dv-solution Skill
Dataverse solution lifecycle — create, export, import, promote across environments, and validate deployments. Use when the user wants to package customizations, deploy to another environment, or move work between dev / test / prod. Published by microsoft in Dataverse-skills.
Decision snapshot
Is this a fit?
Testing, Deployment, Data analysis, Includes SKILL.md
Compatibility not yet detected.
No auth authentication
Copy skill directory
2 months ago · MIT license
Access note: No auth.
What is dv-solution Skill?
Dataverse solution lifecycle — create, export, import, promote across environments, and validate deployments. Use when the user wants to package customizations, deploy to another environment, or move work between dev / test / prod. Published by microsoft in Dataverse-skills. This profile combines repository metadata with install, compatibility, and usage signals so developers can quickly decide whether it fits their agent workflow before opening the source repository.
Automated repository signals based on public metadata such as recency, license, installation evidence, and adoption. These are not a security audit or endorsement. See how SkillIndex evaluates profiles.
Key capabilities
- Includes SKILL.md support
- Reusable instructions support
- Testing
- Deployment
- Data analysis
- Testing use cases
- Deployment use cases
Declared skill metadata
- Source file: .github/plugins/dataverse/skills/dv-solution/SKILL.md
These fields retain source and confidence evidence from the indexed SKILL.md.
Compatibility and setup
- Install or run with Copy skill directory
- No auth
Requirements and access
Security and permissions
Review permissions before connecting any MCP server to an agent. Pay special attention to whether it can read local files, write data, call external services, or perform destructive actions.
When to use dv-solution Skill
- Use it for testing.
- Use it for deployment.
- Use it for data analysis.
Built with
Editorial notes
Source
- Creator: microsoft
- Repository: microsoft/Dataverse-skills
- Skill file: .github/plugins/dataverse/skills/dv-solution/SKILL.md
What it does
Dataverse solution lifecycle — create, export, import, promote across environments, and validate deployments. Use when the user wants to package customizations, deploy to another environment, or move work between dev / test / prod.
Skill instructions
Skill: Solution Create, export, unpack, pack, import, and validate Dataverse solutions via PAC CLI. Includes post-import validation using the Python SDK. Headless / restricted-egress hosts: use the raw Web API (ExportSolution / ImportSolution) for the online steps. pac solution pack/unpack are local file operations (no auth) but need a host that can run PAC -- do them on a capable machine or CI runner. Verify egress with python scripts/auth.py --check. See dv-connect/references/headless-hosts.md. Skill boundaries | Need | Use instead | |---|---| | Create tables, columns, relationships, forms, views | dv-metadata | | Create, update, or delete data records | dv-data | | Query or read records | dv-query | | Connect to Dataverse / set up MCP | dv-connect | --- Create a New Solution Use the Python SDK for publisher and solution record creation — not raw HTTP. Publishers and solutions are standard Dataverse tables. client.records.create() and client.records.list() handle auth, pagination, an
Verified compatibility and discovery
Frequently asked questions
What is dv-solution?
dv-solution is a open-source AI agent skill with Copy skill directory. Dataverse solution lifecycle — create, export, import, promote across environments, and validate deployments.
Who is dv-solution best for?
dv-solution is best for reusing agent instructions, scripts, and references, testing workflows, deployment workflows, data analysis workflows.
How do I install dv-solution?
Install or run dv-solution using Copy skill directory. Check dv-solution for the latest setup command.
Is dv-solution actively maintained?
dv-solution may need a closer maintenance check before production use.
Project health auto-fetched from the source repository.
Maintain this resource?
Review this source-backed profile, send a correction with evidence, or link to it from your documentation. Claims verify your relationship to the project; profile facts still require source evidence and editorial review.
