.github/plugins/azure-sdk-python/skills/azure-containerregistry-py/SKILL.md
Azure Container Registry SDK for Python. Use for managing container images, artifacts, and repositories. Triggers: "azure-containerregistry", "ContainerRegistryClient", "container images", "docker registry", "ACR".
npx skillsauth add microsoft/skills azure-containerregistry-pyInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
Manage container images, artifacts, and repositories in Azure Container Registry.
pip install azure-containerregistry
AZURE_CONTAINERREGISTRY_ENDPOINT=https://<registry-name>.azurecr.io
from azure.containerregistry import ContainerRegistryClient
from azure.identity import DefaultAzureCredential
client = ContainerRegistryClient(
endpoint=os.environ["AZURE_CONTAINERREGISTRY_ENDPOINT"],
credential=DefaultAzureCredential()
)
from azure.containerregistry import ContainerRegistryClient
client = ContainerRegistryClient(
endpoint="https://mcr.microsoft.com",
credential=None,
audience="https://mcr.microsoft.com"
)
client = ContainerRegistryClient(endpoint, DefaultAzureCredential())
for repository in client.list_repository_names():
print(repository)
properties = client.get_repository_properties("my-image")
print(f"Created: {properties.created_on}")
print(f"Modified: {properties.last_updated_on}")
print(f"Manifests: {properties.manifest_count}")
print(f"Tags: {properties.tag_count}")
from azure.containerregistry import RepositoryProperties
client.update_repository_properties(
"my-image",
properties=RepositoryProperties(
can_delete=False,
can_write=False
)
)
client.delete_repository("my-image")
for tag in client.list_tag_properties("my-image"):
print(f"{tag.name}: {tag.created_on}")
from azure.containerregistry import ArtifactTagOrder
# Most recent first
for tag in client.list_tag_properties(
"my-image",
order_by=ArtifactTagOrder.LAST_UPDATED_ON_DESCENDING
):
print(f"{tag.name}: {tag.last_updated_on}")
from azure.containerregistry import ArtifactManifestOrder
for manifest in client.list_manifest_properties(
"my-image",
order_by=ArtifactManifestOrder.LAST_UPDATED_ON_DESCENDING
):
print(f"Digest: {manifest.digest}")
print(f"Tags: {manifest.tags}")
print(f"Size: {manifest.size_in_bytes}")
manifest = client.get_manifest_properties("my-image", "latest")
print(f"Digest: {manifest.digest}")
print(f"Architecture: {manifest.architecture}")
print(f"OS: {manifest.operating_system}")
from azure.containerregistry import ArtifactManifestProperties
client.update_manifest_properties(
"my-image",
"latest",
properties=ArtifactManifestProperties(
can_delete=False,
can_write=False
)
)
# Delete by digest
client.delete_manifest("my-image", "sha256:abc123...")
# Delete by tag
manifest = client.get_manifest_properties("my-image", "old-tag")
client.delete_manifest("my-image", manifest.digest)
tag = client.get_tag_properties("my-image", "latest")
print(f"Digest: {tag.digest}")
print(f"Created: {tag.created_on}")
client.delete_tag("my-image", "old-tag")
from azure.containerregistry import ContainerRegistryClient
client = ContainerRegistryClient(endpoint, DefaultAzureCredential())
# Download manifest
manifest = client.download_manifest("my-image", "latest")
print(f"Media type: {manifest.media_type}")
print(f"Digest: {manifest.digest}")
# Download blob
blob = client.download_blob("my-image", "sha256:abc123...")
with open("layer.tar.gz", "wb") as f:
for chunk in blob:
f.write(chunk)
from azure.containerregistry.aio import ContainerRegistryClient
from azure.identity.aio import DefaultAzureCredential
async def list_repos():
credential = DefaultAzureCredential()
client = ContainerRegistryClient(endpoint, credential)
async for repo in client.list_repository_names():
print(repo)
await client.close()
await credential.close()
from datetime import datetime, timedelta, timezone
cutoff = datetime.now(timezone.utc) - timedelta(days=30)
for manifest in client.list_manifest_properties("my-image"):
if manifest.last_updated_on < cutoff and not manifest.tags:
print(f"Deleting {manifest.digest}")
client.delete_manifest("my-image", manifest.digest)
| Operation | Description |
|-----------|-------------|
| list_repository_names | List all repositories |
| get_repository_properties | Get repository metadata |
| delete_repository | Delete repository and all images |
| list_tag_properties | List tags in repository |
| get_tag_properties | Get tag metadata |
| delete_tag | Delete specific tag |
| list_manifest_properties | List manifests in repository |
| get_manifest_properties | Get manifest metadata |
| delete_manifest | Delete manifest by digest |
| download_manifest | Download manifest content |
| download_blob | Download layer blob |
tools
KQL language expertise for writing correct, efficient Kusto Query Language queries. Covers syntax gotchas, join patterns, dynamic types, datetime pitfalls, regex patterns, serialization, memory management, result-size discipline, and advanced functions (geo, vector, graph). USE THIS SKILL whenever writing, debugging, or reviewing KQL queries — even simple ones — because the gotchas section prevents the most common errors that waste tool calls and cause expensive retry cascades. Trigger on: KQL, Kusto, ADX, Azure Data Explorer, Fabric Real-Time Intelligence, EventHouse, Log Analytics, log analysis, data exploration, time series, anomaly detection, summarize, where clause, join, extend, project, let statement, parse operator, extract function, any mention of pipe-forward query syntax.
development
Deploy, evaluate, and manage Foundry agents end-to-end: Docker build, ACR push, hosted/prompt agent create, container start, batch eval, prompt optimization, prompt optimizer workflows, agent.yaml, dataset curation from traces. USE FOR: deploy agent to Foundry, hosted agent, create agent, invoke agent, evaluate agent, run batch eval, optimize prompt, improve prompt, prompt optimization, prompt optimizer, improve agent instructions, optimize agent instructions, optimize system prompt, deploy model, Foundry project, RBAC, role assignment, permissions, quota, capacity, region, troubleshoot agent, deployment failure, create dataset from traces, dataset versioning, eval trending, create AI Services, Cognitive Services, create Foundry resource, provision resource, knowledge index, agent monitoring, customize deployment, onboard, availability. DO NOT USE FOR: Azure Functions, App Service, general Azure deploy (use azure-deploy), general Azure prep (use azure-prepare).
testing
Pre-deployment validation for Azure readiness. Run deep checks on configuration, infrastructure (Bicep or Terraform), RBAC role assignments, managed identity permissions, and prerequisites before deploying. WHEN: validate my app, check deployment readiness, run preflight checks, verify configuration, check if ready to deploy, validate azure.yaml, validate Bicep, test before deploying, troubleshoot deployment errors, validate Azure Functions, validate function app, validate serverless deployment, verify RBAC roles, check role assignments, review managed identity permissions, what-if analysis, validate Container Apps deployment.
testing
Check/manage Azure quotas and usage across providers. For deployment planning, capacity validation, region selection. WHEN: "check quotas", "service limits", "current usage", "request quota increase", "quota exceeded", "validate capacity", "regional availability", "provisioning limits", "vCPU limit", "how many vCPUs available in my subscription".