Skill UI

This comprehensive guide serves as a decision flowchart for developers using Claude Code. It details when to use specific slash commands (/plan, /compact, /loop), select specialized agents (planner, code-reviewer, build-error-resolver), or invoke workflow skills (e2e-testing, tdd-workflow). It helps users select the optimal tool combination for complex tasks across the entire software development lifecycle, including feature planning, bug fixing, testing, and architectural design.

This skill performs a proactive, comprehensive audit to quantify the business and regulatory impact of a potential data breach before it occurs. It inventories sensitive data (PII, PHI, PCI-DSS), traces complex data flows through the codebase, identifies all exposure vectors, and calculates the 'blast radius.' The output provides law-sourced figures (e.g., GDPR, CCPA, HIPAA fine maximums) alongside heuristic risk estimates, guiding proactive hardening roadmaps for compliance and security.

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 guide details how to use the `go.uber.org/dig` library for dependency injection in Go. It covers advanced concepts like constructor registration (`Provide`), service invocation (`Invoke`), parameter grouping (`dig.In`), result structuring (`dig.Out`), named dependencies, and value groups. It is essential for wiring up application graphs at startup in complex Go applications.

A robust application framework for Go, built on the uber-go/dig container. It provides advanced features essential for long-running services, including structured dependency injection, explicit lifecycle hooks (OnStart/OnStop), modular composition, and signal-aware graceful shutdown handling. Ideal for building robust daemons, HTTP servers, and background workers.

This skill automates the process of making any codebase ready for advanced AI assistance. It analyzes your repository structure, review patterns, and stack details to generate essential configuration files, including AGENTS.md, copilot-instructions.md, CI workflows, and issue templates. Use this when setting up a new project or integrating advanced AI tooling into your existing development workflow.

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.