database-optimization

database-optimization is a skill for Claude Code, Codex from Global-mindee/WAY. It costs 20 tokens per session (1,333 once invoked), scanned A, original, MIT.

A guide to making PostgreSQL and MySQL databases answer queries more efficiently. It covers reading query plans, adding suitable indexes, and tuning database performance.

In plain words
What is it for?
Use it to inspect queries with EXPLAIN, choose indexes, improve joins and sorting, and tune PostgreSQL or MySQL databases.
Why use it?
It helps find causes of slow queries, such as missing indexes, inefficient joins, sorting work, or inaccurate table statistics.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to inspect queries with EXPLAIN, choose indexes, improve joins and sorting, and tune PostgreSQL or MySQL databases.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/global-mindee/way/database-optimization
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.

Any agent
npx skills add Global-mindee/WAY --skill database-optimization
Clone the repo
git clone --depth 1 https://github.com/Global-mindee/WAY

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for database-optimization

README.md
[![agentmods](https://agentmods.dev/badge/skills/global-mindee/way/database-optimization/github.svg)](https://agentmods.dev/skills/global-mindee/way/database-optimization)
Your own site
<a href="https://agentmods.dev/skills/global-mindee/way/database-optimization"><img src="https://agentmods.dev/badge/skills/global-mindee/way/database-optimization/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for database-optimization

Your own site · 80×15
<a href="https://agentmods.dev/skills/global-mindee/way/database-optimization"><img src="https://agentmods.dev/badge/skills/global-mindee/way/database-optimization.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 20 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,333 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00020 $0.01333
Opus 5 $0.00010 $0.00666
Sonnet 5 $0.00004 $0.00267
Haiku 4.5 $0.00002 $0.00133

Measured 6d ago against content hash 30ce37fb0c4f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

database-optimization 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 6d 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/04_infra-platform/database-optimization/SKILL.md · 175 lines

How it starts

The opening of the file, as written. The whole thing — 175 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Database Optimization

EXPLAIN Analysis

Always run EXPLAIN ANALYZE before optimizing. Read the output bottom-up.

-- PostgreSQL
EXPLAIN (ANALYZE, BUFFERS, FORMAT TEXT) SELECT ...;

-- MySQL
EXPLAIN ANALYZE SELECT ...;

Key metrics to watch:

  • Seq Scan on large tables = missing index
  • Nested Loop with high row count = consider hash/merge join
  • Sort without index = add index on sort column
  • Rows estimated vs actual divergence = stale statistics, run ANALYZE

Index Strategies

B-tree (default, most cases)

CREATE INDEX idx_users_email ON users (email);
CREATE INDEX idx_orders_user_date ON orders (user_id, created_at DESC);

Use for: equality, range queries, sorting. Column order matters in composite indexes: put equality columns first, then range/sort columns.

Partial Index (PostgreSQL)

CREATE INDEX idx_orders_pending ON orders (created_at)
  WHERE status = 'pending';

Use when queries always filter on a specific condition. Dramatically smaller than full indexes.

GIN (PostgreSQL - arrays, JSONB, full-text)

CREATE INDEX idx_products_tags ON products USING GIN (tags);
CREATE INDEX idx_docs_search ON documents USING GIN (to_tsvector('english', content));

GiST (PostgreSQL - spatial, range types)

CREATE INDEX idx_locations_point ON locations USING GiST (coordinates);
CREATE INDEX idx_events_period ON events USING GiST (tsrange(start_at, end_at));

Covering Index (index-only scans)

-- PostgreSQL
CREATE INDEX idx_users_email_name ON users (email) INCLUDE (name);

-- MySQL
CREATE INDEX idx_users_email_name ON users (email, name);

N+1 Query Detection

Symptom: 1 query to fetch parent + N queries for each child.

# BAD: N+1
users = db.query(User).all()
for user in users:
    print(user.orders)  # triggers query per user

# GOOD: eager load
users = db.query(User).options(joinedload(User.orders)).all()
// BAD: N+1
const users = await User.findAll();
for (const user of users) {
  const orders = await Order.findAll({ where: { userId: user.id } });
}

// GOOD: batch load
const users = await User.findAll({ include: [Order] });

Read the full file on GitHub · 175 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. 6d ago First seen · 175 lines · 20 tokens per session scan A 30ce37fb0c4f

Subscribe to this mod's changes

database-optimization is a skill published in the GitHub repository Global-mindee/WAY (11 stars, last pushed 2d ago), licensed MIT. It adds 20 tokens to every session and 1,333 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 2026-09-03.

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