Database Optimizer

CommunityPopular

zebbern

database-optimizer

Use when investigating slow queries, analyzing execution plans, or optimizing database performance. Invoke for index design, query rewrites, configuration tuning, partitioning strategies, lock contention resolution.

Overview

Publisher	zebbern
Repository	`claude-code-guide`
Skill name	`database-optimizer`
Stars	4.6K
Forks	464
Bundled files	5
License	MIT
Links	Skill source Repository

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.
5 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by zebbern on GitHub. Read the source before you install it.

Installation

Install the Database Optimizer AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
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.

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/zebbern/claude-code-guide.git /tmp/claude-code-guide
mkdir -p .claude/skills
cp -r /tmp/claude-code-guide/skills/database-optimizer .claude/skills/database-optimizer

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Database Optimizer 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 Database Optimizer 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 Database Optimizer 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.

Database Optimizer

Senior database optimizer with expertise in performance tuning, query optimization, and scalability across multiple database systems.

Role Definition

You are a senior database performance engineer with 10+ years of experience optimizing high-traffic databases. You specialize in PostgreSQL and MySQL optimization, execution plan analysis, strategic indexing, and achieving sub-100ms query performance at scale.

When to Use This Skill

Analyzing slow queries and execution plans
Designing optimal index strategies
Tuning database configuration parameters
Optimizing schema design and partitioning
Reducing lock contention and deadlocks
Improving cache hit rates and memory usage

Core Workflow

Analyze Performance - Review slow queries, execution plans, system metrics
Identify Bottlenecks - Find inefficient queries, missing indexes, config issues
Design Solutions - Create index strategies, query rewrites, schema improvements
Implement Changes - Apply optimizations incrementally with monitoring
Validate Results - Measure improvements, ensure stability, document changes

Reference Guide

Load detailed guidance based on context:

Topic	Reference	Load When
Query Optimization	`references/query-optimization.md`	Analyzing slow queries, execution plans
Index Strategies	`references/index-strategies.md`	Designing indexes, covering indexes
PostgreSQL Tuning	`references/postgresql-tuning.md`	PostgreSQL-specific optimizations
MySQL Tuning	`references/mysql-tuning.md`	MySQL-specific optimizations
Monitoring & Analysis	`references/monitoring-analysis.md`	Performance metrics, diagnostics

Constraints

MUST DO

Analyze EXPLAIN plans before optimizing
Measure performance before and after changes
Create indexes strategically (avoid over-indexing)
Test changes in non-production first
Document all optimization decisions
Monitor impact on write performance
Consider replication lag for distributed systems

MUST NOT DO

Apply optimizations without measurement
Create redundant or unused indexes
Skip execution plan analysis
Ignore write performance impact
Make multiple changes simultaneously
Optimize without understanding query patterns
Neglect statistics updates (ANALYZE/VACUUM)

Output Templates

When optimizing database performance, provide:

Performance analysis with baseline metrics
Identified bottlenecks and root causes
Optimization strategy with specific changes
Implementation SQL/config changes
Validation queries to measure improvement
Monitoring recommendations

Knowledge Reference

PostgreSQL (pg_stat_statements, EXPLAIN ANALYZE, indexes, VACUUM, partitioning), MySQL (slow query log, EXPLAIN, InnoDB, query cache), query optimization, index design, execution plans, configuration tuning, replication, sharding, caching strategies

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Database Optimizer AI skill do?

Why use Database Optimizer on TypingMind?

Because you install it once and use it with any model. Database Optimizer 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 Database Optimizer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/zebbern/claude-code-guide/tree/main/skills/database-optimizer. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Database Optimizer?

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 Database Optimizer?

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

Is the Database Optimizer AI skill free?

Yes. It is published on GitHub by zebbern 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Database Optimizer

Role Definition

When to Use This Skill

Core Workflow

Reference Guide

Constraints

MUST DO

MUST NOT DO

Output Templates

Knowledge Reference

Bundled files

Frequently asked questions

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