Skill UI

A comprehensive SDK client for Java designed to build robust, event-driven applications. It facilitates both publishing and receiving events using Azure Event Grid, supporting both native Azure EventGridEvent schemas and standardized CloudEvents. Ideal for implementing Publish/Subscribe patterns and integrating microservices across the Azure ecosystem.

A comprehensive SDK client for Java designed to build robust, event-driven applications. It facilitates both publishing and receiving events using Azure Event Grid, supporting both native Azure EventGridEvent schemas and standardized CloudEvents. Ideal for implementing Publish/Subscribe patterns and integrating microservices across the Azure ecosystem.

A comprehensive guide to building robust, production-ready GraphQL APIs. This skill covers schema design (SDL/code-first), implementing efficient resolvers with DataLoader for batching, handling real-time subscriptions via WebSockets, and integrating field-level authorization and complexity limiting. Supports major runtimes like Node.js and Python.

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

A comprehensive guide for designing production-grade lead enrichment pipelines in Clay. Covers three integration patterns (Webhook, API), detailed table schema design, advanced data waterfall logic, implementing complex ICP scoring formulas, and setting up robust CRM synchronization flows for go-to-market data operations.

Guidelines for building Convex backends with TypeScript, detailing syntax, validators, schema design, queries, mutations, actions, scheduling, and file storage so you can implement Convex database operations, real-time updates, and cron jobs consistently.

A powerful AI tool designed for complex, coordinated programming tasks. It enables developers to generate, refactor, and scaffold entire features across multiple files (e.g., schema, API routes, service layers, tests) while maintaining consistency with existing codebase patterns. It supports agent mode for autonomous, multi-step changes and allows systematic migration and review of all affected files via detailed diffs.

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.

An expert architect specializing in designing, optimizing, and scaling entire data layers from inception (greenfield) to re-architecture. Proficient in selecting the optimal database technology (SQL, NoSQL, Graph, Time-series), designing robust schemas, implementing sophisticated indexing strategies, and planning complex migration paths. Suitable for defining data storage solutions that meet high performance, scalability, and data integrity requirements.

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.

This skill provides expert-level database design capabilities, including schema analysis, normalization, and index optimization. It assists architects and developers in creating scalable, performant, and maintainable database structures. Features include automated ERD generation, migration planning with zero-downtime strategies, and security best practices. Ideal for SQL and NoSQL environments.

Automates database schema design guidance for backend projects, activating whenever you ask about schema patterns, best practices, or implementation in node.js, Python, Go, microservices, caching, or messaging contexts.