Skill UI

Provides deep expertise in modern Kotlin patterns, covering structured concurrency via Coroutines and Flow, Multiplatform architecture (KMP), declarative UI using Compose, and server implementation with Ktor. Ideal for building robust, type-safe, and highly maintainable applications across various platforms.

Offers automated AWS Lambda function generator guidance within the AWS Skills domain, producing code/configuration, enforcing cloud best practices, and validating serverless outputs when users request lambda function generator help.

This comprehensive guide provides step-by-step instructions for integrating Langfuse LLM observability into various cloud and serverless environments. It covers best practices for deployment on platforms such as Vercel, AWS Lambda, Google Cloud Run, and self-hosted Docker, ensuring robust tracing and monitoring of entire AI workflows.

A comprehensive guide for installing and configuring the Linear SDK for TypeScript/JavaScript. It details two primary authentication methods: using a personal API key for scripts and server-side tools, and implementing the full OAuth 2.0 flow (including PKCE and token refreshing) for user-facing applications. Essential for integrating Linear functionality into custom software.

Provides production-ready bash templates for Linux admins to automate backups, monitor resources, manage users, and handle security tasks across servers and pen-testing setups.

A comprehensive quick reference guide for troubleshooting and resolving common HTTP errors (4xx, 5xx) encountered when integrating with the MaintainX API. It provides detailed root causes, diagnostic commands (using curl/jq), and specific fixes for various status codes, such as 400 Bad Request, 401 Unauthorized, 429 Rate Limit, and 500 Internal Server Error, ensuring stable application integration.

A comprehensive guide to setting up a local development loop for building and testing MaintainX integrations. This workflow utilizes TypeScript, hot reloading, mock API servers, and automated unit/integration testing. It provides a sandboxed environment for developers to efficiently develop and debug their services.

This mandatory guide provides comprehensive best practices, architectural patterns, and security considerations for building production-ready MCP servers. It serves as the primary reference for developers modifying or creating new server components, including tools, resources, prompts, and widgets, ensuring adherence to industry standards and structured workflows.

Guide for building high-quality MCP servers that let LLMs interact with external APIs via workflow-focused tools, SDKs, validation, and error handling in Python or TypeScript.

This guide details the process of building Model Context Protocol (MCP) servers. These servers are crucial for enabling Large Language Models (LLMs) to interact with external APIs and services, facilitating complex, real-world task completion. It provides comprehensive coverage on architectural planning, choosing appropriate languages (Python, TypeScript, C#), and selecting transport mechanisms (HTTP, stdio) for robust integration within enterprise ecosystems like Azure and Foundry.

Used for building, debugging, and extending MCP servers and clients. This skill implements robust connections between AI systems and external tools/data sources using structured protocols like JSON-RPC 2.0. Expertise includes defining tool schemas (Zod/Pydantic), configuring transport layers (HTTP/SSE/stdio), and scaffolding full-stack projects in TypeScript or Python.

Defines MCP server tooling with file search, query execution, resource endpoints, prompt templates, and transport configurations alongside a client setup example for streamlined project automation.