From azure-agent-skills
Provides expert guidance for Azure Data Explorer (ADX) development including troubleshooting, best practices, architecture, security, and deployment. Activates when working with ADX clusters, private endpoints, ingestion, or Power BI integration.
How this skill is triggered — by the user, by Claude, or both
Slash command
/azure-agent-skills:azure-data-explorerThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
This skill provides expert guidance for Azure Data Explorer. Covers troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. It combines local quick-reference content with remote documentation fetching capabilities.
This skill provides expert guidance for Azure Data Explorer. Covers troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. It combines local quick-reference content with remote documentation fetching capabilities.
IMPORTANT for Agent: Use the Category Index below to locate relevant sections. For categories with line ranges (e.g.,
L35-L120), useread_filewith the specified lines. For categories with file links (e.g.,[security.md](security.md)), useread_fileon the linked reference file
IMPORTANT for Agent: If
metadata.generated_atis more than 3 months old, suggest the user pull the latest version from the repository. Ifmcp_microsoftdocstools are not available, suggest the user install it: Installation Guide
This skill requires network access to fetch documentation content:
mcp_microsoftdocs:microsoft_docs_fetch with query string from=learn-agent-skill. Returns Markdown.fetch_webpage with query string from=learn-agent-skill&accept=text/markdown. Returns Markdown.| Category | Lines | Description |
|---|---|---|
| Troubleshooting | L37-L48 | Diagnosing and fixing ADX cluster health, creation, connection, private endpoint, ingestion, and DB/table operation errors, including interpreting ingestion error codes and using Resource Health. |
| Best Practices | L49-L59 | Guidance on ADX performance and reliability: schema design, handling duplicates, JSON ingestion, monitoring queued ingestion, hot/cold data querying, high concurrency, and Power BI integration. |
| Decision Making | L60-L74 | Guidance on ADX cluster sizing and SKUs, cost and reservations, business continuity, confidential/isolated compute, streaming ingestion choices, and migrating from Elasticsearch. |
| Architecture & Design Patterns | L75-L81 | Patterns for ADX deployment: regional DR and replication, cross-cluster access via follower DBs, and multitenant cluster/database design choices. |
| Limits & Quotas | L82-L91 | Cluster limits and behaviors: free cluster quotas, auto-stop, safe delete/recover, ingestion file size and invalid data handling, and supported data/compression formats. |
| Security | L92-L119 | Configuring ADX security: auth/RBAC, managed identities, encryption/CMK, network isolation (private endpoints, outbound/public access), policies, compliance, and data privacy (purge). |
| Configuration | L120-L133 | Configuring ADX clusters, schemas, policies, plugins, and data connections, plus emulator setup, KQL/T-SQL use, monitoring refs, and web UI settings/profiles/shortcuts. |
| Integrations & Coding Patterns | L134-L167 | Integrating ADX with tools and services (SQL, ODBC/JDBC, Power Automate/Apps, Logic Apps, Grafana, Splunk, OpenTelemetry, Functions, Purview) and coding/query patterns for these connectors. |
| Deployment | L168-L174 | Provisioning and automating ADX environments, deploying schema via Azure DevOps, and migrating clusters to availability zones and from VNet injection to private endpoints. |
| Topic | URL |
|---|---|
| Handle duplicate data in Azure Data Explorer | https://learn.microsoft.com/en-us/azure/data-explorer/dealing-with-duplicates |
| Optimize Azure Data Explorer clusters for high-concurrency workloads | https://learn.microsoft.com/en-us/azure/data-explorer/high-concurrency |
| Use hot windows to efficiently query cold data in Azure Data Explorer | https://learn.microsoft.com/en-us/azure/data-explorer/hot-windows |
| Ingest JSON into Azure Data Explorer with KQL, C#, and Python | https://learn.microsoft.com/en-us/azure/data-explorer/ingest-json-formats |
| Monitor queued ingestion metrics in ADX | https://learn.microsoft.com/en-us/azure/data-explorer/monitor-queued-ingestion |
| Apply Power BI best practices for Azure Data Explorer | https://learn.microsoft.com/en-us/azure/data-explorer/power-bi-best-practices |
| Optimize Azure Data Explorer table schema design | https://learn.microsoft.com/en-us/azure/data-explorer/schema-best-practice |
| Topic | URL |
|---|---|
| Design ADX regional DR and replication solutions | https://learn.microsoft.com/en-us/azure/data-explorer/business-continuity-create-solution |
| Use follower databases for cross-cluster ADX access | https://learn.microsoft.com/en-us/azure/data-explorer/follower |
| Choose multitenant architectures for Azure Data Explorer | https://learn.microsoft.com/en-us/azure/data-explorer/multi-tenant |
| Topic | URL |
|---|---|
| Understand automatic stop behavior for inactive clusters | https://learn.microsoft.com/en-us/azure/data-explorer/auto-stop-clusters |
| Apply Event Grid ingestion file size limits in Azure Data Explorer | https://learn.microsoft.com/en-us/azure/data-explorer/create-event-grid-connection |
| Delete and recover Azure Data Explorer clusters safely | https://learn.microsoft.com/en-us/azure/data-explorer/delete-cluster |
| Understand invalid data behavior during ADX ingestion | https://learn.microsoft.com/en-us/azure/data-explorer/ingest-invalid-data |
| Supported data and compression formats for Azure Data Explorer ingestion | https://learn.microsoft.com/en-us/azure/data-explorer/ingestion-supported-formats |
| Upgrade free Azure Data Explorer clusters and remove limits | https://learn.microsoft.com/en-us/azure/data-explorer/start-for-free-upgrade |
| Topic | URL |
|---|---|
| Automate provisioning of Azure Data Explorer environments | https://learn.microsoft.com/en-us/azure/data-explorer/automated-deploy-overview |
| Use Azure DevOps pipelines for Azure Data Explorer schema deployment | https://learn.microsoft.com/en-us/azure/data-explorer/devops |
| Migrate Azure Data Explorer clusters to availability zones | https://learn.microsoft.com/en-us/azure/data-explorer/migrate-cluster-to-multiple-availability-zone |
| Migrate Azure Data Explorer VNet injection to private endpoints | https://learn.microsoft.com/en-us/azure/data-explorer/security-network-migrate-vnet-to-private-endpoint |
npx claudepluginhub microsoftdocs/agent-skills --plugin azure-agent-skillsQueries and analyzes data in Azure Data Explorer (Kusto/ADX) using KQL for log analytics, telemetry, time series, and anomaly detection.
Run read-only KQL queries against Fabric Eventhouse for real-time intelligence and time-series analytics using az rest. Covers schema discovery, query monitoring, and JSON export.
Azure Stream Analytics skill covering troubleshooting, best practices, architecture, patterns, security, and deployment. Use when building ASA jobs with Event Hubs, Cosmos DB, SQL, ML, IoT Edge, or Power BI.