azure-kusto

Execute KQL queries against Azure Data Explorer clusters and databases.

66|41|Updated Mar 4, 2026
One-click install
npx skills add https://github.com/olivomarco/vbd-copilot --skill azure-kusto-olivomarco
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: azure-kusto
Source: https://github.com/olivomarco/vbd-copilot/tree/main/skills/azure-kusto
Command: npx skills add https://github.com/olivomarco/vbd-copilot --skill azure-kusto-olivomarco

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill lets you run fast, scalable KQL queries against Azure Data Explorer (ADX) to analyze logs, telemetry, and time-series data without manual scripting.

Core Features & Use Cases

  • Execute Kusto Query Language (KQL) queries against clusters and databases to fetch, filter, and aggregate data.
  • Discover table schemas, relationships, and data types to plan queries and dashboards.
  • Analyze logs, IoT telemetry, and security data for time-series insights, anomaly detection, and operational monitoring.

Quick Start

Run a basic KQL query on my ADX cluster to fetch the most recent telemetry events.

Frequently Asked Questions about azure-kusto

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I run KQL queries against Azure Data Explorer without manual scripting?

You can execute KQL queries directly against Azure Data Explorer clusters by providing your subscription context, cluster, database, and query string to retrieve logs and telemetry without writing manual scripts.

Can I analyze time-series telemetry data in Azure Data Explorer using KQL?

Yes, KQL queries can perform time-series analysis on telemetry and IoT data, enabling anomaly detection and operational monitoring by aggregating events across specified time ranges within your ADX database.

What do I need to discover table schemas in Azure Data Explorer?

To discover table schemas, data types, and relationships, you provide your subscription context along with the target cluster and database, allowing the query process to return schema details for planning dashboards.

Does this approach support joining data across multiple tables in Log Analytics?

Yes, simple joins are supported for cross-table insights, allowing you to correlate logs, telemetry, and security events across multiple tables within your specified Azure Data Explorer database.

What's the best way to shape and paginate large query results from ADX?

You can use optional parameters like time range, pagination, and result shaping when executing your KQL query to manage and format large telemetry datasets returned from Azure Data Explorer.