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codebase-mapping

Map codebase structure and dependencies by parsing Python and JavaScript imports.

5|Updated Dec 23, 2025
Search Tags:#architecture#codebase#repository#static-analysis#mapping#dependency-graph#entry-points
One-click install
npx skills add https://github.com/Dowwie/agent_framework_study --skill codebase-mapping-dowwie
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: codebase-mapping
Source: https://github.com/Dowwie/agent_framework_study/tree/main/.claude/skills/codebase-mapping
Command: npx skills add https://github.com/Dowwie/agent_framework_study --skill codebase-mapping-dowwie

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

Maps a codebase's structure and dependencies to enable architectural analysis, helping teams quickly understand project layout, module boundaries, and dependency relationships.

Core Features & Use Cases

  • Generate a structural map of the repository, excluding noise like node_modules, pycache, and .git.
  • Parse Python and JavaScript/TypeScript imports to build a comprehensive dependency graph distinguishing external vs internal modules.
  • Identify common entry points (main scripts, setup.py, pyproject.toml, package.json) and public interfaces to aid onboarding and refactoring.
  • Output artifacts such as file_tree.json, dependencies.json, entry_points.md, and module_map.md for downstream tooling.

Quick Start

Run the mapping script to generate a structural map: python scripts/map_codebase.py /path/to/repo --output structure.json Then inspect the generated artifacts at the specified output location.

Frequently Asked Questions about codebase-mapping

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

FAQPage Schema
How do I map my codebase structure to understand module boundaries and dependencies?▼

To map a codebase structure, you run a script that traverses the repository, excludes noise like node_modules, and parses Python and JavaScript imports. This generates artifacts such as file_tree.json and module_map.md to reveal module boundaries and dependency relationships.

What is the best way to identify entry points in a Python or JavaScript repository?▼

Identifying entry points involves scanning for common files like main scripts, setup.py, pyproject.toml, and package.json. The mapping process outputs an entry_points.md file that highlights these public interfaces to aid onboarding and refactoring efforts.

Can I distinguish internal vs external dependencies when analyzing a codebase?▼

Yes, you can distinguish internal vs external dependencies. The mapping tool parses Python and JavaScript imports, builds a comprehensive dependency graph, and outputs dependencies.json, which separates external modules from internal ones for architectural analysis.

Does the codebase mapping process work for both Python and JavaScript files?▼

Yes, codebase mapping works for both Python and JavaScript. It parses imports from both languages, traverses the repository structure, and generates a unified dependency graph while excluding directories like __pycache__ and .git.

How do I generate a dependency graph for architectural audits without including node_modules?▼

You generate a dependency graph by running the mapping script, which automatically excludes noise like node_modules, __pycache__, and .git. It outputs a clean dependencies.json file containing the parsed import relationships for your architectural audits.

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