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Cloudflare D1

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alinaqi
cloudflare-d1

Cloudflare D1 SQLite database with Workers, Drizzle ORM, migrations

Overview

Publisheralinaqi
Repositorymaggy
Skill namecloudflare-d1
Stars
707
Forks
57
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 alinaqi on GitHub. Read the source before you install it.

Installation

Install the Cloudflare D1 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/alinaqi/maggy/tree/main/skills/cloudflare-d1
  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/alinaqi/maggy.git /tmp/maggy
mkdir -p .claude/skills
cp -r /tmp/maggy/skills/cloudflare-d1 .claude/skills/cloudflare-d1
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Cloudflare D1 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 Cloudflare D1 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 Cloudflare D1 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.

Cloudflare D1 Skill

Cloudflare D1 is a serverless SQLite database designed for Cloudflare Workers with global distribution and zero cold starts.

Sources: D1 Docs | Drizzle + D1 | Wrangler CLI


Core Principle

SQLite at the edge, migrations in version control, Drizzle for type safety.

D1 brings SQLite's simplicity to serverless. Design for horizontal scale (multiple small databases) rather than vertical (one large database). Use Drizzle ORM for type-safe queries and migrations.


D1 Stack

ComponentPurpose
D1Serverless SQLite database
WorkersEdge runtime for your application
WranglerCLI for development and deployment
Drizzle ORMType-safe ORM with migrations
Drizzle KitMigration tooling
HonoLightweight web framework (optional)

Project Setup

Create Worker Project

bash
# Create new project
npm create cloudflare@latest my-app -- --template "worker-typescript"
cd my-app

# Install dependencies
npm install drizzle-orm
npm install -D drizzle-kit

Create D1 Database

bash
# Create database (creates both local and remote)
npx wrangler d1 create my-database

# Output:
# [[d1_databases]]
# binding = "DB"
# database_name = "my-database"
# database_id = "xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx"

Configure wrangler.toml

toml
name = "my-app"
main = "src/index.ts"
compatibility_date = "2024-01-01"

[[d1_databases]]
binding = "DB"
database_name = "my-database"
database_id = "xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx"
migrations_dir = "drizzle"
migrations_table = "drizzle_migrations"

Generate TypeScript Types

bash
# Generate env types from wrangler.toml
npx wrangler types

# Creates worker-configuration.d.ts:
# interface Env {
#   DB: D1Database;
# }

Drizzle ORM Setup

Schema Definition

typescript
// src/db/schema.ts
import { sqliteTable, text, integer, real, blob } from 'drizzle-orm/sqlite-core';
import { sql } from 'drizzle-orm';

export const users = sqliteTable('users', {
  id: integer('id').primaryKey({ autoIncrement: true }),
  email: text('email').notNull().unique(),
  name: text('name').notNull(),
  role: text('role', { enum: ['user', 'admin'] }).default('user'),
  createdAt: text('created_at').default(sql`CURRENT_TIMESTAMP`),
  updatedAt: text('updated_at').default(sql`CURRENT_TIMESTAMP`)
});

export const posts = sqliteTable('posts', {
  id: integer('id').primaryKey({ autoIncrement: true }),
  title: text('title').notNull(),
  content: text('content'),
  authorId: integer('author_id').references(() => users.id),
  published: integer('published', { mode: 'boolean' }).default(false),
  viewCount: integer('view_count').default(0),
  createdAt: text('created_at').default(sql`CURRENT_TIMESTAMP`)
});

export const tags = sqliteTable('tags', {
  id: integer('id').primaryKey({ autoIncrement: true }),
  name: text('name').notNull().unique()
});

export const postTags = sqliteTable('post_tags', {
  postId: integer('post_id').references(() => posts.id),
  tagId: integer('tag_id').references(() => tags.id)
});

// Type exports
export type User = typeof users.$inferSelect;
export type NewUser = typeof users.$inferInsert;
export type Post = typeof posts.$inferSelect;
export type NewPost = typeof posts.$inferInsert;

Drizzle Config

typescript
// drizzle.config.ts
import { defineConfig } from 'drizzle-kit';

export default defineConfig({
  schema: './src/db/schema.ts',
  out: './drizzle',
  dialect: 'sqlite',
  driver: 'd1-http',
  dbCredentials: {
    accountId: process.env.CLOUDFLARE_ACCOUNT_ID!,
    databaseId: process.env.CLOUDFLARE_DATABASE_ID!,
    token: process.env.CLOUDFLARE_D1_TOKEN!
  }
});

