Eventhouse Consumption Cli
Run KQL queries against Fabric Eventhouse for real-time intelligence and time-series analytics using `az rest` against the Kusto REST API. Covers KQL operators (where, summarize, join, render), Eventhouse schema discovery (.show tables), time-series patterns with bin(), and ingestion monitoring. Use when the user wants to: 1. Run read-only KQL queries against an Eventhouse or KQL Database 2. Discover Eventhouse table schema and metadata 3. Analyse real-time or time-series data with KQL operators 4. Monitor ingestion health and active KQL queries 5. Export KQL results to JSON Triggers: "kql query", "kusto query", "eventhouse query", "kql database", "real-time intelligence", "time-series kql", "query eventhouse", "explore eventhouse", "show tables kql".
30-Second Summary
Eventhouse Consumption Cli is an agent-readable workflow from microsoft/skills-for-fabric for eventhouse consumption cli.
It gives the agent a trigger, ordered guidance, and source-backed checks instead of treating eventhouse consumption cli as a generic tool.
Use it as a brief only while the linked SKILL.md remains available and the risk boundary is still accurate.
1-Minute Read
What it is
Eventhouse Consumption Cli packages instructions from microsoft/skills-for-fabric into a reusable agent skill brief. The original source is a public SKILL.md file, so the brief can point readers back to the executable workflow instead of a product landing page.
When to use it
Use it when a user asks for help around eventhouse consumption cli and the agent needs a repeatable workflow, checklist, or review path rather than broad background information.
How to test it first
Open the linked SKILL.md, confirm the trigger and procedure still match eventhouse consumption cli, list the risk boundary, then ask the agent to apply the smallest read-only step to a sample task.
Watch out
Do not present this as a generic app or platform. Keep the scope tied to microsoft/skills-for-fabric. Risk boundary: CI/CD, deploy, release, rollback, and migration steps must start with read-only inspection and an approval gate; database, Fabric workspace, notebook, lakehouse, warehouse, or Power BI changes need credential and production-data approval; cloud resources, RBAC, credentials, tokens, and private keys must not be changed or exposed without a separate approval; Microsoft Fabric-specific workflow; do not describe it as a generic data engineering skill.