dv-solution

Q: How do I install dv-solution?

Run npx skills add https://github.com/microsoft/dataverse-skills --skill dv-solution in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/dv-solution/ (personal) or .claude/skills/dv-solution/ (project).

by microsoft OfficialDevOps & Cloud

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.

Installs: 215
Last 24h: —
Trending rank: —
Security: Not audited

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/microsoft/dataverse-skills --skill dv-solution

01
Install
Run the command in your project. The CLI asks which agents to install for.
02
Describe the task
Ask your agent for something this skill covers. It loads dv-solution automatically when relevant.
03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

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, and error handling automatically, avoiding the URL encoding, header boilerplate, and GUID-parsing bugs that raw urllib calls introduce.

Step 1: Find or Create the Publisher

Every solution belongs to a publisher. The publisher's customizationprefix (e.g., contoso, sa, lit) is prepended to every custom table, column, and relationship schema name. This prefix is effectively permanent — existing components keep their prefix forever, even if you change the publisher later.

Never use the default new prefix. It provides no organizational identity, risks naming collisions, and signals the developer did not follow best practices.

Discovery flow — always run this before creating a publisher:

import os, sys
sys.path.insert(0, os.path.join(os.getcwd(), "scripts"))
from auth import get_client

# get_client sets a plugin attribution context on the User-Agent header.
# Do not modify the context value — it is a closed schema for server-side
# telemetry (app/skill/agent). Never include secrets or PII.
client = get_client("dv-solution")

# 1. Query for existing non-Microsoft publishers
publishers = client.records.list(
    "publisher",
    filter="customizationprefix ne 'none' and uniquename ne 'MicrosoftCorporation' and uniquename ne 'Microsoftdynamic'",
    select=["publisherid", "uniquename", "friendlyname", "customizationprefix"],
    top=10,
)

if publishers:
    # Show existing publishers and ask user which to use
    print("Existing publishers in this environment:")
    for p in publishers:
        print(f"  {p['uniquename']} (prefix: {p['customizationprefix']}_)")
    # ASK THE USER: "Which publisher should this solution use?"
    # Or: "Should I reuse '<name>' (prefix: <prefix>_)?"
    publisher_id = publishers[0]["publisherid"]  # after user confirms
else:
    # No custom publisher exists — ASK THE USER for prefix
    # "What publisher prefix should I use? (e.g., 'contoso', 'sa', 'lit' — 2-8 lowercase chars)"
    publisher_id = client.records.create("publisher", {
        "uniquename": "<publisheruniquename>",
        "friendlyname": "<Publisher Display Name>",
        "customizationprefix": "<prefix>",   # from user input, NOT 'new'
        "description": "<description>",
    })

Rules:

Always ask the user before creating a new publisher or choosing a prefix. Never hardcode a prefix.
The prefix must match any tables already created in the solution — you cannot mix prefixes.
One publisher can own many solutions. Reuse an existing publisher when possible.

Step 2: Create the Solution Record

Use the SDK to create the solution record (preferred over raw Web API):

import os, sys
sys.path.insert(0, os.path.join(os.getcwd(), "scripts"))
from auth import get_client

# get_client sets a plugin attribution context on the User-Agent header.
# Do not modify the context value — it is a closed schema for server-side
# telemetry (app/skill/agent). Never include secrets or PII.
client = get_client("dv-solution")

# Create the solution record
solution_id = client.records.create("solution", {
    "uniquename": "<UniqueName>",
    "friendlyname": "<Display Name>",
    "version": "1.0.0.0",
    "publisherid@odata.bind": "/publishers(<publisher_guid>)",
})
print(f"Created solution: {solution_id}")

The required fields:

Table:  solution
Fields: uniquename    = "<UniqueName>"
        friendlyname  = "<Display Name>"
        version       = "1.0.0.0"
        publisherid   = <publisher GUID from step 1>

Note: There is no pac solution create command. PAC CLI handles export/import/pack/unpack, not solution record creation. Use the SDK or Web API to create the record.

Step 3: Add Components

Use pac solution add-solution-component to add tables, forms, views, and other components:

pac solution add-solution-component \
  --solutionUniqueName <UniqueName> \
  --component <ComponentSchemaName> \
  --componentType <TypeCode> \
  --environment <url>

Note: PAC CLI uses camelCase args here (--solutionUniqueName, --componentType), not kebab-case.

Common component type codes:

Type Code	Component
1	Entity (Table)
2	Attribute (Column)
26	View
60	Form
61	Web Resource
300	Canvas App
371	Connector

Repeat the command for each component you need to add.

Alternative: Auto-add via MSCRM.SolutionName Header

When creating metadata via the Web API, include the MSCRM.SolutionName header to auto-add components to the solution:

headers = {
    "Authorization": f"Bearer {token}",
    "Content-Type": "application/json",
    "MSCRM.SolutionName": "<UniqueName>"
}

Important: After using this approach, verify components were added by querying the solutioncomponent table with the SDK (pac solution list-components is not available in current PAC):

sol = client.records.list("solution",
    filter="uniquename eq '<UniqueName>'", select=["solutionid"], top=1).first()
if sol is not None:
    components = client.records.list("solutioncomponent",
        filter=f"_solutionid_value eq {sol['solutionid']}",
        select=["componenttype", "objectid"])
    print(f"{len(components)} components in the solution")

If the header was misspelled or the solution doesn't exist, components will be created in the default solution instead — silently. Always verify.

Find the Solution Name

Before exporting, confirm the exact unique name:

pac solution list --environment <url>

The UniqueName column is what you pass to other commands. Display names have spaces; unique names do not.

