Database Schema Designer
Database Schema Designer
$ npx promptcreek add database-schema-designerAuto-detects your installed agents and installs the skill to each one.
What This Skill Does
The Database Schema Designer skill designs relational database schemas from requirements and generates migrations and types. It handles multi-tenancy, soft deletes, audit trails, versioning, and polymorphic associations. This skill is useful for backend engineers and data architects.
When to Use
- Designing a new feature that needs database tables
- Reviewing a schema for performance issues
- Adding multi-tenancy to an existing schema
- Generating TypeScript types from a Prisma schema
- Planning a schema migration for a breaking change
- Generating seed data
Key Features
Installation
$ npx promptcreek add database-schema-designerAuto-detects your installed agents (Claude Code, Cursor, Codex, etc.) and installs the skill to each one.
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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_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
Supported Agents
Attribution
Details
- License
- MIT
- Source
- seeded
- Published
- 3/17/2026
Tags
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