AI-Ready Format

Generate Database Schema
from plain English

Generate a complete database schema with tables, relationships, and indexes from your app description in under 90 seconds.

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New from Keeborg

Your AI agent is capable.
It just doesn't have a process.

Without a system, every project starts from zero. No structure, no quality bar, no way to carry context between sessions. The Dev System gives your agent a complete methodology — research, plan, build, score, audit, deploy. Personalised to your stack.

Install in 30 seconds One-time $49 — not a subscription Yours to keep and modify
See what's inside
New
your-dev-system/
CLAUDE.md              ← Your rules
skills/
  session-continuity/  ← Never lose context
  multi-agent-qa/      ← 95/100 quality gate
  security-audit/      ← Blocks bad deploys
  seo-aeo-pass/        ← Every public page
  research-and-plan/   ← Before any code
  nextjs-scaffold/     ← Your framework
  vercel-deploy/       ← Your deploy target
  resend-email/        ← Your email provider
  post-launch/         ← Monitoring + care
templates/
  project-CLAUDE.md    ← Per-project setup
  continuity/          ← decisions, changelog,
                          session-log
$49one-time
Personalised to your stack

What is Database Schema?

A database schema is the blueprint for your application's data layer. It defines tables, columns with data types, primary and foreign keys, indexes for performance, and constraints for data integrity. Keeborg generates schemas compatible with PostgreSQL, MySQL, and SQLite.

Why AI agents need it

AI coding agents need precise schema definitions to generate correct database migrations, ORM models, and queries. Without a schema, agents guess at table structures and relationships, leading to data modeling issues that are painful to fix later.

  • Complete table definitions with appropriate data types
  • Primary keys, foreign keys, and relationships
  • Indexes for query performance optimization
  • Constraints for data integrity (unique, not null, check)
  • Compatible with PostgreSQL, MySQL, and SQLite
  • Ready for ORM model generation (Prisma, Drizzle, etc.)
Example Output
-- Users table
CREATE TABLE users (
  id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
  email VARCHAR(255) UNIQUE NOT NULL,
  password_hash VARCHAR(255) NOT NULL,
  name VARCHAR(100),
  created_at TIMESTAMPTZ DEFAULT NOW(),
  updated_at TIMESTAMPTZ DEFAULT NOW()
);

-- Tasks table with foreign key
CREATE TABLE tasks (
  id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
  user_id UUID REFERENCES users(id) ON DELETE CASCADE,
  title VARCHAR(255) NOT NULL,
  status VARCHAR(20) DEFAULT 'pending',
  due_date DATE,
  created_at TIMESTAMPTZ DEFAULT NOW()
);

CREATE INDEX idx_tasks_user_id ON tasks(user_id);
CREATE INDEX idx_tasks_status ON tasks(status);

Works with every AI coding agent

Keeborg generates structured output that any AI tool can understand.

Claude Code

Anthropic's CLI agent

Cursor

AI-first code editor

Windsurf

Codeium's agentic IDE

GitHub Copilot

AI pair programmer

Part of a complete spec suite

Database Schema is one of 8 documents Keeborg generates from your idea.

Requirements Spec

Architecture

API Spec

UX Spec

UI Spec

Implementation

Agent Workflow

Generate your Database Schema in seconds

Describe your app in plain English. Get a complete spec suite in under 90 seconds.

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Frequently Asked Questions