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dataflows-authoring-cli

Automate Fabric Dataflows Gen2 lifecycle management from the command line.

952|267|Updated Feb 17, 2026
Search Tags:#cli#authoring#bindings#fabric#lro#dataflows
One-click install
npx skills add https://github.com/microsoft/skills-for-fabric --skill dataflows-authoring-cli
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: dataflows-authoring-cli
Source: https://github.com/microsoft/skills-for-fabric/tree/main/plugins/fabric-authoring/skills/dataflows-authoring-cli
Command: npx skills add https://github.com/microsoft/skills-for-fabric --skill dataflows-authoring-cli

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Create, update, delete, and refresh Fabric Dataflows Gen2 from the command line, enabling deterministic lifecycle management of dataflows, their mashup and metadata, and connected resources.

Core Features & Use Cases

  • Create new dataflows in a target workspace with a descriptive display name and metadata.
  • Update definitions (mashup.pq, queryMetadata.json, and .platform) and bind connections using the stringified composite connectionId format that combines ClusterId and DatasourceId.
  • Preview changes against bound connections with executeQuery, validate results, persist via updateDefinition, and trigger a refresh to publish changes.
  • Extend workflows to include output destinations (Lakehouse, Warehouse, ADX, Azure SQL) via DataDestinations as part of advanced scenarios.

Quick Start

Use the CLI to bootstrap a dataflow, bind connections, and trigger a refresh.

Frequently Asked Questions about dataflows-authoring-cli

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

FAQPage Schema
How do I create and update Fabric Dataflows Gen2 from the command line?▼

You can author Fabric Dataflows Gen2 via CLI by creating dataflows in a target workspace, updating definitions like mashup.pq and queryMetadata.json, binding connections, and triggering refreshes for deterministic lifecycle management.

How do I bind connections when authoring dataflows via CLI?▼

Binding connections requires the stringified composite connectionId format that combines ClusterId and DatasourceId, which validates connections and integrates with the Fabric CLI before you preview or persist dataflow updates.

Can I preview M query changes against bound connections before publishing a dataflow?▼

Yes, you can preview changes using executeQuery against bound connections, validate the results, persist the updates via updateDefinition, and trigger a refresh to publish the changes to the dataflow.

Does Fabric Dataflows Gen2 CLI support output destinations like Lakehouse and Azure SQL?▼

Yes, you can extend workflows to include output destinations such as Lakehouse, Warehouse, ADX, and Azure SQL via DataDestinations as part of advanced dataflow authoring scenarios.

What files are required to update a Fabric Dataflow Gen2 definition?▼

Updating a dataflow definition requires modifying mashup.pq, queryMetadata.json, and .platform parts, which together manage the mashup logic, query metadata, and connected resource configuration.

How does long-running operation polling work when refreshing dataflows via CLI?▼

The CLI handles long-running operations by performing LRO polling after triggering a dataflow refresh, ensuring the operation completes successfully before returning control to the user.

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