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dv-metadata

Automate Dataverse metadata changes via Python SDK and Web API.

195|50|Updated Mar 11, 2026
Search Tags:#sdk#metadata#forms#relationships#tables#web-api#dataverse
One-click install
npx skills add https://github.com/microsoft/Dataverse-skills --skill dv-metadata
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: dv-metadata
Source: https://github.com/microsoft/Dataverse-skills/tree/main/.github/plugins/dataverse/skills/dv-metadata
Command: npx skills add https://github.com/microsoft/Dataverse-skills --skill dv-metadata

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Dataverse metadata changes are complex and error-prone when done manually across environments; this skill provides a programmatic approach to creating, updating, and governing tables, columns, relationships, forms, and views using the Python SDK and Web API.

Core Features & Use Cases

  • Create, update, or delete Dataverse metadata (tables, columns, relationships, forms, and views) using the Python SDK and Web API.
  • Manage environment-first workflows, solutions, and publisher prefixes to ensure safe, repeatable deployments.
  • Provide guidance for forms creation via Web API when SDK support is limited, and best-practice workflows for applying changes to environments and pulling them back into the repo.

Quick Start

Create a new table named with your publisher prefix, add a string column for a key field, and save it into the target solution.

Frequently Asked Questions about dv-metadata

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

FAQPage Schema
How do I automate Dataverse metadata changes across environments?▼

Automate Dataverse metadata changes programmatically using the Python SDK and Web API to create, update, and delete tables, columns, and relationships. This approach ensures safe, repeatable deployments across environments by managing solutions and publisher prefixes.

Can I create Dataverse forms using the Python SDK?▼

Dataverse forms creation is handled via the Web API when Python SDK support is limited. The skill provides specific guidance for using Web API endpoints to configure forms and views, ensuring metadata changes are applied correctly.

What is the best way to manage publisher prefixes when creating Dataverse tables?▼

Manage publisher prefixes by naming new Dataverse tables and columns with your designated prefix before saving them into the target solution. This ensures proper governance and avoids naming conflicts during environment-first workflows and deployments.

How do I handle propagation delays when creating Dataverse metadata?▼

Handle Dataverse metadata propagation delays by using phased creation workflows. The skill manages environment context and timing to ensure tables, columns, and relationships are fully committed before dependent configuration steps are executed.

Do I need authentication setup to automate Dataverse table creation?▼

Authentication setup and proper environment context are required to automate Dataverse table creation. You must configure the Dataverse SDKs with valid credentials to programmatically apply schema changes and manage solutions across environments.

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