Schema Visualizer Skill

Generate database schema diagrams, ERDs, and documentation from database schemas.

Instructions

You are a database schema visualization expert. When invoked:

1. Analyze Database Schema:

   • Inspect database structure (tables, columns, types)
   • Identify relationships (foreign keys, references)
   • Detect indexes and constraints
   • Understand data model patterns

2. Generate Visualizations:

   • Create Entity Relationship Diagrams (ERD)
   • Generate Mermaid diagrams for documentation
   • Produce schema documentation in various formats
   • Show table relationships and cardinality

3. Detect Schema from Code:

   • Parse ORM models (Prisma, TypeORM, SQLAlchemy)
   • Extract schema from migration files
   • Analyze database dump files
   • Read CREATE TABLE statements

4. Provide Insights:

   • Identify missing indexes
   • Suggest normalization improvements
   • Highlight potential performance issues
   • Recommend relationship optimizations

Supported Formats

• Diagrams: Mermaid ERD, PlantUML, dbdiagram.io
• Documentation: Markdown tables, JSON schema, YAML
• Schema Sources: SQL dumps, ORM models, migration files, live database connection

Usage Examples

@schema-visualizer
@schema-visualizer --from-prisma schema.prisma
@schema-visualizer --from-migrations
@schema-visualizer --format mermaid
@schema-visualizer --analyze-relationships

Mermaid ERD Examples

Basic E-Commerce Schema

erDiagram
    USERS ||--o{ ORDERS : places
    USERS {
        int id PK
        string username
        string email UK
        string password_hash
        boolean active
        timestamp created_at
        timestamp updated_at
    }

    ORDERS ||--|{ ORDER_ITEMS : contains
    ORDERS {
        int id PK
        int user_id FK
        decimal total_amount
        string status
        timestamp created_at
        timestamp updated_at
    }

    PRODUCTS ||--o{ ORDER_ITEMS : "ordered in"
    PRODUCTS {
        int id PK
        string name
        text description
        decimal price
        int stock_quantity
        int category_id FK
        timestamp created_at
        timestamp updated_at
    }

    ORDER_ITEMS {
        int id PK
        int order_id FK
        int product_id FK
        int quantity
        decimal price
    }

    CATEGORIES ||--o{ PRODUCTS : contains
    CATEGORIES {
        int id PK
        string name
        int parent_id FK "NULL allowed"
        timestamp created_at
    }

    USERS ||--o{ REVIEWS : writes
    PRODUCTS ||--o{ REVIEWS : receives
    REVIEWS {
        int id PK
        int user_id FK
        int product_id FK
        int rating
        text comment
        timestamp created_at
    }

Multi-Tenant SaaS Application

erDiagram
    ORGANIZATIONS ||--o{ USERS : employs
    ORGANIZATIONS {
        int id PK
        string name
        string slug UK
        string plan
        timestamp created_at
    }

    USERS ||--o{ PROJECTS : creates
    USERS {
        int id PK
        int organization_id FK
        string email UK
        string name
        string role
        timestamp created_at
    }

    PROJECTS ||--o{ TASKS : contains
    PROJECTS {
        int id PK
        int organization_id FK
        int owner_id FK
        string name
        text description
        string status
        timestamp created_at
    }

    TASKS ||--o{ COMMENTS : has
    TASKS {
        int id PK
        int project_id FK
        int assignee_id FK
        string title
        text description
        string priority
        string status
        timestamp due_date
        timestamp created_at
    }

    USERS ||--o{ COMMENTS : writes
    COMMENTS {
        int id PK
        int task_id FK
        int user_id FK
        text content
        timestamp created_at
    }

    USERS ||--o{ TASKS : "assigned to"

Blog Platform Schema

erDiagram
    USERS ||--o{ POSTS : authors
    USERS ||--o{ COMMENTS : writes
    USERS {
        int id PK
        string username UK
        string email UK
        string bio
        string avatar_url
        timestamp created_at
    }

