| Tril converts every function in a repo into plain English descriptions, then runs and tests them — using an LLM as the interpreter instead of a runtime. The concept: programming languages exist because machines couldn't understand human intent. LLMs can. So what happens if you remove the code entirely and just... describe what each function should do? The tool replaces functions one by one, runs your test suite after each swap to confirm nothing breaks, and outputs a .md file. Then `tril run` spins up an HTTP server that sends each function's English description to Claude and returns the result. Tested on a unit converter (JS) and a 625-line Python CLI tool — tests passed, results matched to 6 decimal places (fortunately). This is mainly a thought experiment: can any code become plain natural language? Will it still work? Let's find out! npm:
npx @sliday/tril convert URL GitHub: https://github.com/sliday/tril |
This isn't accurate as to why programming languages exist. If you want to see english sentences describing the details of code, as working code, just go look at cobol. Machines understand exactly what we tell them, and do exactly what we tell them. The problem is on our side - how do we make sure we are telling them the correct instructions, while giving ourselves syntax that is easy to work with?
Because of that, your entire premise is wrong. Why would I replace working code with English, just to send it through Claude, just to get back... working code? What does that even prove?
You really are just trying to prove that AI can turn pseudocode into code. It can. By all means, go write stuff to test it and prove it, but I don't think anyone questions this. The questions revolve around whether or not those results are secure and stable, not whether it produces working code.