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powerbi-modeling

github/awesome-copilot

Power BI semantic modeling assistant for building optimized data models with DAX, relationships, and best practices.

What is powerbi-modeling?

Guides users in designing and optimizing Power BI semantic models following Microsoft best practices. Use when creating measures, designing star schemas, configuring relationships, implementing RLS, or tuning model performance. Connects to active models via MCP tools to analyze structure before providing guidance.

  • Analyzes current Power BI model structure and identifies optimization opportunities
  • Creates and updates DAX measures with proper naming and documentation
  • Designs and validates star schemas with dimension/fact table classification
  • Configures table relationships with correct cardinality and cross-filter direction
  • Implements row-level security (RLS) roles and permissions
  • Provides model quality assessment against best practices checklist

How to install powerbi-modeling

npx skills add https://github.com/github/awesome-copilot --skill powerbi-modeling
Prerequisites
  • Power BI Modeling MCP Server configured and running
  • Active Power BI Desktop instance or Fabric workspace connection
  • Microsoft Learn MCP Server (optional, for researching latest best practices)
Claude Code
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How to use powerbi-modeling

  1. 1.Connect to your Power BI model using the connection_operations tool
  2. 2.Run model analysis to list tables, relationships, and measures
  3. 3.Compare current model against the best practices checklist
  4. 4.Request specific guidance on areas needing improvement (e.g., star schema design, DAX measures)
  5. 5.Apply recommended changes using the appropriate MCP operations (measure_operations, relationship_operations, etc.)
  6. 6.Document tables, columns, and measures with descriptions for clarity

Use cases

Good for
  • Building a new semantic model from scratch with proper star schema design
  • Optimizing an existing model by adding explicit measures and improving relationships
  • Implementing row-level security to restrict data access by user role
  • Creating calculation groups and field parameters for dynamic calculations
  • Documenting tables, columns, and measures with descriptions for report users
Who it's for
  • Power BI data modelers
  • Business intelligence developers
  • Analytics engineers building semantic layers
  • Data architects designing Fabric models
  • Report developers optimizing model performance

powerbi-modeling FAQ

What happens if I don't have the Power BI Modeling MCP Server installed?

The skill requires the Power BI Modeling MCP Server to connect to and modify semantic models. Without it, you can only receive general guidance without analyzing your specific model structure.

Can this skill help me write DAX formulas?

Yes. The skill provides DAX measure guidance and can create measures with proper syntax, naming conventions, and documentation. Reference MEASURES-DAX.md for detailed DAX patterns and best practices.

Does this skill work with both Power BI Desktop and Fabric?

Yes. The skill supports both Power BI Desktop models and Fabric semantic models through the connection_operations tool (Connect, ConnectFabric).

How does the skill assess model quality?

It uses a best practices checklist covering star schema design, naming conventions, documentation, relationships, hidden fields, and explicit measures. It compares your model against these standards and recommends improvements.

Can this skill implement row-level security?

Yes. The skill can create and configure RLS roles using security_role_operations, restricting data access based on user identity. See RLS.md for implementation patterns.

Full instructions (SKILL.md)

Source of truth, from github/awesome-copilot.


name: powerbi-modeling description: 'Power BI semantic modeling assistant for building optimized data models. Use when working with Power BI semantic models, creating measures, designing star schemas, configuring relationships, implementing RLS, or optimizing model performance. Triggers on queries about DAX calculations, table relationships, dimension/fact table design, naming conventions, model documentation, cardinality, cross-filter direction, calculation groups, and data model best practices. Always connects to the active model first using power-bi-modeling MCP tools to understand the data structure before providing guidance.'

Power BI Semantic Modeling

Guide users in building optimized, well-documented Power BI semantic models following Microsoft best practices.

