Skill UI

Design scalable AWS architectures for startups with guided workflows covering requirement gathering, architecture pattern selection, IaC template generation, cost analysis, and deployment/validation using Lambda, API Gateway, ECS, Aurora, and optimization scripts.

Design scalable AWS architectures for startups with guided workflows covering requirement gathering, architecture pattern selection, IaC template generation, cost analysis, and deployment/validation using Lambda, API Gateway, ECS, Aurora, and optimization scripts.

A comprehensive template for developing modern, full-stack applications. This guide covers architecture overview, file structure, and best-practice code patterns for advanced technology stacks including Next.js, FastAPI, Supabase, and structured AI integration using Claude API. It serves as a robust blueprint for professional development teams.

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

A comprehensive guide to configuring and maximizing the potential of Claude Code, an advanced agentic coding tool. This resource details best practices, setup templates (CLAUDE.md), advanced prompting techniques (e.g., thinking keywords), and debugging strategies for building reliable, complex software autonomously.

This skill serves as an expert guide for writing, reviewing, and optimizing AWS CloudFormation templates. It covers foundational best practices, including utilizing parameterized environments, implementing nested stacks, managing stateful resources with deletion policies, and ensuring production-grade infrastructure consistency. Use it when building robust and maintainable Infrastructure as Code (IaC) for AWS.

Auto-activating AWS skill that guides users through CloudFormation template creation, covering compute, storage, networking, and serverless best practices with validation-ready output.

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.

Guides users through compression optimizer scenarios within data pipelines, offering best practices, code templates, and validation steps for ETL, transformation, and streaming workflows.

Automates guidance for configuring connection pooling during API integrations, offering best practices, validated code/config templates, and step-by-step help so pooling setups resolve quickly.

Assists with coverage report analyzer tasks within test automation, offering best-practice guidance, code/config templates, step-by-step workflows, and validation to keep reports reliable.

A specialist guide for designing, implementing, and optimizing high-performance C++ applications using modern standards (C++20/23). Expertise covers advanced topics like concepts, coroutines, template metaprogramming, and zero-overhead abstractions. Use this when tackling complex memory management, concurrency bottlenecks, or integrating build systems via CMake, ensuring code meets industrial quality standards through rigorous sanitization and profiling.