Skill UI

This is the Azure Resource Manager SDK for .NET, designed to streamline the deployment and management of Weights & Biases (W&B) ML experiment tracking instances directly through Azure Marketplace. It allows developers to programmatically create, configure, and manage W&B environments, including setting up marketplace details, managing admin users, configuring Single Sign-On (SSO), and ensuring robust ML observability within an Azure ecosystem. Ideal for MLOps pipelines.

This SDK provides the management plane capabilities for Azure Cosmos DB within the .NET ecosystem. It allows developers to programmatically provision and manage core infrastructure resources, such as Cosmos DB accounts, databases, containers, throughput settings, and perform resource lifecycle operations using Azure Resource Manager (ARM). It is designed for infrastructure automation and setup tasks.

This skill is designed to execute complex, structured workflows and actions based on a defined overview. It facilitates systematic process completion and adherence to scope. Users must ensure the task precisely matches the skill's scope, and remember that the output is not a substitute for manual validation or expert review.

A comprehensive, multi-phase workflow designed for creating production-ready Bash scripts. This guide covers the entire development lifecycle, including defensive pattern implementation, structured error handling (traps, retry logic), logging strategies, rigorous unit testing using Bats, and professional documentation. Ideal for system administration, CI/CD automation, and core DevOps scripting.

This comprehensive guide details how to utilize the Bun runtime for modern, high-performance JavaScript and TypeScript development. It covers everything from initial setup and project scaffolding to advanced package management, running code, and leveraging built-in APIs like file system operations. It is designed for developers migrating from Node.js seeking superior speed and native tooling.

Designs and executes chaos experiments, failure-injection frameworks, and game days for distributed systems, providing runbooks, manifests, rollback plans, and continuous resilience automation in CI/CD.

A sophisticated, two-stage system designed to capture and internalize user corrections and learnings during ongoing conversations. It automatically detects patterns (e.g., "use X instead of Y") and queues them. Users can manually review and apply these learnings to a persistent knowledge base (CLAUDE.md), ensuring the AI continuously improves its knowledge and adherence to specific user context for future sessions.

This skill provides comprehensive guidance and established patterns for managing and maintaining Windows 11 operating systems. It is designed to assist users in performing routine system updates, troubleshooting issues, and general system administration tasks within a Windows 11 environment, ensuring system stability and optimal performance.

This skill provides comprehensive guidelines based on Clean Code principles, transforming merely functional code into highly readable, maintainable, and robust software. It covers best practices for naming conventions, function design (small, single responsibility), error handling (exceptions over return codes), formatting, and adhering to Test-Driven Development (TDD). Use this skill when writing new features, reviewing pull requests, or refactoring legacy systems to improve overall code quality.

Expert guide for designing robust, scalable, and resilient backend systems. Covers modern patterns including Microservices, Event Sourcing, CQRS, and advanced API contracts (REST, GraphQL, gRPC). Specializes in defining service boundaries, implementing distributed transactions (Saga), and integrating comprehensive security measures like OAuth 2.0 and mTLS.

Chroma is an open-source, AI-native embedding database designed for building sophisticated LLM applications. It allows users to store high-dimensional embeddings and associated metadata, facilitating powerful vector search and full-text filtering. Ideal for implementing Retrieval-Augmented Generation (RAG) systems, semantic search, and document retrieval in local or self-hosted environments, making it perfect for open-source AI projects and prototyping.

Provides expert guidance on designing, implementing, and optimizing cutting-edge computer vision pipelines. Expertise spans real-time object detection (YOLO26), advanced promptable segmentation (SAM 3), and leveraging Vision Language Models (VLMs) for complex visual reasoning. Ideal for building high-performance systems in robotics, autonomous vehicles, and industrial inspection, including 3D reconstruction and edge deployment optimization.