Skill UI

Guides on structuring NUnit test projects, naming fixtures, arranging tests, and applying standard plus data-driven attributes along with assertions and mocking tactics to keep suites clear, independent, and repeatable.

A comprehensive guide covering best practices for writing effective unit tests using the TUnit framework for .NET. Topics include structuring tests using the Arrange-Act-Assert (AAA) pattern, implementing data-driven tests via attributes, utilizing fluent assertion syntax, managing complex test lifecycles (Class/Assembly level hooks), and migrating concepts from xUnit to TUnit. Learn how to write robust, isolated, and advanced tests.

Provides guidance on organizing and writing focused XUnit unit tests, covering project setup, fact/theory patterns, assertions, mocking, and data-driven testing for reliable .NET test suites.

Produces production-ready Dataverse SDK code for Python, showcasing advanced error handling and retries, batch operations, OData query tuning, metadata lifecycle management, configuration/timeouts, cache invalidation, chunked file uploads, and Pandas integrations with references.

Master the art of developing robust and scalable Python applications that interface with Microsoft Dataverse. This skill covers implementing enterprise-grade best practices, including comprehensive error handling using DataverseError hierarchy, advanced retry logic with exponential backoff, and optimizing API calls using OData standards (filtering, selecting, and expanding). It ensures code is clean, maintainable, and production-ready.

Provides Dataverse Python SDK snippets for installation, interactive authentication, CRUD, bulk operations, paging, and optional file uploads aligned with official guidance.

Guides architects through Dataverse SDK use cases by analyzing requirements, designing data models, selecting integration patterns, and producing production-ready Python code with best practices.

Builds production-ready rollout plans covering checks, procedures, verification signals, rollback, and communications for infrastructure or application changes across environments.

Skill that demonstrates injected eval patterns for security testing, simulating a dangerous workflow that executes fetched payloads and unsafe user input handling to help assess protection measures.

Explains Fabric Lakehouse storage, data organization, security, shortcuts, and optimization practices so you can design, build, and monitor Lakehouse solutions leveraging Microsoft Fabric best practices.

This skill provides a comprehensive, step-by-step diagnostic process for debugging failing Power Automate cloud flows. It goes beyond basic status codes provided by the Graph API, offering access to action-level inputs, outputs, and detailed error information to find the true root cause of failures, timeouts, or expression errors. Ideal for diagnosing complex flow logic and connector issues.

This skill serves as the foundational plumbing layer, enabling AI agents to reliably connect with and interact with the Power Automate platform via the FlowStudio MCP server. It provides essential capabilities such as secure authentication setup, reusable helper functions (Python/Node.js), advanced tool discovery (`list_skills`, `tool_search`), and robust response handling, making it the required starting point for building complex automation workflows.