Skill UI

This skill is a powerful orchestrator designed to build complete full-stack applications from simple natural language requests. It analyzes user requirements, determines the optimal project type and technology stack, generates a detailed plan, and coordinates specialized agents (frontend, backend, database, etc.) to scaffold and build the entire project structure, accelerating the development lifecycle.

This skill is a powerful orchestrator designed to build complete full-stack applications from simple natural language requests. It analyzes user requirements, determines the optimal project type and technology stack, generates a detailed plan, and coordinates specialized agents (frontend, backend, database, etc.) to scaffold and build the entire project structure, accelerating the development lifecycle.

This SDK provides the management plane capabilities for Azure Cosmos DB within the .NET ecosystem. It allows developers to programmatically provision and manage core infrastructure resources, such as Cosmos DB accounts, databases, containers, throughput settings, and perform resource lifecycle operations using Azure Resource Manager (ARM). It is designed for infrastructure automation and setup tasks.

A comprehensive guide to modern backend development patterns for scalable server-side applications using Node.js, Express, and Next.js. Covers API design (RESTful), data access patterns (Repository, Service Layer), database optimization (N+1 prevention, Transactions), and advanced caching strategies (Redis, Cache-Aside). Essential for building robust, high-performance APIs.

Documenting backend architecture patterns, API design, database optimization, caching, and error-handling best practices tailored for scalable Node.js, Express, and Next.js API routes.

An expert developer specializing in secure backend coding practices, vulnerability mitigation, and robust API design. Proficient in preventing common attacks such as SQL injection, XSS, and CSRF. Covers comprehensive areas including input validation, authentication mechanisms (OAuth 2.0, MFA), database security, and implementing necessary security headers (CSP, HSTS) for building secure-by-design applications. Ideal for implementing security fixes or building new, hardened backend services.

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 comprehensive template provides a production-grade reference architecture for CodeRabbit AI code reviews. It is designed to guide teams in establishing rigorous coding standards by defining specific, best-practice instructions for various layers (API, Database, Authentication, Frontend, CI/CD, Infrastructure). Use this as a robust starting point to build a comprehensive, automated, and secure code quality review process.

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.

Provides automated guidance for designing and implementing cron job schedulers in backend projects, covering best practices, production-ready code, and validation for node.js, Python, Go, databases, and microservices patterns.

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.