Gnoke Dataforge

Gnoke Dataforge

posted Originally published at dev.to 1 min read

The Community

Vibe developers — people who ship fast with AI assistants like Claude, Cursor, or ChatGPT.

One thing I've learned after years of building: when you hand an AI assistant a well-structured schema upfront, it hallucinates less, asks fewer clarifying questions, and produces far better code. But there was no lightweight, offline-first tool to quickly model a table and export it in AI-ready formats. So I built one.

What I Built

Gnoke DataForge — a browser-based relational schema modeler that runs 100% offline.

You open it, design your tables visually, define column types and constraints (PK, NOT NULL, UNIQUE), and export in formats your AI assistant can immediately use:

  • .json — flat data format
  • .entity.json — structured entity format ideal for pasting into AI prompts
  • .sql — CREATE TABLE + INSERT statements
  • .sqlite — a real binary SQLite database file
  • .csv — universal fallback

Projects are saved locally via IndexedDB. No account. No server. No telemetry.

Demo

???? Live: https://edmundsparrow.github.io/gnoke-dataforge

Open it, edit the demo table, switch to SQLite mode to define types and constraints, then hit Export — all without leaving the browser.

Code

{% embed https://github.com/edmundsparrow/gnoke-dataforge %}

How I Built It

The entire app is vanilla HTML, CSS, and JavaScript — no framework, no build step.

  • SQLite in the browser via sql.js (WebAssembly) — handles .sqlite export and import
  • IndexedDB for local project persistence — each saved table is stored as a real SQLite binary blob
  • A custom JSON normalizer that accepts multiple JSON shapes (array of objects, entity format, flat arrays) so importing from AI-generated output just works
  • Light/dark theme, mobile drawer, and a skip-intro toggle for repeat visits

The design prioritizes speed: open → build → export → paste into AI. That's the whole loop.

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