Official agent skill

Azure Mgmt Fabric Py

by microsoft in microsoft/skills

Azure Fabric Management SDK for Python. An agent skill from microsoft/skills.

OfficialMITAuto-check passedDevOps & Cloud

Install Azure Mgmt Fabric Py

skills CLI
$ npx skills add microsoft/skills --skill azure-mgmt-fabric-py -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install microsoft/skills azure-mgmt-fabric-py --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/microsoft/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.github/plugins/azure-sdk-python/skills/azure-mgmt-fabric-py .claude/skills/azure-mgmt-fabric-py && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
azure-mgmt-fabric-py
GitHub stars
3.1k
Token cost
~2.2k tokens
SKILL.md length
449 words
Files
3 (incl. references)
Skills in repo
150
Repo updated
First seen
Licence
MIT

At a glance

Azure Fabric Management SDK for Python. An agent skill from microsoft/skills.

  • Works in 10 steps: Pick sync OR async and stay consistent.… → Always use context managers for clients… → Use DefaultAzureCredential for code that… → …
  • Managing Microsoft Fabric capacities and resources
  • SKILL.md covers Installation, Environment Variables, Authentication & Lifecycle and Create Fabric Capacity, plus 15 more sections
  • Calls pip; reaches learn.microsoft.com; needs AZURE_TOKEN_CREDENTIALS

What it does

Azure Mgmt Fabric Py is an agent skill from microsoft/skills, published by the product's own GitHub organization. Azure Fabric Management SDK for Python. Use for managing Microsoft Fabric capacities and resources. Triggers: "azure-mgmt-fabric", "FabricMgmtClient", "Fabric capacity", "Microsoft Fabric", "Power BI capacity".

Its SKILL.md is about 2.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including reference files (for example `references/capabilities.md` and `references/non-hero-scenarios.md`).

It sits in DevOps & Cloud. It works with Microsoft Azure, Power BI, Python and Visual Studio Code. The repository describes itself as: Skills, MCP servers, Custom Agents, Agents.md for SDKs to ground Coding Agents. The licence is MIT.

When your agent uses it

  • Managing Microsoft Fabric capacities and resources

Example prompts

  • “azure-mgmt-fabric”
  • “FabricMgmtClient”
  • “Fabric capacity”
  • “/azure-mgmt-fabric-py”

Requirements

  • Python 3

Workflow steps

10 steps, taken from the first numbered list in SKILL.md.

  1. Pick sync OR async and stay consistent. Do not mix azure.xxx sync clients with azure.xxx.aio async clients in the same call path. Choose…
  2. Always use context managers for clients and async credentials. Wrap every client in with Client(...) as client: (sync) or async with…
  3. Use DefaultAzureCredential for code that runs locally. Use a specific token credential for code that runs in Azure.
  4. Suspend unused capacities to reduce costs
  5. Start with smaller SKUs and scale up as needed
  6. Use tags for cost tracking and organization
  7. Check name availability before creating capacities
  8. Handle LRO properly — don't assume immediate completion
  9. Set up capacity admins — specify users who can manage workspaces
  10. Monitor capacity usage via Azure Monitor metrics

What it can do on your machine

Read from SKILL.md and the folder at commit d5741a1. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • pip

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • learn.microsoft.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • AZURE_TOKEN_CREDENTIALS

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Azure Mgmt Fabric Py loads about 2.2k tokens when it runs, and up to ~3.7k if it reads all its reference files. Until then it costs about 58 tokens; SKILL.md has 449 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~58
When it runs · the whole SKILL.md, loaded when a task matches
~2.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from microsoft/skills at commit d5741a1, republished under its MIT licence (© microsoft). 449 words, ~2,222 tokens.

