azure-identity-py
Azure Identity SDK for Python authentication. Use for DefaultAzureCredential, managed identity, service principals, and token caching. Triggers: "azure-identity", "DefaultAzureCredential", "authentication", "managed identity", "service principal", "credential".
What this skill does
# Azure Identity SDK for Python
Authentication library for Azure SDK clients using Microsoft Entra ID (formerly Azure AD).
## Installation
```bash
pip install azure-identity
```
## Environment Variables
```bash
# 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>
```
## DefaultAzureCredential
The recommended credential for most scenarios. Tries multiple authentication methods in order:
```python
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
| Order | Credential | Environment |
|-------|-----------|-------------|
| 1 | EnvironmentCredential | CI/CD, containers |
| 2 | WorkloadIdentityCredential | Kubernetes |
| 3 | ManagedIdentityCredential | Azure VMs, App Service, Functions |
| 4 | SharedTokenCacheCredential | Windows only |
| 5 | VisualStudioCodeCredential | VS Code with Azure extension |
| 6 | AzureCliCredential | `az login` |
| 7 | AzurePowerShellCredential | `Connect-AzAccount` |
| 8 | AzureDeveloperCliCredential | `azd auth login` |
### Customizing DefaultAzureCredential
```python
# 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
)
```
## Specific Credential Types
### ManagedIdentityCredential
For Azure-hosted resources (VMs, App Service, Functions, AKS):
```python
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:
```python
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`:
```python
from azure.identity import AzureCliCredential
credential = AzureCliCredential()
```
### ChainedTokenCredential
Custom credential chain:
```python
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()
)
```
## Credential Types Table
| Credential | Use Case | Auth Method |
|------------|----------|-------------|
| `DefaultAzureCredential` | Most scenarios | Auto-detect |
| `ManagedIdentityCredential` | Azure-hosted apps | Managed Identity |
| `ClientSecretCredential` | Service principal | Client secret |
| `ClientCertificateCredential` | Service principal | Certificate |
| `AzureCliCredential` | Local development | Azure CLI |
| `AzureDeveloperCliCredential` | Local development | Azure Developer CLI |
| `InteractiveBrowserCredential` | User sign-in | Browser OAuth |
| `DeviceCodeCredential` | Headless/SSH | Device code flow |
## Getting Tokens Directly
```python
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")
```
## Async Client
```python
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()
```
## 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
Related in Backend & APIs
jfrog
IncludedInteract with the JFrog Platform via the JFrog CLI and REST/GraphQL APIs. Use this skill when the user wants to manage Artifactory repositories, upload or download artifacts, manage builds, configure permissions, manage users and groups, work with access tokens, configure JFrog CLI servers, search artifacts, manage properties, set up replication, manage JFrog Projects, run security audits or scans, look up CVE details, query exposures scan results from JFrog Advanced Security, manage release bundles and lifecycle operations, aggregate or export platform data, or perform any JFrog Platform administration task. Also use when the user mentions jf, jfrog, artifactory, xray, distribution, evidence, apptrust, onemodel, graphql, workers, mission control, curation, advanced security, exposures, or any JFrog product name.
cupynumeric-migration-readiness
IncludedPre-migration readiness assessor for porting NumPy to cuPyNumeric. Use BEFORE substantial porting work begins when the user asks whether code will scale on GPU, whether they should migrate to cuPyNumeric, which NumPy patterns transfer cleanly, what must be refactored before porting, or mentions pre-port assessment, scaling analysis, or refactor planning. Inspect the user's source code, look up NumPy usage, cross-reference the cuPyNumeric API support manifest, and distinguish distributed-scaling-friendly patterns from blockers such as unsupported APIs, scalar synchronization, host round-trips, Python/object-heavy control flow, shape/data-dependent branching, and in-place mutation hazards. Produce a verdict of READY, LIGHT REFACTOR, SIGNIFICANT REFACTOR, or NOT RECOMMENDED, with concrete refactor pointers.
alibabacloud-data-agent-skill
IncludedInvoke Alibaba Cloud Apsara Data Agent for Analytics via CLI to perform natural language-driven data analysis on enterprise databases. Data Agent for Analytics is an intelligent data analysis agent developed by Alibaba Cloud Database team for enterprise users. It automatically completes requirement analysis, data understanding, analysis insights, and report generation based on natural language descriptions. This tool supports: discovering data resources (instances/databases/tables) managed in DMS, initiating query or deep analysis sessions, real-time progress tracking, and retrieving analysis conclusions and generated reports. Use this Skill when users need to query databases, analyze data trends, generate data reports, ask questions in natural language, or mention "Data Agent", "data analysis", "database query", "SQL analysis", "data insights".
token-optimizer
IncludedReduce OpenClaw token usage and API costs through smart model routing, heartbeat optimization, budget tracking, and native 2026.2.15 features (session pruning, bootstrap size limits, cache TTL alignment). Use when token costs are high, API rate limits are being hit, or hosting multiple agents at scale. The 4 executable scripts (context_optimizer, model_router, heartbeat_optimizer, token_tracker) are local-only — no network requests, no subprocess calls, no system modifications. Reference files (PROVIDERS.md, config-patches.json) document optional multi-provider strategies that require external API keys and network access if you choose to use them. See SECURITY.md for full breakdown.
resend-cli
IncludedUse this skill when the task is specifically about operating Resend from an AI agent, terminal session, or CI job via the official resend CLI: installing/authenticating the CLI, sending/listing/updating/cancelling emails, batch sends, domains and DNS, webhooks and local listeners, inbound receiving, contacts, topics, segments, broadcasts, templates, API keys, profiles, or debugging Resend CLI/API failures. Trigger on mentions of Resend CLI, `resend`, `resend doctor`, `resend emails send`, `resend domains`, `resend webhooks listen`, `resend emails receiving`, or agent-friendly terminal automation.
alibabacloud-odps-maxframe-coding
IncludedUse this skill for MaxFrame SDK development and documentation navigation on Alibaba Cloud MaxCompute (ODPS). Helps answer MaxFrame API, concept, official example, and supported pandas API questions; create data processing programs; read/write MaxCompute tables; debug jobs (remote or local); and build custom DPE runtime images. Trigger when users mention MaxFrame, MaxCompute with MaxFrame, ODPS table processing, DPE runtime, MaxFrame docs/examples, DataFrame/Tensor operations, or GPU runtime setup. Works for both English and Chinese queries about Alibaba Cloud data processing with MaxFrame.