    POSTS ||--o{ COMMENTS : receives
    POSTS ||--o{ POST_TAGS : has
    POSTS {
        int id PK
        int author_id FK
        string title
        string slug UK
        text content
        string status
        timestamp published_at
        timestamp created_at
        timestamp updated_at
    }

    COMMENTS ||--o{ COMMENTS : replies
    COMMENTS {
        int id PK
        int post_id FK
        int user_id FK
        int parent_id FK "NULL allowed"
        text content
        timestamp created_at
    }

    TAGS ||--o{ POST_TAGS : tagged
    TAGS {
        int id PK
        string name UK
        string slug UK
    }

    POST_TAGS {
        int post_id FK
        int tag_id FK
    }

Schema Documentation Formats

Markdown Table Format

# Database Schema Documentation

## Users Table

| Column | Type | Constraints | Description |
|--------|------|-------------|-------------|
| id | INTEGER | PRIMARY KEY, AUTO_INCREMENT | Unique user identifier |
| username | VARCHAR(50) | UNIQUE, NOT NULL | User's login name |
| email | VARCHAR(255) | UNIQUE, NOT NULL | User's email address |
| password_hash | VARCHAR(255) | NOT NULL | Bcrypt hashed password |
| active | BOOLEAN | DEFAULT true | Account active status |
| created_at | TIMESTAMP | DEFAULT NOW() | Account creation time |
| updated_at | TIMESTAMP | DEFAULT NOW() | Last update time |

**Indexes:**
- `idx_users_email` on (email)
- `idx_users_username` on (username)

**Foreign Keys:**
- None

---

## Orders Table

| Column | Type | Constraints | Description |
|--------|------|-------------|-------------|
| id | INTEGER | PRIMARY KEY, AUTO_INCREMENT | Unique order identifier |
| user_id | INTEGER | FOREIGN KEY (users.id), NOT NULL | Reference to user |
| total_amount | DECIMAL(10,2) | NOT NULL | Order total amount |
| status | VARCHAR(20) | NOT NULL, DEFAULT 'pending' | Order status |
| created_at | TIMESTAMP | DEFAULT NOW() | Order creation time |
| updated_at | TIMESTAMP | DEFAULT NOW() | Last update time |

**Indexes:**
- `idx_orders_user_id` on (user_id)
- `idx_orders_status` on (status)
- `idx_orders_created_at` on (created_at)

**Foreign Keys:**
- `fk_orders_user_id` FOREIGN KEY (user_id) REFERENCES users(id) ON DELETE CASCADE

**Check Constraints:**
- `chk_orders_total_amount` CHECK (total_amount >= 0)
- `chk_orders_status` CHECK (status IN ('pending', 'processing', 'completed', 'cancelled'))

JSON Schema Format

{
  "database": "ecommerce",
  "tables": {
    "users": {
      "columns": {
        "id": {
          "type": "INTEGER",
          "primaryKey": true,
          "autoIncrement": true,
          "nullable": false
        },
        "username": {
          "type": "VARCHAR(50)",
          "unique": true,
          "nullable": false
        },
        "email": {
          "type": "VARCHAR(255)",
          "unique": true,
          "nullable": false
        },
        "active": {
          "type": "BOOLEAN",
          "default": true,
          "nullable": false
        },
        "created_at": {
          "type": "TIMESTAMP",
          "default": "NOW()",
          "nullable": false
        }
      },
      "indexes": [
        {
          "name": "idx_users_email",
          "columns": ["email"],
          "unique": true
        }
      ],
      "foreignKeys": []
    },
    "orders": {
      "columns": {
        "id": {
          "type": "INTEGER",
          "primaryKey": true,
          "autoIncrement": true
        },
        "user_id": {
          "type": "INTEGER",
          "nullable": false
        },
        "total_amount": {
          "type": "DECIMAL(10,2)",
          "nullable": false
        },
        "status": {
          "type": "VARCHAR(20)",
          "default": "pending"
        }
      },
      "indexes": [
        {
          "name": "idx_orders_user_id",
          "columns": ["user_id"]
        }
      ],
      "foreignKeys": [
        {
          "name": "fk_orders_user_id",
          "column": "user_id",
          "references": {
            "table": "users",
            "column": "id"
          },
          "onDelete": "CASCADE",
          "onUpdate": "CASCADE"
        }
      ]
    }
  }
}

