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Himanshu040604
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cartographer

Map codebases by orchestrating parallel AI subagents and generate CODEBASE_MAP.md.

Updated Mar 5, 2026
Search Tags:#developer tools#architecture#code analysis#documentation#code understanding#codebase mapping
One-click install
npx skills add https://github.com/Himanshu040604/codex-skills-setup --skill cartographer-himanshu040604
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: cartographer
Source: https://github.com/Himanshu040604/codex-skills-setup/tree/main/assets/codex/skills/claude-import/skills/plugins/cartographer%40cartographer-marketplace/skills/cartographer
Command: npx skills add https://github.com/Himanshu040604/codex-skills-setup --skill cartographer-himanshu040604

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill automates the process of understanding and documenting complex codebases, making it easier to onboard new team members, refactor code, and maintain project knowledge.

Core Features & Use Cases

  • Automated Codebase Mapping: Generates a comprehensive map of your project's architecture, file purposes, dependencies, and navigation guides.
  • Parallel Subagent Orchestration: Leverages multiple AI subagents to efficiently process large codebases.
  • Incremental Updates: Detects changes since the last mapping and updates only affected sections, saving time and resources.
  • Use Case: When joining a new project, use Cartographer to quickly generate a map of the entire codebase, allowing you to understand its structure and key components within minutes.

Quick Start

Use the cartographer skill to map the current codebase.

Frequently Asked Questions about cartographer

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

FAQPage Schema
How do I automatically generate codebase documentation and architecture maps?▼

Automated codebase documentation is generated by orchestrating parallel AI subagents to analyze file structures, purposes, and dependencies. This produces a `CODEBASE_MAP.md` file detailing architecture, module guides, data flow, and navigation.

What is the best way to map an existing codebase for new developer onboarding?▼

Mapping an existing codebase for onboarding is best handled by orchestrating parallel AI subagents to process project files. This quickly generates a comprehensive map of the codebase structure, allowing new team members to understand key components within minutes.

How does incremental codebase mapping work when updating project documentation?▼

Incremental codebase mapping works by detecting file changes since the last analysis and updating only affected documentation sections. This approach saves time and computational resources by avoiding a full rescan of the project architecture.

Do I need Python and tiktoken to map and document my codebase?▼

Yes, Python and the `tiktoken` dependency are required to run the scanning scripts for codebase mapping. The Python scripts scan file structures, while AI models handle the analysis and synthesis of the architecture.

Can I use parallel AI subagents to analyze large codebases and generate navigation guides?▼

Yes, parallel AI subagents can be orchestrated to efficiently analyze large codebases. They process file structures and dependencies to generate a comprehensive `CODEBASE_MAP.md` file detailing architecture and navigation guides.

Why does mapping a complex codebase update the CLAUDE.md file?▼

Mapping a complex codebase updates the `CLAUDE.md` file to store a synthesized summary of the project architecture. This summary works alongside the detailed `CODEBASE_MAP.md` to maintain accessible project knowledge and context.

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