Why This Matters

Database change requests often move through several handoffs: product owners describe the need, data engineers interpret it, platform teams assess risk, analytics engineers propagate the field downstream, and reviewers check whether the change is safe. Important context can be lost at each step.

SchemaFlow addresses this by turning a free-form change request into a structured, inspectable workflow.

This matters because database changes can create hidden failure modes:

• A column added to ODS may not be propagated into staging, core, or marts.
• A nullable field may accidentally be generated as NOT NULL.
• Backfill logic may be omitted even though the request asks for historical population.
• Index requirements may be missed.
• Downstream reporting dependencies may be unknown unless reference documentation is consulted.
• Generated SQL may look plausible but fail basic consistency checks.

This cookbook shows a pattern for reducing those risks with staged agent reasoning, typed outputs, optional retrieval context, deterministic guardrails, saved artifacts, and repeatable evals.