postgresql-optimization

PostgreSQL database optimization workflow for query tuning, indexing strategies, performance analysis, and production database management.

38 stars

Best use case

postgresql-optimization is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

PostgreSQL database optimization workflow for query tuning, indexing strategies, performance analysis, and production database management.

Teams using postgresql-optimization should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/postgresql-optimization/SKILL.md --create-dirs "https://raw.githubusercontent.com/lingxling/awesome-skills-cn/main/antigravity-awesome-skills/plugins/antigravity-awesome-skills-claude/skills/postgresql-optimization/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/postgresql-optimization/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How postgresql-optimization Compares

Feature / Agentpostgresql-optimizationStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

PostgreSQL database optimization workflow for query tuning, indexing strategies, performance analysis, and production database management.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# PostgreSQL Optimization Workflow

## Overview

Specialized workflow for PostgreSQL database optimization including query tuning, indexing strategies, performance analysis, vacuum management, and production database administration.

## When to Use This Workflow

Use this workflow when:
- Optimizing slow PostgreSQL queries
- Designing indexing strategies
- Analyzing database performance
- Tuning PostgreSQL configuration
- Managing production databases

## Workflow Phases

### Phase 1: Performance Assessment

#### Skills to Invoke
- `database-optimizer` - Database optimization
- `postgres-best-practices` - PostgreSQL best practices

#### Actions
1. Check database version
2. Review configuration
3. Analyze slow queries
4. Check resource usage
5. Identify bottlenecks

#### Copy-Paste Prompts
```
Use @database-optimizer to assess PostgreSQL performance
```

### Phase 2: Query Analysis

#### Skills to Invoke
- `sql-optimization-patterns` - SQL optimization
- `postgres-best-practices` - PostgreSQL patterns

#### Actions
1. Run EXPLAIN ANALYZE
2. Identify scan types
3. Check join strategies
4. Analyze execution time
5. Find optimization opportunities

#### Copy-Paste Prompts
```
Use @sql-optimization-patterns to analyze and optimize queries
```

### Phase 3: Indexing Strategy

#### Skills to Invoke
- `database-design` - Index design
- `postgresql` - PostgreSQL indexing

#### Actions
1. Identify missing indexes
2. Create B-tree indexes
3. Add composite indexes
4. Consider partial indexes
5. Review index usage

#### Copy-Paste Prompts
```
Use @database-design to design PostgreSQL indexing strategy
```

### Phase 4: Query Optimization

#### Skills to Invoke
- `sql-optimization-patterns` - Query tuning
- `sql-pro` - SQL expertise

#### Actions
1. Rewrite inefficient queries
2. Optimize joins
3. Add CTEs where helpful
4. Implement pagination
5. Test improvements

#### Copy-Paste Prompts
```
Use @sql-optimization-patterns to optimize SQL queries
```

### Phase 5: Configuration Tuning

#### Skills to Invoke
- `postgres-best-practices` - Configuration
- `database-admin` - Database administration

#### Actions
1. Tune shared_buffers
2. Configure work_mem
3. Set effective_cache_size
4. Adjust checkpoint settings
5. Configure autovacuum

#### Copy-Paste Prompts
```
Use @postgres-best-practices to tune PostgreSQL configuration
```

### Phase 6: Maintenance

#### Skills to Invoke
- `database-admin` - Database maintenance
- `postgresql` - PostgreSQL maintenance

#### Actions
1. Schedule VACUUM
2. Run ANALYZE
3. Check table bloat
4. Monitor autovacuum
5. Review statistics

#### Copy-Paste Prompts
```
Use @database-admin to schedule PostgreSQL maintenance
```

### Phase 7: Monitoring

#### Skills to Invoke
- `grafana-dashboards` - Monitoring dashboards
- `prometheus-configuration` - Metrics collection

#### Actions
1. Set up monitoring
2. Create dashboards
3. Configure alerts
4. Track key metrics
5. Review trends

#### Copy-Paste Prompts
```
Use @grafana-dashboards to create PostgreSQL monitoring
```

## Optimization Checklist

- [ ] Slow queries identified
- [ ] Indexes optimized
- [ ] Configuration tuned
- [ ] Maintenance scheduled
- [ ] Monitoring active
- [ ] Performance improved

## Quality Gates

- [ ] Query performance improved
- [ ] Indexes effective
- [ ] Configuration optimized
- [ ] Maintenance automated
- [ ] Monitoring in place

## Related Workflow Bundles

- `database` - Database operations
- `cloud-devops` - Infrastructure
- `performance-optimization` - Performance

## Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

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