What is the primary output of the Design skill?

The skill generates a comprehensive architecture-doc.md file that includes architectural patterns, component designs, data models, API specs, and testing strategies.

Does this skill only work for Python projects?

While the examples and data modeling templates are optimized for Python and Pydantic, the architectural principles and REST API design patterns are applicable to any programming language.

How does it handle API documentation?

It provides templates for defining RESTful resources, HTTP methods, request/response schemas, and standardized error response formats.

At what stage of development should I use the Design skill?

It is designed to be used after requirements analysis is complete but before implementation begins, ensuring a clear technical roadmap is in place.

System Architecture & API Design

Name: System Architecture & API Design
Author: matteocervelli

bymatteocervelli

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Desarrollo de API

Designs robust software architecture, API contracts, and data models to bridge the gap between requirements and implementation.

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This skill provides a systematic framework for translating analyzed requirements into actionable technical designs, covering everything from high-level architectural patterns to detailed Pydantic data models. It guides the user through creating API contracts, sequence diagrams, and module structures, ensuring that Claude produces consistent, well-organized, and testable codebases. By standardizing the design phase, it helps developers maintain high architectural standards and clear documentation before beginning any implementation.

Características Principales

Pydantic-based data model definition with validation and relationship mapping
15 GitHub stars
Architectural pattern selection including Layered, Modular, and Event-Driven systems
Standardized RESTful and internal API contract specification
Data flow mapping using sequence diagram logic for complex workflows
Module boundary and dependency injection design for improved testability

Casos de Uso

Standardizing API contracts and error handling hierarchies across a project
Designing complex data models and validation logic using Pydantic schemas
Defining technical architecture and module boundaries for new feature implementation

Acerca de

Características Principales

Pydantic-based data model definition with validation and relationship mapping
15 GitHub stars
Architectural pattern selection including Layered, Modular, and Event-Driven systems
Standardized RESTful and internal API contract specification
Data flow mapping using sequence diagram logic for complex workflows
Module boundary and dependency injection design for improved testability

Casos de Uso

Standardizing API contracts and error handling hierarchies across a project
Designing complex data models and validation logic using Pydantic schemas
Defining technical architecture and module boundaries for new feature implementation