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postgres-patterns

Patrones de base de datos PostgreSQL para optimización de consultas, diseño de esquemas, indexación y seguridad. Basado en las mejores prácticas de Supabase. Útil al diseñar esquemas PostgreSQL, índices o políticas RLS, o cuando una consulta es demasiado lenta.

¿Qué es postgres-patterns?

Este skill proporciona una referencia rápida de patrones y mejores prácticas de PostgreSQL para desarrolladores y agentes de IA. Incluye una hoja de trucos de índices (B-tree, GIN, BRIN, compuestos, parciales, covering), tipos de datos recomendados, y patrones comunes como paginación con cursor (O(1) vs O(n) de OFFSET), UPSERT, procesamiento de colas con `FOR UPDATE SKIP LOCKED`, y políticas RLS optimizadas. También ofrece consultas de detección de antipatrones para encontrar claves foráneas sin índice, consultas lentas (usando pg_stat_statements) y bloat en tablas, además de una plantilla de configuración de conexiones y timeouts. Compatible con cualquier agente o herramienta que ejecute comandos SQL en PostgreSQL. Se recomienda usar junto con el agente `database-reviewer` para revisiones de base de datos más completas.

Compatible con~Claude Code~Codex CLI✓Cursor
npx skills add https://github.com/affaan-m/everything-claude-code/tree/main/skills/postgres-patterns

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Documentación

Patrones de PostgreSQL

Referencia rápida de mejores prácticas de PostgreSQL. Para obtener una guía detallada, usa el agente database-reviewer.

Cuándo activarlo

  • Escribir consultas SQL o migraciones
  • Diseñar esquemas de base de datos
  • Solucionar consultas lentas
  • Implementar seguridad a nivel de fila (RLS)
  • Configurar agrupación de conexiones

Referencia rápida

Hoja de trucos de índices

Patrón de consultaTipo de índiceEjemplo
WHERE col = valueB-tree (por defecto)CREATE INDEX idx ON t (col)
WHERE col > valueB-treeCREATE INDEX idx ON t (col)
WHERE a = x AND b > yCompuestoCREATE 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)
Rangos de series temporalesBRINCREATE INDEX idx ON t USING brin (col)

Referencia rápida de tipos de datos

Caso de usoTipo correctoEvitar
IDsbigintint, UUID aleatorio
Cadenastextvarchar(255)
Marcas de tiempotimestamptztimestamp
Dineronumeric(10,2)float
Banderasbooleanvarchar, int

Patrones comunes

Orden del índice compuesto:

-- Columnas de igualdad primero, luego columnas de rango
CREATE INDEX idx ON orders (status, created_at);
-- Funciona para: WHERE status = 'pending' AND created_at > '2024-01-01'

Índice covering:

CREATE INDEX idx ON users (email) INCLUDE (name, created_at);
-- Evita la búsqueda en tabla para SELECT email, name, created_at

Índice parcial:

CREATE INDEX idx ON users (email) WHERE deleted_at IS NULL;
-- Índice más pequeño, solo incluye usuarios activos

Política RLS (optimizada):

CREATE POLICY policy ON orders
  USING ((SELECT auth.uid()) = user_id);  -- ¡Envuélvelo en SELECT!

UPSERT:

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

Paginación con cursor:

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

Procesamiento de colas:

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 *;

Detección de antipatrones

-- Encontrar claves foráneas sin índice
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)
  );

-- Encontrar consultas lentas
SELECT query, mean_exec_time, calls
FROM pg_stat_statements
WHERE mean_exec_time > 100
ORDER BY mean_exec_time DESC;

-- Verificar bloat de tabla
SELECT relname, n_dead_tup, last_vacuum
FROM pg_stat_user_tables
WHERE n_dead_tup > 1000
ORDER BY n_dead_tup DESC;

Plantilla de configuración

-- Límites de conexión (ajustar según RAM)
ALTER SYSTEM SET max_connections = 100;
ALTER SYSTEM SET work_mem = '8MB';

-- Tiempos de espera
ALTER SYSTEM SET idle_in_transaction_session_timeout = '30s';
ALTER SYSTEM SET statement_timeout = '30s';

-- Monitoreo
CREATE EXTENSION IF NOT EXISTS pg_stat_statements;

-- Valores de seguridad por defecto
REVOKE ALL ON SCHEMA public FROM public;

SELECT pg_reload_conf();

Relacionados

  • Agente: database-reviewer - Flujo completo de revisión de base de datos
  • Skill: clickhouse-io - Patrones de análisis ClickHouse
  • Skill: backend-patterns - Patrones de API y backend

Basado en Supabase Agent Skills (crédito: equipo de Supabase) (Licencia MIT)

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

accessibility

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affaan-m/claude-api

Anthropic Claude API patterns for Python and TypeScript. Covers Messages API, streaming, tool use, vision, extended thinking, batches, prompt caching, and Claude Agent SDK. Use when building applications with the Claude API or Anthropic SDKs.

affaan-m/everything-claude-code

End-to-end marketing campaign planning and execution. Covers audience research, positioning, campaign angle definition, landing page copy, email sequences, social posts, ad copy, short-form video scripts, and content calendars. Use as the orchestration layer for multi-channel product launches. Use when planning or executing a multi-channel product launch, or producing landing page, email, social, or ad copy.

affaan-m/everything-claude-code

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/everything-claude-code-conventions

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/frontend-design

Create distinctive, production-grade frontend interfaces with high design quality. Use when the user asks to build web components, pages, or applications and the visual direction matters as much as the code quality.

affaan-m/gget

gget CLI and Python workflow for quick genomic database queries, sequence lookup, BLAST-style searches, enrichment checks, and reproducible bioinformatics evidence logs.

affaan-m/literature-review

Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.

affaan-m/motion-ui

Production-ready UI motion system for React/Next.js. Use when implementing animations, transitions, or motion patterns.

affaan-m/project-guidelines-example

Example project-specific skill template based on a real production application.

affaan-m/pubmed-database

Direct PubMed and NCBI E-utilities search workflows for biomedical literature, MeSH queries, PMID lookup, citation retrieval, and API-backed literature monitoring.

affaan-m/scholar-evaluation

Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.

affaan-m/uspto-database

USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.

agent-architecture-audit

Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature. Use when an agent or LLM feature misbehaves and the failing layer is unknown, or before shipping an agent stack.

agent-eval

Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics. Use when choosing between coding agents, or when a change to an agent setup needs measured pass rate, cost, and time rather than an impression.

agent-harness-construction

Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates. Use when defining or revising an agent

agentic-engineering

Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing. Use when planning or executing engineering work that agents will carry out end to end.

agentic-os

Build persistent multi-agent operating systems on Claude Code. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management without external databases. Use when building a persistent multi-agent system on Claude Code with its own memory, commands, and scheduling.

agent-introspection-debugging

Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.

agent-payment-x402

Add x402 payment execution to AI agents with per-task budgets, spending controls, and non-custodial wallets. Supports Base through agentwallet-sdk and X Layer through OKX Payments / OKX Agent Payments Protocol. Use when an agent must pay for something itself and needs per-task budgets, spending controls, and a non-custodial wallet.

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