Model Generator

Generate SQLAlchemy ORM models and Pydantic schemas for API development.

Updated Aug 27, 2026
One-click install
npx skills add https://github.com/lwilly3/api.audace --skill model-generator
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: Model Generator
Source: https://github.com/lwilly3/api.audace/tree/main/.github/skills/model-generator
Command: npx skills add https://github.com/lwilly3/api.audace --skill model-generator

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill automates the creation of SQLAlchemy models and Pydantic schemas, ensuring consistency and adherence to project standards, thereby reducing boilerplate code and potential errors in database and API development.

Core Features & Use Cases

  • Boilerplate Reduction: Generates standard SQLAlchemy models and Pydantic schemas based on provided entity names and attributes.
  • Standardization: Enforces project conventions like BaseModel inheritance, soft deletes, timestamps, naming conventions, and relation definitions.
  • Use Case: When adding a new feature that requires a new database entity (e.g., 'Product'), use this Skill to quickly generate the model_product.py and schema_product.py files, pre-configured with all necessary fields and relationships.

Quick Start

Use the model generator skill to create a new SQLAlchemy model and Pydantic schema for an entity named 'Category' with string fields 'name' and 'description'.

Frequently Asked Questions about Model Generator

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

FAQPage Schema
How do I generate SQLAlchemy ORM models and Pydantic schemas for new API entities?

To generate SQLAlchemy ORM models and Pydantic schemas, provide an entity name with its attributes. The Skill outputs pre-configured model and schema files, enforcing project conventions like soft deletes, timestamps, and relationship definitions.

What is the best way to reduce boilerplate code when adding database entities for API development?

The best way to reduce boilerplate code for database entities is to automate generation using standard patterns. This Skill creates SQLAlchemy models and Pydantic schemas with BaseModel inheritance and naming conventions, minimizing manual setup errors.

Can I enforce project-specific conventions like soft delete and timestamps when generating Pydantic schemas?

Yes, you can enforce project-specific conventions like soft delete and timestamp management. The generated Pydantic schemas and SQLAlchemy models automatically adhere to these established patterns, ensuring consistency across your API development.

Does this code generation tool support custom relationship definitions for SQLAlchemy models?

Yes, this code generation tool supports custom relationship definitions for SQLAlchemy models. It automatically configures relationships and naming conventions based on your provided entity attributes, ensuring accurate database mapping and API validation structures.

How do I create a new database model and validation schema for an entity named 'Category' with specific fields?

To create a database model and validation schema for an entity like 'Category', specify the entity name and its string fields. The Skill generates the corresponding SQLAlchemy and Pydantic files pre-configured with all necessary fields.