.github/plugins/azure-skills/skills/azure-storage/SKILL.md
Azure Storage Services including Blob Storage, File Shares, Queue Storage, Table Storage, and Data Lake. Provides object storage, SMB file shares, async messaging, NoSQL key-value, and big data analytics capabilities. Includes access tiers (hot, cool, archive) and lifecycle management. USE FOR: blob storage, file shares, queue storage, table storage, data lake, upload files, download blobs, storage accounts, access tiers, lifecycle management. DO NOT USE FOR: SQL databases, Cosmos DB (use azure-prepare), messaging with Event Hubs or Service Bus (use azure-messaging).
npx skillsauth add microsoft/skills azure-storageInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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| Service | Use When | MCP Tools | CLI |
|---------|----------|-----------|-----|
| Blob Storage | Objects, files, backups, static content | azure__storage | az storage blob |
| File Shares | SMB file shares, lift-and-shift | - | az storage file |
| Queue Storage | Async messaging, task queues | - | az storage queue |
| Table Storage | NoSQL key-value (consider Cosmos DB) | - | az storage table |
| Data Lake | Big data analytics, hierarchical namespace | - | az storage fs |
When Azure MCP is enabled:
azure__storage with command storage_account_list - List storage accountsazure__storage with command storage_container_list - List containers in accountazure__storage with command storage_blob_list - List blobs in containerazure__storage with command storage_blob_get - Download blob contentazure__storage with command storage_blob_put - Upload blob contentIf Azure MCP is not enabled: Run /azure:setup or enable via /mcp.
# List storage accounts
az storage account list --output table
# List containers
az storage container list --account-name ACCOUNT --output table
# List blobs
az storage blob list --account-name ACCOUNT --container-name CONTAINER --output table
# Download blob
az storage blob download --account-name ACCOUNT --container-name CONTAINER --name BLOB --file LOCAL_PATH
# Upload blob
az storage blob upload --account-name ACCOUNT --container-name CONTAINER --name BLOB --file LOCAL_PATH
| Tier | Use Case | Performance | |------|----------|-------------| | Standard | General purpose, backup | Milliseconds | | Premium | Databases, high IOPS | Sub-millisecond |
| Tier | Access Frequency | Cost | |------|-----------------|------| | Hot | Frequent | Higher storage, lower access | | Cool | Infrequent (30+ days) | Lower storage, higher access | | Cold | Rare (90+ days) | Lower still | | Archive | Rarely (180+ days) | Lowest storage, rehydration required |
| Type | Durability | Use Case | |------|------------|----------| | LRS | 11 nines | Dev/test, recreatable data | | ZRS | 12 nines | Regional high availability | | GRS | 16 nines | Disaster recovery | | GZRS | 16 nines | Best durability |
For deep documentation on specific services:
For building applications with Azure Storage SDKs, see the condensed guides:
For full package listing across all languages, see SDK Usage Guide.
For building applications that interact with Azure Storage programmatically, Azure provides SDK packages in multiple languages (.NET, Java, JavaScript, Python, Go, Rust). See SDK Usage Guide for package names, installation commands, and quick start examples.
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".