Map JavaScript and TypeScript codebase architecture via import graph regex analysis.
npx skills add https://github.com/Dragoon0x/dragoon-skills --skill map-dragoon0x
Please help me install this Agent Skill. Skill: map Source: https://github.com/Dragoon0x/dragoon-skills/tree/main/skills/map Command: npx skills add https://github.com/Dragoon0x/dragoon-skills --skill map-dragoon0x
Manually mapping a codebase's structure, identifying unused files, and auditing dependencies is time-consuming and error-prone, especially when onboarding to a new project or planning a cleanup.
Use the map skill to generate a full architecture overview of your codebase, including hot files, orphan files, and top external dependencies.
High-intent search queries and answers about installing and using this skill.
To map codebase architecture, run a static import graph analysis using regex to identify hot files, orphan files, and top external dependencies without requiring AST parsing or network access. The tool outputs human-readable or JSON metrics including file counts and largest files.
Yes, you can find dead code in JavaScript and TypeScript projects by analyzing import graphs via regex to detect orphan files that are imported by no other files, eliminating the need for heavy AST parsing. This approach quickly highlights unused files for removal.
The best way to audit external dependencies during codebase onboarding is to run a static import analysis that surfaces the most-used external dependencies, hot files, and structural metrics like total line counts. This provides a fast, zero-dependency overview of the project.
No, this codebase mapping tool requires zero network access and has no external dependencies, relying entirely on local static import graph regex analysis to output architecture metrics and identify dead code. It safely audits JavaScript and TypeScript projects offline.
To prioritize splitting large files in a TypeScript project, run a static architecture mapping tool to identify the largest files by line count and byte size, then target those overgrown files for refactoring based on import metrics. This helps sequence structural cleanup effectively.
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