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Skills ZICQ category:Documents powerbi-modeling

Powerbi Modeling

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.

9930 installs

Official URL:skills.sh

What this skill does

Intro in this page language first. The official description stays in its original wording; we do not rewrite SKILL.md.

What it does

Power BI semantic modeling assistant for building optimized data models

When to use it

This Skill

How agents load it

Per Agent Skills progressive disclosure: name and description load at startup (~100 tokens); the full SKILL.md body loads when the skill activates; scripts/, references/, and assets/ load only as needed. This file's sections: Power BI Semantic Modeling; When to Use This Skill; Prerequisites; Required Tools; Optional Dependencies; Workflow. It includes spec-recommended sections: step-by-step instructions.

File analysis

File analysis: besides SKILL.md, the body references references/STAR-SCHEMA.md, references/RELATIONSHIPS.md, references/MEASURES-DAX.md, references/PERFORMANCE.md, references/RLS.md. Those resources load on demand.

Power BI Semantic ModelingWhen to Use This SkillPrerequisitesRequired ToolsOptional DependenciesWorkflow1. Connect and Analyze First2. Evaluate Model Health3. Provide Targeted GuidanceQuick Reference: Model Quality ChecklistMCP Tools ReferenceCommon Tasks

Source category:skills.sh agent-skill

SKILL.md & Agent activation

Official spec ↗
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.
  1. DiscoverThe client exposes names and descriptions to the agent.
  2. ActivateYour request or the task context selects the skill and loads its instructions.
  3. Load resourcesReferenced scripts, documentation and assets are used when needed.
Files referenced by the instructions · 5
  • references/STAR-SCHEMA.md
  • references/RELATIONSHIPS.md
  • references/MEASURES-DAX.md
  • references/PERFORMANCE.md
  • references/RLS.md

These paths are extracted from the text. Check the upstream package to verify the files exist.

Invocation syntax and available tools depend on your Agent client. Client integration guide ↗

Install this skill

Skills CLI ↗

Choose the target agent and installation scope, keep referenced package files, then verify the skill appears in the client's catalog.

This skill references supporting files. Retrieve the complete directory from the source; copying SKILL.md alone may leave missing dependencies.

Ask your Agent to install

Copy these instructions to a compatible agent and confirm the target directory matches your client.

Install the agent skill "powerbi-modeling" into my project. The full SKILL.md and official description are at https://zicq.com/en/skills/skl-e61234a11cf2b4f8-Powerbi-Modeling.html
Save it as .cursor/skills/powerbi-modeling/SKILL.md or .claude/skills/powerbi-modeling/SKILL.md and keep the frontmatter name and description exactly as-is.
This skill also ships scripts/, references/, or assets/ — fetch the whole folder from https://github.com/github/awesome-copilot instead of creating only a SKILL.md.

Full package on GitHub ↗

Install from the terminal · Skills CLI

Requires Node.js and npx. First inspect the repository's skill list to confirm the name.

npx skills add 'https://github.com/github/awesome-copilot' --list

npx skills add 'https://github.com/github/awesome-copilot' --skill 'powerbi-modeling'

The CLI lets you choose the agent interactively. The default scope is the project; use -g for user scope. Confirm package availability with the discovery command, then use npx skills list to inspect installed skills.

Readable layout

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

| 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

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