codeprobe-code-smells

Name: codeprobe-code-smells
Availability: InStock
Author: Nishil

Detect code smells and anti-patterns in Java, Python, and C# codebases.

4|2|Updated Mar 28, 2026

Search Tags:#anti-patterns #refactoring #maintainability #static-analysis #code-smells #object-orientation

Ready to run

npx skills add https://github.com/nishilbhave/codeprobe --skill codeprobe-code-smells

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: codeprobe-code-smells
Source: https://github.com/nishilbhave/codeprobe/tree/main/skills/codeprobe-code-smells
Command: npx skills add https://github.com/nishilbhave/codeprobe --skill codeprobe-code-smells

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This sub-skill helps development teams identify code smells and anti-patterns to improve maintainability, readability, and long-term software quality.

Core Features & Use Cases

Bloaters — Long Method, Large Class, Data Clumps, Primitive Obsession
Object-Orientation Abusers — Feature Envy, Inappropriate Intimacy, Refused Bequest
Change Preventers — Shotgun Surgery, Divergent Change
Dispensables — Dead Code, Speculative Generality, Middle Man
Couplers — Temporal Coupling
Readability — Magic Numbers, Boolean Blindness, Deep Nesting

Quick Start

Run the detector on your codebase to surface actionable code-smell findings.

Frequently Asked Questions about codeprobe-code-smells

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I detect code smells and anti-patterns in my codebase?▼

Code smells like Long Method, Large Class, and Data Clumps are structural design issues in object-oriented code that hurt maintainability and readability. Identifying these anti-patterns early helps development teams reduce technical debt and improve long-term software quality.

Can I use static analysis to find code smells in Python, Java, and C# projects?▼

Yes, static analysis for code smells applies to object-oriented languages such as Java, Python, and C#. It works across projects of varying sizes, from microservices to monoliths, automatically excluding generated or third-party code to focus on your source.

How do I configure thresholds for identifying Large Class or Long Method smells?▼

Configurable thresholds allow you to customize detection sensitivity for smells like Long Method and Large Class. By adjusting these limits, you control what constitutes a code smell in your specific project, ensuring the reported severity and suggested fixes are relevant to your refactoring goals.

Does this code smell detector exclude generated and third-party code from analysis?▼

Yes, the code smell detector excludes generated and third-party code from analysis. This ensures that the reported findings, locations, and suggested fixes focus strictly on your own source code, preventing false positives from external libraries.

What are the most common anti-patterns and code smells I should look for during refactoring?▼

Common anti-patterns and code smells to target during refactoring include Bloaters like Long Method and Primitive Obsession, Change Preventers like Shotgun Surgery, Couplers, and readability issues like Magic Numbers and Deep Nesting. Surfacing these specific anti-patterns guides targeted refactoring to improve overall code maintainability.

What is the best way to surface actionable code-smell findings for a large monolith?▼

The best way to surface actionable code-smell findings in a monolith is to run an automated static analysis detector. It processes large codebases, excludes third-party code, and reports anti-patterns like Divergent Change with specific locations and suggested fixes to guide targeted refactoring.