kql

Write correct and efficient Kusto Query Language queries for Microsoft data services.

2|Updated Jan 23, 2026

Search Tags:#query optimization #data analysis #query language #kql #kusto

Ready to run

npx skills add https://github.com/yunmoxinghe/Docked-AI --skill kql-yunmoxinghe

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: kql
Source: https://github.com/yunmoxinghe/Docked-AI/tree/main/.kiro/skills/kql
Command: npx skills add https://github.com/yunmoxinghe/Docked-AI --skill kql-yunmoxinghe

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill helps you write accurate, efficient Kusto Query Language (KQL) queries, avoiding common pitfalls and optimizing performance.

Core Features & Use Cases

Syntax Best Practices: Learn how to write KQL queries using the correct syntax for joins, dynamic types, and advanced functions.
Performance Optimization: Improve query performance with memory-safe patterns and result size discipline.
Error Recovery: Identify and fix common KQL errors with the provided error recovery table.

Quick Start

Use the kql skill to debug a KQL query that returns an error message about dynamic types.

Frequently Asked Questions about kql

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

FAQPage Schema

How do I write efficient Kusto Query Language queries for Azure Data Explorer?▼

Efficient Kusto Query Language queries require following syntax best practices for joins, applying memory-safe patterns, and maintaining result size discipline to optimize performance in Azure Data Explorer.

Why does my KQL query return a dynamic type error in Azure Monitor Log Analytics?▼

KQL dynamic type errors occur when queries violate dynamic type discipline, but you can identify and fix them using an error recovery table targeting common Kusto Query Language mistakes.

What is the best way to optimize KQL join patterns in Microsoft Fabric Real-Time Intelligence?▼

Optimizing KQL join patterns in Microsoft Fabric Real-Time Intelligence involves applying correct syntax best practices and memory management techniques to avoid performance bottlenecks.

Can I use regex and advanced functions within Kusto Query Language?▼

Yes, Kusto Query Language supports regex usage and advanced functions, providing specific syntax insights to ensure correct implementation across Microsoft data services.

How do I fix common KQL errors related to serialization and memory management?▼

Fix common KQL errors by applying memory-safe patterns, serialization techniques, and consulting the provided error recovery table to address dynamic type and memory management issues.

Does this Kusto Query Language skill work with both Azure Monitor Log Analytics and Microsoft Fabric?▼

Yes, this Kusto Query Language skill targets Azure Data Explorer, Microsoft Fabric Real-Time Intelligence, Azure Monitor Log Analytics, and other Microsoft data services for query optimization.