database-schema-designer

# Database Schema Designer

**Tier:** POWERFUL  
**Category:** Engineering  
**Domain:** Data Architecture / Backend  

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## Overview

Design relational database schemas from requirements and generate migrations, TypeScript/Python types, seed data, RLS policies, and indexes. Handles multi-tenancy, soft deletes, audit trails, versioning, and polymorphic associations.

## Core Capabilities

- **Schema design** — normalize requirements into tables, relationships, constraints
- **Migration generation** — Drizzle, Prisma, TypeORM, Alembic
- **Type generation** — TypeScript interfaces, Python dataclasses/Pydantic models
- **RLS policies** — Row-Level Security for multi-tenant apps
- **Index strategy** — composite indexes, partial indexes, covering indexes
- **Seed data** — realistic test data generation
- **ERD generation** — Mermaid diagram from schema

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## When to Use

- Designing a new feature that needs database tables
- Reviewing a schema for performance or normalization issues
- Adding multi-tenancy to an existing schema
- Generating TypeScript types from a Prisma schema
- Planning a schema migration for a breaking change

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## Schema Design Process

### Step 1: Requirements → Entities

Given requirements:
> "Users can create projects. Each project has tasks. Tasks can have labels. Tasks can be assigned to users. We need a full audit trail."

Extract entities:
```
User, Project, Task, Label, TaskLabel (junction), TaskAssignment, AuditLog
```

### Step 2: Identify Relationships

```
User 1──* Project         (owner)
Project 1──* Task
Task *──* Label            (via TaskLabel)
Task *──* User            (via TaskAssignment)
User 1──* AuditLog
```

### Step 3: Add Cross-cutting Concerns

- Multi-tenancy: add `organization_id` to all tenant-scoped tables
- Soft deletes: add `deleted_at TIMESTAMPTZ` instead of hard deletes
- Audit trail: add `created_by`, `updated_by`, `created_at`, `updated_at`
- Versioning: add `version INTEGER` for optimistic locking

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