The first 1500 Chinese characters to learn according to Hanzi DB turned into markdown files processable by Obsidian. Obsidian allows us to view all of the markdown files as nodes in a graph with lines to nodes that represent HSK level, stroke count, and radical usage.
For the love of God, if you have a better way of algorithmically relating Chinese characters please tell by leaving a Github issue. What I would love is a way to automatically say "well if you know this character why not learn this related one". I did not make the json by hand, but used Google sheets and a program called Intemplator. As long as I can create a csv of 'character' -> 'label that helps create relations' I can extend this system.
Radical usage follows the Pareto Principle and stroke count follows a normal distribution, they don't really chunk characters well.