🗄️数据库 MCP（PostgreSQL / MySQL / Redis）

How to write tests, when to use each type of test, and how to run them. Contains information about conversion of `.test` to `.sqltest`, and how to write `.sqltest` and rust tests

SQL evaluation criteria for Databricks. Load when the trace contains execute_sql tool calls or SQL code in responses. Covers syntax validity, Unity Catalog patterns, and Databricks-specific SQL features.

Expert system for generating, validating, and optimizing ClickHouse SQL. Use this when the user needs data, queries, or analysis.

Implementation details for the Microsoft.Data.Sqlite ADO.NET provider. Use when changing files under `src/Microsoft.Data.Sqlite.Core/`.

Write correct, performant SQL across all major data warehouse dialects (Snowflake, BigQuery, Databricks, PostgreSQL, etc.). Use when writing queries, optimizing slow SQL, translating between dialects, or building complex analytical queries with CTEs, window functions, or aggregations.

Pre-deployment verification checklist. Use when about to ship a release, deploying a change with database migrations or feature flags, verifying CI status and approvals before going to production, or documenting rollback triggers ahead of time.

SQL 注入漏洞测试技能。覆盖联合注入、布尔盲注、时间盲注、报错注入、堆叠查询等攻击向量， 提供 MySQL/PostgreSQL/MSSQL/Oracle/SQLite 多数据库的特征 Payload， 包含 WAF 绕过策略和系统化测试流程，适用于 Web 应用 SQL 注入漏洞的发现与确认。

Use when reviewing code for security vulnerabilities, implementing authentication flows, auditing OWASP Top 10, configuring CORS/CSP headers, handling secrets, input validation, SQL injection prevention, XSS protection, or any security-related code review.

Identifies Oracle-to-PostgreSQL migration risks by cross-referencing code against known behavioral differences (empty strings, refcursors, type coercion, sorting, timestamps, concurrent transactions, etc.). Use when planning a database migration, reviewing migration artifacts, or validating that integration tests cover Oracle/PostgreSQL differences.

Use this skill when writing SQL queries — selects, joins, aggregations, window functions, or schema modifications. Apply whenever SQL is needed to ensure correctness, safety, and performance.

Expert SQL query generation for DBX Studio. Use when writing, optimizing, or debugging SQL queries against user database connections.

Expert SQL query generation for DBX Studio. Use when writing, optimizing, or debugging SQL queries against user database connections.

Write comprehensive backend tests including unit tests, integration tests, and API tests. Use when testing REST APIs, database operations, authentication flows, or business logic. Handles Jest, Pytest, Mocha, testing strategies, mocking, and test coverage.

Design and optimize database schemas for SQL and NoSQL databases. Use when creating new databases, designing tables, defining relationships, indexing strategies, or database migrations. Handles PostgreSQL, MySQL, MongoDB, normalization, and performance optimization.

Execute authoring T-SQL (DDL, DML, data ingestion, transactions, schema changes) against Microsoft Fabric Data Warehouse and SQL endpoints from agentic CLI environments. Use when the user wants to: (1) create/alter/drop tables from terminal, (2) insert/update/delete/merge data via CLI, (3) run COPY INTO or OPENROWSET ingestion, (4) manage transactions or stored procedures, (5) perform schema evolution, (6) use time travel or snapshots, (7) generate ETL/ELT shell scripts, (8) create views/functions/procedures on Lakehouse SQLEP. Triggers: "create table in warehouse", "insert data via T-SQL", "load from ADLS", "COPY INTO", "run ETL with T-SQL", "alter warehouse table", "upsert with T-SQL", "merge into warehouse", "create T-SQL procedure", "warehouse time travel", "recover deleted warehouse data", "create warehouse schema", "deploy warehouse", "transaction conflict", "snapshot isolation error".

Execute read-only T-SQL queries against Fabric Data Warehouse, Lakehouse SQL Endpoints, and Mirrored Databases via CLI. Default skill for any lakehouse data query (row counts, SELECT, filtering, aggregation) unless the user explicitly requests PySpark or Spark DataFrames. Use when the user wants to: (1) query warehouse/lakehouse data, (2) count rows or explore lakehouse tables, (3) discover schemas/columns, (4) generate T-SQL scripts, (5) monitor SQL performance, (6) export results to CSV/JSON. Triggers: "warehouse", "SQL query", "T-SQL", "query warehouse", "show warehouse tables", "show lakehouse tables", "query lakehouse", "lakehouse table", "how many rows", "count rows", "SQL endpoint", "describe warehouse schema", "generate T-SQL script", "warehouse performance", "export SQL data", "connect to warehouse", "lakehouse data", "explore lakehouse".

Run and troubleshoot tests for DBHub, including unit tests, integration tests with Testcontainers, and database-specific tests. Use when asked to run tests, fix test failures, debug integration tests, troubleshoot Docker/database container issues, or add new tests. Also use when verifying code changes work correctly or when CI test failures need investigation.

后端架构模式、API 设计、数据库优化以及针对 Node.js、Express 和 Next.js API 路由的服务端最佳实践。

后端架构模式、API 设计、数据库优化以及 Node.js、Express 和 Next.js API 路由的服务端最佳实践。

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 路由的服务端最佳实践。

跨 PostgreSQL、MySQL 及常用 ORM（Prisma、Drizzle、Django、TypeORM、golang-migrate）的模式变更（schema changes）、数据迁移、回滚及零停机部署（zero-downtime deployments）的数据库迁移最佳实践。

Design and implement database indexing strategies. Use when creating indexes, choosing index types, or optimizing index performance in PostgreSQL and MySQL.

