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Azure Kusto

Official
microsoft·vlatest·cloud·MIT

Analyze Azure Data Explorer (Kusto) data using natural language queries to gain insights and troubleshoot issues.

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add microsoft/azure-skills --skill azure-kusto -a claude-code
  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

microsoft

Matched to the vendor's own GitHub organisation.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned microsoft/azure-skills at 9bb168c343.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Scanned
2 files, 406 lines
Copies in repo
2 — all of them scanned
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

The Microsoft Azure Kusto skill enables AI agents to interact with and query data using KQL (Kusto Query Language) in Azure Data Explorer. It supports real-time analytics, log management, and monitoring of large datasets across cloud environments.

When to use it

  • Analyzing logs from Azure services for troubleshooting or security audits.
  • Performing ad-hoc queries on structured and unstructured data stored in Azure Data Explorer.
  • Building dashboards and reports based on time-series or event-based data.

Key capabilities

  • Execute KQL queries against Azure Data Explorer clusters.
  • Retrieve, filter, and aggregate large volumes of log and telemetry data.
  • Support for real-time monitoring and alerting via query results.

Example prompts

  • "Run a KQL query to find all error logs from the last 24 hours in the 'app-logs' table."
  • "Generate a report showing user activity trends over the past week using Azure Data Explorer."
  • "Query the 'security-events' table for any unauthorized access attempts in the last 7 days."

Tips & gotchas

  • Ensure your AI agent has proper authentication and permissions to access Azure Data Explorer clusters.
  • KQL queries can be resource-intensive; optimize them for performance when working with large datasets.