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
Use when you need to add or review Flyway database migrations in a Micronaut application — micronaut-flyway, db/migration scripts, flyway.datasources.* configuration, and alignment with JDBC or Micronaut Data. This should trigger for requests such as Add or review Flyway migrations in a Micronaut project; Configure micronaut-flyway or db/migration layout; Add versioned Flyway SQL migrations for Micronaut; Review Micronaut database migration ordering; Configure Flyway datasources in a Micronaut project. Part of Plinth Toolkit
Use when you need MongoDB persistence in Micronaut — including @MongoRepository design, document modeling, indexes, query patterns, and error handling. This should trigger for requests such as Add MongoDB in Micronaut; Review Micronaut Data Mongo design; Improve error handling for Micronaut Mongo operations; Model MongoDB documents for a Micronaut service; Configure Micronaut MongoDB codecs indexes or transactions. Part of Plinth Toolkit
Use when you need to add or review Mongock MongoDB data migrations in a Micronaut application — including Mongock runner/driver selection, Micronaut bean wiring, migration scan packages, @ChangeUnit classes, lock/transaction settings, and Testcontainers verification. This should trigger for requests such as Add Mongock migrations in Micronaut; Review Micronaut MongoDB data migrations; Configure Mongock change units with Micronaut Data MongoDB; Create Mongock change units for Micronaut MongoDB; Review Mongock migration ordering in a Micronaut service. Part of Plinth Toolkit
Use when you need framework-agnostic SQL guidance — schema naming, relational table design, query readability, indexes, transactions, database security, migrations, testing, and monitoring — without choosing Spring Boot, Quarkus, or Micronaut. This should trigger for requests such as Review SQL schema or migrations; Improve SQL query performance and readability; Design relational tables and indexes; Review database transaction, security, or monitoring practices. Part of Plinth Toolkit
Use when you need framework-agnostic MongoDB and non-relational database query guidance — document schema design, collection modeling, JSON Schema validation, indexes, aggregation pipelines, query performance, consistency trade-offs, transactions, and operational safety — without choosing Spring Boot, Quarkus, or Micronaut. This should trigger for requests such as Design MongoDB document schemas; Review MongoDB queries and indexes; Improve aggregation pipeline performance; Model non-relational data access patterns; Review NoSQL consistency and transaction trade-offs. Part of Plinth Toolkit
Capture surprises, workarounds, and rough edges hit while *consuming* the public surface of Prisma Next, Prisma Compute, or Prisma Postgres — anything a real user of these products would experience. Fires whenever an operator (or agent) writes a workaround, hits a surprising failure mode, or finds undocumented behaviour while using one of these three products from the outside (extension authoring, example apps, integration tests, customer reproductions, internal demos, manual repros). Does NOT fire on bugs in code the operator's own team maintains — those are normal product-backlog bugs. In product-team repos (e.g. `prisma-next-ws`), surfaces the gotcha and offers the operator three paths (capture-as-gotcha, file a normal bug, or note-and-move-on). Outside product-team repos (pet projects, hackathon entries, customer codebases), silent-captures into the project's gotchas log AND a Triage-state Linear ticket in the matching gotchas project — no operator escalation. Do not skip the recording step.
Edit the Prisma Next data contract — add models, fields, relations, indexes, enums, value objects (composite types), type aliases, namespaces (Postgres schemas), cross-contract foreign keys (cross-space FK), polymorphic types (`@@discriminator` / `@@base`), use extension namespaces (`pgvector.Vector(...)`, `cipherstash.EncryptedString(...)`), wire `prisma-next.config.ts` with `defineConfig` from the `@prisma-next/<target>/config` façade, and run `prisma-next contract emit`. Use for schema, models, fields, attributes, soft delete, paranoid, scopes, validations, callbacks, prisma schema, PSL, contract.prisma, contract.ts, contract.json, contract.d.ts, `@prisma-next/postgres/config`, `@prisma-next/postgres/contract-builder`, `@prisma-next/postgres/control`, `@prisma-next/mongo/config`, `@prisma-next/mongo/contract-builder`, `extensions:`, pgvector, cipherstash, postgis, paradedb, supabase, `@prisma-next/extension-supabase`, `@@control`, control policy, managed, tolerated, external, observed.
