1 633 database skills from 232 authors. They work on schemas, queries and moving data between them. Half of them fit into 2 236 tokens or less — that is what one costs your context window when the agent loads it. 285 ship runnable scripts rather than instructions alone. 7 of them cannot work without an MCP server, most often rube. We also found 383 copies of these same skills sitting in other people's repositories — counted once here, not 383 times.
1 633 unique 232 authors 712 updated this month 156 from vendors
Core Redis modeling guidance — choose the right data structure (String, Hash, List, Set, Sorted Set, JSON, Stream, Vector Set) and use consistent colon-separated key names. Use when designing a Redis data model, caching objects, deciding between Hash and JSON, building counters, leaderboards, membership sets, or session stores, or when reviewing/cleaning up Redis key naming.
Redis Cluster and replication guidance covering hash tags for multi-key operations, avoiding CROSSSLOT errors, and reading from replicas to scale read-heavy workloads. Use when designing keys for a sharded Redis Cluster, debugging CROSSSLOT errors on MGET / SDIFF / pipelines, configuring a multi-key transaction in a cluster, or routing reads to replicas for caches, analytics, or dashboards.
Redis LangCache guidance for semantic caching of LLM responses on Redis Cloud — calling search/set via the SDK or REST API, tuning the similarity threshold, separating caches per task type, and filtering with custom attributes. Use when caching LLM completions or RAG answers to cut API cost and latency, building a cache-aside layer in front of OpenAI / Anthropic / etc., tuning hit rate vs precision, or splitting one app's LLM workloads into multiple LangCache caches.
Production readiness audit that turns a demo into a real product. Built for apps shipped fast with AI coding tools (Lovable, Bolt, v0, Cursor, Claude Code). Auto-detects your stack and audits 5 domains (Frontend, Backend & Data, Auth & Security, Infrastructure, Operations), then produces a scored scorecard and a prioritized punch list with exact file paths and copy-paste fixes. Use before you go live, or on an app that is already live, when the user says "harden this", "is this production ready", "is this safe to launch", "will this survive real users", "audit my app", "turn this into a product", "production audit", "is my supabase secure", or wants to go from demo to production.
> Expert guide for Monte Carlo's push ingestion model. Use this skill whenever a customer build me a collection script, push metadata/lineage/query logs, invocation_id tracing, custom lineage nodes or edges, deleting push tables, or any question about why pushed data is not showing up. Also trigger when they ask to generate code that collects metadata, table schema, row counts, freshness, lineage, or query history from any data warehouse or data source and sends it to Monte Carlo. If the user mentions any warehouse, database, or data platform alongside any Monte Carlo topic, this skill is almost certainly relevant.
Execute database migrations across ORMs and platforms with zero-downtime strategies, data transformation, and rollback procedures. Use when migrating databases, changing schemas, performing data transformations, or implementing zero-downtime deployment strategies.
Master SQL query optimization, indexing strategies, and EXPLAIN analysis to dramatically improve database performance and eliminate slow queries. Use when debugging slow queries, designing database schemas, or optimizing application performance.
Backend architecture patterns, API design, database optimization, and server-side best practices for Node.js, Express, and Next.js API routes.
Backend architecture patterns, API design, database optimization, and server-side best practices for Node.js, Express, and Next.js API routes.
> Database migration best practices for schema changes, data migrations, rollbacks, and zero-downtime deployments across PostgreSQL, MySQL, and common ORMs (Prisma, Drizzle, Django, TypeORM, golang-migrate). Use when planning or implementing database schema changes.
> PostgreSQL database patterns for query optimization, schema design, indexing, and security. Quick reference for common patterns, index types, data types, and anti-pattern detection. Based on Supabase best practices.
Backend architecture patterns, API design, database optimization, and server-side best practices for Node.js, Express, and Next.js API routes.
ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.
Database migration best practices for schema changes, data migrations, rollbacks, and zero-downtime deployments across PostgreSQL, MySQL, and common ORMs (Prisma, Drizzle, Kysely, Django, TypeORM, golang-migrate).
DjangoおよびCeleryを使用した非同期タスク処理。タスクキューイング、ワーカー管理、エラー処理、スケジューリング。Redis/RabbitMQ ブローカー統合。
Django architecture patterns, REST API design with DRF, ORM best practices, caching, signals, middleware, and production-grade Django apps.
Floxで再現可能なクロスプラットフォーム開発環境を作成します — Nixに基づく宣言的な環境マネージャー。次の場合は必ずこのスキルを使用してください: システムレベルの依存関係（コンパイラー、データベース、openssl・libvips・BLAS・LAPACKなどのネイティブライブラリー）を持つプロジェクトを設定する場合; Python、Node.js、Rust、Go、C/C++、Java、Ruby、Elixir、PHP、その他の言語の再現可能なツールチェーンを設定する場合; macOSとLinux間で同一に動作する環境を管理する場合; チームのために正確なパッケージバージョンを固定する場合; ローカルサービス（PostgreSQL、Redis、Kafka）を開発ツールと並行して実行する場合; 単一コマンドで新しい開発者をオンボードする場合; または「自分のマシンでは動く」問題を解決する場合。AI支援やバイブコーディングに特に価値があります — Floxはエージェントがsudoなし、システム汚染なし、サンドボックス制限なしにプロジェクトスコープの環境にツールをインストールでき、結果の環境はリポジトリにコミットされるため、誰でも即座に再現できます。ユーザーがFloxに言及しない場合でも、再現可能、宣言的、クロスプラットフォームな開発環境とシステムパッケージが必要と説明した場合はこのスキルを使用してください。また、ユーザーが.flox/、manifest.toml、flox activate、またはFloxHubに言及した場合も使用してください。
JetBrains Exposed ORM パターン（DSL クエリ、DAO パターン、トランザクション、HikariCP 接続プーリング、Flyway マイグレーション、リポジトリパターンを含む）。
Laravel言語固有のパターン、Eloquent ORM、ミドルウェア、およびサービスコンテナ。
日本語翻訳：このファイルは mysql-patterns 用の日本語翻訳が必要です
PostgreSQL database patterns for query optimization, schema design, indexing, and security. Based on Supabase best practices.
