Seed Sketch

A database seed data generator app idea: a seed data generator that reads your Drizzle schema. One week build with TypeScript, Node.js, Drizzle ORM and Claude API, for solo developers building supabase or drizzle apps who need realistic test data.

See the spec
Why now

Why now

drizzle-orm and @supabase/supabase-js are both climbing fast on npm, so more small apps are starting from fresh schemas with empty tables. Builders using AI tools to scaffold apps still end up hand-typing test rows. From the signals of the week of 26 Oct 2026.

The spec

The spec

Point it at a Drizzle schema and it produces a seed script with believable rows that respect foreign keys, enums and unique constraints. It replaces hand-written fixtures and lorem ipsum data that hides real UI bugs.

Build time

One weekAPIs or integrations · Level 3 of 5

Audience

Solo developers building Supabase or Drizzle apps who need realistic test data.

Stack

  • TypeScript
  • Node.js
  • Drizzle ORM
  • Claude API

Fun factor

Opening your app and seeing a believable, full dashboard instead of empty tables is an instant payoff.

Core features

  • Parse a Drizzle schema file
  • Generate a runnable seed script
  • Respect foreign keys and unique columns
  • Choose row counts per table

AI features

  • Infers realistic value styles from column and table names such as a plausible SaaS customer list
  • Adds deliberate edge-case rows like long names, empty optionals and unicode

Stretch goals

  • Support Prisma schemas
  • Seed a Supabase project directly
  • Generate a messy-data mode for stress testing the UI

First version

A CLI that reads one Drizzle schema file and writes a seed.ts file with a few dozen related rows per table.

Build plan

Build plan

4 milestones, in the order you would build them. Saved ideas get this plan with checkboxes and notes.

Read the schemaLoad the schema module and list tables, columns and references.
Start here
Order the insertsSort tables by dependency so foreign keys always resolve.
Generate valuesAsk the model for a value style per column, then fill rows from it.
Emit the scriptWrite seed.ts and run it against a local database to check it.
The build prompt

The build prompt

Paste this into ChatGPT, Claude, Codex, or Cursor, then build the first version before anything else.

seed-sketch.prompt.md
# Build Seed Sketch

You are a senior full-stack engineer pairing with me on a side project. Build a working first version of the product described below. Read the whole brief before writing any code, then follow "How to work" at the end.

## The idea

**Seed Sketch.** Point it at a Drizzle schema and it produces a seed script with believable rows that respect foreign keys, enums and unique constraints. It replaces hand-written fixtures and lorem ipsum data that hides real UI bugs.

**Why now:** drizzle-orm and @supabase/supabase-js are both climbing fast on npm, so more small apps are starting from fresh schemas with empty tables. Builders using AI tools to scaffold apps still end up hand-typing test rows.

**Who it is for:** Solo developers building Supabase or Drizzle apps who need realistic test data

**What makes it fun:** Opening your app and seeing a believable, full dashboard instead of empty tables is an instant payoff.

## Scope

- **Build time:** One week. Size every decision to ship a working first version inside this window.
- **Technical ambition:** Level 3 of 5, "APIs or integrations". The product leans on third-party APIs. Wrap each integration in its own module, handle its failures and rate limits, and cache what is safe to cache.
- **First version only.** Ship the core features below end to end. Stretch goals are listed so you can design around them, not build them.

## Core features (each must work end to end in the first version)

1. Parse a Drizzle schema file
2. Generate a runnable seed script
3. Respect foreign keys and unique columns
4. Choose row counts per table

## AI features

- Infers realistic value styles from column and table names such as a plausible SaaS customer list
- Adds deliberate edge-case rows like long names, empty optionals and unicode

How to build them:
- Put every model call behind one server-side module with a typed interface, so the provider can change without touching the UI.
- Read API keys from environment variables only, and document each one in `.env.example`.
- Write prompts as versioned constants with clear instructions and an example of the expected output; parse and validate responses before using them.
- Handle timeouts, rate limits, and malformed output with a graceful fallback the user can understand. Stream responses where a wait would exceed a couple of seconds.
- Never let a feature depend on the model being perfect. Show the result, let the user edit or retry.

