Azure Identity Py V3

Azure Identity SDK for Python

Overview

This public intake copy packages plugins/antigravity-bundle-azure-ai-cloud/skills/azure-identity-py from https://github.com/sickn33/antigravity-awesome-skills into the native Omni Skills editorial shape without hiding its origin.

Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.

This intake keeps the copied upstream files intact and uses the external_source block in metadata.json plus ORIGIN.md as the provenance anchor for review.

Azure Identity SDK for Python Authentication library for Azure SDK clients using Microsoft Entra ID (formerly Azure AD).

Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: Environment Variables, DefaultAzureCredential, Specific Credential Types, Credential Types Table, Getting Tokens Directly, Async Client.

When to Use This Skill

Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.

• This skill is applicable to execute the workflow or actions described in the overview.
• Use when the request clearly matches the imported source intent: Azure Identity SDK for Python authentication. Use for DefaultAzureCredential, managed identity, service principals, and token caching.
• Use when the operator should preserve upstream workflow detail instead of rewriting the process from scratch.
• Use when provenance needs to stay visible in the answer, PR, or review packet.
• Use when copied upstream references, examples, or scripts materially improve the answer.
• Use when the workflow should remain reviewable in the public intake repo before the private enhancer takes over.

Operating Table

Workflow

This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.

1. bash pip install azure-identity
2. Confirm the user goal, the scope of the imported workflow, and whether this skill is still the right router for the task.
3. Read the overview and provenance files before loading any copied upstream support files.
4. Load only the references, examples, prompts, or scripts that materially change the outcome for the current request.
5. Execute the upstream workflow while keeping provenance and source boundaries explicit in the working notes.
6. Validate the result against the upstream expectations and the evidence you can point to in the copied files.
7. Escalate or hand off to a related skill when the work moves out of this imported workflow's center of gravity.

Imported Workflow Notes

Imported: Installation

pip install azure-identity

Imported: Environment Variables

# Service Principal (for production/CI)
AZURE_TENANT_ID=<your-tenant-id>
AZURE_CLIENT_ID=<your-client-id>
AZURE_CLIENT_SECRET=<your-client-secret>

# User-assigned Managed Identity (optional)
AZURE_CLIENT_ID=<managed-identity-client-id>

Examples

Example 1: Ask for the upstream workflow directly

Use @azure-identity-py-v3 to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.

Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.

Example 2: Ask for a provenance-grounded review

Review @azure-identity-py-v3 against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.

Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.

Example 3: Narrow the copied support files before execution

Use @azure-identity-py-v3 for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.

Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.

Example 4: Build a reviewer packet

Review @azure-identity-py-v3 using the copied upstream files plus provenance, then summarize any gaps before merge.

Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.

Best Practices

Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.

• Use DefaultAzureCredential for code that runs locally and in Azure
• Never hardcode credentials — use environment variables or managed identity
• Prefer managed identity in production Azure deployments
• Use ChainedTokenCredential when you need a custom credential order
• Close async credentials explicitly or use context managers
• Set AZURECLIENTID for user-assigned managed identities
• Exclude unused credentials to speed up authentication

Imported Operating Notes

Imported: Best Practices

1. Use DefaultAzureCredential for code that runs locally and in Azure
2. Never hardcode credentials — use environment variables or managed identity
3. Prefer managed identity in production Azure deployments
4. Use ChainedTokenCredential when you need a custom credential order
5. Close async credentials explicitly or use context managers
6. Set AZURE_CLIENT_ID for user-assigned managed identities
7. Exclude unused credentials to speed up authentication

Troubleshooting

Problem: The operator skipped the imported context and answered too generically

Symptoms: The result ignores the upstream workflow in plugins/antigravity-bundle-azure-ai-cloud/skills/azure-identity-py, fails to mention provenance, or does not use any copied source files at all. Solution: Re-open metadata.json, ORIGIN.md, and the most relevant copied upstream files. Check the external_source block first, then restate the provenance before continuing.

Problem: The imported workflow feels incomplete during review

Symptoms: Reviewers can see the generated SKILL.md, but they cannot quickly tell which references, examples, or scripts matter for the current task. Solution: Point at the exact copied references, examples, scripts, or assets that justify the path you took. If the gap is still real, record it in the PR instead of hiding it.

Problem: The task drifted into a different specialization

Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better. Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.

Related Skills

• @ab-test-setup-v3 - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @algolia-search-v3 - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @algorithmic-art-v3 - Use when the work is better handled by that native specialization after this imported skill establishes context.
• @analytics-tracking-v3 - Use when the work is better handled by that native specialization after this imported skill establishes context.

Additional Resources

Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.

Imported Reference Notes

Imported: DefaultAzureCredential

The recommended credential for most scenarios. Tries multiple authentication methods in order:

from azure.identity import DefaultAzureCredential
from azure.storage.blob import BlobServiceClient

# Works in local dev AND production without code changes
credential = DefaultAzureCredential()

client = BlobServiceClient(
    account_url="https://<account>.blob.core.windows.net",
    credential=credential
)

Credential Chain Order

Customizing DefaultAzureCredential

# Exclude credentials you don't need
credential = DefaultAzureCredential(
    exclude_environment_credential=True,
    exclude_shared_token_cache_credential=True,
    managed_identity_client_id="<user-assigned-mi-client-id>"  # For user-assigned MI
)

# Enable interactive browser (disabled by default)
credential = DefaultAzureCredential(
    exclude_interactive_browser_credential=False
)

Imported: Specific Credential Types

ManagedIdentityCredential

For Azure-hosted resources (VMs, App Service, Functions, AKS):

from azure.identity import ManagedIdentityCredential

# System-assigned managed identity
credential = ManagedIdentityCredential()

# User-assigned managed identity
credential = ManagedIdentityCredential(
    client_id="<user-assigned-mi-client-id>"
)

ClientSecretCredential

For service principal with secret:

from azure.identity import ClientSecretCredential

credential = ClientSecretCredential(
    tenant_id=os.environ["AZURE_TENANT_ID"],
    client_id=os.environ["AZURE_CLIENT_ID"],
    client_secret=os.environ["AZURE_CLIENT_SECRET"]
)

AzureCliCredential

Uses the account from az login:

from azure.identity import AzureCliCredential

credential = AzureCliCredential()

ChainedTokenCredential

Custom credential chain:

from azure.identity import (
    ChainedTokenCredential,
    ManagedIdentityCredential,
    AzureCliCredential
)

# Try managed identity first, fall back to CLI
credential = ChainedTokenCredential(
    ManagedIdentityCredential(client_id="<user-assigned-mi-client-id>"),
    AzureCliCredential()
)

Imported: Credential Types Table

Imported: Getting Tokens Directly

from azure.identity import DefaultAzureCredential

credential = DefaultAzureCredential()

# Get token for a specific scope
token = credential.get_token("https://management.azure.com/.default")
print(f"Token expires: {token.expires_on}")

# For Azure Database for PostgreSQL
token = credential.get_token("https://ossrdbms-aad.database.windows.net/.default")

Imported: Async Client

from azure.identity.aio import DefaultAzureCredential
from azure.storage.blob.aio import BlobServiceClient

async def main():
    credential = DefaultAzureCredential()

    async with BlobServiceClient(
        account_url="https://<account>.blob.core.windows.net",
        credential=credential
    ) as client:
        # ... async operations
        pass

    await credential.close()

Imported: Limitations

• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.