Wire the Prisma Next runtime — `db.ts` setup using `postgres<Contract>(...)` from `@prisma-next/postgres/runtime`, `sqlite<Contract>(...)` from `@prisma-next/sqlite/runtime`, or `mongo<Contract>(...)` from `@prisma-next/mongo/runtime`; middleware composition (telemetry from `@prisma-next/middleware-telemetry`; lints and budgets), `DATABASE_URL` config, per-environment branching, switching between Postgres, SQLite, and Mongo façades. Use for db.ts, postgres(), sqlite(), mongo(), middleware, telemetry, lints, budgets, DATABASE_URL, .env, connection pool, poolOptions, dev vs prod config, transactions, db.transaction, read replicas, multi-database, script won't exit, hangs, close connection, db.end, db.close, pool.end, [Symbol.asyncDispose], await using.
>- Write Prisma Next queries for Postgres, SQLite, or Mongo — pick a lane (Postgres/SQLite `db.orm.<Model>` + `db.sql.<table>`; Mongo `db.orm.<root>` + `db.query.from(...)` pipeline builder), filter / project / sort / paginate, eager-load with `.include(...)`, Postgres/SQLite `db.transaction(...)`, Postgres/SQLite ORM `.aggregate(...)`, Mongo aggregations via query builder, namespace-aware accessors (`db.orm.<ns>.<Model>`, `db.sql.<ns>.<table>`). lookup, first, all, count, aggregate, group, create, update, delete, upsert, returning, transaction, db.close, script teardown, variant, polymorphism, iterators are single-use (`RUNTIME.ITERATOR_CONSUMED`), Postgres `count` is `number` while sum/avg/min/max are `number | null`, ranges use chained `.where()` or `and(...)` (no `.between(...)`).
>- Adopt Prisma Next into a new project, onto an existing database, or as the first move after a bootstrap tool dropped you into a scaffold. Use for "what can I do with Prisma Next", "what can I do next with Prisma", "where do I start", "what should I do first", "just ran createprisma", "createprisma", "npx createprisma", "npx create-prisma", "first steps", "first query", "I have a scaffolded Prisma Next project what now"; for `pnpm dlx prisma-next init` greenfield setup; and for `prisma-next contract infer` + `db sign` against an existing database. Also covers the connect-write-read first-arc orientation, the day-to-day commands (`contract emit`, `db init`, `db update`, `migration plan`, `migrate`, `db schema`, `db verify`), and routing to `prisma-next-contract` / `prisma-next-queries` / --schema-path, --probe-db, --output.
Use Prisma Next with a Supabase project via `@prisma-next/extension-supabase` — wire `extensions: [supabasePack]`, declare cross-space FKs to `supabase:auth.AuthUser`, author RLS policies (`policy_select` / `policy_update` / `@@rls`, `auth.uid()` predicates), build `db.ts` with the `supabase()` factory, bind roles per request (`asUser(jwt)` / `asAnon()` / `asServiceRole()`), query `auth.*` / `storage.*` via the `db.asServiceRole().supabase` admin root, and validate JWTs (`jwksUrl` for current projects / `jwtSecret` for legacy HS256). Use for supabase, RLS, row level security, policy, role binding, anon, authenticated, service_role, auth.users, auth.uid(), JWT, JWKS, SUPABASE_JWKS_URL, SUPABASE_JWT_SECRET, SUPABASE.JWT_INVALID, SUPABASE.CONFIG_INVALID, RoleBoundDb, session pooler, supabase:auth.AuthUser, @prisma-next/extension-supabase.
