kql-query-authoring

Generating production-ready KQL queries for Microsoft Sentinel involves using schema validation and official Microsoft Learn patterns to ensure correct table names, validate column types, and return ready-to-run queries with testing guidance.

Schema validation for KQL queries in Defender XDR works by leveraging MCP servers to check table names and column types, ensuring the generated query is structurally sound and compatible before execution.

Yes, you need MCP servers to validate Azure Data Explorer KQL queries, as the skill enforces MCP-based schema checks as a prerequisite to ensure correct table names and column types before returning the final query.

You can generate queries compatible with both Sentinel and Defender XDR, but the skill provides specific guidance to adapt for platform-specific differences to ensure the KQL runs correctly in each environment.

The best way to write a KQL query for failed sign-ins in the last 24 hours is to use schema-driven generation that applies official Microsoft Learn code samples and community examples to target your specific environment table.