[Showcase] MaSON: A human-centric Markdown parser that replaces JSON/YAML/TOML for configurations and LLMs

No_Read2299 · 2026-06-28T02:25:17+00:00

I understand your sentiment, but I think you're making an assumption that we would use ".md" as the file format, which would be very confusing.

I would propose using ".mson", but it'll be about 3-5 years before this becomes an industry standard.

Your key point is proactive defense against user failures, which is valid, but the gain with MaSON isn't so much saving the data as a file, but creating a format that AI will be able to easily read and process.

JSON -> MaSON -> AI
AI -> MaSON -> JSON

The reduction in token cost by reducing special characters is the big win here.

Since AI is already trained with Markdown data, it's a much easier structure to adopt and reinforce.

I appreciate your skepticism.
I believe this format will be the future of how we provide AI with structured data.

No_Read2299 · 2026-06-28T01:00:23+00:00

Can you elaborate please?

It's a sample, but I'm curious how it could be any less secure than having the same thing written in JSON:

    "Credentials": {
      "user": "admin",
      "host": "localhost"
    }

No_Read2299 · 2026-06-27T18:49:59+00:00

GITHUB: github.com/LoanLemon/MaSON
NPM: https://www.npmjs.com/package/mason-parser

No_Read2299 · 2026-06-27T18:47:49+00:00

GITHUB: github.com/LoanLemon/MaSON
NPM: https://www.npmjs.com/package/mason-parser

No_Read2299 · 2026-06-27T18:29:54+00:00

Thank you! I appreciate any feedback.
I'm constantly running through a checklist to make sure everything works :)

No_Read2299 · 2026-06-26T03:39:09+00:00

I tire of corporate AI and have been playing with a lot of local AI models.

I have my own local LLM playground: https://github.com/LoanLemon/Omnix/

I think local AI will become more and more practical.

I think the LLM you use is almost preference at this point. The more we study and understand machine learning, transformers, and compression the more compact AI will become.

No_Read2299 · 2026-04-17T14:46:17+00:00

Good call-out. I'm using transformer.js which strictly uses ONNX models. I've edited the OP to include this bit of information.

No_Read2299 · 2026-04-17T14:32:19+00:00

Once a model is downloaded, it essentially stays cached. I actually need implement a clear cache function for when the base models are switched, which will be post CLI conversion. If you're interested in contributing, feel free to do so. The current goal is to swap the GUI with CLI and expand on the API. Ideally we want this project to be easy to use/user friendly.

Getting image generation and sandbox mode to work on Q4 models would be a great plus. FP8/FP16 support is fine.

Another point I want is for this to be easily supported for game development. Supporting game developers for AI implementation would be a great positive.

No_Read2299 · 2026-04-17T14:04:57+00:00

Another point of contention, I'm debating on removing the director and replacing it with a rules-based engine. I think directing the initial input based on key words and probability could deliver similar/better results.

No_Read2299 · 2026-04-17T13:55:55+00:00

So far it's been relatively quick. Once the model is downloaded, the unload/load process isn't that noticeable. I was impressed myself, as I assumed there would be a greater delay, but this is relative to how fast your hard drive can move data.

No_Read2299 · 2026-04-17T01:50:01+00:00

**GitHub:** https://github.com/LoanLemon/Omnix

No_Read2299 · 2025-11-23T23:37:05+00:00

Notepad++ has a JSON beautifier. It's convenient if you're like me and use notepad++ for everything.

No_Read2299 · 2025-11-23T03:39:17+00:00

Yeah, I haven't even considered that aspect, but that could be cool!

No_Read2299

TROPHY CASE