Implement database sharding for horizontal scalability. Use when scaling large databases, distributing data across multiple servers, or designing sharded architectures.

Document database schemas, ERD diagrams, table relationships, indexes, and constraints. Use when documenting database schema, creating ERD diagrams, or writing table documentation.

Design database schemas with normalization, relationships, and constraints. Use when creating new database schemas, designing tables, or planning data models for PostgreSQL and MySQL.

Implement offline-first mobile apps with local storage, sync strategies, and conflict resolution. Covers AsyncStorage, Realm, SQLite, and background sync patterns.

Generate SQL queries from natural language descriptions. Supports BigQuery, PostgreSQL, MySQL, and other dialects. Reads database schemas from uploaded diagrams or documentation. Use when writing SQL, building data reports, exploring databases, or translating business questions into queries.

View all Claudia memory databases, switch between them, manage isolation. Triggers on "which database?", "switch workspace", "show databases", "list databases".

根据用户提供的自然语言物流订单信息（客户、重量、起止地、类型、日期），生成对应的MySQL INSERT语句或Couchbase N1QL语句。

General Correctness rules, Rust patterns, comments, avoiding over-engineering. When writing code always take these into account

Analyze git repositories to build a security ownership topology (people-to-file), compute bus factor and sensitive-code ownership, and export CSV/JSON for graph databases and visualization. Use when the user explicitly wants a security-oriented ownership or bus-factor analysis grounded in git history (for example: orphaned sensitive code, security maintainers, CODEOWNERS reality checks for risk, sensitive hotspots, or ownership clusters). Do NOT use for general maintainer lists, non-security ownership questions, or threat modeling (use security-threat-model).

This skill should be used when the user asks to "test for SQL injection vulnerabilities", "perform SQLi attacks", "bypass authentication using SQL injection", "extract database information through injection", "detect SQL injection flaws", or "exploit database query vulnerabilities". It provides comprehensive techniques for identifying, exploiting, and understanding SQL injection attack vectors across different database systems.

This skill should be used when the user asks to "automate SQL injection testing," "enumerate database structure," "extract database credentials using sqlmap," "dump tables and columns from a vulnerable database," or "perform automated database penetration testing." It provides comprehensive guidance for using SQLMap to detect and exploit SQL injection vulnerabilities.

This skill should be used when the user asks to "automate SQL injection testing," "enumerate database structure," "extract database credentials using sqlmap," "dump tables and columns...

Backend architecture patterns, API design, database optimization, and server-side best practices for Node.js, Express, and Next.js API routes.

Database development and operations workflow covering SQL, NoSQL, database design, migrations, optimization, and data engineering.

SQLite expert for WAL mode, query optimization, embedded patterns, and advanced features

SQL query expert for optimization, schema design, and data analysis

Database schema validation, data integrity testing, migration testing, transaction isolation, and query performance. Use when testing data persistence, ensuring referential integrity, or validating database migrations.

AI frontend specialist and design consultant that guides users through a structured discovery process before generating any code. Collects visual references, design tokens, typography, icons, layout preferences, and brand guidelines to ensure the final output matches the user's vision with high fidelity. Use when the user asks to build, design, create, or improve any frontend interface — websites, landing pages, dashboards, components, apps, emails, forms, modals, or any UI element. Also triggers on "build me a UI", "design a page", "create a component", "improve this layout", "make this look better", "frontend", "interface", "redesign", or when the user provides mockups, screenshots, or design references. Do NOT use for backend logic, API design, database schemas, or non-visual code tasks.

This skill should be used when handling a sqlglot version bump, updating sqlglot compatibility, working on a renovate/sqlglot branch, fixing sqlglot-related test failures, or migrating functions from invoke_anonymous_function to sqlglot expression classes.

Universal SQL performance optimization assistant for comprehensive query tuning, indexing strategies, and database performance analysis across all SQL databases (MySQL, PostgreSQL, SQL Server, Oracle). Provides execution plan analysis, pagination optimization, batch operations, and performance monitoring guidance.

Universal SQL code review assistant that performs comprehensive security, maintainability, and code quality analysis across all SQL databases (MySQL, PostgreSQL, SQL Server, Oracle). Focuses on SQL injection prevention, access control, code standards, and anti-pattern detection. Complements SQL optimization prompt for complete development coverage.

Review and create distinctive, production-grade frontend interfaces with high design quality and design system compliance. Evaluates using three pillars: frictionless insight-to-action, quality craft, and trustworthy building. USE FOR: PR reviews, design reviews, accessibility audits, design system compliance checks, creative frontend design, UI code review, component reviews, responsive design checks, theme testing, and creating memorable UI. DO NOT USE FOR: Backend API reviews, database schema reviews, infrastructure or DevOps work, pure business logic without UI, or non-frontend code.

Snowflake data warehouse queries and schema inspection. Use when running SQL queries against Snowflake, listing tables, or inspecting schemas.

Comprehensive backend development for building production-ready server-side applications with multiple frameworks, databases, and deployment strategies. Use when building APIs, services, databases, or server infrastructure.

MySQL/MariaDB database inspection and queries. Use when investigating table schemas, running queries, checking processlist, replication status, InnoDB engine status, or lock contention.

PostgreSQL database inspection and queries. Use when investigating table schemas, running queries, checking locks, replication status, or long-running queries.