07-design-validation

Validate Gold layer YAML schemas, ERD diagrams, and column lineage CSVs for consistency.

5|6|Updated Jan 26, 2026
One-click install
npx skills add https://github.com/databricks-solutions/vibe-coding-workshop-template --skill 07-design-validation
Or copy as Structured Prompt for Agent
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Skill: 07-design-validation
Source: https://github.com/databricks-solutions/vibe-coding-workshop-template/tree/main/data_product_accelerator/skills/gold/design-workers/07-design-validation
Command: npx skills add https://github.com/databricks-solutions/vibe-coding-workshop-template --skill 07-design-validation

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill prevents costly implementation bugs by automatically cross-validating all Gold layer design artifacts, ensuring consistency between YAML schemas, ERDs, and lineage documentation before development begins.

Core Features & Use Cases

  • Cross-Artifact Validation: Compares YAML schemas against ERD diagrams to catch missing or extra columns and tables.
  • Lineage Verification: Ensures every Gold layer column has a documented lineage path.
  • PK/FK Integrity: Validates that all foreign key references correctly point to primary keys in other tables.
  • Mandatory Field Check: Confirms that all YAML schemas adhere to required properties and constraints (e.g., clustering, PK nullability).
  • Use Case: Before handing off the design for a new customer dimension table to the engineering team, run this skill to confirm that the ERD accurately reflects the YAML schema, all columns have lineage, and foreign keys are correctly defined, preventing potential runtime errors.

Quick Start

Run the complete design validation suite for the gold layer using the provided project directory.

Frequently Asked Questions about 07-design-validation

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

FAQPage Schema
How do I validate Gold layer design artifacts for schema consistency?

You can validate Gold layer design artifacts by cross-checking YAML schemas against ERD diagrams and column lineage CSVs to identify missing columns, incorrect foreign key references, and non-compliant table properties before implementation begins.

What is the best way to check foreign key integrity in a data model before implementation?

Checking foreign key integrity involves validating that all foreign key references correctly point to primary keys in other tables within your ERD diagrams and YAML schemas to prevent potential runtime errors during implementation.

How does column lineage verification work for Gold layer tables?

Column lineage verification works by ensuring every Gold layer column has a documented lineage path in the CSV files, confirming that all data transformations are accurately tracked and aligned with the defined schema.

Can I use automated validation to catch missing columns between YAML schemas and ERDs?

Yes, automated cross-artifact validation compares YAML schemas directly against ERD diagrams to catch missing or extra columns and tables, ensuring all design elements are aligned before development begins.

What mandatory field checks should I perform on Gold layer YAML schemas?

Mandatory field checks confirm that all YAML schemas adhere to required properties and constraints, verifying specific configurations like clustering and primary key nullability to mitigate design drift risks.

Why does design drift occur and how can I prevent it in data modeling?

Design drift occurs when documentation and schemas become misaligned over time; you prevent it by running a complete design validation suite to ensure ERDs accurately reflect YAML schemas and lineage before engineering handoff.