entity-model-auditor

To audit a database schema against a PRD, compare PRD requirements with existing fields and classify them as table columns, config values, runtime-computed data, or removals. This structured audit identifies field necessity, storage placement, and required migrations.

Deciding between a data column and configuration requires applying structured storage design rules to evaluate necessity and placement. This process determines whether to store, compute, use columns, or use configuration blobs while documenting the design rationale.

Plan database migrations by generating an actionable change list covering renames, additions, removals, storage moves, and API gaps. This tracks data model evolution requirements and ensures reliable schema updates.

Yes, structured audit tables are required to review entity design and evaluate field necessity. They provide the framework to classify fields, apply runtime derivation rules, and document design rationale for data model evolution.

Entity models have bloated or poorly placed fields when schemas are not systematically audited against product requirements. A structured data model audit identifies what should exist, where it should live, and what should change.

Avoid using a configuration blob for data storage when field-by-field analysis indicates the data requires queryability or runtime computation. Apply storage design rules to decide between storing, computing, columns, or configuration blobs.