Download SKILL.mdSave it as .claude/skills/azure-mgmt-fabric-py/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
azure-mgmt-fabric-py
description
Azure Fabric Management SDK for Python. Use for managing Microsoft Fabric capacities and resources. Triggers: "azure-mgmt-fabric", "FabricMgmtClient", "Fabric capacity", "Microsoft Fabric", "Power BI capacity".
license
MIT
metadata.author
Microsoft
metadata.version
1.0.0

Azure Fabric Management SDK for Python

Manage Microsoft Fabric capacities and resources programmatically.

Installation

bash
pip install azure-mgmt-fabric
pip install azure-identity

Environment Variables

bash
AZURE_SUBSCRIPTION_ID=<your-subscription-id>  # Required for all auth methods
AZURE_RESOURCE_GROUP=<your-resource-group>  # Required for all auth methods
AZURE_TOKEN_CREDENTIALS=prod # Required only if DefaultAzureCredential is used in production

Authentication & Lifecycle

🔑 Two rules apply to every code sample below:

  1. Prefer DefaultAzureCredential. It works locally (Azure CLI / VS Code / Developer CLI) and in Azure (managed identity, workload identity) with no code change. Avoid connection strings, account/API keys — they bypass Entra audit and rotation.
    • Local dev: DefaultAzureCredential works as-is.
    • Production: set AZURE_TOKEN_CREDENTIALS=prod (or AZURE_TOKEN_CREDENTIALS=<specific_credential>) to constrain the credential chain to production-safe credentials.
  2. Wrap every client in a context manager so HTTP transports, sockets, and token caches are released deterministically:
    • Sync: with <Client>(...) as client:
    • Async: async with <Client>(...) as client: and async with DefaultAzureCredential() as credential: (from azure.identity.aio)

Snippets may abbreviate this setup, but production code should always follow both rules.

python
from azure.identity import DefaultAzureCredential, ManagedIdentityCredential
from azure.mgmt.fabric import FabricMgmtClient
import os

# Local dev: DefaultAzureCredential. Production: set AZURE_TOKEN_CREDENTIALS=prod or AZURE_TOKEN_CREDENTIALS=<specific_credential>
credential = DefaultAzureCredential(require_envvar=True)
# Or use a specific credential directly in production:
# See https://learn.microsoft.com/python/api/overview/azure/identity-readme?view=azure-python#credential-classes
# credential = ManagedIdentityCredential()

with FabricMgmtClient(
    credential=credential,
    subscription_id=os.environ["AZURE_SUBSCRIPTION_ID"]
) as client:
    # Use `client` for all subsequent operations (see examples below)
    ...

Create Fabric Capacity

python
from azure.mgmt.fabric import FabricMgmtClient
from azure.mgmt.fabric.models import FabricCapacity, FabricCapacityProperties, CapacitySku
from azure.identity import DefaultAzureCredential
import os

resource_group = os.environ["AZURE_RESOURCE_GROUP"]
capacity_name = "myfabriccapacity"

credential = DefaultAzureCredential()
with FabricMgmtClient(
    credential=credential,
    subscription_id=os.environ["AZURE_SUBSCRIPTION_ID"]
) as client:
    capacity = client.fabric_capacities.begin_create_or_update(
        resource_group_name=resource_group,
        capacity_name=capacity_name,
        resource=FabricCapacity(
            location="eastus",
            sku=CapacitySku(
                name="F2",  # Fabric SKU
                tier="Fabric"
            ),
            properties=FabricCapacityProperties(
                administration=FabricCapacityAdministration(
                    members=["user@contoso.com"]
                )
            )
        )
    ).result()

print(f"Capacity created: {capacity.name}")

Get Capacity Details

python
capacity = client.fabric_capacities.get(
    resource_group_name=resource_group,
    capacity_name=capacity_name
)

print(f"Capacity: {capacity.name}")
print(f"SKU: {capacity.sku.name}")
print(f"State: {capacity.properties.state}")
print(f"Location: {capacity.location}")

List Capacities in Resource Group

python
capacities = client.fabric_capacities.list_by_resource_group(
    resource_group_name=resource_group
)

for capacity in capacities:
    print(f"Capacity: {capacity.name} - SKU: {capacity.sku.name}")

