So what if this was vibe-coded? How do you know this was a "slop" if you did not try it?
However I wouldn't be excited to trust one with my AWS key and read/write access to my infra
Because I have eyes and can look at the code for 2 seconds. It's not very difficult to check for the hallmarks of careless slop code.
If you can't tell in a few seconds then you can continue testing it out just like any actual project.
Unfortunately, ratatui requires a lot of verbose code that may be indistinguishable from LLM generated code: https://ratatui.rs/examples/apps/demo/
ESPECIALLY when its from a plan and comments '// STEP 2: ...'
Like here in this posts repo https://github.com/huseyinbabal/taws/blob/2ce4e24797f7f32a52...
This a dead ringer for LLM slop that someone didnt even care enough to go through and clean up.
Edit: Just to keep it going, you ever seen a human write dependencies like this for a small toy tui? https://github.com/huseyinbabal/taws/blob/2ce4e24797f7f32a52...
Edit2: Sure why not, lets reimplement randomly a custom jsonpath when serde_json_path exists https://github.com/huseyinbabal/taws/blob/2ce4e24797f7f32a52...
It's the equivalent of calling something an AI generated images just because the fingers are weird, and requires a judgment more concrete than "I have eyes."
> you ever seen a human write dependencies like this for a small toy tui?
Yes? That's just TOML syntax. I'm not sure which dependency in that list is excessive, especially for something that has to handle HTTP requests. If you mean adding a comment header for each section, then that's a better argument, but see argument above.
But it's more than LLM enough for anyone who has experience with them to conclude the LLM drove the majority of the output. Hence, slop
If it can quickly and easily be identified as LLM code then yes, it is intrinsically slop and of no value. The person who submitted it did not even value it enough to look at/clean it up. Why would anyone else care to look at it.
If it is LLM generated but then HAS BEEN cleaned up then you cant immediately see the LLM and it passes the check anyways.
But read the same link from above: https://github.com/huseyinbabal/taws/blob/2ce4e24797f7f32a52.... LLMs leave temporal comments like "// Now do X", or "// Do X using the new Y", as responses to prompts like "Can you do X with Y instead?".
or below: "// Auto-refresh every 5 seconds (only in Normal mode)". I would guess this comment was during a response to a prompt like: "can you only auto-refresh in Normal mode?"
Sometimes there are tautological comments and sometimes not: https://github.com/huseyinbabal/taws/blob/2ce4e24797f7f32a52...
``` // Get log file path
let log_path = get_log_path(); ```
This is another signal to me that there is less human influence over the project.
No, none of these are a smoking gun. Also none of this means it was completely vibe coded. To me personally, the worrying part is that these patterns signal that perhaps human eyes were never on that section of the code, or at least the code was not considered carefully. For a toy app, who cares? For something that ingests your AWS creds, it's more of a red flag.
Edit: changed the language a bit to sound less sardonic. My comment is more about LLM signals than a judgment on LLM usage.
It worked, no issue there, but the amount of commentary I included definitely surprised me.
I guess I really needed the support structure of comments to keep my logic on track back then, whereas now even convoluted map-reduce one liners are things I see as just obvious literate programming.
I did go a long while in my career still writing code that way when I had to share it with people. I don’t think I stopped until the only people reading my code were senior engineers with way more qualifications than I had.
So, I wouldn’t say just from this code that the creator is an LLM.
> ESPECIALLY when its from a plan and comments '// STEP 2: ...'
There are people who actually program that way. The most extreme I know was Bogdan Iancu from OpenSIPS who I've seen create functions, write step-by-step comments for what they will do, then fill out the implementation.
It's just a signal, not a certain thing.
Ratatui itself has a lot of much nicer AI generated code in it since then ;)
We've also done a bunch of things to help drive down some of the boilerplate (not all of it mind you - as it's a library, not a framework like other TUI libs)