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data-dictionary-definition

Define a data dictionary with entities, attributes, types, and PII classifications.

1|Updated Nov 29, 2025
Search Tags:#governance#entities#pii#data-model#data-dictionary#attributes
One-click install
npx skills add https://github.com/SSiertsema/claude-code-plugins --skill data-dictionary-definition
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: data-dictionary-definition
Source: https://github.com/SSiertsema/claude-code-plugins/tree/main/data-dictionary-definition/skills/data-dictionary-definition
Command: npx skills add https://github.com/SSiertsema/claude-code-plugins --skill data-dictionary-definition

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Define a data dictionary to capture and standardize domain entities, attributes, types, constraints, and governance rules so teams share a common vocabulary and understanding.

Core Features & Use Cases

  • Structured catalog of entities and their attributes with type, constraints, sources, and PII classifications
  • Explicit relationships (foreign keys, associations, and one-to-many / many-to-many mappings) and versioned change history
  • Governance and data quality rules enabling consistent data modeling across products, analytics, and compliance
  • Use across data modeling, analytics, product requirements, and regulatory documentation

Quick Start

Start by enumerating your domain entities and their attributes, then capture relationships, data types, PII classifications, and governance metadata to initialize the data dictionary.

Frequently Asked Questions about data-dictionary-definition

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

FAQPage Schema
How do I create a data dictionary with PII classifications and governance rules?▼

To create a governed data dictionary, enumerate domain entities and attributes, then capture data types, constraints, PII classifications, and explicit relationships to establish a shared vocabulary across cross-functional workflows.

What is the best way to standardize domain entities and attributes for analytics and engineering?▼

Standardizing domain entities requires building a structured data dictionary that codifies attributes with types, sources, and PII classifications, ensuring consistent data modeling and shared understanding across analytics, product, and engineering teams.

How do I document foreign keys and entity relationships in a data model?▼

Document entity relationships by capturing explicit foreign keys, associations, and one-to-many or many-to-many mappings within your data dictionary, maintaining versioned change history to track structural evolution over time.

Can I use a data dictionary to enforce data quality and compliance workflows?▼

Yes, a governed data dictionary enforces data quality and compliance by validating attributes through a formal, phase-based workflow, ensuring every entry meets defined constraints and PII classifications before integration.

Does a structured data dictionary support versioned metadata for cross-functional teams?▼

A structured data dictionary supports versioned metadata by tracking change history for entities and attributes, enabling cross-functional teams in data governance, analytics, and product to rely on a consistent, formal domain model.

When do I need a formal data dictionary for domain modeling?▼

You need a formal data dictionary when cross-functional workflows require a structured domain model with explicit relationships, type constraints, and PII governance to maintain a shared vocabulary and regulatory compliance.

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