List All Capacities in Subscription

python
all_capacities = client.fabric_capacities.list_by_subscription()

for capacity in all_capacities:
    print(f"Capacity: {capacity.name} in {capacity.location}")

Update Capacity

python
from azure.mgmt.fabric.models import FabricCapacityUpdate, CapacitySku

updated = client.fabric_capacities.begin_update(
    resource_group_name=resource_group,
    capacity_name=capacity_name,
    properties=FabricCapacityUpdate(
        sku=CapacitySku(
            name="F4",  # Scale up
            tier="Fabric"
        ),
        tags={"environment": "production"}
    )
).result()

print(f"Updated SKU: {updated.sku.name}")

Suspend Capacity

Pause capacity to stop billing:

python
client.fabric_capacities.begin_suspend(
    resource_group_name=resource_group,
    capacity_name=capacity_name
).result()

print("Capacity suspended")

Resume Capacity

Resume a paused capacity:

python
client.fabric_capacities.begin_resume(
    resource_group_name=resource_group,
    capacity_name=capacity_name
).result()

print("Capacity resumed")

Delete Capacity

python
client.fabric_capacities.begin_delete(
    resource_group_name=resource_group,
    capacity_name=capacity_name
).result()

print("Capacity deleted")

Check Name Availability

python
from azure.mgmt.fabric.models import CheckNameAvailabilityRequest

result = client.fabric_capacities.check_name_availability(
    location="eastus",
    body=CheckNameAvailabilityRequest(
        name="my-new-capacity",
        type="Microsoft.Fabric/capacities"
    )
)

if result.name_available:
    print("Name is available")
else:
    print(f"Name not available: {result.reason}")

List Available SKUs

python
skus = client.fabric_capacities.list_skus(
    resource_group_name=resource_group,
    capacity_name=capacity_name
)

for sku in skus:
    print(f"SKU: {sku.name} - Tier: {sku.tier}")

Client Operations

OperationMethod
client.fabric_capacitiesCapacity CRUD operations
client.operationsList available operations

Fabric SKUs

SKUDescriptionCUs
F2Entry level2 Capacity Units
F4Small4 Capacity Units
F8Medium8 Capacity Units
F16Large16 Capacity Units
F32X-Large32 Capacity Units
F642X-Large64 Capacity Units
F1284X-Large128 Capacity Units
F2568X-Large256 Capacity Units
F51216X-Large512 Capacity Units
F102432X-Large1024 Capacity Units
F204864X-Large2048 Capacity Units

Capacity States

StateDescription
ActiveCapacity is running
PausedCapacity is suspended (no billing)
ProvisioningBeing created
UpdatingBeing modified
DeletingBeing removed
FailedOperation failed
Show full SKILL.md (183 more words)Show less

Long-Running Operations

All mutating operations are long-running (LRO). Use .result() to wait:

python
# Synchronous wait
capacity = client.fabric_capacities.begin_create_or_update(...).result()

# Or poll manually
poller = client.fabric_capacities.begin_create_or_update(...)
while not poller.done():
    print(f"Status: {poller.status()}")
    time.sleep(5)
capacity = poller.result()

Best Practices

  1. Pick sync OR async and stay consistent. Do not mix azure.xxx sync clients with azure.xxx.aio async clients in the same call path. Choose one mode per module.
  2. Always use context managers for clients and async credentials. Wrap every client in with Client(...) as client: (sync) or async with Client(...) as client: (async). For async DefaultAzureCredential from azure.identity.aio, also use async with credential: so tokens and transports are cleaned up.
  3. Use DefaultAzureCredential for code that runs locally. Use a specific token credential for code that runs in Azure.
  4. Suspend unused capacities to reduce costs
  5. Start with smaller SKUs and scale up as needed
  6. Use tags for cost tracking and organization
  7. Check name availability before creating capacities
  8. Handle LRO properly — don't assume immediate completion
  9. Set up capacity admins — specify users who can manage workspaces
  10. Monitor capacity usage via Azure Monitor metrics

Reference Files

FileContents
references/capabilities.mdAdditional non-hero capabilities, operation-group coverage, and production checklists.
references/non-hero-scenarios.mdDedicated non-hero examples for secondary/advanced scenarios.