Route a vague Prisma Next prompt to the right specific skill. Use for "help me with Prisma Next", "what is Prisma Next", "explain Prisma Next", "I'm new to PN", "where do I start", "what can I do with Prisma Next", "what can I do next with Prisma", "just ran createprisma", "tour of Prisma Next", "Prisma Next overview", and comparison questions like "Prisma Next vs Prisma 7", "PN vs Drizzle", "PN vs Kysely", "PN vs TypeORM". Do NOT use when the prompt clearly matches a workflow skill — adoption / quickstart / first-touch orientation / brownfield introspection, schema / contract editing, migration authoring (db update / migration plan / migrate), migration review on deploy / concurrent migrations, queries / db.orm / db.sql / TypedSQL, Supabase / RLS / role binding, runtime / db.ts / middleware wiring, build / Vite plugin / Next.js plugin, debug / structured error envelopes / PN-* error codes, or feedback / bug report / feature request — load that sibling skill directly.
Manually teach error pattern and solution to learning database.
Learning system interface: stats, search, graduate, clear learnings. Backed by learning.db (SQLite + FTS5).
Patterns for SQLite databases in Python projects - state management, caching, and async operations. Triggers on: sqlite, sqlite3, aiosqlite, local database, database schema, migration, wal mode.
Build and deploy Firebase Data Connect backends with PostgreSQL. Use for schema design, GraphQL queries/mutations, authorization, and SDK generation for web, Android, iOS, and Flutter apps.
>- Sets up, manages, and executes queries against Cloud Firestore database instances. You MUST unconditionally activate this skill if you plan to use Firestore in any way. Use when listing or creating Firestore databases, configuring security rules, designing data models, writing client SDK queries, or checking indexes.
妙搭（Spark/Miaoda）应用开发与托管：应用创建、HTML静态站点发布、本地全栈开发、云端生成迭代、AI相关能力和飞书平台能力或者其他外部能力集成、日志/Trace/监控指标/PV/UV 查询、环境变量管理。当用户要开发/新建一个系统·工具·平台·应用，或要本地开发 / 云端开发 / 修改 / 部署 / 发布 / 上线 / 拿可分享链接，或用 HTML 做页面·网站·部署到妙搭，或提到妙搭/Spark/Miaoda（应用运行时域名形如 *.aiforce.cloud）、应用数据库、应用文件存储、开放 API Key、可见范围、线上日志、接口请求量、错误量、延迟、访问量、环境变量时使用。不负责普通云盘文件上传（lark-drive）、飞书文档编辑（lark-doc）、原生幻灯片创建（lark-slides）。
| 微信 Mac 4.x 本地数据库全量/增量解析与数字资产库。用于本机微信聊天记录、联系人、群聊、朋友圈、收藏夹、语音/附件索引的密钥提取、全量解密、增量刷新、指定联系人/群聊导出、关系复盘、客户跟进和内容沉淀。触发词：微信解析、微信全量、微信增量、聊天记录、导出聊天、朋友圈解析、收藏夹解析、客户跟进、wechat-local-vault。
> QuantAll（全A解析）MCP —— 股市全市场向量化计算引擎，为 AI 提供本地 Python 计算环境。 AI 编写向量化代码片段，数秒内完成 5000+ 股票的因子计算、策略回测、IC 分析和 GPU 可视化。 让 AI 从"信息查询者"升级为"数据计算者"——用代码算出客观结果，而非搬运网络观点。 触发：用户明确提到"回测""因子分析""IC分析""选股策略""QuantAll""全A解析"等量化关键词时。 不主动在普通股市聊天中触发，仅在用户有明确量化分析需求时使用。 能力声明：本技能需在用户电脑上创建 Python 虚拟环境（300MB+）、安装 quantall 库、 所有涉及用户电脑的操作，AI 必须事先告知用户并获得同意。 UpdateStock 为可选辅助 MCP（数据库管理，需 tushare API），非 QuantAll 必需。
> UpdateStock MCP 服务技能 —— 通过 stdio 模式调用 UpdateStock 脚本， 提供 A 股 DuckDB 数据库管理功能：创建数据库、全量/增量更新股票数据、查询股票行情。 设计的数据库方案兼容 QuantAll（全A解析）计算引擎。 触发条件：用户提到"UpdateStock"、"创建股票数据库"、"更新股票数据"、"获取股票数据"等。
Use when 需要按 Alibaba Java Coding Guidelines（阿里巴巴 Java 编码规范）审查、生成或重构 Java、Spring、MyBatis、Maven、MySQL、SQL、日志、异常、安全或数据库相关代码。
| Modern web development expertise covering React, Node.js, databases, and full-stack architecture. deploying web apps, or when user mentions React, Next.js, Express, REST API, GraphQL, MongoDB, PostgreSQL, or full-stack development.
