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patrikborosch
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dataflows-authoring-cli

Automate Microsoft Fabric Dataflows Gen2 lifecycle via Azure CLI and REST API.

14|3|Updated Mar 13, 2026
Search Tags:#fabric#rest-api#data-engineering#azure-cli#power-query#dataflows
One-click install
npx skills add https://github.com/patrikborosch/AnalyticsPlatformAgents --skill dataflows-authoring-cli-patrikborosch
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: dataflows-authoring-cli
Source: https://github.com/patrikborosch/AnalyticsPlatformAgents/tree/main/creator/skills/dataflows-authoring-cli
Command: npx skills add https://github.com/patrikborosch/AnalyticsPlatformAgents --skill dataflows-authoring-cli-patrikborosch

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Managing Microsoft Fabric Dataflows Gen2 through the web UI is slow, repetitive, and difficult to integrate into automated data engineering pipelines. This Skill eliminates manual toil by providing a complete CLI-driven authoring workflow for creating, updating, previewing, and refreshing dataflows, including connection management and output destination configuration.

Core Features & Use Cases

  • Full CRUD Operations: Create, read, update, and delete Fabric Dataflows Gen2 via the Azure CLI against the Fabric REST API.
  • Connection Lifecycle Management: Discover, create, validate, and bind Fabric connections to dataflows, including ClusterId resolution for composite binding.
  • Preview-Driven Authoring: Evaluate candidate Power Query M documents via the executeQuery endpoint before persisting changes, catching syntax and credential errors early.
  • Output Destinations: Configure dataflows to write results to Lakehouse tables or files, Warehouse, Azure Data Explorer, or Azure SQL using DataDestinations annotations.
  • Robust Error Handling: Includes long-running operation polling patterns, connection validation pre-refresh checks, and troubleshooting guides for common API failures.

Quick Start

Use the dataflows-authoring-cli skill to create a new Fabric dataflow named "SalesETL" in the "analytics-prod" workspace that writes transformed sales data to the "SalesLakehouse" Lakehouse table.

Frequently Asked Questions about dataflows-authoring-cli

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

FAQPage Schema
How do I automate Fabric Dataflows Gen2 creation using the Azure CLI?▼

You can automate Fabric Dataflows Gen2 creation by sending requests to the Fabric REST API via the Azure CLI, using base64 encoding for definition parts and jq to parse JSON responses for programmatic dataflow lifecycle management.

Can I preview a Power Query M script before saving a Fabric dataflow?▼

Yes, you can preview Power Query M scripts by calling the executeQuery endpoint, which evaluates the candidate M document to catch syntax and credential errors early before persisting changes to the dataflow.

How do I configure a Fabric dataflow to write output to a Lakehouse or Warehouse?▼

You configure dataflow output destinations by applying DataDestinations annotations during creation or update, directing transformed results to Lakehouse tables, Lakehouse files, Warehouse, Azure Data Explorer, or Azure SQL.

What do I need to manage Fabric dataflow connections programmatically?▼

Managing Fabric connections programmatically requires the Azure CLI to discover, create, validate, and bind connections to dataflows, including resolving the ClusterId for composite connection binding.

Why does my Fabric dataflow refresh fail after updating it via the REST API?▼

Dataflow refresh failures often stem from unvalidated connections or incomplete long-running operation polling, so you should run connection validation pre-refresh checks and ensure LRO polling patterns complete successfully.

Does dataflows-authoring-cli support deleting a Fabric dataflow through the command line?▼

Yes, the dataflows-authoring-cli skill supports full CRUD operations, allowing you to delete Fabric Dataflows Gen2 directly through Azure CLI commands targeting the Fabric REST API.

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