© microsoft, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files (references) in .github/plugins/azure-sdk-python/skills/azure-mgmt-fabric-py of microsoft/skills.

  • SKILL.md
  • references/capabilities.md
  • references/non-hero-scenarios.md

Open the folder on GitHubat commit d5741a1

Compare with similar skills

Azure Mgmt Fabric Py next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Azure Mgmt Fabric Py compared with similar skills
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Azure Architecture Autopilotgithub/awesome-copilot40k1 repos~1.9kAutomated safety check: PassMIT
Terraform Azurerm Set Diff Analyzergithub/awesome-copilot40k1 repos~547Automated safety check: PassMIT
Osmo Lerobot Trainingmicrosoft/physical-ai-toolchain126—~3.8kAutomated safety check: NotesMIT

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Questions about Azure Mgmt Fabric Py

What does Azure Mgmt Fabric Py do?

Azure Fabric Management SDK for Python. An agent skill from microsoft/skills. Azure Mgmt Fabric Py is an agent skill from microsoft/skills, published by the product's own GitHub organization. Azure Fabric Management SDK for Python.

When should I use Azure Mgmt Fabric Py?

Azure Mgmt Fabric Py fits situations like: managing Microsoft Fabric capacities and resources.

How do I install Azure Mgmt Fabric Py in Claude Code?

Run `npx skills add microsoft/skills --skill azure-mgmt-fabric-py -a claude-code`. Or copy the skill folder (.github/plugins/azure-sdk-python/skills/azure-mgmt-fabric-py in microsoft/skills) into .claude/skills/azure-mgmt-fabric-py in your project. Claude Code loads it when a task matches its description.

How do I install Azure Mgmt Fabric Py in Codex?

Run `npx skills add microsoft/skills --skill azure-mgmt-fabric-py -a codex`. Or copy the skill folder (.github/plugins/azure-sdk-python/skills/azure-mgmt-fabric-py in microsoft/skills) into .agents/skills/azure-mgmt-fabric-py in your project. Codex loads it when a task matches its description.

Can I use Azure Mgmt Fabric Py in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add microsoft/skills --skill azure-mgmt-fabric-py -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/azure-mgmt-fabric-py, .gemini/skills/azure-mgmt-fabric-py, .github/skills/azure-mgmt-fabric-py and .opencode/skills/azure-mgmt-fabric-py in your project.

What does Azure Mgmt Fabric Py need to run?

Going by SKILL.md and its folder, Azure Mgmt Fabric Py needs the command-line tools its instructions call (pip) and credentials named AZURE_TOKEN_CREDENTIALS. Our summary lists: Python 3.

Does Azure Mgmt Fabric Py access the network?

SKILL.md names 1 domain. In commands or code: learn.microsoft.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Azure Mgmt Fabric Py safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Azure Mgmt Fabric Py use?

Azure Mgmt Fabric Py is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Azure Mgmt Fabric Py use?

About 2.2k tokens (SKILL.md is roughly 8.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.5k tokens, read only when the agent opens those files.

What are the alternatives to Azure Mgmt Fabric Py?

Skills that share tags, products or a category with Azure Mgmt Fabric Py: Azure Storage File Datalake Py (aiskillstore/marketplace, 433 stars), Azure Resource Graph (MicrosoftDocs/Agent-Skills, 776 stars), Azure Architecture Autopilot (github/awesome-copilot, 40k stars) and Terraform Azurerm Set Diff Analyzer (github/awesome-copilot, 40k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Azure Mgmt Fabric Py?

microsoft (a GitHub organization, an official publisher) maintains it in microsoft/skills, which has 3,097 GitHub stars. The repository holds 150 skills in this directory. The repository was last updated on October 9, 2026.

Source: microsoft/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.