---
title: Open-Sourced K-MAPS
description: A lightweight JavaScript library for visualizing King Safety, Material, Activity, Pawn Structure, and Space
image: https://image.lichess1.org/display?fmt=webp&h=550&op=thumbnail&path=ublog:CH4KqiEE:UGlHbsUc.webp&w=880&sig=d854577c9af89b3647f791d59987b3983263ec31
---

While working on the **Chessboard Magic Repertoire Builder**, a fellow chess enthusiast **@mattchessic** mentioned that it would be great to have something called *K-MAPS* to help visualize and refine one’s repertoire.
At the time, I had no idea what K-MAPS were — but the concept intrigued me: a simple, visual way to assess a chess position across key strategic dimensions. Naturally, I did what any developer would do — I went searching for an existing library.
To my surprise, there wasn’t one. So, with help from the **Chess Programming Wiki**, some late-night AI assistance, and more than a few long coding sessions, I decided to put something together.

> **TLDR: GitHub Repository:** **[https://github.com/HollowLeaf1981/chess-kmaps](https://github.com/HollowLeaf1981/chess-kmaps)**

### What Are K-MAPS?

**K-MAPS (King, Material, Activity, Pawn Structure, Space)** is a conceptual framework that breaks down a chess position into **five fundamental strategic factors**:

* **King Safety** — How exposed or protected each king is.
* **Material** — The relative balance of pieces.
* **Activity** — The mobility and coordination of your forces.
* **Pawn Structure** — The health and formation of your pawns.
* **Space** — The territorial control and influence across the board.

The goal is to express a position’s *strategic balance* numerically — and visually — making it easier to spot imbalances, strengths, and weaknesses at a glance.

### The Rabbit Hole

The first step was research — reading through the various mathematical approaches and evaluation formulas used in chess engines and theory, to understand what an implementation might look like.
However, I quickly discovered there wasn’t a **definitive definition or set of algorithms** for K-MAPS anywhere — at least not in a form that could be directly implemented. So, I took a **best-guess approach**: studying how each factor might be quantified and how those metrics could interact in a balanced way.
Next came **the design**. I wanted the package to be simple — just **one function** that takes a FEN and returns normalized scores for **White and Black**.
To achieve this, I relied on **chess.js** for basic board manipulation, while the rest would be pure logic — identifying positional attributes, computing ratios, and developing a weighting system to blend them into five unified K-MAPS metrics.
Then came the coding. I built the initial version from scratch, guided by notes, intuition, and plenty of trial and error. Once it worked, I ran the entire library through multiple AIs — **ChatGPT**, **Grok**, and **Gemini** — to identify possible improvements, missed conditions, or edge cases I hadn’t considered. Each iteration brought refinements until it became a stable, modular, and surprisingly robust little library.

> I’m an **amateur programmer at best**, and with the number of algorithms and calculations involved, I’ve most definitely missed something — but that’s part of the fun. The project is open so others can explore, improve, and build on it.

### The Result

The result is **Chess K-MAPS** — an open-source, MIT-licensed JavaScript library that evaluates a position and returns normalized scores for the five core factors.
It also includes a **simple demo app** so you can plug in your own positions and see how each metric shifts as the board evolves.
![image.png](https://image.lichess1.org/display?fmt=png&h=0&op=resize&path=ublogBody:jOPEGxxTn2uK:mEjg3NS1.png&w=800&sig=69c724b7f8cee24b67d943d11280e5dbb752ef6f)

> Image from the Chessboard Magic Repertoire Builder

It’s still a basic implementation — a foundation rather than a finished tool — but I’m hoping others in the chess and dev community will pick it up, refine it, and expand upon it. **For now, it’s a simple function that takes a FEN and returns the output — clear, direct, and ready to experiment with.**
**GitHub Repository:** **[https://github.com/HollowLeaf1981/chess-kmaps](https://github.com/HollowLeaf1981/chess-kmaps)**

Do let me know what you think — and if you end up using this in your own chess products, I’d love to hear about it.

Kind Regards,
**Toan Hoang (@HollowLeaf)**