Plugin check: Run node "${CLAUDE_PLUGIN_ROOT}/scripts/check-version.js" — if it outputs a message, show it to the user before proceeding.

Set Up Dataverse Data Model

Guide the user through creating Dataverse tables, columns, and relationships for their Power Pages site. Follow a systematic approach: verify prerequisites, obtain a data model (via AI analysis or user-provided diagram), review and approve, then create all schema objects via OData API.

Core Principles

• Never create without approval: Always present the full data model proposal and get explicit user confirmation before making any Dataverse changes.
• Use TaskCreate/TaskUpdate: Track all progress throughout all phases — create the todo list upfront with all phases before starting any work.
• Resilient execution: Refresh tokens proactively, check for existing tables before creating, and report failures without automated rollback.

Initial request: $ARGUMENTS

Phase 1: Verify Prerequisites

Goal: Confirm PAC CLI authentication, acquire an Azure CLI token, and verify API access

Actions:

1. Create todo list with all 8 phases (see Progress Tracking table)
2. Follow the prerequisite steps in ${CLAUDE_PLUGIN_ROOT}/references/dataverse-prerequisites.md to verify PAC CLI auth, acquire an Azure CLI token, and confirm API access. Note the environment URL as <envUrl> for subsequent script calls.

Output: Verified PAC CLI auth, valid Azure CLI token, confirmed API access, <envUrl> noted

Phase 2: Choose Data Model Source

Goal: Determine whether the user will upload an existing ER diagram or let AI analyze the site

Actions:

1. Ask the user how they want to define the data model using the AskUserQuestion tool:

   Question: "How would you like to define the data model for your site?"

   Option	Description
   Upload an existing ER diagram	Provide an image (PNG/JPG) or Mermaid diagram of your existing data model
   Let the Data Model Architect figure it out	The Data Model Architect will analyze your site's source code and propose a data model automatically

2. Route to the appropriate path:

Path A: Upload Existing ER Diagram

If the user chooses to upload an existing diagram:

1. Ask the user to provide their ER diagram. Supported formats:

   • Image file (PNG, JPG) — Use the Read tool to view the image and extract tables, columns, relationships, and cardinalities from it
   • Mermaid syntax — The user can paste Mermaid ER diagram text directly in chat
   • Text description — A structured list of tables, columns, and relationships

2. Parse the diagram into the same structured format used by the data-model-architect agent:

   • Publisher prefix (ask the user, or retrieve from the environment via pac env who)
   • Table definitions: logicalName, displayName, status (new/modified/reused), columns, relationships
   • Column definitions: logicalName, displayName, type, required
   • Relationship definitions: type (1:N or M:N), referenced/referencing tables

3. Query existing Dataverse tables (same as Phase 3 would) to mark each table as new, modified, or reused.

4. Generate a Mermaid ER diagram from the parsed data (if the user provided an image or text) for visual confirmation.

5. Proceed directly to Phase 4: Review Proposal with the parsed data model.

Path B: Let the Data Model Architect Figure It Out

If the user chooses to let the Data Model Architect figure it out, proceed to Phase 3: Invoke Data Model Architect (the existing automated flow).

Output: Data model source chosen and, for Path A, parsed data model ready for review

Phase 3: Invoke Data Model Architect

Goal: Spawn the data-model-architect agent to autonomously analyze the site and propose a data model

Actions:

…