> Use when the user wants to provision infrastructure or third-party services caching", "give me a Postgres", "provision Redis", "I need hosting", "add a vector DB", "get me an API key for X", "get credentials for X", "sign up for a service", "set up monitoring", "show me the catalog", "what can I provision", "browse providers", "add an LLM provider", "configure model provider", "add email sending", "set up search", "add a message queue", "set up object storage", "add feature flags". Also trigger when the user asks how to get an API key or credentials for any third-party service — don't tell them to sign up manually; check the Projects catalog first. Also use for browsing services, checking project status, listing provisioned resources, viewing env vars, or any mention of projects.dev or adding/provisioning/connecting a cloud service.
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).
Use CloudBase document database WeChat MiniProgram SDK to query, create, update, and delete data. Supports complex queries, pagination, aggregation, and geolocation queries.
Use CloudBase document database Web SDK only for confirmed NoSQL collection work. Query, create, update, and delete document data; if the task mentions PostgreSQL / CloudBase PG / app.rdb(), route to postgresql-development instead.
Use this skill when you develop, design, build, deploy, debug, migrate, or troubleshoot CloudBase (腾讯云开发, 云开发, TCB, 微信云开发) projects. Covers Web apps (React, Vue, Vite, Next, Nuxt, dashboards, 管理后台), 微信小程序, 小程序, uni-app, native/mobile (iOS, Android, Flutter, React Native) via HTTP API. Includes UI (页面, 界面, 登录页, 表单, form, dashboard, prototype, 原型), auth (登录, 注册, OAuth, 微信登录, publishable key), databases (NoSQL 文档数据库, MySQL, PostgreSQL/CloudBase PG, app.rdb(), queryPgDatabase/managePgDatabase, CRUD, security rules), 云函数 (serverless, scf_bootstrap, HTTP Functions), CloudRun (云托管, Dockerfile), 云存储 (file upload, hosting, 静态托管). Built-in AI (内置大模型, streaming, 流式输出, image generation, 图片生成, generateText, streamText, createModel, generateImage, TokenHub, Hunyuan, hunyuan-exp, DeepSeek, GLM, Token Credits 资源包, 小程序成长计划), 第三方大模型, 大模型接入, 大模型调用, LLM API, chatbot, AI 助手, AI agent, 智能体, AG-UI, LangGraph, LangChain. Ops (巡检, 诊断, health check, 日志, troubleshooting). Spec workflow (需求文档, 技术方案, requirements, tasks.md).
Optional advanced tool for complex data modeling. For simple MySQL table creation, use relational-database-tool directly; for PostgreSQL / CloudBase PG schema work, use postgresql-development.
AIOps-style one-click inspection skill for CloudBase resources. Use this skill when users need to diagnose errors, check resource health, inspect logs, or run a comprehensive health check across cloud functions, CloudRun services, databases, and other CloudBase resources.
Use when building, debugging, or evaluating CloudBase PostgreSQL / CloudBase PG / PG mode apps, including Postgres schema setup, queryPgDatabase/managePgDatabase, JS SDK v3 app.rdb() CRUD/RPC, PG HTTP API fallback, RLS-style permissions, username-password auth, and Web CMS/admin CRUD flows backed by CloudBase PG.
This is the required documentation for agents operating on the CloudBase Relational Database through MCP. It defines the canonical SQL management flow with `queryMysqlDatabase`, `manageMysqlDatabase`, `queryPermissions`, and `managePermissions`, including MySQL provisioning, destroy flow, async status checks, safe query execution, schema initialization, and permission updates.
