Token导航 LogoToken导航TokenDH.com
研究检索权限需确认github未标认证来源可访问许可证需确认审计通过

postgres-optimizationPostgres optimization 搜索

Agent Skill

用于辅助数据库表结构、查询语句、迁移脚本和数据维护任务。它适合让 Agent 分析 schema、编写 SQL、排查查询问题、整理索引或生成迁移建议。使用时需要明确数据库类型、连接环境和目标表,区分只读分析与写入变更;涉及删除、更新、迁移和批量导入时,应优先 dry-run、备份或事务保护,避免误操作。

总安装

1,162

周安装

47

GitHub Stars

1,465

下载量

365
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:postgres-optimization(Postgres optimization 搜索)
来源仓库:https://github.com/rohitg00/awesome-claude-code-toolkit
仓库路径:skills/postgres-optimization
安装命令:
npx skills add https://github.com/rohitg00/awesome-claude-code-toolkit --skill postgres-optimization
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/rohitg00/awesome-claude-code-toolkit --skill postgres-optimization

简介

用于辅助 PostgreSQL 数据库优化。

  • 适合分析 schema、编写 SQL 或排查查询问题。
  • 可生成索引建议但需区分只读与写入操作。
  • 涉及删除或更新时应优先 dry-run 保护。
  • 使用前需明确连接环境和目标表。postgres-optimization 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

PostgreSQL Optimization

Index Strategies

-- B-tree index for equality and range queries (default)
CREATE INDEX idx_orders_customer_id ON orders (customer_id);

-- Composite index (column order matters: equality columns first, range last)
CREATE INDEX idx_orders_status_created ON orders (status, created_at DESC);

-- Partial index (smaller, faster for filtered queries)
CREATE INDEX idx_orders_pending ON orders (created_at)
  WHERE status = 'pending';

-- Covering index (avoids table lookup entirely)
CREATE INDEX idx_users_email_name ON users (email) INCLUDE (name, avatar_url);

-- GIN index for JSONB containment queries
CREATE INDEX idx_products_metadata ON products USING GIN (metadata);

-- GiST index for full-text search
CREATE INDEX idx_articles_search ON articles USING GiST (
  to_tsvector('english', title || ' ' || body)
);

-- Concurrent index creation (no table lock)
CREATE INDEX CONCURRENTLY idx_large_table_col ON large_table (col);

Reading Query Plans

EXPLAIN (ANALYZE, BUFFERS, FORMAT TEXT)
SELECT o.id, o.total, u.name
FROM orders o
JOIN users u ON o.user_id = u.id
WHERE o.status = 'shipped'
  AND o.created_at > NOW() - INTERVAL '30 days'
ORDER BY o.created_at DESC
LIMIT 20;

Key things to look for in the plan:

  • Seq Scan on large tables indicates a missing index
  • Nested Loop with high row estimates suggests missing join index
  • Sort without Index Scan means the sort is happening in memory/disk
  • Buffers: shared hit vs shared read shows cache efficiency

Partitioning

CREATE TABLE events (
    id          BIGINT GENERATED ALWAYS AS IDENTITY,
    event_type  TEXT NOT NULL,
    payload     JSONB NOT NULL,
    created_at  TIMESTAMPTZ NOT NULL DEFAULT NOW()
) PARTITION BY RANGE (created_at);

CREATE TABLE events_2024_q1 PARTITION OF events
    FOR VALUES FROM ('2024-01-01') TO ('2024-04-01');
CREATE TABLE events_2024_q2 PARTITION OF events
    FOR VALUES FROM ('2024-04-01') TO ('2024-07-01');

-- Index on each partition (inherited automatically in PG 11+)
CREATE INDEX ON events (created_at, event_type);

Partition tables with more than 10M rows when queries consistently filter on the partition key.

JSONB Operations

-- Query nested JSONB fields
SELECT * FROM products
WHERE metadata @> '{"category": "electronics"}'
  AND (metadata ->> 'price')::numeric < 500;

-- Update nested JSONB
UPDATE products
SET metadata = jsonb_set(metadata, '{stock}', to_jsonb(stock - 1))
WHERE id = 'abc';

-- Aggregate JSONB arrays
SELECT id, jsonb_array_elements_text(metadata -> 'tags') AS tag
FROM products
WHERE metadata ? 'tags';

Connection Pooling

# pgbouncer.ini
[databases]
app = host=localhost port=5432 dbname=app

[pgbouncer]
pool_mode = transaction
max_client_conn = 1000
default_pool_size = 25
min_pool_size = 5
reserve_pool_size = 5
server_idle_timeout = 300

Use transaction-level pooling for web applications. Session-level pooling for apps that use prepared statements or temp tables.

Common Tuning Parameters

-- Check for slow queries
SELECT query, calls, mean_exec_time, total_exec_time
FROM pg_stat_statements
ORDER BY total_exec_time DESC
LIMIT 10;

-- Find unused indexes
SELECT indexrelname, idx_scan, pg_size_pretty(pg_relation_size(indexrelid))
FROM pg_stat_user_indexes
WHERE idx_scan = 0
ORDER BY pg_relation_size(indexrelid) DESC;

Anti-Patterns

  • Creating indexes on every column instead of analyzing actual query patterns
  • Using SELECT * when only a few columns are needed
  • Not using EXPLAIN ANALYZE to verify index usage
  • Storing large blobs in JSONB when a separate table with proper types is better
  • Missing connection pooling (each connection uses ~10MB of server memory)
  • Running VACUUM FULL during peak hours (locks the entire table)

Checklist

  • Indexes match actual query patterns (check pg_stat_statements)
  • Composite indexes ordered: equality, then sort, then range columns
  • EXPLAIN ANALYZE run on all critical queries
  • Partial indexes used for frequently filtered subsets
  • Connection pooler (PgBouncer/pgcat) in front of PostgreSQL
  • Table partitioning considered for tables over 10M rows
  • Unused indexes identified and dropped
  • pg_stat_statements enabled for query performance monitoring

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

37.45%
按下载量换算137

Claude

31.61%
按下载量换算115

Cursor

16.98%
按下载量换算62

Gemini CLI

9.46%
按下载量换算35

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

权限需确认

当前来源未能明确判断权限范围,默认进入异常复核队列。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

继续浏览同类 Skills