Enforce Python coding conventions with Ruff linting and Pyright type checking.
npx skills add https://github.com/mesca/claude-plugins --skill conventions-mesca
Please help me install this Agent Skill. Skill: conventions Source: https://github.com/mesca/claude-plugins/tree/main/plugins/wf/skills/conventions Command: npx skills add https://github.com/mesca/claude-plugins --skill conventions-mesca
Consistent coding conventions remove ambiguity and improve readability, maintainability, and collaboration across Python projects by standardizing structure, typing, logging, and documentation practices.
Start by aligning your project with the recommended src-layout, enabling proper typing, and applying the logging conventions described.
High-intent search queries and answers about installing and using this skill.
To standardize Python coding conventions, adopt a src-layout and enforce typing, Google-style docstrings, and centralized logging practices. This removes ambiguity and improves readability, maintainability, and collaboration across your codebase.
The best way to enforce Python typing and linting is configuring Ruff for linting and Pyright for type checking. These tools catch issues early and ensure code quality consistency across your contracts, core, models, services, and interfaces modules.
You need Ruff and Pyright to maintain Python coding conventions effectively. Configuring Ruff for linting and Pyright for type checking ensures code quality, enforces typing guidelines, and automates the detection of structural inconsistencies across your project.
Centralized logging improves Python project maintainability by standardizing error handling and logging practices across all modules. Consistent logging conventions boost reliability and ensure structured outputs across contracts, core, models, services, and interfaces.
Yes, you can apply Google-style docstrings to existing Python services and interfaces to improve API clarity and tooling support. Enforcing these docstrings alongside typing guidelines ensures consistent documentation practices across your entire project structure.
Your Python project structure needs separate contracts and models directories to provide a clear layout that standardizes project structure. This separation enforces consistent coding conventions, improves readability, and standardizes structure across modules.
mntheCreate a Python automation project scaffold with docs, src, and tests directories.
Vasallo94Format, lint, and type check Python projects with Ruff and Pyright.
jrmatherlyStandardize API error handling with structured AppError classes and middleware.
ekremmkasapEnforce Python code style with ruff, mypy, and Google-style docstrings.
