Document Database Schemas Comprehensively

Database Schema Documentation helps create maintainable documentation for database structures. It organizes content from database overview to tables, columns, and relationships, and can describe logical and physical models. A schema reference may include an entity relationship diagram, table purpose, column types and constraints, defaults, relationships, indexes, and business rules. It can also document views, data types, migrations, rollback scripts, and change history.

Examples include a relational table format with column specifications and foreign key details, a database view example, PostgreSQL type notes, and a MongoDB collection example. It recommends cross-references, consistent naming, version history, and keeping documentation alongside schema changes.

Use this skill when documenting a database for developers, analysts, maintainers, or teams that need to understand data structures and constraints. It is useful for describing relationships, indexes, business rules, views, data retention, and changes introduced by migrations.

Do not copy example table names, column definitions, policies, migration identifiers, people, dates, downtime estimates, or sample values as facts about a real database. The examples are templates. Verify actual schema, enforcement location, cardinality, delete behavior, and migration impact against the database and application. Do not include sensitive production data in sample records.

Inputs include database and schema names, table and column definitions, data types, constraints, defaults, indexes, keys, relationships, views, business rules, migration history, and common query patterns. For NoSQL systems, document collection structure, nested objects, validation rules, and indexes. When describing migrations, record their changes, rationale, impact, and tested rollback approach.

The output can be Markdown organized by database objects, an ERD, table and view references, type guides, and migration notes. A table entry can state purpose, columns, relationships, indexes, and business rules. Relationship documentation can identify foreign keys, delete constraints, and cardinality. View documentation can list base tables, definition, output columns, and intended usage. For ongoing maintenance, update documentation with each schema change and link it to relevant code, APIs, and business requirements.

Guidance covers PostgreSQL, MySQL, SQL Server, Oracle, and NoSQL databases, with examples for MongoDB. It uses Markdown, SQL, JavaScript index creation syntax, and ERD diagrams. Suggested practices include version control alongside schema changes and automated tools that generate baseline documentation. It does not name a required documentation generator or diagramming product.

This skill is for database engineers, application developers, data modelers, technical writers, and analysts who need accurate schema references. Teams can use it to make structure and constraints easier to discover and maintain. Review generated documentation whenever the schema changes, and distinguish database-enforced rules from application-level rules.

Purpose: Stores user account information and authentication data

Relationships:

• One-to-many with orders (users.id → orders.user_id)