
Database Schema Designer
FreeDesign and manage relational database schemas effortlessly.
Free · Opens the source repo
What Database Schema Designer does
The Database Schema Designer skill is a powerful tool for developers and data architects looking to create and manage relational database schemas. It enables users to transform requirements into well-structured database tables, define relationships, and establish constraints. This skill is particularly useful for those who need to ensure their database designs are normalized and efficient, handling complexities such as multi-tenancy, soft deletes, and audit trails with ease.
With this skill, users can generate migrations for various database systems, including Drizzle, Prisma, TypeORM, and Alembic. It also supports the creation of TypeScript interfaces and Python dataclasses/Pydantic models, making it easier to integrate database designs with application code. The skill includes features for generating realistic seed data, which is essential for testing and development environments, as well as Row-Level Security (RLS) policies for multi-tenant applications.
Additionally, the Database Schema Designer skill can produce Entity-Relationship Diagrams (ERDs) using Mermaid syntax, allowing users to visualize their database structure. This is especially helpful for communicating designs with team members or stakeholders. The step-by-step schema design process outlined in the skill guides users from extracting entities from requirements to implementing cross-cutting concerns like versioning and audit trails.
Overall, this skill is ideal for developers and designers involved in backend development and data architecture, providing a comprehensive solution for schema design and management.
When to use it
Use this skill when designing new database features, reviewing existing schemas, or planning migrations for breaking changes.
When not to use it
This skill may not be suitable for non-relational databases or when simple data storage solutions are sufficient.
What you can build with it
Designing a New Feature
When planning a new feature that requires database tables, use this skill to design the schema efficiently.
Schema Review for Performance
Utilize the skill to review existing schemas for normalization and performance issues, ensuring optimal database design.
Planning Schema Migrations
When preparing for a breaking change, this skill helps in generating the necessary migrations to update your database.
How to install Database Schema Designer
View source1. Install with the skills CLI
npx skills add alirezarezvani/claude-skills/database-schema-designer --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by alirezarezvaniDatabase Schema Designer
Tier: POWERFUL
Category: Engineering
Domain: Data Architecture / Backend
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
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
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_idto all tenant-scoped tables - Soft deletes: add
deleted_at TIMESTAMPTZinstead of hard deletes - Audit trail: add
created_by,updated_by,created_at,updated_at - Versioning: add
version INTEGERfor optimistic locking
Full Schema Example (Task Management SaaS)
→ See references/full-schema-examples.md for details
Row-Level Security (RLS) Policies
-- Enable RLS
ALTER TABLE tasks ENABLE ROW LEVEL SECURITY;
ALTER TABLE projects ENABLE ROW LEVEL SECURITY;
-- Create app role
CREATE ROLE app_user;
-- Users can only see tasks in their organization's projects
CREATE POLICY tasks_org_isolation ON tasks
FOR ALL TO app_user
USING (
project_id IN (
SELECT p.id FROM projects p
JOIN organization_members om ON om.organization_id = p.organization_id
WHERE om.user_id = current_setting('app.current_user_id')::text
)
);
-- Soft delete: never show deleted records
CREATE POLICY tasks_no_deleted ON tasks
FOR SELECT TO app_user
USING (deleted_at IS NULL);
-- Only task creator or admin can delete
CREATE POLICY tasks_delete_policy ON tasks
FOR DELETE TO app_user
USING (
created_by_id = current_setting('app.current_user_id')::text
OR EXISTS (
SELECT 1 FROM organization_members om
JOIN projects p ON p.organization_id = om.organization_id
WHERE p.id = tasks.project_id
AND om.user_id = current_setting('app.current_user_id')::text
AND om.role IN ('owner', 'admin')
)
);
-- Set user context (call at start of each request)
SELECT set_config('app.current_user_id', $1, true);
Seed Data Generation
// db/seed.ts
import { faker } from '@faker-js/faker'
import { db } from './client'
import { organizations, users, projects, tasks } from './schema'
import { createId } from '@paralleldrive/cuid2'
import { hashPassword } from '../src/lib/auth'
async function seed() {
console.log('Seeding database...')
// Create org
const [org] = await db.insert(organizations).values({
id: createId(),
name: "acme-corp",
slug: 'acme',
plan: 'growth',
}).returning()
// Create users
const adminUser = await db.insert(users).values({
id: createId(),
email: 'admin@acme.com',
name: "alice-admin",
passwordHash: await hashPassword('password123'),
}).returning().then(r => r[0])
// Create projects
const projectsData = Array.from({ length: 3 }, () => ({
id: createId(),
organizationId: org.id,
ownerId: adminUser.id,
name: "fakercompanycatchphrase"
description: faker.lorem.paragraph(),
status: 'active' as const,
}))
const createdProjects = await db.insert(projects).values(projectsData).returning()
// Create tasks for each project
for (const project of createdProjects) {
const tasksData = Array.from({ length: faker.number.int({ min: 5, max: 20 }) }, (_, i) => ({
id: createId(),
projectId: project.id,
title: faker.hacker.phrase(),
description: faker.lorem.sentences(2),
status: faker.helpers.arrayElement(['todo', 'in_progress', 'done'] as const),
priority: faker.helpers.arrayElement(['low', 'medium', 'high'] as const),
position: i * 1000,
createdById: adminUser.id,
updatedById: adminUser.id,
}))
await db.insert(tasks).values(tasksData)
}
console.log(`✅ Seeded: 1 org, ${projectsData.length} projects, tasks`)
}
seed().catch(console.error).finally(() => process.exit(0))
ERD Generation (Mermaid)
erDiagram
Organization ||--o{ OrganizationMember : has
Organization ||--o{ Project : owns
User ||--o{ OrganizationMember : joins
User ||--o{ Task : "created by"
Project ||--o{ Task : contains
Task ||--o{ TaskAssignment : has
Task ||--o{ TaskLabel : has
Task ||--o{ Comment : has
Task ||--o{ Attachment : has
Label ||--o{ TaskLabel : "applied to"
User ||--o{ TaskAssignment : assigned
Organization {
string id PK
string name
string slug
string plan
}
Task {
string id PK
string project_id FK
string title
string status
string priority
timestamp due_date
timestamp deleted_at
int version
}
Generate from Prisma:
npx prisma-erd-generator
# or: npx @dbml/cli prisma2dbml -i schema.prisma | npx dbml-to-mermaid
Common Pitfalls
- Soft delete without index —
WHERE deleted_at IS NULLwithout index = full scan - Missing composite indexes —
WHERE org_id = ? AND status = ?needs a composite index - Mutable surrogate keys — never use email or slug as PK; use UUID/CUID
- Non-nullable without default — adding a NOT NULL column to existing table requires default or migration plan
- No optimistic locking — concurrent updates overwrite each other; add
versioncolumn - RLS not tested — always test RLS with a non-superuser role
Best Practices
- Timestamps everywhere —
created_at,updated_aton every table - Soft deletes for auditable data —
deleted_atinstead of DELETE - Audit log for compliance — log before/after JSON for regulated domains
- UUIDs or CUIDs as PKs — avoid sequential integer leakage
- Index foreign keys — every FK column should have an index
- Partial indexes — use
WHERE deleted_at IS NULLfor active-only queries - RLS over application-level filtering — database enforces tenancy, not just app code
Frequently asked questions about Database Schema Designer
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