Skill UI

A comprehensive workflow designed to transition machine learning models from experimental notebooks to reliable, production-grade systems. It enforces best practices including data contract management, reproducible training pipelines, rigorous model evaluation gates, secure deployment strategies, and continuous monitoring/rollback capabilities. Essential for any team moving beyond proof-of-concept ML.

This skill reads a detailed, multi-step plan document (e.g., PRD, RFC) and automatically decomposes it into individual, actionable steps. It then generates ready-to-paste, structured agent chains using a predefined catalogue of specialized AI agents, allowing users to execute complex workflows without manually composing prompts.

Provides comprehensive architectural patterns for building cloud-native, event-driven microservices using Quarkus 3.x. It covers RESTful API design (JAX-RS), service layering, message queuing with Apache Camel/RabbitMQ, and data persistence via Hibernate Panache. The guide details advanced topics like asynchronous processing, custom logging context, and implementing complex business workflows in Java.

A comprehensive guide for implementing Test-Driven Development (TDD) for Quarkus 3.x services. It achieves high code coverage (80%+) and is optimized for event-driven architectures using Apache Camel. Use this guide when adding new features, fixing bugs, or refactoring services, especially those involving REST endpoints, asynchronous processing, or message queues.

A comprehensive technical and aesthetic guide for building a modern, high-contrast user interface. This system defines foundational constraints, including color tokens, typography scales, and spacing grids, while rigorously ensuring WCAG 2.2 AA accessibility standards. It provides structured rules for component states, interactions, and development workflow to ensure consistency and superior user experience.

This skill functions as an expert guide for creating comprehensive, implementation-ready design systems. It covers foundational elements like color tokens, typography, and spacing, while strictly adhering to accessibility standards (WCAG 2.2 AA) and defining structured workflows for designers and engineers. Ideal for establishing robust, scalable, and aesthetically premium UI guidelines.

Acts as an expert guide for generating comprehensive, implementation-ready design system documentation. It enforces strict best practices covering visual foundations, component anatomy, accessibility standards (WCAG 2.2 AA), and structured writing workflows, ensuring consistency and clarity for engineering and design teams.

Skill Scout is a meta-skill designed to prevent the duplication of existing workflows. Before building a new skill, it systematically searches local environments, market places, GitHub, and the wider web to identify the closest match. It analyzes intent, vets external sources, ranks results, and presents clear options (Use, Fork, Create) to guide the user to the optimal solution.

This comprehensive guide establishes the standards for a modern, minimalist, and highly functional design system. It defines foundational elements like typography, color tokens, and spacing scales, while strictly adhering to WCAG 2.2 AA accessibility. It provides structured workflows, detailed component rules, and quality gates for both designers and engineers to ensure consistent, usable, and aesthetically pleasing product experiences.

A specialized assistant designed to navigate and accurately retrieve commands and parameters from the offline Alibaba Cloud CLI Chinese documentation mirror. It enforces a strict, hierarchical workflow: first consulting quick usage guides, then checking the main index, and finally drilling down to specific chapter pages. This structured approach ensures all provided information is accurate, evidence-based, and highly relevant to the user's intent.

A comprehensive guide for designing and implementing robust Infrastructure as Code (IaC) using Terraform or OpenTofu. Covers module hierarchy design, best practices for naming conventions, structuring multi-environment pipelines, advanced testing strategies (native tests, Terratest, static analysis), and integrating security scanning (trivy, checkov) into CI/CD workflows.

This guide provides a comprehensive framework for authoring new, structured AI agent skills. It details a three-phase workflow, including gathering requirements, drafting the main instructions (SKILL.md), and ensuring optimal structure. It emphasizes best practices for descriptions, scripting, and file splitting to improve agent reliability and usability.