Skill UI

Analyzes query workloads with the database-index-advisor plugin to spot missing or unused indexes and recommends creations or removals to boost performance and reclaim storage.

Analyzes query workloads with the database-index-advisor plugin to spot missing or unused indexes and recommends creations or removals to boost performance and reclaim storage.

Enables Claude to examine EXPLAIN plans, spot slow queries or missing indexes, and deliver concrete optimization steps—ideal for improving database query speed and resource usage when performance issues arise.

This comprehensive guide covers modern state management patterns in Angular, including local state using Signals, complex global state handling with NgRx, and remote data synchronization with NgRx Query. It helps developers understand when to use Signals, NgRx, or other solutions for building robust, scalable, and maintainable applications.

This library provides a comprehensive Java client for interacting with Azure Table Storage and Cosmos DB Table API. It supports all standard CRUD operations (Create, Read, Update, Delete), advanced querying using OData filters, and batch transactions. Ideal for building scalable, high-performance applications requiring structured NoSQL data persistence on Azure Cloud.

A comprehensive Python SDK for interacting with Azure Monitor services. It enables developers to execute complex Kusto Query Language (KQL) queries against Log Analytics workspaces and retrieve various resource metrics (CPU usage, network traffic, etc.). Ideal for building robust monitoring dashboards, automated alerting systems, and custom data analysis pipelines in cloud environments.

Automates guidance for setting up and optimizing BigQuery scheduled queries within GCP, offering best practices, configuration templates, and validation for production-ready data workflows.

This guide provides comprehensive patterns and best practices for working with ClickHouse, a high-performance OLAP database. It covers advanced topics such as MergeTree engine design, efficient query optimization (filtering, aggregations, window functions), bulk/streaming data ingestion, materialized view creation, and performance monitoring techniques, ensuring optimal performance for large-scale analytical workloads.

Guides ClickHouse database architects through schema designs, query optimization, ingestion strategies, and monitoring techniques tailored for high-performance analytical workloads.

This skill provides a comprehensive guide to implementing the Command Query Responsibility Segregation (CQRS) pattern. It is crucial for separating read and write concerns, allowing independent scaling of read models, optimizing complex query performance, and building robust, event-sourced architectures when read and write data models differ.

This comprehensive workflow guides the entire database lifecycle, from initial architecture design (covering both SQL and NoSQL) to advanced implementation, optimization, and maintenance. It covers crucial stages like schema design, implementing migrations, optimizing query performance, developing robust data pipelines (using tools like Airflow and dbt), and managing data quality and operations. Ideal for engineers building complex, production-grade data systems.

Provides a practical checklist and principles for designing database schemas, indexing strategies, query optimization, and migration planning for both SQL and NoSQL systems, plus guidance on spotting and fixing N+1 issues and denormalization trade-offs.