## Stretch goals (later, not in the first version)

- Support Prisma schemas
- Seed a Supabase project directly
- Generate a messy-data mode for stress testing the UI

Leave clean seams for these (a module boundary, a nullable column, a feature flag), but do not implement them unless I ask.

## Tech stack

Use exactly: TypeScript, Node.js, Drizzle, Claude.

Stay on current stable versions, follow each tool's official conventions, and add a library only when the standard library or the chosen stack cannot do the job cleanly. If part of this stack is a poor fit for a specific requirement, say so and propose the smallest change.

## Owner's notes

Written by me, the project owner. Treat these as requirements and preferences that override the generated material above when they conflict.

The first version should be exactly this, and no bigger: A CLI that reads one Drizzle schema file and writes a seed.ts file with a few dozen related rows per table.

## Build plan (with saved progress)

0 of 4 steps complete. Resume at step 1: Read the schema. Before you start it, check what is already implemented so you do not repeat finished work.

1. **Read the schema** [not started]
   Load the schema module and list tables, columns and references.

2. **Order the inserts** [not started]
   Sort tables by dependency so foreign keys always resolve.

3. **Generate values** [not started]
   Ask the model for a value style per column, then fill rows from it.

4. **Emit the script** [not started]
   Write seed.ts and run it against a local database to check it.

## Definition of done for the first version

- [ ] Parse a Drizzle schema file works end to end, with real data, not a placeholder.
- [ ] Generate a runnable seed script works end to end, with real data, not a placeholder.
- [ ] Respect foreign keys and unique columns works end to end, with real data, not a placeholder.
- [ ] Choose row counts per table works end to end, with real data, not a placeholder.
- [ ] Every screen handles loading, empty, and error states.
- [ ] Typecheck, lint, and any tests pass, and the main user flow was exercised by hand.
- [ ] A README explains setup, environment variables, and how to run it locally.

## Quality bar

- Responsive from a phone to a desktop, keyboard-accessible, semantic HTML, visible focus states, labelled inputs, and sensible contrast.
- Loading, empty, and error states for every screen that reads or writes data. Errors say what happened and what to do next.
- Validate on the server, never trust the client, and keep secrets in environment variables with a committed `.env.example`.
- Type-safe end to end. No `any` without a comment explaining why.
- Small, readable modules named after what they do. No premature abstraction, no dead code, no TODOs left for later without a note.
- Sensible defaults over settings. If a choice is not in this brief, pick the simplest option that keeps the product coherent and say what you chose.

## How to work

1. **Read, then restate.** Summarize the product in three sentences and list your assumptions. Ask only the questions that block implementation. For everything else, decide and note the decision.
2. **Plan before code.** List the files and modules you will create, in build order, mapped to the core features. If a build plan is included above, use it instead: resume at the first step not marked done and check what already exists before touching it.
3. **Set up.** If a project already exists, inspect its code, instructions, and conventions first and build on them. Otherwise scaffold the stack above with linting, formatting, a typecheck script, `.env.example`, and a README stub.
4. **Model the data first.** Define the types, schema, and any migrations before the UI, so the shape of the product is settled early.
5. **Build in vertical slices.** Finish one core feature end to end (data, logic, UI) before starting the next. Keep the app runnable after every slice and commit each slice with a message that says what changed and why.
6. **Then the interface.** Apply the quality bar above to each screen as it lands, not as a final pass.
7. **Verify.** Run typecheck, lint, and tests. Exercise the main user flow by hand. Check each item in the definition of done and each acceptance criterion.
8. **Report.** Tell me what works, what you tested and how, what is not done, every setup step I must complete myself, and the three most useful next steps. Never claim a service, test, or flow was verified when it was not.

If you can edit and run the project, start implementing right after the short plan. If you cannot, give me concrete code and the exact commands to run for the next step.

Rules: keep the product name and the scope as written, do not invent features, prefer boring and proven choices, and stop to ask me when a decision would be expensive to reverse.

How to use

  1. Copy the prompt above.
  2. Open ChatGPT, Claude, or your AI editor and paste it into a new conversation.
  3. Build milestone one, run it, then move to the next. Add stretch goals only after the first version works.

Want ideas built around you instead? Generate four from your own interests, time, and stack.

Frequently asked questions

FAQ

Frequently asked questions

Answers on what Seed Sketch is, how to build it, and where example ideas come from.

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