Skill UI

This tool provides comprehensive automation capabilities for managing cloud infrastructure on the Render platform via Rube MCP. Users can list, filter, and browse various services (web services, static sites, etc.), manually trigger new deployments, and continuously monitor the deployment status (e.g., checking for 'live' status or catching 'build_failed' errors). It is essential for streamlining CI/CD pipelines, managing projects, and ensuring reliable, automated service updates without manual intervention.

A comprehensive tool that analyzes existing codebases to generate detailed, definitive architectural blueprints. It automatically detects technology stacks, identifies architectural patterns (e.g., Microservices, Clean Architecture), and documents implementation details, including dependency flow, cross-cutting concerns (security, logging), and data models. This ensures architectural consistency, aids in onboarding new team members, and guides future development efforts.

This advanced workflow automates the process of analyzing the operational health of specific Azure resources. It ingests and analyzes raw logs, telemetry data, and performance metrics from diverse Azure services (e.g., VMs, Web Apps, Databases). The system performs comprehensive root cause analysis, classifies issues (Critical, High, Medium), and generates actionable, step-by-step remediation plans, significantly reducing manual troubleshooting time.

This skill guides the end-to-end process of building automated evaluation pipelines for Python applications powered by Large Language Models (LLMs). It teaches how to define evaluation criteria, instrument the application, build golden datasets, and run real-world evaluations using tools like pixie, ensuring the app's logic (not just the LLM) is rigorously tested. Ideal for QA, benchmarking, and improving LLM-based services.

Guides setting up Microsoft Fluent UI Blazor components, ensuring providers/services registrations, handling icon packages, binding lists and autocomplete, plus using dialog and toast services in Blazor apps.

Analyzes diverse codebases to auto-detect technology stacks, microservices/monorepo traits, and frontend presence, then documents consistent folder conventions, visualization options, and template guidance to keep large projects organized.

Guides hooking Phoenix AI services with OpenInference tracing, covering setup, spans, instrumentation, and production deployment for LLM workflows using Python or TypeScript.

This tool generates a complete, production-ready PHP Model Context Protocol (MCP) server project. It automatically scaffolds the entire structure, including tools, resources, prompts, and comprehensive tests, utilizing the official PHP SDK. It provides a standardized, robust starting point for developers building AI-integrated backend services in PHP.

Generates detailed prompts to document end-to-end application workflows by auto-detecting architectures, stacks, entry points, services, data access, error handling, and tests across .NET, Java/Spring, React, microservices, and other tech stacks.

Generate a TypeSpec API plugin tailored for Microsoft 365 Copilot, wiring REST operations, authentication flows, confirmation cards, and Adaptive Cards into a guided workflow so Copilot can interact with external services securely.

Expert technique for narrowing down Asian drama candidates by leveraging streaming platform and broadcast channel information. Use this when the query mentions services like Netflix, Viki, or Amazon Prime, combined with genre and year details. This method significantly increases search precision, especially when combining platform data with temporal or thematic keywords.

BioServices provides Python wrappers for 40+ bioinformatics services, allowing cross-database queries, identifier mapping, pathway exploration, and sequence or compound research within consistent workflows.