Skill UI

A comprehensive guide for building, reviewing, and optimizing GraphQL APIs in Golang. This skill covers best practices including robust schema design (nullability, pagination), proper resolver separation, and critical performance optimizations like using DataLoaders to prevent N+1 query issues. Ideal for engineers working with gqlgen or graphql-go.

This domain-agnostic skill ranks impediments, risks, and gaps by using a specialized value-stream scoring model. It evaluates countermeasures based on four criteria: Return on Investment (ROI), Cost to Implement, Ease of Deployment, and Risk Factor. A proprietary formula calculates a final Priority score (1-100), allowing users to quickly determine the optimal sequence for remediation, improvement backlogs, or triage items.

This tool analyzes and refactors code to detect and correct anemic domain models. It enforces rich domain modeling patterns (Entities, Value Objects, Aggregates, Domain Events), improving encapsulation and business logic ownership. Use it when validating, reviewing, or refactoring core domain logic to ensure adherence to Domain-Driven Design (DDD) principles.

This tool reads your local GitHub Copilot CLI conversation history using the specialized `vardoger` CLI. It analyzes your behavioral patterns, coding conventions, and usage style to generate a personalized instructions block. This block is written directly to your local Copilot configuration file, allowing the assistant to adapt its guidance and suggestions specifically to your unique habits and preferences. The process runs entirely offline, ensuring maximum privacy.

This skill performs comprehensive, feature-level integration validation after all associated development tasks are implemented. It goes beyond checking individual tasks to ensure cross-task consistency, full test suite passage, and complete specification coverage. It validates data flow, architectural adherence, and performs critical security scans for residual issues (e.g., TODOs, hardcoded secrets), providing a holistic GO/NO-GO assessment for deployment. Use this skill as a final quality gate to verify that the completed feature set respects the designed boundaries and dependencies end-...

A comprehensive guide for connecting resource-constrained microcontrollers (like Arduino) to Azure IoT Hub and IoT Edge. It provides structured patterns for secure provisioning, handling intermittent networks (store-and-forward), robust telemetry transmission (MQTT over TLS), and implementing local edge decision-making for industrial and field deployments.

This skill guides users through building comprehensive Smart City and IoT solutions on the Azure platform. It covers the entire solution lifecycle, from initial high-level requirements and defining city domains (e.g., traffic, energy) to designing robust, scalable architectures. Outputs include detailed reference architectures, security checklists, cost strategies, and phased implementation roadmaps for enterprise deployment.

This skill guides the end-to-end development, implementation, and validation of production-ready Python modules for Azure IoT Edge. It covers critical aspects including telemetry processing, protocol adaptation (Modbus, OPC-UA), local inference, and ensuring robust, secure edge-to-cloud messaging under variable network conditions.

This skill analyzes your entire codebase to ensure it is optimized for AI contributions and developer tooling. It automatically generates essential configuration files such as `AGENTS.md`, Copilot instructions, CI workflows, and customizable issue templates. It learns from your existing PR review patterns to tailor the setup precisely to your project's stack. Use it when you need to prepare a repository for advanced AI-assisted development.

This advanced code reviewer analyzes your codebase through the principles of 12 classic software engineering books (e.g., Clean Code, DDIA, Mythical Man-Month). It detects conceptual flaws, design smells, tight coupling, missing abstractions, and architectural risks—issues that standard linters and basic AI tools often miss. Essential for major refactoring and pre-design validation.

This skill performs a rigorous, 5-dimension expert critique on any digital artifact, such as landing pages, presentations, or prototypes. It systematically evaluates five critical areas—Philosophy, Visual Hierarchy, Detail Execution, Functionality, and Innovation—scoring each 0-10. The output is a comprehensive, evidence-backed HTML report providing actionable insights, a radar chart, and prioritized lists (Keep/Fix/Quick-wins) to guide systemic design improvements.

This skill creates a comprehensive, three-column documentation page in pure HTML. It is ideal when the brief requires a professional "guide," "tutorial," or "API reference." It includes structured elements like a sticky left navigation sidebar, a main article body, and a dynamic right Table of Contents, ensuring technical content is highly readable and navigable.