Skill UI

This skill facilitates the deployment of WebContainer applications to popular hosting platforms like Vercel and Netlify. It handles complex configuration, including setting necessary COOP/COEP security headers. It is essential when developing modern web projects using WebContainers or the StackBlitz SDK, ensuring proper and secure deployment.

This module provides core use case abstractions for interacting with a standardized language catalog. It offers two key functionalities: retrieving a specific language entry using its unique code (GetLanguageByCodeUseCase), and listing all available language entries (ListLanguagesUseCase). These abstractions ensure consistent and structured data access across the application.

This powerful tool compares identical tables across two SQL Server instances (e.g., Production vs. Staging). It efficiently detects missing rows, extra columns, schema drifts, and data mismatches. Leveraging Python and Apache Arrow for fast columnar data transfer, it provides a comprehensive reconciliation report, making it essential for data migration validation and ETL verification.

This comprehensive guide details the programmatic management of semantic model refreshes using the Power BI Enhanced Refresh REST API and Fabric CLI. It covers the entire refresh lifecycle, including resolving model IDs, validating baseline data, triggering various refresh types (full, data-only, calculate), monitoring status, and performing robust post-refresh validation. Essential for automating ETL and data pipeline processes in a modern data platform.

This skill generates a complete and detailed specification for an ETL/ELT data pipeline. It covers everything from source systems, transformation logic, and data quality rules to destination data warehousing and required SLAs. Use this when planning data ingestion, designing complex data flows, or needing comprehensive architecture documentation for engineering handoff.

Run arbitrary PySpark or pure Python code directly on Fabric Spark compute using the Livy API. These sessions are ephemeral, meaning no notebook artifacts are created or persisted, making it ideal for automated ETL processes, programmatic data transformations, or agent-driven compute workflows. Provides full read/write access to lakehouse Delta tables via Spark SQL.