A sophisticated analysis engine that identifies code smells and suggests refactoring strategies to improve maintainability.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install code-smell-analyzer
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install code-smell-analyzer using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Code Smell Analyzer?
The Code Smell Analyzer is a specialized utility within the Openclaw Skills ecosystem designed to evaluate source code against industry-standard best practices. It goes beyond simple linting by analyzing structural integrity, design pattern implementation, and overall maintainability. It helps developers transform complex, messy code into clean, modular, and high-performance software.
By leveraging this tool, teams can automate a significant portion of the code review process. The skill provides detailed rationale for every suggestion, making it an excellent educational resource for developers looking to master SOLID principles and efficient architectural patterns across various languages like JavaScript, Python, and Java.
Code Smell Analyzer Use Cases
- Automating code reviews during the development lifecycle
- Identifying technical debt and long-term maintainability issues in legacy systems
- Refactoring codebases to implement modern creational or behavioral design patterns
- Optimizing application performance by detecting inefficient algorithms or memory leaks
- Standardizing code quality and naming conventions across cross-functional teams
How Code Smell Analyzer Works
- Parse the provided source code or file contents to understand the logical structure and flow.
- Evaluate the code against a comprehensive framework of common smells such as Long Methods, Large Classes, and Magic Numbers.
- Analyze the architecture to recommend structural improvements via specific design patterns like Factory, Observer, or Strategy.
- Assess adherence to language-specific best practices, including DRY, SOLID, and proper error handling.
- Generate a structured report featuring the problematic code, a suggested improvement, and a detailed rationale.
- Categorize every finding by priority (High, Medium, Low) to help developers triage critical issues first.
Code Smell Analyzer Setup
To integrate this functionality into your environment using Openclaw Skills, follow these configuration steps:
# Install the skill via your agent manager
openclaw install code-smell-analyzer
# Configure language-specific parameters if necessary
openclaw configure code-smell-analyzer --lang=javascript
Once installed, you can trigger the analysis by asking your AI agent to review specific files, folders, or code snippets provided in the chat.
Code Smell Analyzer Data Schema & Taxonomy
The analyzer organizes its output into a structured schema to ensure clarity and actionability for the developer. The following data points are included for every suggestion:
| Field | Description | Example |
|---|---|---|
| Issue | A concise label for the detected code smell or anti-pattern. | Long Method with Multiple Responsibilities |
| Priority | The urgency of the fix based on impact (High, Medium, Low). | High |
| Current Code | The original code snippet containing the identified issue. | (Code Block) |
| Suggested Improvement | Optimized, refactored code following best practices. | (Code Block) |
| Rationale | Technical explanation of why the change is beneficial. | Single Responsibility and Testability |
| Specifics | Language-specific considerations (e.g., PEP 8, PEP 20). | Java Stream API usage |
Code Smell Analyzer Advanced Features
- Multi-language support for JavaScript, TypeScript, Python, Java, and WeChat Mini Program environments
- Automated design pattern detection and recommendation engine
- Deep architectural analysis focusing on coupling, cohesion, and modularity
- Performance-focused scanning for O(n^2) complexities and unnecessary I/O operations
- Detailed rationale mapping to SOLID principles and DRY standards
SKILL.md
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