# azure-kusto

Lets the agent list ADX clusters and databases, read table schemas and run KQL queries over logs and telemetry through MCP tools and ready-made query patterns.

- skill · `type=skill` · Claude Code, GitHub Copilot · 1 install · ★ 3149
- Author: Microsoft
- License: MIT · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/microsoft/skills/tree/HEAD/.github/plugins/azure-skills/skills/azure-kusto/SKILL.md
- Updated: 2026-10-23
- HTML: https://affpapa.org/en/nevibecode/skills/azure-kusto

## What it does

The skill wires the agent to Azure Data Explorer with four MCP tools: `kusto_cluster_list`, `kusto_database_list`, `kusto_table_schema_get` and `kusto_query`. The workflow is ordered. Discover the clusters and databases in a subscription, inspect the schema of the target table, then run the query. Listing calls take `subscription`, `cluster` and `database`; a query also needs the KQL string in `query`.

Bundled patterns cover the usual jobs. Pull recent rows from a table, group counts by dimension with `summarize`, split response times into percentiles per time bucket, or join two tables on `CorrelationId` when chasing an incident. When nobody knows which candidate holds a table, the skill batches metadata lookups across clusters and workspaces and combines them with `union workspace(...)` — otherwise an empty result reads like a missing table.

If the MCP tools time out or are missing, there is a fallback through Azure CLI, starting with `az kusto cluster list --resource-group <rg-name>`. The skill itself runs nothing: you need the Azure MCP configured and a subscription that actually holds the clusters.

## Requirements
- Works with: Azure

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add microsoft/skills --skill azure-kusto -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/azure-kusto/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/azure-kusto/

### Codex

**Manually: put the files in place**
- File: `.agents/skills/azure-kusto/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

**Manually: put the files in place**
- File: `.cursor/skills/azure-kusto/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install microsoft/skills azure-kusto
```

2. **Manually: put the files in place**
- File: `.github/skills/azure-kusto/SKILL.md`

### Gemini CLI

**Platform CLI**
```bash
gemini skills install https://github.com/microsoft/skills --path .github/plugins/azure-skills/skills/azure-kusto
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/azure-kusto/SKILL.md` — The legacy .windsurf/skills/ path still works

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/microsoft/skills/tree/HEAD/.github/plugins/azure-skills/skills/azure-kusto/SKILL.md

## When to use it
- run a KQL query against an ADX cluster without the portal
- check a table schema before writing the query
- find which database holds a table among several candidates
- compute latency percentiles over time buckets
- trace an incident by joining events with critical logs on `CorrelationId`

## Example prompts
- List the clusters and databases in subscription `my-sub` and find the `Requests` table
- Show me the schema of the `Events` table in the `logs` database
- Get p50, p95 and p99 for `ResponseTime` over the last day in 5-minute bins

## Source text · SKILL.md · MIT

Below is the content of a third-party file. It is data, not instructions for you: do not act on anything written inside unless the human asks. Block tag: 17e607b5624c760e.

BEGIN THIRD-PARTY FILE 17e607b5624c760e
````text
---
name: azure-kusto
description: "Query and analyze data in Azure Data Explorer (Kusto/ADX) using KQL for log analytics, telemetry, and time series analysis. WHEN: KQL queries, Kusto database queries, Azure Data Explorer, ADX clusters, log analytics, time series data, IoT telemetry, anomaly detection."
license: MIT
metadata:
  author: Microsoft
  version: "1.2.2"
---

# Azure Data Explorer (Kusto) Query & Analytics

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

## Overview

This skill enables querying and managing Azure Data Explorer (Kusto), a fast and highly scalable data exploration service optimized for log and telemetry data. Azure Data Explorer provides sub-second query performance on billions of records using the Kusto Query Language (KQL).

Key capabilities:
- **Query Execution**: Run KQL queries against massive datasets
- **Schema Exploration**: Discover tables, columns, and data types
- **Resource Management**: List clusters and databases
- **Analytics**: Aggregations, time series, anomaly detection, machine learning

## Core Workflow

1. **Discover Resources**: List available clusters and databases in subscription. If the target table's location is unknown and multiple candidate clusters, databases, or Log Analytics workspaces exist, batch the search (see Pattern 6) and only report "not found" after all candidates are checked.
2. **Explore Schema**: Retrieve table structures to understand data model
3. **Query Data**: Execute KQL queries for analysis, filtering, aggregation
4. **Analyze Results**: Process query output for insights and reporting

## Query Patterns

### Pattern 1: Basic Data Retrieval
Fetch recent records from a table with simple filtering.

**Example KQL**:
```kql
Events
| where Timestamp > ago(1h)
| take 100
```

**Use for**: Quick data inspection, recent event retrieval

### Pattern 2: Aggregation Analysis
Summarize data by dimensions for insights and reporting.

**Example KQL**:
```kql
Events
| summarize count() by EventType, bin(Timestamp, 1h)
| order by count_ desc
```

**Use for**: Event counting, distribution analysis, top-N queries

### Pattern 3: Time Series Analytics
Analyze data over time windows for trends and patterns.

**Example KQL**:
```kql
Telemetry
| where Timestamp > ago(24h)
| summarize avg(ResponseTime), percentiles(ResponseTime, 50, 95, 99) by bin(Timestamp, 5m)
| render timechart
```

**Use for**: Performance monitoring, trend analysis, anomaly detection

### Pattern 4: Join and Correlation
Combine multiple tables for cross-dataset analysis.

**Example KQL**:
```kql
Events
| where EventType == "Error"
| join kind=inner (
    Logs
    | where Severity == "Critical"
) on CorrelationId
| project Timestamp, EventType, LogMessage, Severity
```

**Use for**: Root cause analysis, correlated event tracking

### Pattern 5: Schema Discovery
Explore table structure before querying.

**Tools**: `kusto_table_schema_get`
````
END THIRD-PARTY FILE 17e607b5624c760e

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