial data type consistency and schema validity within your Postgres data warehouse.

How do I run a standalone schema audit for data platforms outside of sprint cycles?▼

You can run a standalone data integrity audit against your data-platform workspace to validate schemas, models, and lineage. This verifies dbt project health, data type consistency, and safe query practices independently of sprint execution.

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