Automatically audits and refines generated code for quality, performance, and accessibility before final output.
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This skill acts as an automated quality gate for AI-generated code, scanning for common issues like linting errors, performance bottlenecks, and accessibility gaps. It goes beyond simple detection by applying auto-fixes—such as removing unused imports, extracting duplicate code, and optimizing file structure—to ensure that the final output is production-ready, clean, and tested before it is presented to the developer.
Características Principales
Automated linting and cleanup of unused imports and variables
Accessibility auditing for image alt text and proper heading hierarchy
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Structural optimization including component extraction and function splitting
Regression verification to ensure auto-fixes don't break functionality
Performance checks to prevent N+1 queries and blocking operations
Casos de Uso
Enforcing organizational coding standards and naming conventions automatically
Ensuring production-grade code quality for complex feature generation
Polishing experimental AI outputs before user review or deployment
