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213yuka
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fabric-demo-builder

Provision Fabric demo environments in GHCP via REST API and MCP tools.

Updated Mar 10, 2026
Search Tags:#demo#fabric#rest-api#lakehouse#semantic-model#data-agent
One-click install
npx skills add https://github.com/213yuka/fabric-ghcp-demo-template --skill fabric-demo-builder
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: fabric-demo-builder
Source: https://github.com/213yuka/fabric-ghcp-demo-template/tree/main/.github/skills/fabric-demo-builder
Command: npx skills add https://github.com/213yuka/fabric-ghcp-demo-template --skill fabric-demo-builder

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Microsoft Fabric のデモ環境を GHCP 内で構築するスキル。Fabric MCP の OneLake ツール + Fabric REST API を用い、Lakehouse の作成からデータ投入・Data Agent の構築までを一連の自動化で実行します。全て GHCP 内で完結し、データモデルはスタースキーマで設計され、CSV は変換済みで REST API Tables_LoadTable によって Delta へ変換されます。Semantic Model は REST API を用いて TMSL 形式（model.bim）の定義付きで一発作成します。updateDefinition や TMDL は使用しません。MCP ツールに無い API はターミナルから Fabric REST API を直接呼び出します。

Core Features & Use Cases

  • end-to-end Fabric demo provisioning inside GHCP (Lakehouse, Data Ingestion, Semantic Model, Data Agent)
  • star-schema data model design with pre-converted CSVs (ETL is not required)
  • REST API and MCP orchestration to automate workspace creation, data load, model and agent setup
  • 代表質問セットを用いた Data Agent の動作検証とデモの再現性確保
  • すべての作成・設定を GHCP 内で完結させ、ポータルでの手動設定を不要とする

Quick Start

Run /fabric-demo-create in GHCP to start the end-to-end Fabric demo environment provisioning.

Frequently Asked Questions about fabric-demo-builder

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

FAQPage Schema
How do I automate Microsoft Fabric demo environment provisioning end-to-end?▼

You automate Fabric demo environment provisioning by orchestrating workspace creation, Lakehouse data ingestion, star-schema Semantic Model setup, and Data Agent configuration via Fabric REST API and MCP tools inside GHCP.

Does this approach require manual ETL for loading CSVs into the Fabric Lakehouse?▼

No ETL is required for loading CSVs into the Fabric Lakehouse. Pre-converted CSVs are loaded directly and automatically transformed into Delta format using the Fabric REST API Tables_LoadTable operation.

Can I create a Semantic Model in Fabric using TMSL definitions via REST API?▼

Yes, you can create a Semantic Model in Fabric using TMSL definitions. The process uses the REST API with a model.bim file to generate the semantic model in one operation without using updateDefinition or TMDL.

How do I set up and validate a Fabric Data Agent for AI-driven querying?▼

You set up and validate a Fabric Data Agent by orchestrating its configuration via REST API and running a representative question set. This ensures the AI-driven data querying functions correctly and maintains demo reproducibility.

What is the best way to design a star-schema data model for a Fabric Lakehouse demo?▼

The best way to design a star-schema data model for a Fabric Lakehouse demo is to automate the modeling step using REST API with TMSL definitions, ingesting pre-converted CSVs to structure tables for scenarios like retail analytics or manufacturing quality.

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