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code_tools

Search codebases semantically and analyze Python files for complexity and maintainability.

5|Updated Aug 9, 2025
Search Tags:#codebase#maintainability#embeddings#complexity#code-analysis#semantic-search#radon
One-click install
npx skills add https://github.com/gatovillano/KogniTerm --skill code-tools-gatovillano
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: code_tools
Source: https://github.com/gatovillano/KogniTerm/tree/main/kogniterm/skills/bundled/code_tools
Command: npx skills add https://github.com/gatovillano/KogniTerm --skill code-tools-gatovillano

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires radon, and includes scripts (resource) components.

What problem does it solve?

Consolidates code analysis and semantic search tools into a single, cohesive workflow to speed up code understanding and quality improvement.

Core Features & Use Cases

  • Semantic code search: Find relevant code snippets across a project using embeddings.
  • Static analysis: Assess Python code with metrics like complexity and maintainability and perform lint checks when tools are available.
  • Use Case: Onboarding new codebases, quickly locating related implementations and identifying hotspots for improvement.

Quick Start

Ask the tool to perform a semantic search for a code topic and run static analysis on Python files to surface complexity and maintainability insights.

Frequently Asked Questions about code_tools

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

FAQPage Schema
How do I perform a semantic code search across a large multi-language repository?▼

You can perform semantic code search by generating embeddings for your codebase and querying by topic. This retrieves relevant code snippets across multiple languages without relying on exact string matches.

How do I calculate code complexity and maintainability metrics for Python files?▼

To calculate code complexity and maintainability metrics for Python files, run the bundled static analysis. This uses radon to measure metrics and surface specific code hotspots needing improvement.

Can I analyze code quality across different programming languages in one workflow?▼

Yes, you can analyze code quality across different programming languages in one workflow. Semantic search supports multiple languages, while static analysis metrics are calculated specifically for Python files.

What is the best way to find related code implementations during codebase onboarding?▼

The best way to find related implementations during codebase onboarding is using semantic search. It applies vector-based retrieval to locate relevant snippets by topic, speeding up code understanding.

Does semantic code search require any specific dependencies to run?▼

Semantic code search requires the radon dependency to run. Radon is bundled to calculate static analysis metrics like complexity and maintainability alongside the vector-based retrieval features.

When should I use static analysis instead of semantic search for code analysis?▼

Use static analysis instead of semantic search when you need measurable code quality metrics. Static analysis calculates Python complexity and maintainability, while semantic search locates snippets by topic.

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