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magic-etl

Automate Magic ETL dataflow creation, updates, and execution via Domo APIs and CLI.

19|13|Updated Jan 20, 2026
Search Tags:#api#cli#etl#data-pipelines#dataflow#domo#magic-etl
One-click install
npx skills add https://github.com/stahura/domo-ai-vibe-rules --skill magic-etl
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: magic-etl
Source: https://github.com/stahura/domo-ai-vibe-rules/tree/main/skills/transformation/magic-etl
Command: npx skills add https://github.com/stahura/domo-ai-vibe-rules --skill magic-etl

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Automates the management of Magic ETL dataflows in Domo through API and CLI, reducing manual setup, deployment, and lifecycle maintenance.

Core Features & Use Cases

  • Create, update, and execute Magic ETL dataflows via REST API and the Java CLI (domoutil.jar).
  • Export and import complete dataflow definitions as JSON to version, share, and reuse.
  • Define inputs, transforms, and outputs as code to enable repeatable pipelines and automated deployments.

Quick Start

Create a new dataflow via POST /api/dataprocessing/v1/dataflows, then run it with dataflow-run-now and monitor executions via GET requests.

Frequently Asked Questions about magic-etl

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

FAQPage Schema
How do I automate Domo Magic ETL dataflow management via API?▼

Automate Domo Magic ETL dataflow management by using REST API endpoints to create, update, and execute dataflows. You can define inputs, transforms, and outputs as code to enable repeatable pipelines and automated deployments.

Can I export and import Magic ETL dataflow definitions as JSON?▼

Yes, you can export and import complete Magic ETL dataflow definitions as JSON files. This allows you to version, share, and reuse dataflow configurations across different Domo environments or projects.

What do I need to use the Java CLI tool for Domo Magic ETL automation?▼

You need access to Domo Magic ETL REST APIs and the Java CLI tool, domoutil.jar, to operate this automation. These dependencies are required to execute CLI workflows and manage data pipelines in real-world scenarios.

How do I create and run a Magic ETL dataflow from the command line?▼

Create a new dataflow via a POST request to the /api/dataprocessing/v1/dataflows endpoint, then run it using the dataflow-run-now command. You can monitor subsequent executions via GET requests to track pipeline status.

Does this approach support defining ETL transforms and outputs as code?▼

Yes, defining inputs, transforms, and outputs as code is a core feature. This approach enables repeatable data pipelines and automated deployments, reducing manual setup and lifecycle maintenance for Magic ETL dataflows.

Why automate Magic ETL dataflow lifecycle maintenance instead of using the UI?▼

Automating Magic ETL dataflows via API and CLI reduces manual setup, deployment, and lifecycle maintenance. It allows you to version dataflow definitions as JSON and guide CLI workflows to streamline real-world data pipeline operations.

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