Can this skill help with existing database migrations?

Yes, it provides specific workflows for mapping legacy schemas to modern architectures while resolving inconsistencies and establishing canonical data models.

What database types does this skill support?

It supports a wide range of architectures including Relational (SQL), Document (NoSQL), Graph (Ontologies), Time-Series, and Dimensional (Data Warehouse) schemas.

How does it handle complex relationships?

The skill includes advanced patterns for many-to-many junction tables, polymorphic associations, and various hierarchy models like closure tables or adjacency lists.

Does it generate executable code?

It generates structured documentation and implementation artifacts, including SQL DDL, JSON Schema validation rules, and visual diagrams to guide development.

Data Schema & Knowledge Modeling

Name: Data Schema & Knowledge Modeling
Author: lyndonkl

bylyndonkl

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Database Management

Standardizes the design of rigorous database schemas, domain models, and knowledge graphs to ensure data integrity and system scalability.

This skill empowers Claude to act as a senior data architect by providing structured workflows for designing complex entity-relationship models, ontologies, and API contracts. Whether building a transactional SQL database, a flexible NoSQL document store, or a semantic knowledge graph, the skill guides the identification of entities, attributes, and constraints while enforcing best practices like normalization, referential integrity, and lifecycle modeling. It is particularly useful for resolving ambiguity in domain concepts, establishing data governance, and ensuring consistent structures across disparate systems during migrations or new builds.

Key Features

01Relationship & Cardinality Mapping: Clear definition of one-to-many, many-to-many, and polymorphic associations.

02Rigorous Constraint Definition: Establishment of business invariants, uniqueness rules, and data governance standards.

038 GitHub stars

04Multi-Paradigm Modeling: Comprehensive support for SQL, NoSQL, Graph, and Time-Series architectures.

05Standardized Documentation: Generates ERDs, UML diagrams, JSON Schemas, and SQL DDL statements.

06Entity Lifecycle Tracking: Advanced patterns for state transitions, soft deletes, and historical data modeling.

Use Cases

01Migrating legacy data structures to modern, scalable cloud architectures while maintaining referential integrity.

02Designing a new application's core database architecture and entity relationships from scratch.

03Building complex knowledge graphs and ontologies for semantic search and AI reasoning systems.

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add lyndonkl/claude data-schema-knowledge-modeling

For use in Claude.ai and ChatGPT

Download Skill