Database Claude Skills
1 639 database skills from 232 authors. They work on schemas, queries and moving data between them. Half of them fit into 2 210 tokens or less — that is what one costs your context window when the agent loads it. 286 ship runnable scripts rather than instructions alone. 7 of them cannot work without an MCP server, most often rube. We also found 387 copies of these same skills sitting in other people's repositories — counted once here, not 387 times.
1 639 unique 232 authors 5 updated this month 163 from vendors
Implement, fix, review, migrate, test, or debug Drift persistence in Flutter apps using SQLite, drift_flutter, type-safe Dart queries, generated tables, StreamBuilder or Riverpod StreamProvider UI, write operations, transactions, schema migrations, web assets, isolate sharing, and local database testing. Use when a Flutter task mentions drift, local database storage, SQLite, reactive database streams, CRUD, schemaVersion, build_runner, drift_dev make-migrations, migration tests, or Flutter-specific database setup across mobile, web, or desktop.
Two-phase LinkedIn lead pipeline driven by linkedin-cli. Phase A imports leads from a search URL or filters, qualifies them against a configurable ICP via sub-agent, and stores them in a local SQLite database with round-robin assignment across one or more LinkedIn accounts. Phase B runs on a schedule per account — sends connection invites up to a daily limit and withdraws stale pending requests. Use when the user wants to grow their network from LinkedIn searches, manage outgoing invites at scale, ask status questions (counts, conversion, pending older than N days, last imports), pause/resume an account, change ICP, or install the recurring scheduler.
Build a safe recommendation plan for PlanetScale Postgres Database Traffic Control budgets and rules without applying them.
Collect read-only evidence about PlanetScale org, database, branches, webhooks, backups, roles, Insights, recommendations, and traffic configuration.
Use PlanetScale Insights and SQLCommenter-style query tags to attribute database load, identify risky queries, and prepare safe Traffic Control or schema recommendations.
Review PlanetScale Postgres for Traffic Control, query tags, roles, pg_strict, backups/PITR, private connectivity, webhooks, branches, and safe agent operation.
Review a PlanetScale Vitess database for safe migrations, deploy requests, schema recommendations, Insights, webhooks, and operational safety.
Enforce explicit approval gates for any PlanetScale, database, repository, credential, network, or automation mutation.
Search, query, and manage Weaviate vector database collections. Use for semantic search, hybrid search, keyword search, natural language queries with AI-generated answers, collection management, data exploration, filtered fetching, data imports from PDF/CSV/JSON/JSONL files, create example data and collection creation.
Diagnoses and fixes slow Neo4j Cypher queries by reading execution plans, identifying bad operators (AllNodesScan, CartesianProduct, Eager, NodeByLabelScan), and prescribing fixes (indexes, hints, query rewrites, runtime selection). Use when a query is slow, when EXPLAIN or PROFILE output needs interpretation, when dbHits or pageCacheHitRatio are poor, when cardinality estimation diverges from actuals, or when deciding between slotted/pipelined/parallel runtimes. Covers USING INDEX / USING SCAN / USING JOIN hints, db.stats.retrieve, SHOW QUERIES, SHOW TRANSACTIONS, TERMINATE TRANSACTION. Does NOT write new Cypher from scratch — use neo4j-cypher-skill. Does NOT cover GDS algorithm tuning — use neo4j-gds-skill. Does NOT cover index/constraint creation syntax details — use neo4j-cypher-skill references/indexes.md.
Programmatic security management in Neo4j — RBAC/ABAC, user lifecycle (CREATE/ALTER/DROP USER), role lifecycle (CREATE/GRANT ROLE/DROP ROLE), privilege grants and denies (GRANT/DENY/REVOKE on graph, database, DBMS), property-level access control, sub-graph access control, SHOW PRIVILEGES inspection, and auth provider config reference (LDAP, OIDC/SSO). Use when an agent needs to manage users, roles, or privileges programmatically via Cypher on the system database. Does NOT handle Cypher query writing — use neo4j-cypher-skill. Does NOT handle cluster ops or backups — use neo4j-cli-tools-skill. Property-level security and ABAC require Enterprise Edition.
Controls interactive terminal sessions for running long-lived processes, servers, REPLs, debuggers, and TUI programs without blocking. Use when you need to run dev servers (npm run dev), debuggers (pdb, gdb), REPLs (python, node), databases (psql, mysql), SSH sessions, or editors (vim, nano) — any interactive or blocking program.
This skill should be used when the user asks to "design system architecture", "evaluate microservices vs monolith", "create architecture diagrams", "analyze dependencies", "choose a database", "plan for scalability", "make technical decisions", or "review system design". Use for architecture decision records (ADRs), tech stack evaluation, system design reviews, dependency analysis, and generating architecture diagrams in Mermaid, PlantUML, or ASCII format.
Redis observability guidance — which metrics to monitor (memory, connections, hit ratio, ops/sec, rejected connections), which built-in commands to reach for during incident triage (SLOWLOG, INFO, MEMORY DOCTOR, CLIENT LIST, FT.PROFILE), and when to use the Redis Insight GUI. Use when setting up monitoring or alerts for a Redis instance, diagnosing a performance regression, profiling a slow FT.SEARCH query, or wiring Redis metrics into Prometheus, Datadog, or similar.
Redis Search guidance covering FT.CREATE schema design, field type selection (TEXT, TAG, NUMERIC, GEO, GEOSHAPE, VECTOR, JSON path), DIALECT 2 query syntax, FT.SEARCH / FT.AGGREGATE / FT.HYBRID command selection, vector similarity with HNSW or FLAT, hybrid retrieval combining lexical and vector ranking, RAG pipelines, zero-downtime index updates via aliases, and debugging with FT.PROFILE and FT.EXPLAIN. Use when defining a search index on Hash or JSON documents, writing FT.SEARCH queries with filters, sorting, aggregation, or vector KNN, tuning HNSW parameters, building a RAG retrieval pipeline, or troubleshooting slow or empty search results.
Redis client and connection guidance covering connection pooling, multiplexing, pipelining, client-side caching with RESP3, avoiding slow commands (KEYS, SMEMBERS, HGETALL), and tuning socket timeouts. Use when configuring a Redis client (redis-py, Jedis, Lettuce, NRedisStack), batching commands for throughput, eliminating per-request connection creation, iterating large keyspaces with SCAN, enabling client-side caching for read-heavy workloads, or setting connect and read timeouts.
Redis security guidance covering authentication (requirepass and ACL users), TLS, ACL-based least-privilege access control, restricting network exposure via bind and protected-mode, firewall rules, and disabling dangerous commands. Use when deploying Redis to production, defining ACL users for an application, configuring TLS connections, locking down a Redis instance behind a firewall, or auditing a Redis deployment for security hardening.
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。