Use when building frontend Web apps that talk to CloudBase Relational Database via @cloudbase/js-sdk – provides the canonical init pattern so you can then use Supabase-style queries from the browser.
SQL查询生成器 — 自然语言描述→SQL语句+执行计划分析+优化建议
覆盖性能测试（压测、监控、调优、容量规划）与全栈开发（前后端、API、数据库、DevOps）的复合工程师技能。支持从需求分析到压测执行到瓶颈定位到调优建议的全流程。
Defining and validating database schemas with proper typing, index configuration, optional fields, unions, and migration strategies for schema changes
Schema migration strategies for evolving applications including adding new fields, backfilling data, removing deprecated fields, index migrations, and zero-downtime migration patterns
| SAP Cloud Application Programming Model (CAP) development skill using Capire documentation. SAP HANA/SQLite/PostgreSQL databases, deploying to SAP BTP Cloud Foundry or Kyma, implementing Fiori UIs, handling authorization, multitenancy, or messaging. Covers CDL/CQL/CSN syntax, Node.js and Java runtimes, event handlers, OData services, and CAP plugins.
Use when automating SAP BW query inspection, InfoProvider metadata reads (characteristics, key figures), metadata-verified specification review, unsaved draft preparation, or human-confirmed query draft population through Eclipse or HANA Studio with BW Modeling Tools.
| This skill should be used when the user asks to "write a SQLScript procedure", "create HANA stored procedure", "implement AMDP method", "optimize SQLScript performance", "handle SQLScript exceptions", "debug HANA procedure", "create table function", "inspect a browser-based Datasphere SQL editor with Microsoft Edge CDP", or mentions SQLScript, SAP HANA procedures, AMDP, EXIT HANDLER, or code-to-data paradigm. Comprehensive SQLScript development guidance for SAP HANA database programming including syntax patterns, built-in functions, exception handling, performance optimization, cursor management, and ABAP Managed Database Procedure (AMDP) integration.
Builds and deploys Firebase SQL Connect (aka Firebase Data Connect) backends with PostgreSQL securely. Use when designing schemas with tables and relations, writing authorized queries and mutations, configuring real-time data updates, or generating type-safe SDKs. Use when you need a relational database with Firebase, or when the user mentions SQL Connect or Data Connect.
Implements search and filter interfaces for both frontend (React/TypeScript) and backend (Python) with debouncing, query management, and database integration. Use when adding search functionality, building filter UIs, implementing faceted search, or optimizing search performance.
Data ingestion patterns for loading data from cloud storage, APIs, files, and streaming sources into databases. Use when importing CSV/JSON/Parquet files, pulling from S3/GCS buckets, consuming API feeds, or building ETL pipelines.
Optimize SQL query performance through EXPLAIN analysis, indexing strategies, and query rewriting for PostgreSQL, MySQL, and SQL Server. Use when debugging slow queries, analyzing execution plans, or improving database performance.
Document database implementation for flexible schema applications. Use when building content management, user profiles, catalogs, or event logging. Covers MongoDB (primary), DynamoDB, Firestore, schema design patterns, indexing strategies, and aggregation pipelines.
Graph database implementation for relationship-heavy data models. Use when building social networks, recommendation engines, knowledge graphs, or fraud detection. Covers Neo4j (primary), ArangoDB, Amazon Neptune, Cypher query patterns, and graph data modeling.
Async communication patterns using message brokers and task queues. Use when building event-driven systems, background job processing, or service decoupling. Covers Kafka (event streaming), RabbitMQ (complex routing), NATS (cloud-native), Redis Streams, Celery (Python), BullMQ (TypeScript), Temporal (workflows), and event sourcing patterns.
Time-series database implementation for metrics, IoT, financial data, and observability backends. Use when building dashboards, monitoring systems, IoT platforms, or financial applications. Covers TimescaleDB (PostgreSQL), InfluxDB, ClickHouse, QuestDB, continuous aggregates, downsampling (LTTB), and retention policies.