Microsoft-Fabric

Create, update, delete, and refresh Fabric Dataflows Gen2 via write-side CLI against Fabric Items and Connections APIs. Builds mashup.pq + queryMetadata definitions, triggers parameterized refreshes, manages connections, and configures output destinations (Lakehouse, Warehouse, ADX, Azure SQL). Includes preview-driven authoring loop (executeQuery + customMashupDocument). For executing saved queries or reading refresh status, use `dataflows-consumption-cli`. Triggers: "create dataflow", "update dataflow", "delete dataflow", "trigger dataflow refresh", "refresh dataflow", "preview Power Query M", "preview mashup", "preview before save", "iterate dataflow M", "create Fabric data source connection", "create dataflow connection", "bind connection", "list supportedConnectionTypes", "dataflow output destination", "dataflow write to lakehouse", "dataflow write to warehouse", "dataflow write to ADX", "DataDestinations annotation", "author dataflow".

Implement end-to-end Medallion Architecture (Bronze/Silver/Gold) lakehouse patterns in Microsoft Fabric using PySpark, Delta Lake, and Fabric Pipelines. Use when the user wants to: (1) design a Bronze/Silver/Gold data lakehouse, (2) set up multi-layer workspace with lakehouses for each tier, (3) build ingestion-to-analytics pipelines with data quality enforcement, (4) optimize Spark configurations per medallion layer, (5) orchestrate Bronze-to-Silver-to-Gold flows via notebooks. Triggers: "medallion architecture", "bronze silver gold", "lakehouse layers", "e2e data pipeline", "end-to-end lakehouse", "data lakehouse pattern", "multi-layer lakehouse", "build medallion", "setup medallion".

Develops and manages Power BI semantic models across Desktop, PBIP projects, and Fabric Service. Handles: (1) creating new models (Import, DirectQuery, Direct Lake), (2) editing existing models (e.g. measures, tables, columns, relationships), (3) deploying models to Fabric workspaces, (4) working with PBIP project files, (5) refreshing semantic models, (6) configuring data sources and permissions, (7) DAX performance optimization. Supports both Power BI Desktop and Fabric Service development workflows. For read-only DAX queries, use `semantic-model-consumption`. Does NOT handle report layout/visual authoring, workspace administration, or RLS/OLS role membership management. Triggers: "create semantic model", "edit semantic model", "add a DAX measure to semantic model", "refresh semantic model", "set semantic model permissions", "Prepare semantic model for AI/Copilot".

Develop Microsoft Fabric Spark/data engineering workflows and write code in Fabric Notebook cells with intelligent routing to specialized resources. Provides workspace/lakehouse management, notebook code authoring (PySpark, Scala, SparkR, SQL), and routes to: data engineering patterns, development workflow, or infrastructure orchestration. Use when the user wants to: (1) manage Fabric workspaces and resources, (2) write or debug code in notebook cells, (3) use notebookutils, (4) develop notebooks and PySpark applications, (5) design data pipelines, (6) provision infrastructure as code. Triggers: "develop notebook", "data engineering", "workspace setup", "pipeline design", "infrastructure provisioning", "Delta Lake patterns", "Spark development", "lakehouse configuration", "write notebook code", "notebookutils", "notebook cell", "PySpark notebook", "%%sql cell", "%%configure", "fabric notebook", "run notebook", "notebook deployment".

Monitor, inspect, and query saved Fabric Dataflows Gen2 via read-only CLI. List dataflows, decode base64 definitions (mashup.pq, queryMetadata.json, .platform), discover parameters, retrieve refresh status and job history, classify queries by staging, and execute queries against saved dataflows via the read-side `executeQuery` mashup engine (Arrow IPC response). Three executeQuery read modes: (a) execute a persisted query by QueryName, (b) run an ad-hoc read-only customMashupDocument **with no intent to persist**, (c) parse and render Arrow results. For previewing candidate M before persisting via updateDefinition, use `dataflows-authoring-cli`. Triggers: "list dataflows", "inspect dataflow", "decode dataflow definition", "dataflow parameters", "dataflow refresh status", "refresh history", "last refresh status", "dataflow job history", "execute dataflow query", "executeQuery saved query", "executeQuery fetch rows", "ad-hoc dataflow query", "parse Arrow response", "Arrow IPC", "dataflow staging analysis".

Answer business questions by querying Power BI reports and dashboards through the FabricIQ MCP endpoint. Orchestrates: discover Power BI artifacts, inspect report/model schemas, resolve entity values, generate DAX, execute queries. Returns plain-language answers from Power BI semantic models. Use when the user asks a natural-language question about Power BI report or dashboard content (not raw DAX). Triggers: "ask power bi", "PBI question", "discover report", "report data", "dashboard data", "what are the top", "show me the power bi data", "which products sold", "compare sales in report".