What problem does it solve? Designing Power BI semantic models that follow Microsoft best practices is difficult: star schema design, relationship cardinality, DAX measure authoring, naming conventions, and row-level security all require specialized knowledge, and mistakes lead to slow, ambiguous, or insecure models. ## Core Features & Use Cases - Model Analysis and Health Checks: Connects to the active Power BI model via the Power BI Modeling MCP server to inspect tables, relationships, and measures before recommending improvements. - Guided Modeling Tasks: Creates and updates DAX measures, configures relationship cardinality and cross-filter direction, implements row-level security roles, and applies naming and documentation conventions. - Performance Optimization: Reduces model size and query time through data type optimization, cardinality reduction, variable-based DAX patterns, and aggregation strategies. - Use Case: A data analyst asks to add a "Total Sales" measure with proper formatting and description, fix a bidirectional relationship causing ambiguous paths, and document all dimension columns — the skill inspects the live model and applies each change through MCP operations. ## Quick Start Connect to my open Power BI model, review its tables and relationships against star schema best practices, and create a formatted Total Sales measure with a description.
