Skill UI

This comprehensive guide details how to construct a complete, robust Model Context Protocol (MCP) server using TypeScript and the specialized v2 SDK. It covers all aspects of Node.js project setup, selecting appropriate transport layers (HTTP or stdio), implementing complex, schema-validated tools, and integrating resources, resulting in a highly type-safe AI backend service.

This skill guides the setup of isolated development environments using Git worktrees and best practices. It ensures that all development work is kept separate from the main repository branch, preventing accidental commits or state corruption. The process involves checking the current worktree status, creating new isolated environments (prioritizing native tools), installing project dependencies (e.g., Node, Python, Go), and running essential baseline tests to guarantee a clean, stable starting state.

Provides comprehensive guidance on determining the optimal scaling strategy for Qdrant vector databases. Covers when to transition from vertical to horizontal scaling, how to select the right number of nodes and shards, and best practices for setting replication factors to ensure zero-downtime operation and fault tolerance. Also details proper shard management and common scaling pitfalls to avoid.

PyTorch Geometric is a standard library for Graph Neural Networks built on PyTorch. It supports node, link, and graph classification, message passing algorithms like GCN and GAT, heterogeneous graphs, and neighbor sampling. Ideal for building scalable GNN models with custom datasets and transforms.

This comprehensive guide provides minimal working examples for key Adobe APIs: Firefly AI image generation, PDF content extraction, and Photoshop background removal. It serves as a practical quickstart for developers starting new Adobe integrations, testing API connectivity, or learning basic API calling patterns using TypeScript and Node.js.

A comprehensive guide for integrating the Algolia JavaScript v5 client into Node.js/TypeScript projects. It covers proper installation, secure management of Application IDs and API keys (Admin vs. Search-Only), and best practices for client initialization, ensuring robust and safe search functionality implementation.

This guide provides comprehensive troubleshooting for common issues encountered when converting Figma designs to code using the Anima SDK. It covers authentication failures (Figma/Anima tokens), specific node/file lookup errors, code rate limits, and output quality problems, helping developers ensure accurate and robust code generation.

A comprehensive reference architecture detailing how to automate Apple Notes on macOS. Since there is no public REST API, this system relies on a layered approach using Node.js, JXA scripting via osascript, local SQLite caching, and FSEvents polling. It outlines best practices for creating robust, local automation solutions for note management and data export.

This guide provides comprehensive instructions for setting up the AssemblyAI SDK in both Node.js and Python environments. It covers package installation, secure API key management using environment variables, and client initialization for utilizing transcription and streaming services.

This guide provides comprehensive steps to install and configure authentication for the BambooHR REST API. It utilizes HTTP Basic Authentication, requiring users to set up environment variables with their API key and company domain. The content includes setup instructions for Node.js and Python, along with full code examples for verifying a successful connection and retrieving employee directory data.

Collects comprehensive diagnostic evidence for Canva Connect API troubleshooting. This bundle checks API connectivity, validates OAuth tokens, monitors rate limits, and captures environment details (OS, Node version, etc.). It is essential for preparing detailed support tickets when encountering persistent API issues.

Automate the deployment of CAST AI across various multi-cloud Kubernetes clusters, including EKS, GKE, and AKS. This module uses Terraform Infrastructure as Code (IaC) patterns to reliably configure necessary components like IAM roles, node autoscaling policies, and cluster resources, ensuring standardized onboarding across different cloud environments.