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
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.
>- Diagnose and fix excessive Postgres egress (network data transfer) in a codebase. Use when a user mentions high database bills, unexpected data transfer costs, network transfer charges, egress spikes, "why is my Neon bill so high", "database costs jumped", SELECT * optimization, query overfetching, reduce Neon costs, optimize database usage, or wants to reduce data sent from their database to their application. Also use when reviewing query patterns for cost efficiency, even if the user doesn't explicitly mention egress or data transfer.
老王我是后端通才，啥后端技术都能搞！但你得告诉老王你想用啥语言，别tm让老王我瞎猜！ 后端服务开发专家（通才）。精通多种后端技术栈，能够根据需求选择最合适的技术方案。 当用户需要开发API、数据库设计、微服务架构或后端业务逻辑时使用此技能。 根据用户需求的技术栈，自动切换到对应语言的专家模式：
Node.js后端开发专家。精通NestJS、Express、Koa等框架，以及TypeScript、Prisma、Redis等技术栈。
Database schema migration, versioning, and rollback management for SQL and NoSQL databases. Use when: (1) creating database migrations, (2) modifying table schemas, (3) adding/removing columns, (4) creating indexes, (5) data migrations, (6) rollback operations, (7) multi-environment sync, (8) seed data management. Supports PostgreSQL, MySQL, MongoDB, SQLite. Triggers: "migration", "alter table", "schema change", "database migration", "rollback migration", "knex", "prisma migrate", "flyway", "alembic".
DuckDB CLI specialist for SQL analysis, data processing and file conversion. Use for SQL queries, CSV/Parquet/JSON analysis, database queries, or data conversion. Triggers on "duckdb", "sql", "query", "data analysis", "parquet", "convert data".
自动化 Notion 操作。当用户需要管理 Notion 页面、数据库、块内容、项目跟踪或进行内容组织和搜索时使用此技能。
Comprehensive PostgreSQL database engineering skill covering indexing strategies, query optimization, performance tuning, partitioning, replication, backup and recovery, high availability, and production database management. Master advanced PostgreSQL features including MVCC, VACUUM operations, connection pooling, monitoring, and scalability patterns.
Inspect Redis cache keys, values, and TTLs for debugging. Supports both main cache and system cache. Use for debugging cache issues, checking cached values, and monitoring cache state. Read-only by default.
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.
Master modern SQL with cloud-native databases, OLTP/OLAP optimization, and advanced query techniques. Expert in performance tuning, data modeling, and hybrid analytical systems. Use PROACTIVELY for database optimization or complex analysis.
Automate Supabase database queries, table management, project administration, storage, edge functions, and SQL execution via Rube MCP (Composio). Always search tools first for current schemas.
Use when doing ANY task involving Supabase. Triggers: Supabase products (Database, Auth, Edge Functions, Realtime, Storage, Vectors, Cron, Queues); client libraries and SSR integrations (supabase-js, @supabase/ssr) in Next.js, React, SvelteKit, Astro, Remix; auth issues (login, logout, sessions, JWT, cookies, getSession, getUser, getClaims, RLS); Supabase CLI or MCP server; schema changes, migrations, security audits, Postgres extensions (pg_graphql, pg_cron, pg_vector).
蒸馏antirez(Salvatore Sanfilippo)思维模式的实用框架——极简代码哲学、Redis设计哲学、工程美学
Implement and route HitKeep contributions through the repository-owned hk developer platform. Use for any HitKeep code, UI, API, database, analytics-feature, seed, screenshot, documentation, integration, or release-preparation change, as well as setup, local development, builds, smoke tests, and contributor workflow discovery.
GoFrame v2 development skill. Use only when the target Go project uses or is explicitly adopting GoFrame v2: the nearest go.mod requires github.com/gogf/gf/v2, existing Go files import github.com/gogf/gf/v2 or any github.com/gogf/gf/v2/... component package, or the user asks to scaffold, migrate, or build with GoFrame. Trigger for GoFrame-backed Go work such as APIs/controllers/services, middleware, routing/config, ORM/DAO/DO/entity/database operations, gf CLI/codegen, HTTP/gRPC services, and microservice conventions. Do not trigger for generic Go projects without GoFrame evidence, frontend-only work, shell scripts, or unrelated infrastructure tasks.
Load and parse CSV/TXT files from travel database for itinerary planning
Querying travel planning datasets (cities, restaurants, accommodations, attractions, distances) for itinerary generation.
Extract and validate travel data from CSV/TXT databases ensuring city-specific matching and constraint compliance.
Use this skill to understand the database file structure and how to search for Ohio cities, restaurants, accommodations, attractions, and distances in the provided dataset files for trip planning.
Use this skill to build a multi-day travel itinerary from structured requirements (origin, cities, dates, budget, constraints). It queries available database files and produces a day-by-day plan with transportation, meals, attractions, and accommodations.
Guidelines for selecting database-compliant restaurants, accommodations, and attractions based on specific user constraints like budget, pets, and cuisine.
Logic to parse nested security database objects into a scalar CVSS score for the final CSV report.
Instructions for querying the provided datasets to ensure constraints regarding pet-friendly lodging, specific cuisines, and valid locations are met.
Use this skill to query the local databases for distances, cities, accommodations, restaurants, and attractions to gather real-world data for an itinerary.
Parse and search travel-related databases including cities, accommodations, restaurants, attractions, and distances. Use this skill whenever building a travel itinerary that requires querying real-world data from CSV files or text databases. This skill helps extract relevant POIs, lodging, dining, and routing information from structured datasets.
Build multi-day travel itineraries in JSON format from database lookups. Use this skill when constructing day-by-day travel plans with transportation, meals, attractions, and accommodations.
Look up travel data from the local CSV/TXT database for cities, restaurants, accommodations, attractions, and distances. Use this skill whenever planning a trip, building an itinerary, or querying travel-related datasets in /app/data/.
Query and filter travel CSV datasets (restaurants, accommodations, attractions, distances) using Python. Use this skill whenever you need to extract specific records from the travel database files, check pet policies, filter by cuisine, look up driving times, or validate that a city exists in the dataset.
Build a structured multi-day travel itinerary JSON from real CSV datasets. Use this skill whenever the user asks to create a travel plan, trip itinerary, or vacation schedule from a local database of cities, restaurants, accommodations, and attractions.
How to query CSV datasets in /app/data to extract information like accommodations, attractions, and restaurants. Use this skill whenever you need to look up data from files in the /app/data directory.
How to filter tabular datasets. Use this skill whenever you need to process or filter CSV files, tabular data, or databases to find records that match specific criteria such as location, price, category, or flags (like pet-friendly).