Analyze code to reveal symbols, dependencies, and complexity metrics.
npx skills add https://github.com/snqb/my-skills --skill code-intelligence-snqb
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
Symbols, dependencies, and complexity in codebases are hard to inspect manually; this skill provides a unified view to understand structure and plan refactors.
Run the intel script on a target file or directory to generate symbols, dependencies, and complexity metrics.
High-intent search queries and answers about installing and using this skill.
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.
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.
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.
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.
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.
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