Does it work with specific frameworks like React?

Yes, it includes specialized flows for UI components that address visual states, accessibility, and styling patterns specific to your project.

How does this skill prevent over-engineering?

It explicitly follows the YAGNI (You Ain't Gonna Need It) principle, directing the AI to write only the code necessary for the requested feature without adding unrequested abstractions.

How does it handle existing codebase conventions?

The skill instructs Claude to use tools like grep and ls to study your current file structures, naming conventions, and error handling before proposing new code.

What is the 'Iron Law' of this skill?

The Iron Law dictates that no code should be written before the functionality, user flow, and existing project patterns are fully understood and documented.

Pattern-Aware Code Generation

Name: Pattern-Aware Code Generation
Author: romiluz13

byromiluz13

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Herramientas para Desarrolladores

Enforces high-quality, minimal code production by prioritizing functional understanding and strict adherence to existing project patterns.

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This skill transforms Claude into a disciplined senior engineer that adheres to the 'Iron Law': no code is written until functionality and project patterns are fully understood. It streamlines the development process by requiring Claude to answer universal questions about users, inputs, and edge cases while actively studying the existing codebase to match naming conventions and architectural styles. It is ideal for developers working in established codebases who want to maintain consistency, avoid over-engineering, and ensure that AI-generated code is production-ready from the first iteration.

Características Principales

Automatically aligns generated code with existing project naming, import, and export conventions.
Provides context-specific workflows for UI components, API endpoints, and database operations.
Enforces a 'Universal Questions' protocol to ensure deep functional understanding before coding.
18 GitHub stars
Prioritizes the YAGNI principle to deliver minimal, efficient implementations without bloat.
Includes a comprehensive code quality checklist covering edge cases, types, and error handling.

Casos de Uso

Enforcing senior-level engineering standards and edge-case handling in AI-generated pull requests.
Maintaining architectural consistency when adding new features to a legacy codebase.
Standardizing the code generation process across a team to ensure uniform style and logic patterns.

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Características Principales

Automatically aligns generated code with existing project naming, import, and export conventions.
Provides context-specific workflows for UI components, API endpoints, and database operations.
Enforces a 'Universal Questions' protocol to ensure deep functional understanding before coding.
18 GitHub stars
Prioritizes the YAGNI principle to deliver minimal, efficient implementations without bloat.
Includes a comprehensive code quality checklist covering edge cases, types, and error handling.

Casos de Uso

Enforcing senior-level engineering standards and edge-case handling in AI-generated pull requests.
Maintaining architectural consistency when adding new features to a legacy codebase.
Standardizing the code generation process across a team to ensure uniform style and logic patterns.