How do I install the Azure Kusto skill?

Run npx skillmds@latest add jonathan-vella/azure-kusto in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

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Is Azure Kusto free to use?

Yes. Installing skills from SkillMD is free. This skill is licensed under MIT.

Who published Azure Kusto?

jonathan-vella (@jonathan-vella) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Azure Kusto by jonathan-vella — Agent Skill

Name: Azure Kusto
Author: jonathan-vella

Azure Kusto

**ANALYSIS SKILL** — Query and analyze data in Azure Data Explorer (Kusto/ADX) using KQL. WHEN: "KQL queries", "Kusto database queries", "Azure Data Explorer", "ADX clusters", "time series data", "IoT telemetry", "anomaly detection". DO NOT USE FOR: App Insights / Log Analytics troubleshooting (azure-diagnostics), cost analysis (azure-cost-optimization).

File contents

Azure Data Explorer (Kusto) Query & Analytics

Execute KQL queries against Azure Data Explorer for fast, scalable big-data analytics on log, telemetry, and time-series data.

Prerequisites

Azure CLI authenticated (az login) with a subscription containing Kusto resources
RBAC: AllDatabasesViewer on the cluster, or Database Viewer per database
Azure MCP server configured in .vscode/mcp.json for the mcp_azure-mcp_kusto namespace; CLI fallback in references/fallback-strategy.md

Steps

Discover resources — list clusters and databases in the subscription
Explore schema — kusto_table_schema_get for table structure
Query data — kusto_query with a KQL expression
Analyse results — aggregate, visualise, export

Query Patterns Quick Reference

Pattern	Use For
Basic Data Retrieval	Quick inspection, recent events
Aggregation Analysis	Counting, distribution, top-N
Time Series Analytics	Performance monitoring, trends
Join and Correlation	Root-cause analysis, event tracing
Schema Discovery	Data model exploration

For full KQL syntax, examples, best practices, and performance tips, read references/query-patterns.md.

Rules

Always include a time-range filter (where Timestamp > ago(...)) on time-series tables
Use take/limit for exploratory queries
Filter early (where before join / summarize)
Use summarize for aggregations; bin() for time bucketing
Use project to select only needed columns

MCP Tools

Tool	Purpose
`kusto_cluster_list`	List Kusto clusters in a subscription
`kusto_database_list`	List databases in a cluster
`kusto_query`	Execute KQL against a database
`kusto_table_schema_get`	Retrieve table schema

Required parameters: subscription, cluster, database, query (or table). Optional: resource-group, tenant.

For CLI fallback (timeouts, auth failures), read references/fallback-strategy.md.

Reference Index

Reference	When to Load
`references/query-patterns.md`	KQL patterns, examples, best practices, common functions
`references/fallback-strategy.md`	CLI commands and REST API fallback when MCP tools fail

---name: azure-kustodescription: **ANALYSIS SKILL** — Query and analyze data in Azure Data Explorer (Kusto/ADX) using KQL. WHEN: "KQL queries", "Kusto database queries", "Azure Data Explorer", "ADX clusters", "time series data", "IoT telemetry", "anomaly detection". DO NOT USE FOR: App Insights / Log Analytics troubleshooting (azure-diagnostics), cost analysis (azure-cost-optimization).license: MIT---# Azure Data Explorer (Kusto) Query & AnalyticsExecute KQL queries against Azure Data Explorer for fast, scalable big-dataanalytics on log, telemetry, and time-series data.## Prerequisites- **Azure CLI** authenticated (`az login`) with a subscription containing Kusto resources- **RBAC**: `AllDatabasesViewer` on the cluster, or `Database Viewer` per database- **Azure MCP server** configured in `.vscode/mcp.json` for the `mcp_azure-mcp_kusto` namespace; CLI fallback in [`references/fallback-strategy.md`](references/fallback-strategy.md)## Steps1. **Discover resources** — list clusters and databases in the subscription2. **Explore schema** — `kusto_table_schema_get` for table structure3. **Query data** — `kusto_query` with a KQL expression4. **Analyse results** — aggregate, visualise, export## Query Patterns Quick Reference| Pattern | Use For || --------------------- | ---------------------------------- || Basic Data Retrieval | Quick inspection, recent events || Aggregation Analysis | Counting, distribution, top-N || Time Series Analytics | Performance monitoring, trends || Join and Correlation | Root-cause analysis, event tracing || Schema Discovery | Data model exploration |For full KQL syntax, examples, best practices, and performance tips, read[`references/query-patterns.md`](references/query-patterns.md).## Rules- Always include a time-range filter (`where Timestamp > ago(...)`) on time-series tables- Use `take`/`limit` for exploratory queries- Filter early (`where` before `join` / `summarize`)- Use `summarize` for aggregations; `bin()` for time bucketing- Use `project` to select only needed columns## MCP Tools| Tool | Purpose || ------------------------ | ------------------------------------------------------- || `kusto_cluster_list` | List Kusto clusters in a subscription || `kusto_database_list` | List databases in a cluster || `kusto_query` | Execute KQL against a database || `kusto_table_schema_get` | Retrieve table schema |Required parameters: `subscription`, `cluster`, `database`, `query` (or `table`).Optional: `resource-group`, `tenant`.For CLI fallback (timeouts, auth failures), read[`references/fallback-strategy.md`](references/fallback-strategy.md).## Reference Index| Reference | When to Load || --------------------------------- | -------------------------------------------------------- || `references/query-patterns.md` | KQL patterns, examples, best practices, common functions || `references/fallback-strategy.md` | CLI commands and REST API fallback when MCP tools fail |

Frequently asked questions