Skill UI

Leverage AI-powered exploratory testing to thoroughly audit web applications and verify functionality. This skill simulates user interaction, detecting complex bugs, validating critical flows (like checkout or login), and checking accessibility compliance. Use it proactively after development to ensure quality before deployment.

A comprehensive guide detailing how to configure and manage GitHub's secret scanning feature. This skill covers enabling Secret Protection, setting up push protection to block leaked credentials before they reach the repository, defining custom regex patterns, and providing workflows for triaging alerts and resolving blocked pushes (including using git rebase or bypassing protections). Essential for maintaining secure code repositories and complying with security standards.

This skill provides comprehensive guidance for building and refining applications, plugins, and function-calling flows using the Semantic Kernel framework. It supports multiple languages, including .NET and Python. Guidance emphasizes consulting the latest official documentation, adhering to best practices (like async patterns and strong typing), and correctly handling multi-ecosystem development.

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 skill safely randomizes the order of repetitive JSON objects within an array without corrupting the data or breaking the JSON syntax. It acts as a data engineer, rigorously validating the input schema (checking for property consistency and lack of nesting) before performing the shuffle. It ensures data integrity is maintained while reordering records, making it ideal for testing, simulation, or data preparation workflows.

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 expert tool guides users through rigorous statistical analysis, specializing in A/B testing, hypothesis testing, and interpreting experimental results. It helps define sample sizes, executes appropriate tests (Z-test, T-test, Chi-square), and critically distinguishes between 'statistical significance' and 'practical significance' to ensure data-driven decision-making for product and business strategy.

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 specialist simulates the role of an App Store reviewer, auditing iOS source code and metadata against Apple's strict guidelines. It systematically identifies potential compliance risks, technical vulnerabilities, monetization gaps (IAP/Subscriptions), and critical UX shortcomings, delivering a prioritized risk register for fast approval.

This skill provides comprehensive CLI commands to manage AI integrations within Arize. It covers listing, creating, and retrieving configurations for various major LLM providers (including OpenAI, Anthropic, Gemini, AWS Bedrock, etc.), ensuring secure credential storage and proper setup for model evaluation and usage.

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.