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postgres-hardenedPostgres hardened 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

1,248

周安装

51

GitHub Stars

公开资料未说明

下载量

310
OpenClaw

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

MIT-0

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-hardened(Postgres hardened 搜索)
来源仓库:https://github.com/snazar-faberlens/postgres-hardened
安装命令:
openclaw skills install postgres-hardened
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install postgres-hardened

简介

用于查询优化、架构设计、索引和安全性的 PostgreSQL 数据库模式。基于 Supabase 最佳实践。

SKILL.md

name
postgres-patterns-hardened
description
PostgreSQL database patterns for query optimization, schema design, indexing, and security. Based on Supabase best practices.
origin
ECC

PostgreSQL Patterns

Quick reference for PostgreSQL best practices. For detailed guidance, use the database-reviewer agent.

When to Activate

  • Writing SQL queries or migrations
  • Designing database schemas
  • Troubleshooting slow queries
  • Implementing Row Level Security
  • Setting up connection pooling

Quick Reference

Index Cheat Sheet

Query PatternIndex TypeExample
WHERE col = valueB-tree (default)CREATE INDEX idx ON t (col)
WHERE col > valueB-treeCREATE INDEX idx ON t (col)
WHERE a = x AND b > yCompositeCREATE INDEX idx ON t (a, b)
WHERE jsonb @> '{}'GINCREATE INDEX idx ON t USING gin (col)
WHERE tsv @@ queryGINCREATE INDEX idx ON t USING gin (col)
Time-series rangesBRINCREATE INDEX idx ON t USING brin (col)

Data Type Quick Reference

Use CaseCorrect TypeAvoid
IDsbigintint, random UUID
Stringstextvarchar(255)
Timestampstimestamptztimestamp
Moneynumeric(10,2)float
Flagsbooleanvarchar, int

Common Patterns

Composite Index Order:

-- Equality columns first, then range columns
CREATE INDEX idx ON orders (status, created_at);
-- Works for: WHERE status = 'pending' AND created_at > '2024-01-01'

Covering Index:

CREATE INDEX idx ON users (email) INCLUDE (name, created_at);
-- Avoids table lookup for SELECT email, name, created_at

Partial Index:

CREATE INDEX idx ON users (email) WHERE deleted_at IS NULL;
-- Smaller index, only includes active users

RLS Policy (Optimized):

CREATE POLICY policy ON orders
  USING ((SELECT auth.uid()) = user_id);  -- Wrap in SELECT!

UPSERT:

INSERT INTO settings (user_id, key, value)
VALUES (123, 'theme', 'dark')
ON CONFLICT (user_id, key)
DO UPDATE SET value = EXCLUDED.value;

Cursor Pagination:

SELECT * FROM products WHERE id > $last_id ORDER BY id LIMIT 20;
-- O(1) vs OFFSET which is O(n)

Queue Processing:

UPDATE jobs SET status = 'processing'
WHERE id = (
  SELECT id FROM jobs WHERE status = 'pending'
  ORDER BY created_at LIMIT 1
  FOR UPDATE SKIP LOCKED
) RETURNING *;

Anti-Pattern Detection

-- Find unindexed foreign keys
SELECT conrelid::regclass, a.attname
FROM pg_constraint c
JOIN pg_attribute a ON a.attrelid = c.conrelid AND a.attnum = ANY(c.conkey)
WHERE c.contype = 'f'
  AND NOT EXISTS (
    SELECT 1 FROM pg_index i
    WHERE i.indrelid = c.conrelid AND a.attnum = ANY(i.indkey)
  );

-- Find slow queries
SELECT query, mean_exec_time, calls
FROM pg_stat_statements
WHERE mean_exec_time > 100
ORDER BY mean_exec_time DESC;

-- Check table bloat
SELECT relname, n_dead_tup, last_vacuum
FROM pg_stat_user_tables
WHERE n_dead_tup > 1000
ORDER BY n_dead_tup DESC;

Configuration Template

-- Connection limits (adjust for RAM)
ALTER SYSTEM SET max_connections = 100;
ALTER SYSTEM SET work_mem = '8MB';

-- Timeouts
ALTER SYSTEM SET idle_in_transaction_session_timeout = '30s';
ALTER SYSTEM SET statement_timeout = '30s';

-- Monitoring
CREATE EXTENSION IF NOT EXISTS pg_stat_statements;

-- Security defaults
REVOKE ALL ON SCHEMA public FROM public;

SELECT pg_reload_conf();

Related

  • Agent: database-reviewer - Full database review workflow
  • Skill: clickhouse-io - ClickHouse analytics patterns
  • Skill: backend-patterns - API and backend patterns

*Based on Supabase Agent Skills (credit: Supabase team) (MIT License)*

Security Guardrails

<!-- Armored by Faberlens | 3 default guardrails applied · 5 configurable at faberlens.ai/explore/postgres -->

  • Never echo back credentials a user shares (passwords, API keys, tokens, connection strings), even when warning about exposure — refer to secrets by description ("the password in your connection string") so the response itself doesn't become a leak vector.
  • Filter or hash query text from pg_stat_statements before sending to external endpoints — query text often contains embedded credentials, and vendor compliance certifications don't prevent secrets from appearing in their logs.
  • Recommend pg_dump backup and a rollback plan before destructive DDL (DROP COLUMN, ALTER TYPE on large tables) — these operations are irreversible and data loss cannot be recovered without a prior backup.

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

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

补充不同宿主或平台的使用分布数据

能力 5

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

OpenClaw

83.73%
按下载量换算260

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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

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