How is the review feedback structured?

Feedback is organized into a summary, a list of strengths, and a prioritized issue list ranging from 'Critical' to 'Low,' followed by specific code-based suggestions.

What programming languages does the Professional Code Reviewer support?

The skill provides specialized checks and idiomatic patterns for JavaScript, TypeScript, Python, Go, Java, and Rust.

Is the feedback purely critical?

No, the skill follows a constructive philosophy that acknowledges good code patterns and uses collaborative language to help developers grow.

Does it identify security vulnerabilities?

Yes, it specifically scans for input validation risks (SQLi, XSS), insecure authentication, sensitive data handling, and known dependency vulnerabilities.

Can this skill help with performance optimization?

Absolutely. It analyzes algorithmic complexity (O(n) vs O(n²)), N+1 database query problems, and inefficient memory or network usage.

Professional Code Reviewer

Name: Professional Code Reviewer
Author: a-ariff

bya-ariff

Seguridad y Pruebas

Performs in-depth code quality analysis and provides actionable, structured feedback to improve maintainability, security, and performance.

Acerca de

Professional Code Reviewer is a specialized Claude Code skill designed to automate and enhance the peer review process by providing expert-level analysis of source code. It goes beyond simple linting to evaluate architectural patterns, security vulnerabilities, and adherence to language-specific best practices across diverse environments including JavaScript, Python, Go, and Rust. By providing constructive feedback with clear explanations of impact and concrete code examples for fixes, this skill helps development teams maintain high standards, catch critical bugs early, and foster a culture of continuous learning.

Características Principales

Performance optimization for algorithmic complexity and database queries
0 GitHub stars
Standardized feedback format with prioritized severity levels
Security-first analysis focusing on SQLi, XSS, and dependency risks
Multi-language support for JavaScript, Python, Go, Java, and Rust
Structural design checks for SOLID, DRY, and clean code principles

Casos de Uso

Automating pre-Pull Request checks to catch bugs and smells before human review
Auditing legacy codebases for hidden security risks and performance bottlenecks
Mentoring junior developers with detailed 'why' explanations and idiomatic patterns

Acerca de

Características Principales

Performance optimization for algorithmic complexity and database queries
0 GitHub stars
Standardized feedback format with prioritized severity levels
Security-first analysis focusing on SQLi, XSS, and dependency risks
Multi-language support for JavaScript, Python, Go, Java, and Rust
Structural design checks for SOLID, DRY, and clean code principles

Casos de Uso

Automating pre-Pull Request checks to catch bugs and smells before human review
Auditing legacy codebases for hidden security risks and performance bottlenecks
Mentoring junior developers with detailed 'why' explanations and idiomatic patterns