Database Client

typescript
// src/db/index.ts
import { drizzle } from 'drizzle-orm/d1';
import * as schema from './schema';

export function createDb(d1: D1Database) {
  return drizzle(d1, { schema });
}

export type Database = ReturnType<typeof createDb>;
export * from './schema';

Migration Workflow

Generate Migration

bash
# Generate migration from schema changes
npx drizzle-kit generate

# Output: drizzle/0000_initial.sql

Apply Migrations Locally

bash
# Apply to local D1
npx wrangler d1 migrations apply my-database --local

# Or via Drizzle
npx drizzle-kit migrate

Apply Migrations to Production

bash
# Apply to remote D1
npx wrangler d1 migrations apply my-database --remote

# Preview first (dry run)
npx wrangler d1 migrations apply my-database --remote --dry-run

Migration File Example

sql
-- drizzle/0000_initial.sql
CREATE TABLE `users` (
  `id` integer PRIMARY KEY AUTOINCREMENT NOT NULL,
  `email` text NOT NULL,
  `name` text NOT NULL,
  `role` text DEFAULT 'user',
  `created_at` text DEFAULT CURRENT_TIMESTAMP,
  `updated_at` text DEFAULT CURRENT_TIMESTAMP
);

CREATE UNIQUE INDEX `users_email_unique` ON `users` (`email`);

CREATE TABLE `posts` (
  `id` integer PRIMARY KEY AUTOINCREMENT NOT NULL,
  `title` text NOT NULL,
  `content` text,
  `author_id` integer REFERENCES `users`(`id`),
  `published` integer DEFAULT false,
  `view_count` integer DEFAULT 0,
  `created_at` text DEFAULT CURRENT_TIMESTAMP
);

Worker Implementation

Basic Worker with Hono

typescript
// src/index.ts
import { Hono } from 'hono';
import { createDb, users, posts } from './db';
import { eq, desc } from 'drizzle-orm';

type Bindings = {
  DB: D1Database;
};

const app = new Hono<{ Bindings: Bindings }>();

// Middleware to inject db
app.use('*', async (c, next) => {
  c.set('db', createDb(c.env.DB));
  await next();
});

// List users
app.get('/users', async (c) => {
  const db = c.get('db');
  const allUsers = await db.select().from(users);
  return c.json(allUsers);
});

// Get user by ID
app.get('/users/:id', async (c) => {
  const db = c.get('db');
  const id = parseInt(c.req.param('id'));

  const user = await db.select().from(users).where(eq(users.id, id)).get();

  if (!user) {
    return c.json({ error: 'User not found' }, 404);
  }
  return c.json(user);
});

// Create user
app.post('/users', async (c) => {
  const db = c.get('db');
  const body = await c.req.json<{ email: string; name: string }>();

  const result = await db.insert(users).values({
    email: body.email,
    name: body.name
  }).returning();

  return c.json(result[0], 201);
});

// Update user
app.put('/users/:id', async (c) => {
  const db = c.get('db');
  const id = parseInt(c.req.param('id'));
  const body = await c.req.json<Partial<{ email: string; name: string }>>();

  const result = await db.update(users)
    .set({ ...body, updatedAt: new Date().toISOString() })
    .where(eq(users.id, id))
    .returning();

  if (result.length === 0) {
    return c.json({ error: 'User not found' }, 404);
  }
  return c.json(result[0]);
});

// Delete user
app.delete('/users/:id', async (c) => {
  const db = c.get('db');
  const id = parseInt(c.req.param('id'));

  const result = await db.delete(users).where(eq(users.id, id)).returning();

  if (result.length === 0) {
    return c.json({ error: 'User not found' }, 404);
  }
  return c.json({ deleted: true });
});

export default app;

Raw D1 API (Without ORM)

typescript
// src/index.ts
export default {
  async fetch(request: Request, env: Env): Promise<Response> {
    const url = new URL(request.url);

    if (url.pathname === '/users' && request.method === 'GET') {
      const { results } = await env.DB.prepare(
        'SELECT * FROM users ORDER BY created_at DESC'
      ).all();
      return Response.json(results);
    }

    if (url.pathname === '/users' && request.method === 'POST') {
      const body = await request.json() as { email: string; name: string };

      const result = await env.DB.prepare(
        'INSERT INTO users (email, name) VALUES (?, ?) RETURNING *'
      ).bind(body.email, body.name).first();

      return Response.json(result, { status: 201 });
    }

    return new Response('Not Found', { status: 404 });
  }
};

