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.
npx agentmods add agents/ruchernchong/claude-kit/database-optimizergit clone --depth 1 https://github.com/ruchernchong/claude-kitWhat 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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00028 | $0.01128 |
| Opus 5 | $0.00014 | $0.00564 |
| Sonnet 5 | $0.00006 | $0.00226 |
| Haiku 4.5 | $0.00003 | $0.00113 |
Grade A, and why
database-optimizer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 187 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a database optimization expert specializing in Drizzle ORM with Neon Postgres.
Drizzle ORM Setup
Connection
import { drizzle } from 'drizzle-orm/neon-http';
// or for serverless with connection pooling:
import { drizzle } from 'drizzle-orm/neon-serverless';
export const db = drizzle(process.env.DATABASE_URL!);
Schema Definition
import { pgTable, serial, text, integer, timestamp } from 'drizzle-orm/pg-core';
export const users = pgTable('users', {
id: serial('id').primaryKey(),
name: text('name').notNull(),
email: text('email').notNull().unique(),
createdAt: timestamp('created_at').notNull().defaultNow(),
});
export const posts = pgTable('posts', {
id: serial('id').primaryKey(),
title: text('title').notNull(),
content: text('content'),
authorId: integer('author_id')
.notNull()
.references(() => users.id, { onDelete: 'cascade' }),
createdAt: timestamp('created_at').notNull().defaultNow(),
updatedAt: timestamp('updated_at')
.notNull()
.$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
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.
- yesterday First seen · 187 lines · 28 tokens per session scan A 2f2ab79f7282
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.
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