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Found 796 Skills
An analytical in-process SQL database management system. Designed for fast analytical queries (OLAP). Highly interoperable with Python's data ecosystem (Pandas, NumPy, Arrow, Polars). Supports querying files (CSV, Parquet, JSON) directly without an ingestion step. Use for complex SQL queries on Pandas/Polars data, querying large Parquet/CSV files directly, joining data from different sources, analytical pipelines, local datasets too big for Excel, intermediate data storage and feature engineering for ML.
Transform raw data into analytical assets using ETL/ELT patterns, SQL (dbt), Python (pandas/polars/PySpark), and orchestration (Airflow). Use when building data pipelines, implementing incremental models, migrating from pandas to polars, or orchestrating multi-step transformations with testing and quality checks.
Execute read-only SQL queries against PostgreSQL databases. Use when: (1) querying PostgreSQL data, (2) exploring schemas/tables, (3) running SELECT queries for analysis, (4) checking database contents. Supports multiple database connections with descriptions for auto-selection. Blocks all write operations (INSERT, UPDATE, DELETE, DROP, etc.) for safety.
Provides comprehensive Drizzle ORM patterns for schema definition, CRUD operations, relations, queries, transactions, and migrations. Proactively use for any Drizzle ORM development including defining database schemas, writing type-safe queries, implementing relations, managing transactions, and setting up migrations with Drizzle Kit. Supports PostgreSQL, MySQL, SQLite, MSSQL, and CockroachDB.
MongoDB and PostgreSQL database administration. Databases: MongoDB (document store, aggregation, Atlas), PostgreSQL (relational, SQL, psql). Capabilities: schema design, query optimization, indexing, migrations, replication, sharding, backup/restore, user management, performance analysis. Actions: design, query, optimize, migrate, backup, restore, index, shard databases. Keywords: MongoDB, PostgreSQL, SQL, NoSQL, BSON, aggregation pipeline, Atlas, psql, pgAdmin, schema design, index, query optimization, EXPLAIN, replication, sharding, backup, restore, migration, ORM, Prisma, Mongoose, connection pooling, transactions, ACID. Use when: designing database schemas, writing complex queries, optimizing query performance, creating indexes, performing migrations, setting up replication, implementing backup strategies, managing database permissions, troubleshooting slow queries.
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).
Programmatic JDBC in Quarkus with Agroal DataSource, parameterized SQL, transactions, batching, and Dev Services. Part of the skills-for-java project
Best practices and guidelines for working with Postgres. Covers schema design, indexing strategies, query optimization, migrations, and common pitfalls. Use when writing SQL, designing database schemas, optimizing queries, or setting up a Postgres database.
Drizzle ORM documentation covering queries, CRUD operations, schema definitions, migrations, caching (50 topics), custom types, and database connections. Includes integrations for PostgreSQL (Neon, Vercel, Supabase, AWS Data API, PlanetScale, Prisma), MySQL (AWS Data API, PlanetScale, TiDB), and SQLite (Bun, Cloudflare D1/Durable Objects, Expo, Turso, OP SQLite). Use when working with Drizzle queries, database schemas, migrations, type-safe SQL, ORM patterns, or connecting to supported databases.
Database specialist for SQL, NoSQL, and vector database modeling, schema design, normalization, indexing, transactions, integrity, concurrency control, backup, capacity planning, data standards, anti-pattern review, and compliance-aware database design. Use for database, schema, ERD, table design, document model, vector index design, RAG retrieval architecture, migration, query tuning, glossary, capacity estimation, backup strategy, database anti-pattern remediation work, and ISO 27001, ISO 27002, or ISO 22301-aware database recommendations.
Guide for implementing Syncfusion EditControl (SyntaxEditor) in Windows Forms applications. Use when creating interactive code editors with syntax highlighting, IntelliSense, multi-language support, or Visual Studio-like editing capabilities. Covers installation, syntax highlighting for 12+ built-in languages (C#, VB.NET, XML, HTML, Java, SQL, PowerShell, JavaScript), custom language configuration, code outlining, auto-completion, find/replace dialogs, file operations, export (XML/RTF/HTML), split views, and comprehensive event handling for building professional code editor applications.
Run SQL queries against the attached DuckDB database or ad-hoc against files. Accepts raw SQL or natural language questions. Uses DuckDB Friendly SQL idioms.