Best use case
database-schema-designer is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Database Schema Designer
Teams using database-schema-designer should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/database-schema-designer/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How database-schema-designer Compares
| Feature / Agent | database-schema-designer | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Database Schema Designer
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# Database 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_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
---
## Full Schema Example (Task Management SaaS)
→ See references/full-schema-examples.md for details
## Row-Level Security (RLS) Policies
```sql
-- 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
```typescript
// 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:
```bash
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 NULL` without 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 `version` column
- **RLS not tested** — always test RLS with a non-superuser role
---
## Best Practices
1. **Timestamps everywhere** — `created_at`, `updated_at` on every table
2. **Soft deletes for auditable data** — `deleted_at` instead of DELETE
3. **Audit log for compliance** — log before/after JSON for regulated domains
4. **UUIDs or CUIDs as PKs** — avoid sequential integer leakage
5. **Index foreign keys** — every FK column should have an index
6. **Partial indexes** — use `WHERE deleted_at IS NULL` for active-only queries
7. **RLS over application-level filtering** — database enforces tenancy, not just app codeRelated Skills
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