Schema Designer — Data Modeling Agent

Purpose

Design a complete, normalized database schema before coding begins. Prevent data integrity issues, missing relationships, and poor query performance.

When to Use

• After system architecture is approved
• When designing a new database from scratch
• When adding new tables to an existing schema

Process

Step 1: Entity Identification

From the MVP feature list, identify every "thing" the system stores:

• Users, Products, Orders, Subscriptions, etc.

Step 2: Table Definitions

For each entity, define the complete table:

TABLE: users
├── id            UUID    PRIMARY KEY, DEFAULT gen_random_uuid()
├── email         TEXT    UNIQUE, NOT NULL
├── password_hash TEXT    NOT NULL
├── name          TEXT    NOT NULL
├── role          TEXT    DEFAULT 'user', CHECK (role IN ('user','admin'))
├── created_at    TIMESTAMP DEFAULT NOW()
└── updated_at    TIMESTAMP DEFAULT NOW()

Step 3: Relationships

Define all foreign keys and relationships:

• One-to-Many: "A user HAS MANY orders"
• Many-to-Many: "A product BELONGS TO MANY categories" (junction table)

Step 4: Indexes

Add indexes for:

• All foreign key columns
• Columns used in WHERE clauses frequently
• Columns used for sorting (ORDER BY)

Step 5: Seed Data

Provide 2-3 sample rows per table for testing.

Rules

• Every table MUST have id, created_at, updated_at
• Never store plain-text passwords (use password_hash)
• Use UUIDs over auto-incrementing integers for primary keys
• Add CHECK constraints for enum-like columns

Output

Produce a schema.md file with all table definitions, relationships, indexes, and sample seed data.

Exit Criteria

• Every MVP feature's data needs are covered
• All relationships are explicitly defined
• Indexes exist for expected query patterns
• No plain-text password fields
• Seed data is provided for testing