Define reusable warehouse metrics

2. Ask your agent

Paste this into your agent, then provide your task and example inputs when it asks:

/deepline-analytics Prepare a small semantic layer for the metric I describe using the current supported Snowflake connector. Inspect the actual columns and row grain. Validate the proposed definition, then compare a representative semantic query with direct SQL for the same population. Specify filters explicitly; do not assume base filters or relationship annotations are applied automatically. Show the comparison before saving a changed model.

Complete any requested sign-in yourself. Give the agent the missing information before approving execution. Provider-backed work can incur usage.

3. Review the result

The rendered query and returned values match the intended business definition. A valid model file does not establish table existence or metric correctness.

Ask your agent:

/deepline-analytics Compare the result with the acceptance rule we agreed. Show the evidence for accepted and rejected outcomes, unresolved questions, and recorded Deepline usage where work ran. If work is still running or a response is uncertain, inspect the original saved execution before proposing another request. Explain the next decision I need to make.

Approve a larger job, recurring work, or external changes only after reviewing that decision.

No. Ask it to compare representative results with the known query and your intended population and row grain.

How-to guides

Define reusable warehouse metrics

1. Have your context ready

2. Ask your agent

3. Review the result

Check your understanding

​1. Have your context ready

​2. Ask your agent

​3. Review the result

​Check your understanding

​Related guides

1. Have your context ready

2. Ask your agent

3. Review the result

Check your understanding

Related guides