Skill UI

A comprehensive toolkit designed to automate core Shopify operations via Rube MCP. It provides structured workflows for managing all key aspects of an e-commerce store, including products (listing, creation), orders (tracking, retrieval), customers, collections, and inventory levels. Utilizes direct tool calls for listing, searching, and bulk operations, making it ideal for integrating complex business logic into automated systems.

This comprehensive guide provides a detailed framework for authoring effective and structured SKILL.md files for AI coding agents. It covers best practices for structuring content, including frontmatter fields, defining natural language triggers, establishing core principles, and incorporating advanced elements like decision trees and verification checklists, ensuring agents receive clear, actionable, and consistent technical guidance.

This comprehensive toolkit automates all major Stripe payment operations, including customer management, creating charges, handling subscriptions, generating invoices, and processing refunds. By leveraging structured workflows through Rube MCP, it provides a unified interface for complex financial processes, ensuring reliable and efficient automation of your billing and payment systems.

Provides patterns and techniques for building robust evaluation loops for AI agents. This skill guides the implementation of self-critique, evaluator-optimizer pipelines, and test-driven refinement workflows. Use it to significantly enhance the accuracy and quality of complex outputs like code, reports, and analyses by implementing structured, iterative improvement cycles (Generate → Evaluate → Critique → Refine).

This skill provides comprehensive command-line interface (CLI) functionality for managing the entire lifecycle of experiments within the Arize platform. Users can list, retrieve metadata, create new experiments from various data files (CSV, JSON, Parquet), and export detailed run results for deep analysis. It supports linking experiments to specific dataset versions, making it essential for structured ML model evaluation and performance comparison workflows.

This comprehensive guide provides step-by-step instructions for setting up a development environment to use AWS CDK (Cloud Development Kit) with Python. It covers installing prerequisites (Node.js, AWS CLI), initializing a CDK project, managing Python dependencies, and mastering the full deployment workflow, enabling users to define and deploy scalable AWS infrastructure as code.

Transforms existing code files into highly effective learning resources by adding context-aware educational comments. Acting as an expert educator, this tool tailors explanations—from foundational concepts for beginners to deep architectural insights for advanced practitioners—while strictly maintaining the original file's structure, encoding, and syntax. Ideal for generating self-documenting, pedagogically rich codebases.

Design, analyze, and refine Azure infrastructure through natural language prompts, generate interactive architecture diagrams locally with bundled scripts, and produce deployable Bicep templates to automate infrastructure-as-code workflows.

This skill analyzes Azure resource groups in depth, identifying all resources, their configurations, and complex interdependencies. It maps relationships—including network connections, data flows, and managed identities—to generate comprehensive, detailed Mermaid architecture diagrams. Use this when you need a clear, structured visualization and full documentation of an Azure environment's topology.

Reviews Python + BigQuery pipelines to flag runaway costs, missing dry-run safeguards, unsafe backfills, write idempotency issues, and monitoring gaps, returning a structured report with exact function/line references for minimal fixes.

Generates a structured Epic architecture specification from a Product Requirements Document, guiding senior architects to capture high-level approaches, layered Mermeid diagrams, features, technical enablers, stack choices, and value estimates for TypeScript/Next.js monorepo projects.

Generates comprehensive Epic-level PRDs for large SaaS initiatives, translating high-level requests into structured goals, journeys, requirements, and value summaries saved for architecture planning.