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postgres-patterns

Padrões PostgreSQL para otimização de consultas, design de esquemas, indexação e segurança. Baseado nas melhores práticas do Supabase. Use ao projetar esquemas, índices ou políticas RLS no PostgreSQL, ou quando uma consulta estiver muito lenta.

O que é postgres-patterns?

Este skill fornece um guia de referência rápida com as melhores práticas do PostgreSQL para desenvolvedores e agentes de IA. Ele cobre padrões essenciais como criação de índices (B-tree, GIN, BRIN e compostos), seleção de tipos de dados (bigint, text, timestamptz), e implementação de otimizações comuns como índices parciais, índices cobertos, UPSERT e paginação baseada em cursor. Também inclui práticas de segurança com políticas RLS, filas de processamento com SKIP LOCKED, e scripts prontos para detectar problemas como chaves estrangeiras não indexadas, consultas lentas e bloat de tabelas. Baseado nas práticas do Supabase, é compatível com agentes como Claude Code e Cursor, e é especialmente útil quando integrado com o agente 'database-reviewer' para revisões completas.

Funciona com~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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Documentação

Padrões PostgreSQL

Referência rápida para as melhores práticas do PostgreSQL. Para orientação detalhada, use o agente database-reviewer.

Quando Ativar

  • Escrevendo consultas SQL ou migrações
  • Projetando esquemas de banco de dados
  • Diagnosticando consultas lentas
  • Implementando Segurança em Nível de Linha (RLS)
  • Configurando pool de conexões

Referência Rápida

Folha de Dicas de Índices

Padrão de ConsultaTipo de ÍndiceExemplo
WHERE col = valorB-tree (padrão)CREATE INDEX idx ON t (col)
WHERE col > valorB-treeCREATE INDEX idx ON t (col)
WHERE a = x AND b > yCompostoCREATE INDEX idx ON t (a, b)
WHERE jsonb @> '{}'GINCREATE INDEX idx ON t USING gin (col)
WHERE tsv @@ consultaGINCREATE INDEX idx ON t USING gin (col)
Intervalos de séries temporaisBRINCREATE INDEX idx ON t USING brin (col)

Referência Rápida de Tipos de Dados

Caso de UsoTipo CorretoEvite
IDsbigintint, UUID aleatório
Stringstextvarchar(255)
Carimbos de data/horatimestamptztimestamp
Moedanumeric(10,2)float
Flagsbooleanvarchar, int

Padrões Comuns

Ordem do Índice Composto:

-- Colunas de igualdade primeiro, depois colunas de intervalo
CREATE INDEX idx ON pedidos (status, criado_em);
-- Funciona para: WHERE status = 'pendente' AND criado_em > '2024-01-01'

Índice Coberto:

CREATE INDEX idx ON usuarios (email) INCLUDE (nome, criado_em);
-- Evita consulta à tabela para SELECT email, nome, criado_em

Índice Parcial:

CREATE INDEX idx ON usuarios (email) WHERE deleted_at IS NULL;
-- Índice menor, inclui apenas usuários ativos

Política RLS (Otimizada):

CREATE POLICY politica ON pedidos
  USING ((SELECT auth.uid()) = user_id);  -- Encapsule em SELECT!

UPSERT:

INSERT INTO configuracoes (user_id, chave, valor)
VALUES (123, 'tema', 'escuro')
ON CONFLICT (user_id, chave)
DO UPDATE SET valor = EXCLUDED.valor;

Paginação por Cursor:

SELECT * FROM produtos WHERE id > $ultimo_id ORDER BY id LIMIT 20;
-- O(1) vs OFFSET que é O(n)

Processamento de Filas:

UPDATE tarefas SET status = 'processando'
WHERE id = (
  SELECT id FROM tarefas WHERE status = 'pendente'
  ORDER BY criado_em LIMIT 1
  FOR UPDATE SKIP LOCKED
) RETURNING *;

Detecção de Antipadrões

-- Encontrar chaves estrangeiras não indexadas
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, chamadas
FROM pg_stat_statements
WHERE mean_exec_time > 100
ORDER BY mean_exec_time DESC;

-- Verificar inchaço da tabela
SELECT relname, n_dead_tup, ultima_vacuum
FROM pg_stat_user_tables
WHERE n_dead_tup > 1000
ORDER BY n_dead_tup DESC;

Modelo de Configuração

-- Limites de conexão (ajuste conforme 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';

-- Monitoramento
CREATE EXTENSION IF NOT EXISTS pg_stat_statements;

-- Padrões de segurança
REVOKE ALL ON SCHEMA public FROM public;

SELECT pg_reload_conf();

Relacionados

  • Agente: database-reviewer - Fluxo completo de revisão de banco de dados
  • Skill: clickhouse-io - Padrões de análise do ClickHouse
  • Skill: backend-patterns - Padrões de API e backend

Baseado em Agent Skills do Supabase (créditos: equipe Supabase) (Licença MIT)

Individual skills in this repo

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

accessibility

Design, implement, and audit inclusive digital products using WCAG 2.2 Level AA. Use when building or auditing UI that must meet WCAG 2.2 Level AA, or when reviewing a change for keyboard, contrast, or screen-reader support.

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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