Pull: Export + Unpack

Confirm the target environment before exporting or importing. Run pac auth list + pac org who, show the output to the user, and confirm it matches the intended environment. Developers work across multiple environments — do not assume.

Export the solution as unmanaged (source of truth):

pac solution export \
  --name <UniqueName> \
  --path ./solutions/<UniqueName>.zip \
  --managed false \
  --environment <url>

Unpack into editable source files:

pac solution unpack \
  --zipfile ./solutions/<UniqueName>.zip \
  --folder ./solutions/<UniqueName> \
  --packagetype Unmanaged

Windows file-lock race. Run export and unpack as separate commands (as above); chaining them immediately can hit a transient ZIP file-lock right after export. If unpack fails with a lock / "in use" error, retry after a moment, and verify the unpacked folder has the expected components before deleting the zip.

Delete the zip — the unpacked folder is the source:

rm ./solutions/<UniqueName>.zip

Commit:

git add ./solutions/<UniqueName>
git commit -m "chore: pull <UniqueName> baseline"
git push

Push: Pack + Import

Pack the source files back into a zip:

pac solution pack \
  --zipfile ./solutions/<UniqueName>.zip \
  --folder ./solutions/<UniqueName> \
  --packagetype Unmanaged

Import (async recommended for large solutions):

pac solution import \
  --path ./solutions/<UniqueName>.zip \
  --environment <url> \
  --async \
  --activate-plugins

Poll Import Status

After async import, check the job:

pac solution list --environment <url>

Post-Import Validation

After importing a solution, verify that components are live. Use the Python SDK to check directly — no external scripts needed.

Check a table exists

info = client.tables.get("<logical_name>")
if info:
    print(f"[PASS] Table '{info.logical_name}' exists")
else:
    print(f"[FAIL] Table '<logical_name>' not found")

Check a form is published

forms = client.records.list(
    "systemform",
    filter="objecttypecode eq '<entity>' and type eq <form_type_code>",
    select=["name", "formid"],
    top=5,
)
# Form type codes: 2 = main, 7 = quick create

Check a view exists

views = client.records.list(
    "savedquery",
    filter="returnedtypecode eq '<entity>'",
    select=["name", "savedqueryid", "statuscode"],
    top=10,
)

Check a user's role assignment (N:N `$expand`)

records.list passes $expand straight through, so read the N:N navigation property directly with the SDK:

users = list(client.records.list(
    "systemuser",
    filter="internalemailaddress eq '<email>'",   # fallback: domainname eq '<upn>'
    select=["fullname"],
    expand=["systemuserroles_association($select=name)"],
    top=1,
))
roles = [r["name"] for r in users[0].get("systemuserroles_association", [])] if users else []

Alternatively, the managed Dataverse CLI escape hatch (dataverse api request — not urllib), or FetchXML with a link-entity:

dataverse api request --target dataverse --method GET \
  --path "/api/data/v9.2/systemusers?%24filter=internalemailaddress eq '<email>'&%24select=fullname&%24expand=systemuserroles_association(%24select=name)&%24top=1" \
  --environment <DATAVERSE_URL> \
  --context "app=dataverse-skills/<ver>;skill=dv-solution;agent=<agent>"

The response value[0].systemuserroles_association is the list of assigned roles (each with name).

Check import errors

jobs = client.records.list(
    "importjob",
    select=["importjobid", "solutionname", "startedon", "completedon", "progress"],
    orderby=["startedon desc"],
    top=5,
)

For detailed error history, also query msdyn_solutionhistory:

history = client.records.list(
    "msdyn_solutionhistory",
    filter="msdyn_status eq 1",  # 1 = failed
    select=["msdyn_name", "msdyn_starttime", "msdyn_exceptionmessage"],
    orderby=["msdyn_starttime desc"],
    top=5,
)

Validation error reference

Error	Cause	Fix
Table not found after import	Component not in solution	Add via `pac solution add-solution-component`
Form check fails immediately	Publishing is async	Wait 30 seconds and retry
Role not assigned	User not provisioned	Assign the role via `pac admin assign-user` or the Power Platform Admin Center
Import job at 0%	Import still running	Poll again in 60 seconds

Notes

Always use --managed false / --packagetype Unmanaged for the development solution. Managed packages are for deployment to downstream environments (test, prod).
--activate-plugins ensures any registered plugins in the solution are activated on import.
If you see "solution already exists" errors, use --import-mode ForceUpgrade to overwrite.
Large solutions (Sales, Customer Service) can take 10–20 minutes to import. Be patient and poll rather than re-importing.
All validation queries above require auth. Use scripts/auth.py for credential/token acquisition. See dv-query for SDK query patterns and dv-data for write patterns.

FAQ

What does the dv-solution skill do?

How do I install dv-solution?

Run npx skills add https://github.com/microsoft/dataverse-skills --skill dv-solution in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/dv-solution/ (personal) or .claude/skills/dv-solution/ (project).

Which AI agents can use dv-solution?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is dv-solution safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains dv-solution?

It is published by microsoft in microsoft/dataverse-skills, and it is an official skill from the maker of the technology it covers. It has 215 recorded installs.

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dv-solution

Install

Install

Describe the task

Review the result

SKILL.md

Skill: Solution

Skill boundaries

Create a New Solution

Step 1: Find or Create the Publisher

Step 2: Create the Solution Record

Step 3: Add Components

Alternative: Auto-add via MSCRM.SolutionName Header

Find the Solution Name

Pull: Export + Unpack

Push: Pack + Import

Poll Import Status

Post-Import Validation

Check a table exists

Check a form is published

Check a view exists

Check a user's role assignment (N:N $expand)

Check import errors

Validation error reference

Notes

FAQ

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Check a user's role assignment (N:N `$expand`)