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validate-gold

Validate Gold layer implementations against approved design specifications and data quality standards.

5|1|Updated Sep 23, 2025
Search Tags:#drift detection#data engineering#schema validation#gold layer#dq compliance#dag audit#scd2 check
One-click install
npx skills add https://github.com/RDEWAI/Redefining-DataEngineering-With-AI --skill validate-gold
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: validate-gold
Source: https://github.com/RDEWAI/Redefining-DataEngineering-With-AI/tree/main/chapter-6/developer-plugin/skills/validate-gold
Command: npx skills add https://github.com/RDEWAI/Redefining-DataEngineering-With-AI --skill validate-gold

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pyyaml, and includes scripts (resource) components.

What problem does it solve?

Manually verifying that Gold layer data engineering implementations match approved design specifications is time-consuming and error-prone, with drift between code and specs causing downstream analytics failures and production incidents.

Core Features & Use Cases

  • Comprehensive Compliance Checks: Validates builder presence, schema alignment, SCD2 read patterns, DQ gate ordering, DAG wiring, and requirement traceability against LLD §5.3, DMS §4, STM Silver-to-Gold mappings, and DQS §2-3 rules.
  • Severity-Ranked Reporting: Produces clear, prioritized audit findings (CRITICAL, WARNING, INFO) so teams can fix high-impact issues first.
  • Use Case: Run this skill before promoting a Gold layer build to production to catch missing builders, schema mismatches, or incorrect SCD2 filtering that would break downstream consumer reports.

Quick Start

Use the validate-gold skill to audit the patient_360 Gold layer implementation against the latest approved design specifications and receive a severity-ranked list of any compliance gaps or implementation drift.

Frequently Asked Questions about validate-gold

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

FAQPage Schema
How do I detect implementation drift in Gold layer data engineering code?▼

To detect Gold layer implementation drift, validate your data engineering code against approved low-level design, data model specifications, and data quality standards to identify schema mismatches and non-compliant read patterns before production promotion.

Can I validate SCD2 read patterns and DQ gate ordering before promoting a Gold layer build?▼

Yes, you can validate SCD2 read pattern compliance and DQ gate ordering by auditing Airflow DAG wiring and builder implementations against state transition matrix mappings and DQS section 2-3 Gold rules.

What is the best way to audit schema alignment for a patient_360 Gold layer implementation?▼

The best way to audit schema alignment for a patient_360 Gold layer is to validate builder presence and schema structures against LLD section 5.3 and DMS section 4, generating severity-ranked findings for engineering remediation.

Does schema validation for Gold layer data engineering require Airflow DAG wiring checks?▼

Yes, comprehensive Gold layer schema validation requires checking Airflow DAG wiring to ensure data quality gate ordering and state transition matrix Silver-to-Gold mappings are correctly implemented before production promotion.

Why does my Gold layer implementation fail requirement traceability checks during a pre-promotion audit?▼

Gold layer implementations fail requirement traceability checks when code drifts from approved LLD section 5.3 specifications, missing required builders or incorrect SCD2 filtering that breaks downstream consumer reports.

Do I need pyyaml to run a Gold layer data quality compliance audit?▼

Yes, pyyaml is required as a dependency to parse and validate the YAML-formatted low-level design and data model specification documents during the Gold layer data quality compliance audit.

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