应用简介
PostgreSQL数据库优化工作流程,包括查询调优、索引策略、性能分析和生产数据库管理。
--- name: postgresql-optimization description: "PostgreSQL database optimization workflow for query tuning, indexing strategies, performance analysis, and production database management." category: granular-workflow-bundle risk: safe source: personal date_added: "2026-02-27" --- # 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.
发布日期
5/16/2026
提供方
SkillOPIC
来源类型
导入
sickn33
coding
数据安全
使用 Skill 时,您的对话内容将被发送至 AI 模型进行处理。我们会严格保护您的隐私数据,不会将您的对话内容用于模型训练或分享给第三方。 以下为此 Skill 的数据处理说明。
此 Skill 将处理您的对话输入
您的消息将作为 Prompt 上下文发送至 AI 模型
所有通信均通过加密通道传输
对话记录仅保存在本地
您可以随时清除本地对话历史,清除后数据不可恢复
评分和评价
已验证评分
Skill 信息
了解此 Skill 的详细信息和功能特性
编程开发
后端开发
文件结构
SKILL.md4.0 KB
版本历史
- 公开
- 来源于用户导入
如需详细了解相关要求,请访问帮助中心,或给我们提交反馈信息