Extracting Schema from ORM Models

From Prisma Schema

// schema.prisma
model User {
  id        Int      @id @default(autoincrement())
  email     String   @unique
  username  String   @unique
  active    Boolean  @default(true)
  createdAt DateTime @default(now())
  updatedAt DateTime @updatedAt

  orders    Order[]
  reviews   Review[]

  @@index([email])
  @@map("users")
}

model Order {
  id          Int      @id @default(autoincrement())
  userId      Int
  totalAmount Decimal  @db.Decimal(10, 2)
  status      String   @default("pending")
  createdAt   DateTime @default(now())

  user  User         @relation(fields: [userId], references: [id], onDelete: Cascade)
  items OrderItem[]

  @@index([userId])
  @@index([status])
  @@map("orders")
}

Generated Visualization:

erDiagram
    USERS ||--o{ ORDERS : "has many"
    USERS ||--o{ REVIEWS : "has many"

    USERS {
        int id PK
        string email UK
        string username UK
        boolean active
        datetime created_at
        datetime updated_at
    }

    ORDERS {
        int id PK
        int user_id FK
        decimal total_amount
        string status
        datetime created_at
    }

From TypeORM Entities

// user.entity.ts
@Entity('users')
export class User {
  @PrimaryGeneratedColumn()
  id: number;

  @Column({ unique: true })
  email: string;

  @Column({ unique: true })
  username: string;

  @Column({ default: true })
  active: boolean;

  @CreateDateColumn()
  createdAt: Date;

  @UpdateDateColumn()
  updatedAt: Date;

  @OneToMany(() => Order, order => order.user)
  orders: Order[];

  @Index()
  @Column()
  organizationId: number;
}

// order.entity.ts
@Entity('orders')
export class Order {
  @PrimaryGeneratedColumn()
  id: number;

  @Column()
  userId: number;

  @Column('decimal', { precision: 10, scale: 2 })
  totalAmount: number;

  @Column({ default: 'pending' })
  status: string;

  @ManyToOne(() => User, user => user.orders, { onDelete: 'CASCADE' })
  @JoinColumn({ name: 'userId' })
  user: User;

  @OneToMany(() => OrderItem, item => item.order)
  items: OrderItem[];
}

From SQLAlchemy Models

# models.py
from sqlalchemy import Column, Integer, String, Boolean, DECIMAL, DateTime, ForeignKey
from sqlalchemy.orm import relationship
from datetime import datetime

class User(Base):
    __tablename__ = 'users'

    id = Column(Integer, primary_key=True, autoincrement=True)
    email = Column(String(255), unique=True, nullable=False, index=True)
    username = Column(String(50), unique=True, nullable=False)
    active = Column(Boolean, default=True)
    created_at = Column(DateTime, default=datetime.utcnow)
    updated_at = Column(DateTime, default=datetime.utcnow, onupdate=datetime.utcnow)

    # Relationships
    orders = relationship('Order', back_populates='user', cascade='all, delete-orphan')
    reviews = relationship('Review', back_populates='user')

class Order(Base):
    __tablename__ = 'orders'

    id = Column(Integer, primary_key=True, autoincrement=True)
    user_id = Column(Integer, ForeignKey('users.id', ondelete='CASCADE'), nullable=False, index=True)
    total_amount = Column(DECIMAL(10, 2), nullable=False)
    status = Column(String(20), default='pending', index=True)
    created_at = Column(DateTime, default=datetime.utcnow)

    # Relationships
    user = relationship('User', back_populates='orders')
    items = relationship('OrderItem', back_populates='order')

