Show HN: I analyzed why my post got 0 votes and built this

[fwystup]

Maybe you've had this experience too: You build something you're proud of, post it on HN with your low-karma account, and... crickets. Zero votes, zero comments. That's what happened to me last Monday. I posted my coding tool (XaresAICoder - an open-source browser IDE) that I'd built with AI assistance. In my mind it was revolutionary. On HN? Completely ignored. Then I wondered: How many other potentially great projects suffer the same fate? What "hidden gems" are we missing because they come from low-karma accounts? So I built hn-gems (with help from Claude and my own XaresAICoder). It works in two stages:

Continuous scanning: Analyzes all new HN posts from accounts with <100 karma, scoring them for technical merit, originality, and problem-solving value AI curation: Every 12 hours, an LLM deep-dives into the top 10 candidates, checking GitHub repos, documentation quality, and actual utility

The result is what you see at the link - a curated list of overlooked quality posts that deserve more attention. The interesting part: I barely wrote any criteria. I just told Claude "open source good, pure commercial bad, working demos good" and let it figure out the scoring. The AI assessment varies slightly each run, which actually makes it more interesting. GitHub: https://github.com/DG1001/hn-gems

Is this useful? Do you have ideas how to improve this tool if necessary?

(And yes, my XaresAICoder that got 0 votes? The AI thinks it's actually pretty good. I'll take that as a win.)

[PaulHoule]

Hate to break it to you but karma doesn’t count for anything, although always spamming articles from your own blog is the rookie mistake that gets your posts to start out [dead]

Take a look at /new, choked with AI products and “Ask HN: How come Vibe Coding Doesn’t Work For Me Although It Works For Everyone Else?” Or “Show HN: I Vibe Coded Something and It Almost Works”, “Is MCP really that evil program from Tron?”, etc.

The cheat code for August 2025 is it’s not about AI and if it an AI-oriented product it doesn’t say so right out front.

[fwystup]

Thanks for the feedback — definitely not meant as spam. It’s open source, not a commercial blog. Just wanted to surface some fresh ideas that might otherwise get missed. Really appreciate the tip!

[PaulHoule]

To make it clear I'm not accusing you of spamming, but I do think the supply vs demand for AI articles right now is out of whack.

What I was trying to say about spam is that your karma doesn't count so much as being a participant in the community counts. Like, I post a lot of articles to web sites that aren't my blog so if I post a few links to my blog it is OK. Now I'm an extreme case because I post a lot of links, but somebody who has like 1/10,000 the karma I have or less could post what they like so long as they aren't posting all links to the same web site. That's the place where your participation matters -- my posts don't do any better than anyone else's.

[fwystup]

Got it, thanks for clarifying. Makes sense that participation matters more than raw karma. I’ll keep that in mind and try to contribute more broadly, posting less about my own projects.

[dbaman]

Maybe I'm missing something, but should the "discuss on HN" hyperlink on your page goto the Show HN entry being referenced?

It seems to go to a HN post that is something else entirely??

[fwystup]

You're right — I totally missed that. Fixed it, please reload.

[dbaman]

Yep I can confirm the bug is fixed.

Nice UI btw, plus good use of AI for scoring/summarization.

I wrote something kinda similar that scrapes HN (using Firebase) for particular keywords I'm interested in. It gathers all hyperlinks mentioned in comments and uses NLTK to summarize. Kind of a curated HN reading list.

I'm currently working on using an LLM for the summaries.

Your project has given me a few ideas for mine. Thanks!

[fwystup]

Glad to hear it. Your NLTK approach sounds interesting — would love to hear more about it. BTW, I’m planning to improve my project’s documentation. Funny enough, under “consideration” it flagged itself: "Documentation quality is not explicitly high. The effectiveness of the LLM’s scoring criteria is subjective and not deeply explained." Sadly, that’s true.