When I ask chatgpt to create a mermaid diagram for me it regularly will add new lines to certain labels that will break the parse. If you then feed the parse error back to it the second version is always correct And it seems to exactly know the problem. There are some other examples where it will almost always get it wrong the first time but right if nudged to correct itself. I wonder what the underlying cause is

I think the problem should be defined as "why does it not loop back the errors from the first attempt so it can fix it on the second attempt" rather than why it fails to produce a fully correct implementation on the first pass.

> I wonder what the underlying cause is

It responds with the statistically most probable text based on its training data, which happens to be different with the errors vs without. I suspect high-fidelity diagramming requires a different attention architecture from the common ones used in sentence-optimized models.

This is one of the issues I’ve attempted to tackle with the Mermaid Studio plugin for IntelliJ.

It provides both syntax guides and syntax/semantic analysis as MCP Tools, so you can have an agent iteratively refine diagrams with good context for patterns like multi-line text and comments (LLMs love end-of-line comments, but Mermaid.js often doesn’t).

"Prompt Repetition Improves Non-Reasoning LLMs " - https://arxiv.org/pdf/2512.14982

What instance of ChatGPT are you doing that with? (Reasoning?)

Mermaid is really bad about cutting off text after spaces, so you have to insert <br>s everywhere. I’m guessing this is getting rendered instead of escaped by your interface. Or just lost in translation at the tokenizer.

Today I asked Claude to create me a squidward looking out the window meme and it started generating HTML & CSS to draw squidward in a style best described as "4 year old preschooler". Not quite it yet.