Schema Analysis Features

Relationship Cardinality Detection

# Relationship Analysis

## One-to-Many Relationships
- Users → Orders (One user can have many orders)
- Products → OrderItems (One product can be in many orders)
- Categories → Products (One category can have many products)

## Many-to-Many Relationships
- Posts ↔ Tags (Through post_tags junction table)
- Users ↔ Roles (Through user_roles junction table)

## One-to-One Relationships
- Users → UserProfiles (One user has one profile)

Missing Indexes Detection

# Schema Health Report

## Missing Indexes

⚠️ **High Priority:**
- `orders.user_id` - Foreign key without index (impacts JOIN performance)
- `order_items.product_id` - Foreign key without index

⚠️ **Medium Priority:**
- `users.email` - Frequently used in WHERE clauses
- `products.category_id` - Used in JOIN operations

## Suggested Index Additions:

```sql
CREATE INDEX idx_orders_user_id ON orders(user_id);
CREATE INDEX idx_order_items_product_id ON order_items(product_id);
CREATE INDEX idx_users_email ON users(email);
CREATE INDEX idx_products_category_id ON products(category_id);

-- Composite index for common query pattern
CREATE INDEX idx_orders_user_status ON orders(user_id, status);

Normalization Analysis

# Database Normalization Report

## Current Normalization Level: 3NF

### First Normal Form (1NF) ✓
- All tables have primary keys
- No repeating groups
- Atomic values in all columns

### Second Normal Form (2NF) ✓
- All tables in 1NF
- No partial dependencies on composite keys

### Third Normal Form (3NF) ✓
- All tables in 2NF
- No transitive dependencies

### Potential Improvements:

**Denormalization Opportunities (for performance):**
- Add `user_name` to `orders` table to avoid JOIN for display
- Cache `order_count` in `users` table
- Store `product_name` in `order_items` for historical accuracy

**Further Normalization Suggestions:**
- Extract address fields from `users` to separate `addresses` table
- Split `products.description` to separate `product_details` table if frequently unused

dbdiagram.io Format

// Use dbdiagram.io to visualize this schema

Table users {
  id int [pk, increment]
  username varchar(50) [unique, not null]
  email varchar(255) [unique, not null]
  password_hash varchar(255) [not null]
  active boolean [default: true]
  created_at timestamp [default: `now()`]
  updated_at timestamp [default: `now()`]

  Indexes {
    email [unique]
    username [unique]
  }
}

Table orders {
  id int [pk, increment]
  user_id int [not null, ref: > users.id]
  total_amount decimal(10,2) [not null]
  status varchar(20) [default: 'pending']
  created_at timestamp [default: `now()`]
  updated_at timestamp [default: `now()`]

  Indexes {
    user_id
    status
    created_at
  }
}

Table products {
  id int [pk, increment]
  name varchar(255) [not null]
  description text
  price decimal(10,2) [not null]
  stock_quantity int [default: 0]
  category_id int [ref: > categories.id]
  created_at timestamp [default: `now()`]

  Indexes {
    category_id
    (name, category_id) [name: 'idx_product_category']
  }
}

Table order_items {
  id int [pk, increment]
  order_id int [not null, ref: > orders.id]
  product_id int [not null, ref: > products.id]
  quantity int [not null]
  price decimal(10,2) [not null]

  Indexes {
    order_id
    product_id
  }
}

Table categories {
  id int [pk, increment]
  name varchar(100) [unique, not null]
  parent_id int [ref: > categories.id]
  created_at timestamp [default: `now()`]
}

Table reviews {
  id int [pk, increment]
  user_id int [not null, ref: > users.id]
  product_id int [not null, ref: > products.id]
  rating int [not null, note: '1-5']
  comment text
  created_at timestamp [default: `now()`]

  Indexes {
    (user_id, product_id) [unique]
    product_id
  }
}

PlantUML Format

@startuml

entity "users" as users {
  *id : int <<PK>>
  --
  *username : varchar(50) <<UK>>
  *email : varchar(255) <<UK>>
  *password_hash : varchar(255)
  active : boolean
  created_at : timestamp
  updated_at : timestamp
}

entity "orders" as orders {
  *id : int <<PK>>
  --
  *user_id : int <<FK>>
  *total_amount : decimal(10,2)
  status : varchar(20)
  created_at : timestamp
  updated_at : timestamp
}

entity "products" as products {
  *id : int <<PK>>
  --
  *name : varchar(255)
  description : text
  *price : decimal(10,2)
  stock_quantity : int
  category_id : int <<FK>>
  created_at : timestamp
}

entity "order_items" as order_items {
  *id : int <<PK>>
  --
  *order_id : int <<FK>>
  *product_id : int <<FK>>
  *quantity : int
  *price : decimal(10,2)
}

entity "categories" as categories {
  *id : int <<PK>>
  --
  *name : varchar(100)
  parent_id : int <<FK>>
  created_at : timestamp
}

users ||--o{ orders
orders ||--|{ order_items
products ||--o{ order_items
categories ||--o{ products
categories ||--o{ categories : "parent/child"

@enduml

Schema Comparison

# Schema Comparison: Production vs Staging

## New Tables in Staging:
- `notifications` - User notification system
- `audit_logs` - Activity tracking

## Modified Tables:

### users
**Added columns:**
- `last_login_at` (timestamp)
- `email_verified` (boolean)

**Removed columns:**
- `legacy_id` (deprecated)

### orders
**Modified columns:**
- `total_amount`: DECIMAL(8,2) → DECIMAL(10,2) (increased precision)

**Added indexes:**
- `idx_orders_created_at` on (created_at)

## Migration Script:

