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complexity-analyzer

Measure code complexity metrics and identify high-complexity areas in software projects.

27|4|Updated Oct 20, 2025
Search Tags:#code quality#code review#refactoring#maintainability#cyclomatic complexity#code complexity
One-click install
npx skills add https://github.com/CuriousLearner/devkit --skill complexity-analyzer-curiouslearner
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: complexity-analyzer
Source: https://github.com/CuriousLearner/devkit/tree/main/skills/complexity-analyzer
Command: npx skills add https://github.com/CuriousLearner/devkit --skill complexity-analyzer-curiouslearner

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill addresses the challenge of maintaining code quality and readability by identifying and quantifying code complexity, which often leads to bugs and maintenance difficulties.

Core Features & Use Cases

  • Metric Calculation: Computes key complexity metrics like Cyclomatic Complexity, Cognitive Complexity, Lines of Code, Halstead Metrics, and Maintainability Index.
  • Detailed Analysis: Provides in-depth analysis of functions and files, highlighting the most complex areas and potential issues.
  • Actionable Recommendations: Offers concrete refactoring suggestions and best practices to reduce complexity and improve code health.
  • Use Case: A development team can use this skill to proactively identify and refactor overly complex functions before they become a source of bugs, ensuring a more maintainable codebase.

Quick Start

Run a detailed complexity analysis on the entire src directory.

Frequently Asked Questions about complexity-analyzer

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

FAQPage Schema
How do I measure cyclomatic complexity to identify functions that need refactoring?▼

Cyclomatic complexity is measured by analyzing your project's functions and files to quantify code complexity. This process identifies high complexity areas and provides actionable refactoring recommendations to improve overall code health and reduce potential bugs.

What code complexity metrics should I track for maintainability?▼

Key code complexity metrics to track include Cyclomatic Complexity, Cognitive Complexity, Lines of Code, Halstead Metrics, and the Maintainability Index. Quantifying these metrics highlights problematic areas requiring refactoring to ensure long-term codebase health and readability.

How do I analyze my src directory for code complexity and maintainability issues?▼

To analyze your src directory for code complexity, run a detailed complexity analysis across the entire project structure. This computes maintainability metrics, identifies the most complex files and functions, and offers concrete refactoring suggestions to resolve potential maintenance difficulties.

Does code complexity analysis work with different programming languages?▼

Code complexity analysis integrates with various language-specific analysis tools to support diverse software projects. This allows you to compute complexity metrics and identify refactoring opportunities across multiple programming languages to maintain code quality.

Why does high cognitive complexity lead to bugs and maintenance difficulties?▼

High cognitive complexity leads to maintenance difficulties because it quantifies how hard code is to read and understand. Identifying these overly complex areas through analysis helps proactively refactor them before they become a source of bugs and readability issues.

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