When to Use This Skill

Use this skill when users ask about:

  • Creating or optimizing Power BI semantic models
  • Designing star schemas (dimension/fact tables)
  • Writing DAX measures or calculated columns
  • Configuring table relationships (cardinality, cross-filter)
  • Implementing row-level security (RLS)
  • Naming conventions for tables, columns, measures
  • Adding descriptions and documentation to models
  • Performance tuning and optimization
  • Calculation groups and field parameters
  • Model validation and best practice checks

Trigger phrases: "create a measure", "add relationship", "star schema", "optimize model", "DAX formula", "RLS", "naming convention", "model documentation", "cardinality", "cross-filter"

Prerequisites

Required Tools

  • Power BI Modeling MCP Server: Required for connecting to and modifying semantic models
    • Enables: connection_operations, table_operations, measure_operations, relationship_operations, etc.
    • Must be configured and running to interact with models

Optional Dependencies

  • Microsoft Learn MCP Server: Recommended for researching latest best practices
    • Enables: microsoft_docs_search, microsoft_docs_fetch
    • Use for complex scenarios, new features, and official documentation

Workflow

1. Connect and Analyze First

Before providing any modeling guidance, always examine the current model state:

1. List connections: connection_operations(operation: "ListConnections")
2. If no connection, check for local instances: connection_operations(operation: "ListLocalInstances")
3. Connect to the model (Desktop or Fabric)
4. Get model overview: model_operations(operation: "Get")
5. List tables: table_operations(operation: "List")
6. List relationships: relationship_operations(operation: "List")
7. List measures: measure_operations(operation: "List")

2. Evaluate Model Health

After connecting, assess the model against best practices:

  • Star Schema: Are tables properly classified as dimension or fact?
  • Relationships: Correct cardinality? Minimal bidirectional filters?
  • Naming: Human-readable, consistent naming conventions?
  • Documentation: Do tables, columns, measures have descriptions?
  • Measures: Explicit measures for key calculations?
  • Hidden Fields: Are technical columns hidden from report view?

3. Provide Targeted Guidance

Based on analysis, guide improvements using references:

Quick Reference: Model Quality Checklist

AreaBest Practice
TablesClear dimension vs fact classification
NamingHuman-readable: Customer Name not CUST_NM
DescriptionsAll tables, columns, measures documented
MeasuresExplicit DAX measures for business metrics
RelationshipsOne-to-many from dimension to fact
Cross-filterSingle direction unless specifically needed
Hidden fieldsHide technical keys, IDs from report view
Date tableDedicated marked date table

MCP Tools Reference

Use these Power BI Modeling MCP operations:

Operation CategoryKey Operations
connection_operationsConnect, ListConnections, ListLocalInstances, ConnectFabric
model_operationsGet, GetStats, ExportTMDL
table_operationsList, Get, Create, Update, GetSchema
column_operationsList, Get, Create, Update (descriptions, hidden, format)
measure_operationsList, Get, Create, Update, Move
relationship_operationsList, Get, Create, Update, Activate, Deactivate
dax_query_operationsExecute, Validate
calculation_group_operationsList, Create, Update
security_role_operationsList, Create, Update, GetEffectivePermissions

Common Tasks

Add Measure with Description

measure_operations(
  operation: "Create",
  definitions: [{
    name: "Total Sales",
    tableName: "Sales",
    expression: "SUM(Sales[Amount])",
    formatString: "$#,##0",
    description: "Sum of all sales amounts"
  }]
)

Update Column Description

column_operations(
  operation: "Update",
  definitions: [{
    tableName: "Customer",
    name: "CustomerKey",
    description: "Unique identifier for customer dimension",
    isHidden: true
  }]
)

Create Relationship

relationship_operations(
  operation: "Create",
  definitions: [{
    fromTable: "Sales",
    fromColumn: "CustomerKey",
    toTable: "Customer",
    toColumn: "CustomerKey",
    crossFilteringBehavior: "OneDirection"
  }]
)

When to Use Microsoft Learn MCP

Research current best practices using microsoft_docs_search for:

  • Latest DAX function documentation
  • New Power BI features and capabilities
  • Complex modeling scenarios (SCD Type 2, many-to-many)
  • Performance optimization techniques
  • Security implementation patterns