Schema Designer
VerifiedDesigns relational and NoSQL database schemas with proper normalization, indexing strategies, migration scripts, and entity-relationship diagrams.
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Copy the SKILL.md file to your project's .claude/skills/ directory About This Skill
Schema Designer creates well-structured database schemas from business requirements. It handles both OLTP (transactional) and OLAP (analytical) design patterns, producing proper normalization for operational databases and dimensional modeling for data warehouses.
How It Works
- Domain modeling — Identifies entities, relationships, cardinalities, and business rules from your description
- Normalization — Applies appropriate normalization (1NF through BCNF) with justified denormalization where needed
- DDL generation — Produces CREATE TABLE statements with proper types, constraints, and indexes
- Migration planning — Creates reversible migration scripts for schema changes on existing databases
- ORM mapping — Generates model definitions for Prisma, Drizzle, SQLAlchemy, TypeORM, or Django ORM
Best For
- Designing databases for new applications from scratch
- Refactoring schemas that grew organically without planning
- Creating analytics schemas (star/snowflake) for BI tools
- Planning safe schema migrations for production databases
Design Patterns
Supports polymorphic associations, multi-tenant isolation (schema-per-tenant vs shared), soft deletes, audit trails, temporal tables, and JSON column strategies for semi-structured data.
Use Cases
- Design normalized relational schemas from business requirements
- Create migration scripts for schema evolution with zero-downtime
- Generate Prisma, Drizzle, or SQLAlchemy model definitions from schema
- Design star/snowflake schemas for analytics data warehouses
Pros & Cons
Pros
- + Covers both OLTP normalization and OLAP dimensional modeling
- + Generates ORM model definitions for 5+ frameworks
- + Plans safe zero-downtime migration strategies
- + Handles advanced patterns: multi-tenant, temporal, polymorphic
Cons
- - Cannot validate schema against actual data volumes and access patterns
- - NoSQL schema design (MongoDB, DynamoDB) is less mature than relational
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