schema-import

Convert database schemas and ETL logic into draft MD-DDL domain models.

1|Updated Feb 7, 2026

Search Tags:#database #schema #data modeling #etl #brownfield #md-ddl

Ready to run

npx skills add https://github.com/Semprini/md-ddl --skill schema-import

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: schema-import
Source: https://github.com/Semprini/md-ddl/tree/main/agents/agent-ontology/skills/schema-import
Command: npx skills add https://github.com/Semprini/md-ddl --skill schema-import

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) and scripts (resource) components.

What problem does it solve?

This Skill automates the conversion of existing database schemas and ETL logic into a draft MD-DDL domain, significantly accelerating brownfield adoption.

Core Features & Use Cases

Schema to Domain Mapping: Infers canonical entities, relationships, and enums from database DDL or schema definitions.
ETL Logic Parsing: Parses SQL, dbt models, or stored procedures to generate draft source transform files.
Use Case: A data team needs to adopt MD-DDL for their existing data warehouse. They use this Skill to automatically generate the initial MD-DDL domain files from their Snowflake schema and dbt models, providing a solid foundation for further refinement.

Quick Start

Use the schema-import skill to convert my existing PostgreSQL schema into an MD-DDL domain.

Frequently Asked Questions about schema-import

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I convert an existing database schema into an MD-DDL domain model?▼

You convert an existing database schema into an MD-DDL domain model by using a schema import process that automatically infers canonical entities, relationships, and enums directly from your DDL, minimizing manual mapping for brownfield adoption.

Can I parse dbt models and SQL scripts to generate source transform files?▼

Yes, you can parse dbt models, SQL scripts, or stored procedures to automatically generate draft source transform files, extracting the existing ETL logic to accelerate the creation of your canonical data models.

What is the best way to migrate Snowflake DDL to a draft MD-DDL domain?▼

The best way to migrate Snowflake DDL to a draft MD-DDL domain is to automate the schema conversion process, which infers entities and relationships from your existing data warehouse schema to provide a solid foundation for further refinement.

Does the schema to domain mapping process support PostgreSQL schemas?▼

Yes, the schema to domain mapping process supports PostgreSQL schemas, allowing you to automatically infer canonical entities, relationships, and enums from your existing DDL to facilitate brownfield adoption of MD-DDL.

What are the limitations of automatically inferring entities and relationships from DDL?▼

Automatically inferring entities and relationships from DDL produces a draft MD-DDL domain model that serves as a solid foundation, but it still requires further manual refinement to ensure the canonical data models accurately reflect complex business logic.