code-intelligence

Analyze code to reveal symbols, dependencies, and complexity metrics.

1|Updated Feb 17, 2026

Search Tags:#refactoring #dependencies #complexity #analyze #tree-sitter #ctags

Ready to run

npx skills add https://github.com/snqb/my-skills --skill code-intelligence-snqb

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: code-intelligence
Source: https://github.com/snqb/my-skills/tree/main/code-intelligence
Command: npx skills add https://github.com/snqb/my-skills --skill code-intelligence-snqb

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

Symbols, dependencies, and complexity in codebases are hard to inspect manually; this skill provides a unified view to understand structure and plan refactors.

Core Features & Use Cases

Symbol lookup with fast, language-agnostic tag data based on ctags.
Dependency graphs and imports mapping across modules using dep-tree/pydeps.
Complexity, hotspots, and code maps to guide refactoring and architectural decisions.
Use Case: Quickly identify modules with high CC and large code bases to prioritize redesigns.

Quick Start

Run the intel script on a target file or directory to generate symbols, dependencies, and complexity metrics.

Frequently Asked Questions about code-intelligence

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

FAQPage Schema

How do I analyze code complexity and identify refactoring hotspots in a large codebase?▼

To analyze code complexity and identify refactoring hotspots, this skill calculates metrics and generates code maps to pinpoint modules with high cyclomatic complexity. It uses tree-sitter and ctags to parse structures, guiding prioritization for redesigns across mid-to-large codebases.

What is the best way to map code structure and trace dependencies across Python or JavaScript modules?▼

The best way to map code structure and trace dependencies across Python or JavaScript modules is through language-aware parsing with tree-sitter and dependency visualization using dep-tree or pydeps. This skill reveals imports and structural relationships to simplify architectural analysis.

Can I use ctags for fast symbol lookup across different programming languages?▼

Yes, you can use ctags for fast, language-agnostic symbol lookup across different programming languages. This skill leverages ctags to quickly extract and map symbols from files, enabling rapid navigation and structural understanding without being tied to a specific language framework.

How do I generate dependency graphs and output JSON for downstream tooling?▼

To generate dependency graphs and output JSON for downstream tooling, run the analysis script on a target directory. The skill processes imports and module relationships using dep-tree or pydeps, outputting structured JSON data that other tools can consume for further visualization or automation.

Does this code analysis approach work with Go codebases for architectural planning?▼

Yes, this code analysis approach works with Go codebases for architectural planning. The skill is explicitly applicable to Go, alongside Python and JavaScript, using language-aware parsing to trace imports, map symbols, and evaluate complexity to support mid-to-large scale refactoring decisions.