Agent skill · Data & Analytics

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.

GitHub68,948★ · +463/wk · 2 repos on radarProfile →
copilotMIT
Install
npx skills add github/awesome-copilot --skill powerbi-modeling --agent copilot

Same command for any agent — swap --agent for claude-code, codex, cursor.

Facts
Files in the skill folder: 6
SKILL.md size: 6 KB
Bundled scripts: none
Path: skills/powerbi-modeling/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 37,432 · +281 this week
Language: Python

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the 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 M

What's inside
Steps it walks through
  1. When to Use This Skill
  2. Prerequisites
  3. Required Tools
  4. Optional Dependencies
  5. Workflow
  6. 1. Connect and Analyze First
  7. 2. Evaluate Model Health
  8. 3. Provide Targeted Guidance
  9. Quick Reference: Model Quality Checklist
  10. MCP Tools Reference
  11. Common Tasks
  12. Add Measure with Description
  13. Update Column Description
  14. Create Relationship
Ships with 5 files
  • references/MEASURES-DAX.md
  • references/PERFORMANCE.md
  • references/RELATIONSHIPS.md
  • references/RLS.md
  • references/STAR-SCHEMA.md
More from awesome-copilot
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About this skill
What does the powerbi-modeling skill do?

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.

How do I install it?

Run `npx skills add github/awesome-copilot --skill powerbi-modeling --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From github/awesome-copilot, a repository with 37,432 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going