Skill UI

Comprehensive guide for authenticating to various Azure services using the official Azure Identity SDK in TypeScript. This SDK supports multiple credential types, including DefaultAzureCredential, Managed Identity, Service Principal (secrets/certificates), and integration with Azure CLI/PowerShell, ensuring secure and flexible authentication across local development, CI/CD, and cloud environments.

This skill provides comprehensive scripts and workflows to automatically identify and remove unused AWS resources across multiple services (EBS, S3, EC2, EIPs). By automating the cleanup of orphaned volumes, old snapshots, and stale data, users can eliminate cloud waste, significantly optimizing their AWS expenditure and ensuring a cost-efficient infrastructure.

This skill details the architecture and implementation of a robust API Gateway, serving as the single entry point for multiple backend microservices. It centrally manages critical cross-cutting concerns, including path-based and header-based routing, JWT/OAuth2 authentication, rate limiting, load balancing, and circuit breaker protection. This pattern is essential for building resilient, scalable, and maintainable microservices architectures, significantly simplifying client integration and request management.

A comprehensive guide detailing reference architecture patterns for implementing Clerk authentication in modern, enterprise-grade applications. Covers best practices for Next.js full-stack, microservices, multi-tenant SaaS, and cross-platform mobile/web synchronization, ensuring secure and scalable authentication flows.

A comprehensive workflow designed to orchestrate the entire lifecycle of large-scale features, from initial requirement gathering and architectural design through multi-service implementation, rigorous testing, and modern deployment strategies (e.g., canary, blue-green). Use this skill when coordinating complex, cross-functional feature delivery across frontend, backend, and data teams, ensuring quality and consistency at every phase.

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 skill guides the definition of relationships and integration contracts between distinct bounded contexts within a complex system using Domain-Driven Design (DDD) patterns. It is crucial for preventing domain leakage, planning anti-corruption layers (ACLs), and clarifying ownership boundaries when multiple services interact, ensuring a robust and scalable system architecture.

This guide offers a comprehensive deep dive into migrating existing voice transcription workflows from multiple major providers, including AWS Transcribe, Google Cloud STT, OpenAI Whisper, and others, to Deepgram. It details feature mapping, best practices, and implements an adapter pattern, enabling seamless, reliable, and validated service switching.

This skill acts as an expert guide for setting up comprehensive debugging environments, implementing distributed tracing solutions, and establishing robust diagnostic workflows. It is ideal for diagnosing complex, multi-service issues in development or production environments by standardizing logging, tracking correlation IDs, and ensuring end-to-end observability.

This skill provides comprehensive guidance on implementing distributed tracing using industry standards like OpenTelemetry and tools such as Jaeger/Tempo. It enables developers to monitor the end-to-end lifecycle of a request across multiple microservices. Use this skill to debug latency issues, visualize complex service dependencies, pinpoint performance bottlenecks, and accurately trace error propagation in highly distributed systems.

A comprehensive guide providing production-ready architectural patterns for building scalable, maintainable, and reliable integrations with Evernote. This skill covers microservices design, multi-level caching strategies (e.g., Redis), robust synchronization processes using webhooks and message queues, and establishing data mirroring schemas for complex SaaS applications.

This skill provides guidance and patterns for generating structured JSON files that define complex workflow pipelines. It is essential for chaining multiple distinct AI models together, enabling multi-step, automated data processing. Use this when a single task requires a sequence of interconnected AI operations or services.