Where is the final review report stored?

The skill writes a consolidated report to a REVIEW.md file located directly within the directory of the module being reviewed.

Does this skill modify my source code automatically?

No, this is a read-only analysis task. It identifies issues and suggests improvements in a report without altering your source files.

What specific code issues does this skill look for?

It focuses on simplifications, generalizations of duplicated logic, naming consistency, dead code detection, API cleanliness, and data flow efficiency.

How are the findings prioritized in the report?

Findings are grouped into four priority levels based on high impact and low invasiveness, ensuring you address the most meaningful changes first.

Can I use this for any programming language?

Yes, while it is particularly effective for modular structures, the logic for identifying architectural debt and consistency issues is language-agnostic.

Automated Code Quality Reviewer

Name: Automated Code Quality Reviewer
Author: xorza

byxorza

0•

Collaboration Tools

Performs deep architectural reviews of code modules to identify simplifications, logic generalizations, and consistency improvements.

The improve-module skill empowers Claude to act as a senior technical architect by systematically analyzing code submodules for structural weaknesses and technical debt. It evaluates findings based on impact, meaningfulness, and risk, helping developers prioritize refactoring efforts without making premature changes. By focusing on data flow, API cleanliness, and pattern consistency, the skill generates a structured REVIEW.md report that guides long-term maintainability and code health across the entire project.

Key Features

010 GitHub stars

02Detection of redundant abstractions, dead code, and unnecessary indirection

03Multi-dimensional scoring based on impact, meaningfulness, and invasiveness

04Automated generation of prioritized markdown reports for developer review

05Identification of cross-cutting pattern inconsistencies across submodules

06Deep analysis of API cleanliness and data flow linearity

Use Cases

01Ensuring architectural consistency and API standards are met across sibling submodules.

02Preparing a complex module for a major refactor by mapping out high-impact, low-risk improvements.

03Onboarding onto a legacy codebase to identify immediate technical debt and low-hanging fruit.

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add xorza/scenarium improve-module

For use in Claude.ai and ChatGPT

Download Skill