Is this skill suitable for existing projects?

Absolutely. It can be used to refactor monolithic code into more maintainable service layers or to add standardized testing and validation to an existing FastAPI app.

How does this skill ensure code quality?

It follows a strict workflow including architectural design, layered logic separation, and a mandatory verification checklist using ruff and pytest.

What technology stack does this skill support?

The skill defaults to Python 3.10+, FastAPI, Pydantic v2, SQLAlchemy, Alembic, and the uv/ruff/pytest toolchain, though it can be adapted to user overrides.

Does this skill help with database management?

Yes, it provides specific guidance on implementing repository patterns and managing schema changes via SQLAlchemy and Alembic migrations.

Backend Engineering Playbook

Name: Backend Engineering Playbook
Author: Tendo33

byTendo33

0•

Desarrollo de API

Implements production-grade backend APIs and services using structured architectural patterns and data safety standards.

The Backend Engineering Playbook is a specialized skill designed to standardize the development of robust Python-based services. It enforces a layered architecture—separating concerns across API, service, repository, and domain layers—to ensure codebases remain maintainable and scalable. By leveraging a modern stack including FastAPI and Pydantic v2, the skill prioritizes type safety, explicit error handling, and transaction boundaries. It streamlines the development lifecycle by integrating automated verification steps such as linting, formatting, and unit testing, ensuring that every backend change is predictable and production-ready.

Características Principales

01Automated code quality verification using uv, ruff, and pytest

02Layered architecture enforcement (API, Service, Repository, Domain)

030 GitHub stars

04Standardized FastAPI and Pydantic v2 implementation patterns

05Security-first logging and explicit transaction boundary management

06Robust database migration management with SQLAlchemy and Alembic

Casos de Uso

01Ensuring consistent data validation and migration workflows across team projects

02Refactoring existing backend logic into clean, testable architectural layers

03Building scalable, type-safe RESTful APIs from scratch using FastAPI

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add tendo33/ideago backend-engineering-playbook

For use in Claude.ai and ChatGPT

Download Skill