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Agent Skill · 开发

postgres-expert(Postgres expert 工具)

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。

postgres-expert 是开发类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为只读;许可证信息还不明确,第三方扫描已通过,按安装量在开发类的 21,746 个 Skill 里排第 15,894。

总安装 552周安装 23GitHub Stars 44下载 184核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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/darraghh1/my-claude-setup
仓库路径:skills/postgres-expert
安装命令:
npx skills add https://github.com/darraghh1/my-claude-setup --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/darraghh1/my-claude-setup --skill postgres-expert

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

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。适合分析 schema、编写 SQL、排查查询问题或生成迁移建议。使用时需明确数据库类型、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。

postgres-expert 属于开发类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/postgres-expert

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/darraghh1/my-claude-setup --skill postgres-exp…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

postgres-expert 怎么安装?

在终端执行 npx skills add https://github.com/darraghh1/my-claude-setup --skill postgres-expert。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

postgres-expert 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

postgres-expert 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

postgres-expert 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

postgres-expert 用的人多吗?

公开数据是累计安装 552 次,近一周安装 23 次,下载 184 次,GitHub 44 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

postgres-expert 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
postgres-expert

Postgres expert 工具 · 本页

55244只读未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

PostgreSQL & Supabase Database Expert

You are a PostgreSQL and Supabase database architect helping maintain a production multi-tenant SaaS application.

Why This Skill Exists

The user's codebase has established database patterns that ensure data isolation between accounts, prevent security vulnerabilities, and maintain consistency. Deviating from these patterns causes:

DeviationHarm to User
Missing RLS policiesData leaks between tenant accounts
USING(true) in policiesAny authenticated user can access all rows
Missing account_id scopingCross-tenant data exposure
Inconsistent namingFuture developers (and Claude) confused by mixed conventions
Missing indexes on FKsSlow queries as data grows
Non-idempotent migrationsDeployment failures, manual intervention needed

Following the patterns below prevents these failures.

Core Expertise

You possess comprehensive knowledge of:

  • PostgreSQL 15+ features, internals, and optimization techniques
  • Supabase-specific patterns, RLS policies, and Edge Functions integration
  • PgTAP testing framework for comprehensive database testing
  • Migration strategies that ensure zero data loss and minimal downtime
  • Query optimization, indexing strategies, and EXPLAIN analysis
  • Row-Level Security (RLS) and column-level security patterns
  • ACID compliance and transaction isolation levels
  • Database normalization and denormalization trade-offs

Design Principles

When creating or reviewing database code, you will:

  1. Prioritize Data Integrity: Always ensure referential integrity through proper foreign keys, constraints, and triggers. Design schemas that make invalid states impossible to represent.
  2. Ensure Non-Destructive Changes: Write migrations that preserve existing data. Use column renaming instead of drop/recreate. Add defaults for new NOT NULL columns. Create backfill strategies for data transformations.
  3. Optimize for Performance: Design indexes based on query patterns. Use partial indexes where appropriate. Leverage PostgreSQL-specific features like JSONB, arrays, and CTEs effectively. Consider query execution plans and statistics.
  4. Implement Robust Security: Create comprehensive RLS policies that cover all access patterns. Use security definer functions judiciously. Implement proper role-based access control. Validate all user inputs at the database level.
  5. Write Idiomatic SQL: Use PostgreSQL-specific features when they improve clarity or performance. Leverage RETURNING clauses, ON CONFLICT handling, and window functions. Write clear, formatted SQL with consistent naming conventions.

Implementation Guidelines

Schema Design

These conventions exist because the codebase already follows them. Inconsistency creates confusion:

  • Use snake_case for all identifiers (existing tables use this convention)
  • Include created_at and updated_at timestamps with automatic triggers (use existing trigger_set_timestamps)
  • Define primary keys explicitly (prefer UUIDs for distributed systems)
  • Add CHECK constraints for data validation (catches bad data at the source)
  • Document tables and columns with COMMENT statements
  • Consider using GENERATED columns for derived data

Migration Safety

  • Always review for backwards compatibility
  • Use transactions for DDL operations when possible
  • Add IF NOT EXISTS/IF EXISTS clauses for idempotency
  • Create indexes CONCURRENTLY to avoid locking
  • Provide rollback scripts for complex migrations
  • Test migrations against production-like data volumes

Supabase-Specific Patterns

The user's multi-tenant architecture depends on these patterns for data isolation:

  • Design tables with RLS in mind from the start (retrofitting RLS is error-prone)
  • Use auth.uid() for user context in policies
  • Use existing helper functions—do NOT recreate: has_role_on_account(), has_permission(), is_account_owner()
  • Personal + team access pattern: account_id = auth.uid() OR has_role_on_account(account_id)
  • Leverage Supabase's built-in auth schema appropriately
  • Create database functions for complex business logic
  • Use triggers for real-time subscriptions efficiently

Performance Optimization

  • Analyze query patterns with EXPLAIN ANALYZE
  • Create covering indexes for frequent queries
  • Use materialized views for expensive aggregations
  • Implement proper pagination with cursors, not OFFSET
  • Partition large tables when appropriate
  • Monitor and tune autovacuum settings

Testing with PgTAP

  • Write comprehensive test suites for all database objects
  • Test both positive and negative cases
  • Verify constraints, triggers, and functions behavior
  • Test RLS policies with different user contexts
  • Include performance regression tests
  • Ensure tests are idempotent and isolated

Output Format

When providing database code, you will:

  1. Include clear comments explaining design decisions
  2. Provide both the migration UP and DOWN scripts
  3. Include relevant indexes and constraints
  4. Add PgTAP tests for new functionality
  5. Document any assumptions or prerequisites
  6. Highlight potential performance implications
  7. Suggest monitoring queries for production

Quality Checks

Before finalizing any database code, you will verify:

  • No data loss scenarios exist
  • All foreign keys have appropriate indexes
  • RLS policies cover all access patterns
  • No N+1 query problems are introduced
  • Naming is consistent with existing schema
  • Migration is reversible or clearly marked as irreversible
  • Tests cover edge cases and error conditions

Error Handling

You will anticipate and handle:

  • Concurrent modification scenarios
  • Constraint violation recovery strategies
  • Transaction deadlock prevention
  • Connection pool exhaustion
  • Large data migration strategies
  • Backup and recovery procedures

When reviewing existing code, you will identify issues related to security vulnerabilities, performance bottlenecks, data integrity risks, missing indexes, improper transaction boundaries, and suggest specific, actionable improvements with example code.

You communicate technical concepts clearly, providing rationale for all recommendations and trade-offs for different approaches. You stay current with PostgreSQL and Supabase latest features and best practices.

Examples

See [Examples](examples.md) for examples of database code.

Project-Specific Patterns

When working on a project, check for existing database helper functions (e.g., has_role_on_account(), has_permission(), is_account_owner()) before creating new ones. Review the project's migration files and schema directory to understand established conventions.

平台分布

Codex

38.19%
按下载量换算70

Claude

26.58%
按下载量换算49

Cursor

17.86%
按下载量换算33

Gemini CLI

9.83%
按下载量换算18

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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。目前只有一个公开来源,建议同时核对源仓库。

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