Skip to main content

Project Mapper

Project Mapper Banner

Generate LLM-friendly project summaries to help AI assistants understand your codebase.

npm version License: MIT Node.js Version

Overview​

Project Mapper analyzes your codebase and creates a comprehensive knowledge transfer document optimized for Large Language Models (LLMs). This enables AI assistants to quickly understand your project's architecture, components, and patterns, providing more accurate and contextual assistance.

The Problem​

When working with LLMs on code projects, you face these challenges:

  1. Token Limitations - LLMs can only process a limited amount of text at once
  2. Context Fragmentation - Sending individual files loses the overall project structure
  3. Missing Relationships - Dependencies between components are hard to communicate
  4. Terminology Gaps - Project-specific concepts need explanation

The Solution​

Project Mapper solves these problems by creating an intelligent summary focused on what matters most:

  • Project Overview - Quickly identify the project's purpose and type
  • Architecture Insights - Understand the major components and control flow
  • Core Functionality - Learn about the primary operations and language-specific handling
  • Integration Points - See how the project interfaces with users and external systems
  • Domain Knowledge - Grasp project-specific terminology and assumptions

Key Features​

  • Multiple Templates: Choose between Standard, Minimal, and Detailed summaries based on your needs
  • Semantic Analysis: Extract domain concepts and their relationships to understand project-specific terminology
  • Visualizations: Generate concept networks and relationship diagrams to better understand project structure
  • Flexible Output: Get results in Markdown or JSON formats
  • Questionnaire Generation: Create tailored questionnaires to gather additional context from developers
  • LLM Optimization: Summaries are structured specifically for effective LLM consumption

Who Should Use Project Mapper?​

  • Developers working with AI assistants on complex codebases
  • Technical writers creating documentation for software projects
  • Software teams onboarding new members to existing projects
  • Open source maintainers helping contributors understand the project
  • Anyone who wants to get AI assistance on their codebase

Quick Example​

Here's a quick example of how easy it is to use Project Mapper:

# Navigate to your project directory
cd your-project

# Run Project Mapper
npx project-mapper

# Share the generated document with your LLM
# The summary will be saved as project-knowledge-transfer.md

Then ask your LLM: "Based on this knowledge transfer document, please become an expert on my project."

Ready to get started? Check out our Getting Started guide!