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validate-dms

Validate DMS documents for completeness and quality standards.

5|1|Updated Sep 23, 2025
Search Tags:#data engineering#yaml validation#schema quality#scd strategy#dms validation#data model specification#hld traceability
One-click install
npx skills add https://github.com/RDEWAI/Redefining-DataEngineering-With-AI --skill validate-dms
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: validate-dms
Source: https://github.com/RDEWAI/Redefining-DataEngineering-With-AI/tree/main/chapter-6/data-modeler-plugin/skills/validate-dms
Command: npx skills add https://github.com/RDEWAI/Redefining-DataEngineering-With-AI --skill validate-dms

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill eliminates the risk of incomplete or non-compliant Data Model Specifications (DMS) that block downstream data engineering work, catching gaps, missing requirements, and errors before handoff to mapping engineers.

Core Features & Use Cases

  • Comprehensive DMS Validation: Checks all 9 required DMS sections, YAML schema block syntax, metadata completeness, and layer-specific requirements for bronze, silver, and gold schemas.
  • Severity-Ranked Issue Reporting: Flags gaps as CRITICAL (blocks downstream work), WARNING (needs attention), or INFO (suggestions for improvement) with actionable fix suggestions for each finding.
  • Use Case: A data modeler preparing a DMS for a retail customer 360 dataset can use this Skill to audit the spec for missing SCD type documentation, absent HLD traceability citations, or invalid YAML schema blocks before passing it to the mapping team.

Quick Start

Use the validate-dms skill to review the completeness and quality of your Data Model Specification document at path 'outputs/dms/v1/customer-360-dms.md' and receive a prioritized list of issues to address.

Frequently Asked Questions about validate-dms

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

FAQPage Schema
How do I validate a Data Model Specification before handing it to the mapping team?▼

To validate a Data Model Specification, you can check it against completeness and quality standards to catch missing sections, invalid YAML schema blocks, and absent HLD traceability before downstream data engineering work begins.

What does DMS validation check for in bronze, silver, and gold layer schemas?▼

DMS validation checks all 9 required DMS sections, YAML schema block syntax, metadata completeness, SCD type documentation, naming conventions, and layer-specific requirements for bronze, silver, and gold schemas.

Can I validate an entire directory of DMS documents at once?▼

Yes, you can validate an entire directory of DMS documents. The validation supports both single DMS files and batch processing of full directories to report severity-ranked issues across multiple specs.

How are DMS validation issues reported and prioritized?▼

DMS validation issues are reported as severity-ranked CRITICAL, WARNING, or INFO findings. Each issue includes actionable fix suggestions, with CRITICAL items representing gaps that block downstream data engineering work.

What happens if my DMS is missing SCD type documentation or HLD traceability citations?▼

Missing SCD type documentation or absent HLD traceability citations are flagged as severity-ranked issues during DMS validation. You receive actionable fix suggestions to address these gaps before the spec is passed downstream.

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