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Found 705 Skills
Seed test databases with pgsql-test using loadJson, loadSql, and loadCsv. Use when asked to "seed test data", "load fixtures", "populate test database", or when setting up test data for database tests.
Query SQLite databases, inspect schemas, and explain queries via MCP. Use when working with local SQLite databases.
Use Electric with Drizzle ORM or Prisma for the write path. Covers getting pg_current_xact_id() from ORM transactions using Drizzle tx.execute(sql) and Prisma $queryRaw, running migrations that preserve REPLICA IDENTITY FULL, and schema management patterns compatible with Electric shapes. Load when using Drizzle or Prisma alongside Electric for writes.
Expert knowledge for Azure Database for PostgreSQL development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when building, debugging, or optimizing Azure Database for PostgreSQL applications. Not for Azure SQL Database (use azure-sql-database), Azure SQL Managed Instance (use azure-sql-managed-instance), SQL Server on Azure Virtual Machines (use azure-sql-virtual-machines), Azure Cosmos DB (use azure-cosmos-db).
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".
Analyze and optimize slow SQL queries. Use when the user says a query is slow, asks to optimize or speed up SQL, wants to find anti-patterns, needs index recommendations, or asks for a query rewrite. Also use when EXPLAIN output shows full table scans or poor join strategies.
Create new Azure Database for PostgreSQL Flexible Server instances and configure passwordless authentication with Microsoft Entra ID. Set up developer access, managed identities for apps, group-based permissions, and migrate from password-based to Entra ID authentication. Trigger phrases include "passwordless for postgres", "entra id postgres", "azure ad postgres authentication", "postgres managed identity", "migrate postgres to passwordless".
Analyze datasets to extract insights, identify patterns, and generate reports. Use when exploring data, creating visualizations, or performing statistical analysis. Handles CSV, JSON, SQL queries, and Python pandas operations.
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.
Database security, access control, and data protection
Step-by-step guide for capturing key application requirements for NoSQL use-case and produce Azure Cosmos DB Data NoSQL Model design using best practices and common patterns, artifacts_produced: "cosmosdb_requirements.md" file and "cosmosdb_data_model.md" file
Tests project primitive (SELECT fields)