Name: Data Model Analyzer
Author: JaviMontano

Reverse-engineer and evaluate database schemas, ORM models, migration histories, and entity relationships for correctness, normalization, and evolution patterns.

Guiding Principle

"Data outlives code. A flawed data model is the most expensive debt to pay."

Procedure

Step 1 — Schema Discovery

Locate ORM model definitions (Prisma schema, Django models, TypeORM entities, SQLAlchemy models).
Find raw migration files and SQL schema definitions.
Identify database types: relational (PostgreSQL, MySQL), document (MongoDB), key-value (Redis), graph (Neo4j).
Map each entity with its fields, types, constraints, and indexes [HECHO].
Detect multi-database configurations.

Step 2 — Relationship Mapping

Reverse-engineer and evaluate database schemas, ORM models, migration histories, and entity relationships for correctness, normalization, and evolution patterns.

Guiding Principle

"Data outlives code. A flawed data model is the most expensive debt to pay."

Procedure

Step 1 — Schema Discovery

Locate ORM model definitions (Prisma schema, Django models, TypeORM entities, SQLAlchemy models).
Find raw migration files and SQL schema definitions.
Identify database types: relational (PostgreSQL, MySQL), document (MongoDB), key-value (Redis), graph (Neo4j).
Map each entity with its fields, types, constraints, and indexes [HECHO].
Detect multi-database configurations.

Data Model Analyzer

Guiding Principle

Procedure

Step 1 — Schema Discovery

Step 2 — Relationship Mapping

Data Model Analyzer

Guiding Principle

Procedure

Step 1 — Schema Discovery

Step 2 — Relationship Mapping

Step 3 — Migration Health

Step 4 — Quality Assessment

Quality Criteria

Anti-Patterns

Postgres Patterns

Postgres Patterns

Database Migrations

Postgres Patterns

Postgres Patterns

Jpa Patterns