Query Patterns

Select Queries

typescript
import { eq, and, or, like, gt, desc, asc, count, sql } from 'drizzle-orm';

// Basic select
const allPosts = await db.select().from(posts);

// Select specific columns
const titles = await db.select({ id: posts.id, title: posts.title }).from(posts);

// Where clause
const published = await db.select().from(posts).where(eq(posts.published, true));

// Multiple conditions
const recentPublished = await db.select().from(posts).where(
  and(
    eq(posts.published, true),
    gt(posts.createdAt, '2024-01-01')
  )
);

// OR conditions
const featured = await db.select().from(posts).where(
  or(
    eq(posts.viewCount, 1000),
    like(posts.title, '%featured%')
  )
);

// Order and limit
const topPosts = await db.select()
  .from(posts)
  .orderBy(desc(posts.viewCount))
  .limit(10);

// Pagination
const page2 = await db.select()
  .from(posts)
  .orderBy(desc(posts.createdAt))
  .limit(10)
  .offset(10);

// Count
const postCount = await db.select({ count: count() }).from(posts);

Joins

typescript
// Inner join
const postsWithAuthors = await db.select({
  post: posts,
  author: users
})
.from(posts)
.innerJoin(users, eq(posts.authorId, users.id));

// Left join
const allPostsWithAuthors = await db.select()
  .from(posts)
  .leftJoin(users, eq(posts.authorId, users.id));

// Many-to-many via junction table
const postsWithTags = await db.select({
  post: posts,
  tag: tags
})
.from(posts)
.leftJoin(postTags, eq(posts.id, postTags.postId))
.leftJoin(tags, eq(postTags.tagId, tags.id));

Insert, Update, Delete

typescript
// Insert single
const newUser = await db.insert(users).values({
  email: 'user@example.com',
  name: 'John Doe'
}).returning();

// Insert multiple
await db.insert(users).values([
  { email: 'a@test.com', name: 'Alice' },
  { email: 'b@test.com', name: 'Bob' }
]);

// Upsert (insert or update on conflict)
await db.insert(users)
  .values({ email: 'user@test.com', name: 'New Name' })
  .onConflictDoUpdate({
    target: users.email,
    set: { name: 'New Name' }
  });

// Update
await db.update(posts)
  .set({ published: true })
  .where(eq(posts.id, 1));

// Update with increment
await db.update(posts)
  .set({ viewCount: sql`${posts.viewCount} + 1` })
  .where(eq(posts.id, 1));

// Delete
await db.delete(posts).where(eq(posts.id, 1));

Transactions

typescript
// D1 supports transactions via batch
const results = await db.batch([
  db.insert(users).values({ email: 'a@test.com', name: 'A' }),
  db.insert(users).values({ email: 'b@test.com', name: 'B' }),
  db.update(posts).set({ published: true }).where(eq(posts.id, 1))
]);

// Raw D1 batch
const batchResults = await env.DB.batch([
  env.DB.prepare('INSERT INTO users (email, name) VALUES (?, ?)').bind('a@test.com', 'A'),
  env.DB.prepare('INSERT INTO users (email, name) VALUES (?, ?)').bind('b@test.com', 'B')
]);

Local Development

Start Dev Server

bash
# Local development with D1
npx wrangler dev

# With specific port
npx wrangler dev --port 8787

Database Management

bash
# Execute SQL locally
npx wrangler d1 execute my-database --local --command "SELECT * FROM users"

# Execute SQL file
npx wrangler d1 execute my-database --local --file ./seed.sql

# Open SQLite shell
npx wrangler d1 execute my-database --local --command ".tables"

Drizzle Studio

bash
# Run Drizzle Studio for visual DB management
npx drizzle-kit studio

Seed Data

sql
-- seed.sql
INSERT INTO users (email, name, role) VALUES
  ('admin@example.com', 'Admin User', 'admin'),
  ('user@example.com', 'Test User', 'user');

