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powerbi-authoring-cli

Automate Power BI semantic model lifecycle in Fabric workspaces via Azure CLI REST API calls.

Updated Jun 1, 2026
Search Tags:#CLI automation#power bi#semantic model#microsoft fabric#deployment pipelines#TMDL#dataset refresh
One-click install
npx skills add https://github.com/weiflycc-cmd/skills-for-fabric --skill powerbi-authoring-cli
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: powerbi-authoring-cli
Source: https://github.com/weiflycc-cmd/skills-for-fabric/tree/main/plugins/fabric-authoring/skills/powerbi-authoring-cli
Command: npx skills add https://github.com/weiflycc-cmd/skills-for-fabric --skill powerbi-authoring-cli

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Manually managing Power BI semantic models in Microsoft Fabric via the web UI is slow, error-prone, and difficult to automate for repeatable deployment, refresh, and authoring workflows. This Skill eliminates that friction by providing programmatic CLI-based control over the full semantic model lifecycle.

Core Features & Use Cases

  • TMDL-Based Semantic Model Authoring: Create, download, and update semantic models using text-based TMDL definition files, enabling version control, collaborative editing, and infrastructure-as-code practices for Fabric workloads.
  • Operational Management: Trigger and monitor dataset refreshes, configure data sources and parameters, manage dataset permissions and security role memberships, and deploy semantic models between deployment pipeline stages.
  • Use Case: A data engineer can use this Skill to pull a semantic model definition from a development workspace, modify its TMDL to add a new measure, deploy the updated model to a production workspace, trigger a refresh, and grant read access to the business analytics team in a single automated workflow.

Quick Start

Use the powerbi-authoring-cli skill to create a new Power BI semantic model in my default Fabric workspace from the TMDL files stored in the ./my-semantic-model folder and trigger a full dataset refresh after the model is successfully deployed.

Frequently Asked Questions about powerbi-authoring-cli

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate Power BI semantic model deployment in Microsoft Fabric without the web UI?▼

You can automate Power BI semantic model deployment using Azure CLI REST API calls to script the full lifecycle. This approach enables programmatic control over creation, updates, and deployment pipeline stage management for Fabric workloads without relying on the UI.

Can I use TMDL files to version control and author Power BI datasets in Fabric?▼

Yes, you can author Power BI semantic models using text-based TMDL definition files. This enables version control, collaborative editing, and infrastructure-as-code practices by downloading, modifying, and updating model definitions programmatically.

What's the best way to trigger a dataset refresh and manage permissions for Power BI semantic models via CLI?▼

The best way to trigger dataset refreshes and manage permissions is through Azure CLI REST API automation. You can orchestrate refreshes, configure data sources, and manage security role memberships and dataset permissions within a single scripted workflow.

Does CLI automation support moving Power BI semantic models between deployment pipeline stages in Fabric?▼

Yes, CLI automation supports moving Power BI semantic models between deployment pipeline stages in Fabric. You can programmatically manage stage transitions, allowing automated deployment from development to production workspaces.

How do I handle authentication and TMDL definition integrity when managing Power BI semantic models via CLI?▼

When managing Power BI semantic models via CLI, built-in guardrails handle authentication audience configuration and TMDL definition integrity. These safeguards ensure secure Azure CLI REST API calls and valid semantic model deployments.

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