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Datamodellm

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nimbalyst
datamodellm

Create visual data models for database schemas using Nimbalyst's DataModelLM editor. Use when the user wants to design a data model, database schema, entity relationship diagram, or Prisma schema.

Overview

Publishernimbalyst
Repositorynimbalyst
Skill namedatamodellm
Stars
1.9K
Forks
300
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by nimbalyst on GitHub. Read the source before you install it.

Installation

Install the Datamodellm AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/nimbalyst/nimbalyst/tree/main/packages/extensions/datamodellm/claude-plugin/skills/datamodellm
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/nimbalyst/nimbalyst.git /tmp/nimbalyst
mkdir -p .claude/skills
cp -r /tmp/nimbalyst/packages/extensions/datamodellm/claude-plugin/skills/datamodellm .claude/skills/datamodellm
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Datamodellm in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Datamodellm on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Datamodellm is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

DataModelLM - Visual Data Modeling

DataModelLM is Nimbalyst's visual editor for creating database schemas using Prisma format. It displays entity-relationship diagrams with a visual canvas.

When to Use DataModelLM

  • Designing database schemas
  • Creating entity relationship diagrams (ERDs)
  • Planning data models for applications
  • Working with Prisma schemas
  • Any visual data modeling task

File Format

  • Extension: .prisma
  • Format: Prisma schema with special metadata header
  • Location: Any directory (commonly workspace root or models/, schema/)

Required Header

Every DataModelLM file MUST start with a @nimbalyst metadata comment:

prisma
// @nimbalyst {"viewport":{"x":0,"y":0,"zoom":1},"positions":{},"entityViewMode":"standard"}

Basic Structure

prisma
// @nimbalyst {"viewport":{"x":0,"y":0,"zoom":1},"positions":{},"entityViewMode":"standard"}

datasource db {
  provider = "postgresql"
  url      = env("DATABASE_URL")
}

model User {
  id        Int      @id @default(autoincrement())
  email     String   @unique
  name      String?
  posts     Post[]
  createdAt DateTime @default(now())
  updatedAt DateTime @updatedAt
}

model Post {
  id        Int      @id @default(autoincrement())
  title     String
  content   String?
  published Boolean  @default(false)
  author    User     @relation(fields: [authorId], references: [id])
  authorId  Int
  createdAt DateTime @default(now())
}

Supported Types

Scalar Types

  • Int, BigInt, Float, Decimal
  • String, Boolean
  • DateTime, Json, Bytes

Modifiers

  • ? - Optional field
  • [] - Array/list

Attributes

  • @id - Primary key
  • @unique - Unique constraint
  • @default(value) - Default value
  • @updatedAt - Auto-update timestamp
  • @relation - Define relationships

Relationship Patterns

One-to-Many

prisma
model User {
  posts Post[]
}
model Post {
  author   User @relation(fields: [authorId], references: [id])
  authorId Int
}

One-to-One

prisma
model User {
  profile Profile?
}
model Profile {
  user   User @relation(fields: [userId], references: [id])
  userId Int  @unique
}

Many-to-Many (Implicit)

prisma
model Post {
  categories Category[]
}
model Category {
  posts Post[]
}

Best Practices

  1. Always include the @nimbalyst header - Required for visual editor
  2. Use meaningful model names - PascalCase, singular (User not Users)
  3. Include timestamps - Add createdAt and updatedAt to most models
  4. Define explicit relations - Always specify @relation with fields and references

Frequently asked questions

What does the Datamodellm AI skill do?

Create visual data models for database schemas using Nimbalyst's DataModelLM editor. Use when the user wants to design a data model, database schema, entity relationship diagram, or Prisma schema.

Why use Datamodellm on TypingMind?

Because you install it once and use it with any model. Datamodellm is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Datamodellm in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/nimbalyst/nimbalyst/tree/main/packages/extensions/datamodellm/claude-plugin/skills/datamodellm. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Datamodellm?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Datamodellm?

As many as you like. As long as a model supports skills, you can use Datamodellm with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Datamodellm AI skill free?

Yes. It is published on GitHub by nimbalyst under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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