INSERT INTO posts (title, content, author_id, published) VALUES
  ('First Post', 'Hello World!', 1, true),
  ('Draft Post', 'Work in progress...', 1, false);
bash
# Seed local database
npx wrangler d1 execute my-database --local --file ./seed.sql

Multi-Environment Setup

wrangler.toml

toml
name = "my-app"
main = "src/index.ts"
compatibility_date = "2024-01-01"

# Development
[env.dev]
[[env.dev.d1_databases]]
binding = "DB"
database_name = "my-database-dev"
database_id = "dev-database-id"

# Staging
[env.staging]
[[env.staging.d1_databases]]
binding = "DB"
database_name = "my-database-staging"
database_id = "staging-database-id"

# Production
[env.production]
[[env.production.d1_databases]]
binding = "DB"
database_name = "my-database-prod"
database_id = "prod-database-id"

Deploy to Environments

bash
# Deploy to staging
npx wrangler deploy --env staging

# Deploy to production
npx wrangler deploy --env production

# Apply migrations to staging
npx wrangler d1 migrations apply my-database-staging --remote --env staging

Testing

Integration Tests

typescript
// tests/api.test.ts
import { unstable_dev } from 'wrangler';
import type { UnstableDevWorker } from 'wrangler';
import { describe, beforeAll, afterAll, it, expect } from 'vitest';

describe('API', () => {
  let worker: UnstableDevWorker;

  beforeAll(async () => {
    worker = await unstable_dev('src/index.ts', {
      experimental: { disableExperimentalWarning: true }
    });
  });

  afterAll(async () => {
    await worker.stop();
  });

  it('should list users', async () => {
    const res = await worker.fetch('/users');
    expect(res.status).toBe(200);
    const data = await res.json();
    expect(Array.isArray(data)).toBe(true);
  });

  it('should create user', async () => {
    const res = await worker.fetch('/users', {
      method: 'POST',
      headers: { 'Content-Type': 'application/json' },
      body: JSON.stringify({ email: 'test@test.com', name: 'Test' })
    });
    expect(res.status).toBe(201);
  });
});

CLI Quick Reference

bash
# Database
wrangler d1 create <name>                    # Create database
wrangler d1 list                             # List databases
wrangler d1 info <name>                      # Database info
wrangler d1 delete <name>                    # Delete database

# Migrations
wrangler d1 migrations list <name>           # List migrations
wrangler d1 migrations apply <name> --local  # Apply locally
wrangler d1 migrations apply <name> --remote # Apply to production

# SQL execution
wrangler d1 execute <name> --command "SQL"   # Run SQL
wrangler d1 execute <name> --file ./file.sql # Run SQL file
wrangler d1 execute <name> --local           # Run on local
wrangler d1 execute <name> --remote          # Run on production

# Development
wrangler dev                                 # Start local server
wrangler types                               # Generate TypeScript types
wrangler deploy                              # Deploy to production

# Drizzle
drizzle-kit generate                         # Generate migrations
drizzle-kit migrate                          # Apply migrations
drizzle-kit studio                           # Open Drizzle Studio
drizzle-kit push                             # Push schema (dev only)

D1 Limits & Considerations

LimitValue
Database size10 GB max
Row size1 MB max
SQL statement100 KB max
Batch size1000 statements
Reads per day (free)5 million
Writes per day (free)100,000

Anti-Patterns

  • Single large database - Design for multiple smaller databases (per-tenant)
  • No migrations - Always version control schema changes
  • Raw SQL everywhere - Use Drizzle for type safety
  • No connection to remote - Always test against real D1 before deploy
  • Large blobs in D1 - Use R2 for file storage
  • Complex joins - D1 is SQLite; keep queries simple
  • No batching - Use batch for multiple operations
  • Ignoring limits - Monitor usage on free tier

Frequently asked questions

What does the Cloudflare D1 AI skill do?

Cloudflare D1 SQLite database with Workers, Drizzle ORM, migrations

Why use Cloudflare D1 on TypingMind?

Because you install it once and use it with any model. Cloudflare D1 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 Cloudflare D1 in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/alinaqi/maggy/tree/main/skills/cloudflare-d1. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Cloudflare D1?

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 Cloudflare D1?

As many as you like. As long as a model supports skills, you can use Cloudflare D1 with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Cloudflare D1 AI skill free?

Yes. It is published on GitHub by alinaqi 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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