Does it support multiple programming languages?

Yes, it is designed to work with various ecosystems by looking for standard configuration files like package.json for JavaScript/TypeScript, pyproject.toml for Python, and .editorconfig for general settings.

What happens if my codebase has inconsistent conventions?

The skill follows a priority system: it prefers newer code, actively maintained modules, and explicit documentation like CLAUDE.md or config files over older, inconsistent patterns.

Can it help with testing and error handling?

Absolutely. It specifically looks for existing test file locations, assertion styles, and try-catch patterns to ensure new code handles errors and tests exactly like the rest of your project.

How does the skill identify project-specific patterns?

The skill performs a discovery process that scans configuration files like ESLint and Prettier, analyzes directory structures via shell commands, and uses grep to find recurring naming and import patterns in existing source code.

Project Conventions

Name: Project Conventions
Author: sequenzia

bysequenzia

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Herramientas para Desarrolladores

Discovers and applies project-specific coding patterns, naming conventions, and architectural structures to ensure AI-generated code remains consistent.

The Project Conventions skill enables Claude to automatically identify and adhere to the unique standards of any codebase. By scanning configuration files, analyzing existing directory structures, and searching for implicit naming patterns, this skill ensures that new features blend seamlessly into your project. It is essential for maintaining high code quality and consistency, especially when working across diverse repositories with varying styles for error handling, testing, and file organization.

Características Principales

01Automated discovery of linting and formatting rules from project config files

02Comprehensive verification checklist for style, structure, and testing consistency

031 GitHub stars

04Contextual search for similar features to mirror existing implementation styles

05Structural mapping of file organization and feature-based directory patterns

06Analysis of implicit naming patterns for variables, functions, and components

Casos de Uso

01Maintaining consistent test structures and mocking strategies across a codebase

02Onboarding to a legacy repository with undocumented coding standards

03Ensuring new features follow project-specific error handling and API patterns

Características Principales

01Automated discovery of linting and formatting rules from project config files

02Comprehensive verification checklist for style, structure, and testing consistency

031 GitHub stars

04Contextual search for similar features to mirror existing implementation styles

05Structural mapping of file organization and feature-based directory patterns

06Analysis of implicit naming patterns for variables, functions, and components

Casos de Uso

01Maintaining consistent test structures and mocking strategies across a codebase

02Onboarding to a legacy repository with undocumented coding standards

03Ensuring new features follow project-specific error handling and API patterns