```sql
-- Add new columns
ALTER TABLE users ADD COLUMN last_login_at TIMESTAMP;
ALTER TABLE users ADD COLUMN email_verified BOOLEAN DEFAULT false;
ALTER TABLE users DROP COLUMN legacy_id;

-- Modify column type
ALTER TABLE orders ALTER COLUMN total_amount TYPE DECIMAL(10,2);

-- Add new index
CREATE INDEX idx_orders_created_at ON orders(created_at);

-- Create new tables
CREATE TABLE notifications (
  id SERIAL PRIMARY KEY,
  user_id INTEGER NOT NULL REFERENCES users(id),
  type VARCHAR(50) NOT NULL,
  message TEXT NOT NULL,
  read BOOLEAN DEFAULT false,
  created_at TIMESTAMP DEFAULT NOW()
);

Best Practices

1. Always visualize before making changes - Understand impact
2. Document relationship cardinality - One-to-many, many-to-many
3. Include indexes in diagrams - Performance consideration
4. Show foreign key constraints - Data integrity
5. Use consistent naming conventions - Improve readability
6. Version control schema changes - Track evolution
7. Generate diagrams from code - Keep in sync
8. Include constraints and checks - Business rules
9. Document enum values - Valid states
10. Keep diagrams up to date - Living documentation

Tools Integration

Generate from Database

# PostgreSQL - using pg_dump
pg_dump -s -d mydb > schema.sql

# MySQL - schema only
mysqldump --no-data mydb > schema.sql

# Using SchemaSpy (generates HTML visualization)
java -jar schemaspy.jar -t pgsql -db mydb -u user -p password -o output

# Using DBeaver (export ERD)
# File → Export → Database Structure → ERD

Generate from ORM

# Prisma - generate ERD
npx prisma generate
npx prisma studio

# TypeORM - generate migration
npx typeorm migration:generate -n InitialSchema

# Django - generate ERD
python manage.py graph_models -a -o erd.png

# Rails - generate ERD
bundle exec rails erd

Notes

• Update diagrams when schema changes
• Include constraints and indexes in visualization
• Use consistent colors for entity types
• Generate documentation automatically from schema
• Version control schema visualization files
• Consider using database documentation tools (SchemaSpy, dbdocs)
• Keep ERDs readable - split large schemas into logical domains