Redisデータ構造パターン、キャッシング戦略、分散ロック、レート制限、Pub/Sub、本番アプリケーション用コネクション管理。
生物医学文献、MeSH クエリ、PMID 検索、引用取得、および API を利用した文献モニタリングのための PubMed および NCBI E-utilities の直接検索ワークフロー。
公式記録の検索、PatentSearch クエリ、TSDR チェック、譲渡データ、および再現可能な IP 調査ログのための USPTO 特許・商標データワークフロー。
ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.
쿼리 최적화, 스키마 설계, 인덱싱, 보안을 위한 PostgreSQL 데이터베이스 패턴. Supabase 모범 사례 기반.
Şema değişiklikleri, veri migration'ları, rollback'ler ve PostgreSQL, MySQL ve yaygın ORM'ler (Prisma, Drizzle, Django, TypeORM, golang-migrate) arasında sıfır kesinti deployment'ları için veritabanı migration en iyi uygulamaları.
Django architecture patterns, REST API design with DRF, ORM best practices, caching, signals, middleware, and production-grade Django apps.
Laravel architecture patterns, routing/controllers, Eloquent ORM, service layers, queues, events, caching, and API resources for production apps.
Sorgu optimizasyonu, şema tasarımı, indeksleme ve güvenlik için PostgreSQL veritabanı kalıpları. Supabase en iyi uygulamalarına dayanır.
后端架构模式、API设计、数据库优化以及适用于Node.js、Express和Next.js API路由的服务器端最佳实践。
ClickHouse数据库模式、查询优化、分析以及高性能分析工作负载的数据工程最佳实践。
数据库迁移最佳实践，涵盖模式变更、数据迁移、回滚以及零停机部署，适用于PostgreSQL、MySQL及常用ORM（Prisma、Drizzle、Django、TypeORM、golang-migrate）。
Django架构模式，使用DRF设计REST API，ORM最佳实践，缓存，信号，中间件，以及生产级Django应用程序。
JetBrains Exposed ORM patterns including DSL queries, DAO pattern, transactions, HikariCP connection pooling, Flyway migrations, and repository pattern.
Laravel架构模式、路由/控制器、Eloquent ORM、服务层、队列、事件、缓存以及用于生产应用的API资源。
用于查询优化、模式设计、索引和安全性的PostgreSQL数据库模式。基于Supabase最佳实践。
Backend architecture patterns, API design, database optimization, and server-side best practices for Node.js, Express, and Next.js API routes.
ClickHouse database patterns, query optimization, analytics, and data engineering best practices for high-performance analytical workloads.
PostgreSQL database patterns for query optimization, schema design, indexing, and security. Based on Supabase best practices.
Build persistent multi-agent operating systems on OpenAI Codex. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management without external databases.
Track and report OpenAI Codex token usage, spending, and budgets from a local cost-tracking database. Use when the user asks about costs, spending, usage, tokens, budgets, or cost breakdowns by project, tool, session, or date.
Create reproducible, cross-platform development environments with Flox — a declarative environment manager built on Nix. ALWAYS use this skill when the user needs to: set up a project with system-level dependencies (compilers, databases, native libraries like openssl, libvips, BLAS, LAPACK); configure reproducible toolchains for Python, Node.js, Rust, Go, C/C++, Java, Ruby, Elixir, PHP, or any language; manage environments that must work identically across macOS and Linux; pin exact package versions for a team; run local services (PostgreSQL, Redis, Kafka) alongside development tools; onboard new developers with a single command; or solve 'works on my machine' problems. Especially valuable for AI-assisted and vibe coding — Flox lets agents install tools into a project-scoped environment without sudo, system pollution, or sandbox restrictions, and the resulting environment is committed to the repo so anyone can reproduce it instantly. Use this skill even if the user doesn't mention Flox — if they describe needing reproducible, declarative, cross-platform dev environments with system packages, this is the right tool. Also use when the user mentions .flox/, manifest.toml, flox activate, or FloxHub.
MySQL and MariaDB schema, query, indexing, transaction, replication, and connection-pool patterns for production backends.
Prisma ORM patterns for TypeScript backends — schema design, query optimization, transactions, pagination, and critical traps like updateMany returning count not records, $transaction timeouts, migrate dev resetting the DB, @updatedAt skipped on bulk writes, and serverless connection exhaustion.
Redis data structure patterns, caching strategies, distributed locks, rate limiting, pub/sub, and connection management for production applications.
USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.
gget CLI and Python workflow for quick genomic database queries, sequence lookup, BLAST-style searches, enrichment checks, and reproducible bioinformatics evidence logs.