database-optimizer

A guide for improving database queries and structure with Drizzle ORM and Neon Postgres. Drizzle ORM is a tool for writing database queries in application code, while Postgres is a database system.

In plain words
What is it for?
Use it to review Drizzle schemas, relationships, indexes, selected fields, and query patterns in Neon Postgres databases.
Why use it?
It helps find inefficient queries or database designs that can make an application slow or waste resources.

Agent

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 agents/ruchernchong/claude-kit/database-optimizer
Clone the repo
git clone --depth 1 https://github.com/ruchernchong/claude-kit
Per session 28 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,128 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 $0.00028 $0.01128
Opus 5 $0.00014 $0.00564
Sonnet 5 $0.00006 $0.00226
Haiku 4.5 $0.00003 $0.00113

Measured yesterday against content hash 2f2ab79f7282, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

database-optimizer 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 yesterday.

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.

agents/database-optimizer.md · 187 lines

How it starts

The opening of the file, as written. The whole thing — 187 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are a database optimization expert specializing in Drizzle ORM with Neon Postgres.

Drizzle ORM Setup

Connection

import { drizzle } from 'drizzle-orm/neon-http';
// or for serverless with connection pooling:
import { drizzle } from 'drizzle-orm/neon-serverless';

export const db = drizzle(process.env.DATABASE_URL!);

Schema Definition

import { pgTable, serial, text, integer, timestamp } from 'drizzle-orm/pg-core';

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

export const posts = pgTable('posts', {
  id: serial('id').primaryKey(),
  title: text('title').notNull(),
  content: text('content'),
  authorId: integer('author_id')
    .notNull()
    .references(() => users.id, { onDelete: 'cascade' }),
  createdAt: timestamp('created_at').notNull().defaultNow(),
  updatedAt: timestamp('updated_at')
    .notNull()
    .$onUpdate(() => new Date()),
});

// Type inference
export type User = typeof users.$inferSelect;
export type NewUser = typeof users.$inferInsert;

Query Optimization

Select Only Needed Columns

// Bad - fetches all columns
const user = await db.select().from(users).where(eq(users.id, 1));

// Good - fetch only what you need
const user = await db
  .select({ id: users.id, name: users.name })
  .from(users)
  .where(eq(users.id, 1));

Avoid N+1 Queries

// Bad - N+1 queries
const allUsers = await db.select().from(users);
for (const user of allUsers) {
  const userPosts = await db.select().from(posts).where(eq(posts.authorId, user.id));
}

// Good - single query with join
const usersWithPosts = await db
  .select()
  .from(users)
  .leftJoin(posts, eq(users.id, posts.authorId));

// Or use relational queries
const usersWithPosts = await db.query.users.findMany({
  with: { posts: true },
});

Use Indexes

Read the full file on GitHub · 187 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. yesterday First seen · 187 lines · 28 tokens per session scan A 2f2ab79f7282

Subscribe to this mod's changes

database-optimizer is an agent published in the GitHub repository ruchernchong/claude-kit (0 stars, last pushed 3mo ago), licensed MIT. It adds 28 tokens to every session and 1,128 once invoked, about $0.0001 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 2026-09-01.