modo-carreira-padrao

Name: modo-carreira-padrao
Availability: InStock
Author: slooowlly

Standardize Python code modifications with layered architecture and snake_case conventions.

Updated Aug 23, 2026

Search Tags:#code quality #architecture #python #standardization #maintenance #pyside6

Ready to run

npx skills add https://github.com/Slooowlly/meu-modo-carreira-v4 --skill modo-carreira-padrao

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: modo-carreira-padrao
Source: https://github.com/Slooowlly/meu-modo-carreira-v4/tree/main
Command: npx skills add https://github.com/Slooowlly/meu-modo-carreira-v4 --skill modo-carreira-padrao

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill ensures technical consistency across the "Modo Carreira" project by enforcing architectural patterns, naming conventions, and safe data migrations, thereby reducing technical debt and improving maintainability.

Core Features & Use Cases

Architectural Enforcement: Maintains a strict layered architecture (Dados/Logica/UI/Utils).
Code Quality: Enforces naming conventions (snake_case), docstrings, and type hints.
Data Integrity: Ensures safe JSON schema migrations and consistent data handling.
Testing: Integrates with automated pattern auditing and unit tests.
Use Case: When adding a new feature to the race simulation logic, this Skill guides the developer to implement it within the Logica/ layer, use proper type hints, add docstrings, and run the auditar_padrao.py script to ensure compliance before committing.

Quick Start

Use the modo-carreira-padrao skill to standardize code changes in the project.

Frequently Asked Questions about modo-carreira-padrao

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

FAQPage Schema

How do I enforce layered architecture in a Python project to reduce technical debt?▼

Enforce layered architecture in Python by separating code into Dados, Logica, UI, and Utils layers. This standardization reduces technical debt by ensuring strict separation of concerns and improving overall project maintainability.

How do I standardize Python code modifications with snake_case and type hints?▼

Standardize Python code modifications by enforcing snake_case naming conventions, mandatory type hints, and docstrings across all new changes. This ensures consistent code quality and reduces maintenance overhead during feature development.

How do I perform safe JSON schema migrations in Python without breaking existing data?▼

Safe JSON schema migrations in Python require consistent data handling and schema validation before applying changes. Enforcing safe migration patterns prevents data corruption and ensures backward compatibility when modifying data structures.

Does PySide6 work well with strict layered architecture for UI separation?▼

PySide6 integrates effectively with strict layered architecture by isolating all interface components within the UI layer. This separation ensures that interface logic remains decoupled from data and business logic, maintaining code standardization.

How do I automate pattern auditing for Python code standardization?▼

Automate pattern auditing for Python code standardization by running the auditar_padrao.py script before committing changes. This script automatically checks code against architectural patterns, naming conventions, and type hint requirements to ensure compliance.

What are the limitations of enforcing strict code standardization in Python projects?▼

Enforcing strict code standardization in Python projects limits rapid prototyping flexibility by requiring mandatory docstrings, type hints, and architectural compliance checks before commits. This overhead is a trade-off for achieving long-term maintainability and consistent code quality.