Communitygithub.com

postgres-patterns

PostgreSQL-Datenbankmuster für Abfrageoptimierung, Schema-Design, Indizierung und Sicherheit – basierend auf Supabase-Best-Practices. Verwenden Sie dieses Skill beim Entwerfen von PostgreSQL-Schemas, Indizes oder RLS-Richtlinien oder wenn eine Abfrage zu langsam ist.

Was ist postgres-patterns?

Dieses Skill bietet eine schnelle Referenz für PostgreSQL-Best-Practices, die sich auf Abfrageoptimierung, Schema-Design, Indizierung und Sicherheit konzentriert. Es basiert auf den Best-Practices von Supabase und hilft Entwicklern, typische Datenbankprobleme wie langsame Abfragen, fehlende Indizes oder suboptimale Schemas zu vermeiden. Das Skill enthält einen Index-Spickzettel (B-tree, GIN, BRIN), Muster für Composite-, Covering- und Partial-Indizes, RLS-Richtlinien-Optimierungen, UPSERT-Logik, Cursor-Paginierung und Queue-Verarbeitung. Zusätzlich bietet es Anti-Pattern-Erkennung mittels Systemabfragen (z. B. unindexierte Fremdschlüssel, table bloat) und eine Konfigurationsvorlage für Zeitüberschreitungen und Verbindungslimits. Es ist für alle gängigen KI-Agenten geeignet, die PostgreSQL nutzen, und dient als Ergänzung zum `database-reviewer`-Agenten für tiefergehende Reviews.

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

In Ihrer bevorzugten KI fragen

Öffnet einen neuen Chat, in dem dieser Agent-Skill bereits geladen ist.

Dokumentation

PostgreSQL Patterns

Schnellreferenz für PostgreSQL-Best-Practices. Für detaillierte Anleitung nutzen Sie den database-reviewer-Agenten.

Wann zu aktivieren

  • SQL-Abfragen oder Migrationen schreiben
  • Datenbankschemas entwerfen
  • Langsame Abfragen analysieren
  • Row-Level Security implementieren
  • Connection-Pooling einrichten

Schnellreferenz

Index-Spickzettel

AbfragemusterIndex-TypBeispiel
WHERE col = valueB-tree (Standard)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)
ZeitreihenbereicheBRINCREATE INDEX idx ON t USING brin (col)

Datentyp-Schnellreferenz

AnwendungsfallKorrekter TypVermeiden
IDsbigintint, zufällige UUID
Zeichenkettentextvarchar(255)
Zeitstempeltimestamptztimestamp
Geldbeträgenumeric(10,2)float
Markierungenbooleanvarchar, int

Häufige Muster

Composite-Index-Reihenfolge:

-- Gleichheitsspalten zuerst, dann Bereichsspalten
CREATE INDEX idx ON orders (status, created_at);
-- Funktioniert für: WHERE status = 'pending' AND created_at > '2024-01-01'

Covering Index:

CREATE INDEX idx ON users (email) INCLUDE (name, created_at);
-- Vermeidet Tabellenzugriff für SELECT email, name, created_at

Partial Index:

CREATE INDEX idx ON users (email) WHERE deleted_at IS NULL;
-- Kleinerer Index, nur aktive Benutzer

RLS-Richtlinie (optimiert):

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

UPSERT:

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

Cursor-Paginierung:

SELECT * FROM products WHERE id > $last_id ORDER BY id LIMIT 20;
-- O(1) vs. OFFSET, das O(n) ist

Queue-Verarbeitung:

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-Erkennung

-- Unindexierte Fremdschlüssel finden
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)
  );

-- Langsame Abfragen finden
SELECT query, mean_exec_time, calls
FROM pg_stat_statements
WHERE mean_exec_time > 100
ORDER BY mean_exec_time DESC;

-- Tabellenblähung prüfen
SELECT relname, n_dead_tup, last_vacuum
FROM pg_stat_user_tables
WHERE n_dead_tup > 1000
ORDER BY n_dead_tup DESC;

Konfigurationsvorlage

-- Verbindungslimits (je nach RAM anpassen)
ALTER SYSTEM SET max_connections = 100;
ALTER SYSTEM SET work_mem = '8MB';

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

-- Überwachung
CREATE EXTENSION IF NOT EXISTS pg_stat_statements;

-- Sicherheitsstandards
REVOKE ALL ON SCHEMA public FROM public;

SELECT pg_reload_conf();

Verwandtes

  • Agent: database-reviewer – Vollständiger Datenbank-Review-Workflow
  • Skill: clickhouse-io – ClickHouse-Analytik-Muster
  • Skill: backend-patterns – API- und Backend-Muster

Basierend auf Supabase Agent Skills (Credit: Supabase-Team) (MIT Lizenz)

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.

Verwandte Skills