drizzle-orm

A TypeScript library that lets applications define SQL database tables and write database queries in code. It supports PostgreSQL, MySQL, SQLite, Turso, SingleStore, and several runtime clients.

In plain words
What is it for?
Use it to define schemas, read and change records, join related tables, run migrations, configure databases, and seed test or initial data.
Why use it?
It reduces the need to write raw SQL everywhere while keeping database structure and queries checked against TypeScript types.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/fellipeutaka/leon/drizzle-orm
Any agent
npx skills add fellipeutaka/leon --skill drizzle-orm
Clone the repo
git clone --depth 1 https://github.com/fellipeutaka/leon

Made for: Claude Code, Codex.

Per session 128 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,746 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00128 $0.02746
Opus 5 $0.00064 $0.01373
Sonnet 5 $0.00026 $0.00549
Haiku 4.5 $0.00013 $0.00275

Measured 2d ago against content hash d793f3abaca2, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

drizzle-orm scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/drizzle-orm/SKILL.md · 343 lines

How it starts

The opening of the file, as written. The whole thing — 343 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Drizzle ORM

~7.4kb minified+gzipped, zero dependencies, serverless-ready.

Quick Start

Install

# PostgreSQL
npm i drizzle-orm pg
npm i -D drizzle-kit @types/pg

# MySQL
npm i drizzle-orm mysql2
npm i -D drizzle-kit

# SQLite
npm i drizzle-orm better-sqlite3
npm i -D drizzle-kit @types/better-sqlite3

# Turso / LibSQL
npm i drizzle-orm @libsql/client
npm i -D drizzle-kit

# Bun SQL (PostgreSQL — zero extra deps)
bun add drizzle-orm
bun add -D drizzle-kit

# Bun SQLite (zero extra deps, sync APIs)
bun add drizzle-orm
bun add -D drizzle-kit

Config

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

export default defineConfig({
  dialect: "postgresql", // "postgresql" | "mysql" | "sqlite" | "turso" | "singlestore"
  schema: "./src/db/schema.ts",
  out: "./drizzle",
  dbCredentials: {
    url: process.env.DATABASE_URL!,
  },
});

Schema

// src/db/schema.ts
import { pgTable, serial, text, integer, timestamp } from "drizzle-orm/pg-core";

export const users = pgTable("users", {
  id: serial().primaryKey(),
  name: text().notNull(),
  email: text().unique(),
  createdAt: timestamp().defaultNow(),
});

export const posts = pgTable("posts", {
  id: serial().primaryKey(),
  title: text().notNull(),
  content: text(),
  authorId: integer("author_id").references(() => users.id),
});

Connect & Query

import { drizzle } from "drizzle-orm/node-postgres";
import { eq } from "drizzle-orm";
import * as schema from "./schema";

const db = drizzle(process.env.DATABASE_URL!, { schema });

// select
const allUsers = await db.select().from(schema.users);

// insert
const [user] = await db.insert(schema.users)
  .values({ name: "Dan", email: "[email protected]" })
  .returning();

// update
await db.update(schema.users)
  .set({ name: "Daniel" })
  .where(eq(schema.users.id, 1));

// delete
await db.delete(schema.users).where(eq(schema.users.id, 1));

See references/connections.md for all provider setups (Neon, Turso, Supabase, D1, etc.).

Read the full file on GitHub · 343 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 343 lines · 128 tokens per session scan A d793f3abaca2

Subscribe to this mod's changes

drizzle-orm is a skill published in the GitHub repository fellipeutaka/leon (5 stars, last pushed 4d ago), licensed MIT. It adds 128 tokens to every session and 2,746 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

brainstorming

You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.

obra/superpowers · 37 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

agent-host-chat-contributions

Build and review cross-cutting agent-host chat behavior through lifecycle contributions. Use when adding turn lifecycle side effects, prompt or context injection, restored-history transformation, protocol-action observation, or when reviewing changes that add code to AgentSideEffects or AgentService.

microsoft/vscode · 56 tokens

auto-perf-optimize

Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.

microsoft/vscode · 62 tokens