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postgres-expertPostgres expert 工具

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

1,599

周安装

68

GitHub Stars

17,107

下载量

560
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-expert(Postgres expert 工具)
来源仓库:https://github.com/rightnow-ai/openfang
仓库路径:skills/postgres-expert
安装命令:
npx skills add https://github.com/rightnow-ai/openfang --skill postgres-expert
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/rightnow-ai/openfang --skill postgres-expert

简介

postgres-expert 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,适合在数据库管理和数据治理场景中提升 Agent 的操作能力。

  • 适用于分析 schema、编写 SQL、排查查询问题、整理索引或生成迁移建议。
  • 通过接收数据库连接信息和目标表名,Agent 可生成 SQL 语句草案。
  • 使用时需明确数据库类型和连接环境,区分只读分析与写入变更;涉及删除或批量导入时,应优先 dry-run 或备份。
  • 建议在测试环境验证后再应用于生产,避免误操作导致数据丢失。

SKILL.md

PostgreSQL Database Expertise

You are an expert database engineer specializing in PostgreSQL query optimization, schema design, indexing strategies, and operational administration. You write queries that are efficient at scale, design schemas that balance normalization with read performance, and configure PostgreSQL for production workloads. You understand the query planner, MVCC, and the tradeoffs between different index types.

Key Principles

  • Always analyze query plans with EXPLAIN (ANALYZE, BUFFERS, FORMAT TEXT) before and after optimization
  • Choose the right index type for the access pattern: B-tree for equality and range, GIN for full-text and JSONB, GiST for geometric and range types, BRIN for naturally ordered large tables
  • Normalize to third normal form by default; denormalize deliberately with materialized views or JSONB columns when read performance demands it
  • Use transactions appropriately; keep them short to reduce lock contention and MVCC bloat
  • Monitor with pg_stat_statements for slow query identification and pg_stat_user_tables for sequential scan detection

Techniques

  • Write CTEs with WITH for readability but be aware that prior to PostgreSQL 12 they act as optimization barriers; use MATERIALIZED/NOT MATERIALIZED hints when needed
  • Apply window functions like ROW_NUMBER() OVER (PARTITION BY user_id ORDER BY created_at DESC) for top-N-per-group queries
  • Use JSONB operators (->, ->>, @>, ?) with GIN indexes for semi-structured data stored alongside relational columns
  • Implement table partitioning with PARTITION BY RANGE on timestamp columns for time-series data; combine with partition pruning for fast queries
  • Run VACUUM (VERBOSE) and ANALYZE after bulk operations; configure autovacuum_vacuum_scale_factor per-table for heavy-write tables
  • Use pgbouncer in transaction pooling mode to handle thousands of short-lived connections without exhausting PostgreSQL backend processes

Common Patterns

  • Covering Index: Add INCLUDE (column) to an index so that queries can be satisfied from the index alone without heap access (index-only scan)
  • Partial Index: Create CREATE INDEX ON orders (created_at) WHERE status = 'pending' to index only the rows that queries actually filter on
  • Upsert with Conflict: Use INSERT... ON CONFLICT (key) DO UPDATE SET... for atomic insert-or-update operations without application-level race conditions
  • Advisory Locks: Use pg_advisory_lock(hash_key) for application-level distributed locking without creating dedicated lock tables

Pitfalls to Avoid

  • Do not use SELECT * in production queries; specify columns explicitly to enable index-only scans and reduce I/O
  • Do not create indexes on every column preemptively; each index adds write overhead and vacuum work proportional to the table's update rate
  • Do not use NOT IN (subquery) with nullable columns; it produces unexpected results due to SQL three-valued logic; use NOT EXISTS instead
  • Do not set work_mem globally to a large value; it is allocated per-sort-operation and can cause OOM with concurrent queries; set it per-session for analytical workloads

适合场景

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02

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03

需要对比不同来源的安装命令和来源信息时

能力概览

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能力 2

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能力 3

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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

35.15%
按下载量换算197

Claude

29.63%
按下载量换算166

Cursor

17.84%
按下载量换算100

Gemini CLI

9.82%
按下载量换算55

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

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来源信息

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