powerbi-modeling

SKILL.md

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:

Star schema design: See STAR-SCHEMA.md

Relationship configuration: See RELATIONSHIPS.md

DAX measures and naming: See MEASURES-DAX.md

Performance optimization: See PERFORMANCE.md

Row-level security: See RLS.md

Quick Reference: Model Quality Checklist

Area
Best Practice

Tables
Clear dimension vs fact classification

Naming
Human-readable: Customer Name not CUST_NM

Descriptions
All tables, columns, measures documented

Measures
Explicit DAX measures for business metrics

Relationships
One-to-many from dimension to fact

Cross-filter
Single direction unless specifically needed

Hidden fields
Hide technical keys, IDs from report view

Date table
Dedicated marked date table

MCP Tools Reference

Use these Power BI Modeling MCP operations:

Operation Category
Key Operations

connection_operations
Connect, ListConnections, ListLocalInstances, ConnectFabric

model_operations
Get, GetStats, ExportTMDL

table_operations
List, Get, Create, Update, GetSchema

column_operations
List, Get, Create, Update (descriptions, hidden, format)

measure_operations
List, Get, Create, Update, Move

relationship_operations
List, Get, Create, Update, Activate, Deactivate

dax_query_operations
Execute, Validate

calculation_group_operations
List, Create, Update

security_role_operations
List, 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