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I built a tool that helps predict HN front page success

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Hey HN community,I built a tool that helps optimize your post for hitting the first page of Show HN.How it works: I used a Hugging Face dataset of all Hacker News posts from the past 3 years and trained a model that predicts how successful your post might be. There's still a lot of randomness on HN, so nothing is guaranteed, but the tool helps optimize your post for higher odds.A couple of interesting findings:- GitHub repo links work x3 better than regular domains - Open-source tools have a steady virality rate (13.9% - one of the highest) - "I built" outperforms "We built" - Using parentheses and mentioning technologies (Lua, Postgres, Rust, etc.) helps a ton.You can try the tool at wannalaunch.com or read the blog posts for more insights from the analysis. The model is also available as open source if you want to retrain it or look under the hood.Happy to hear the feedback!

HN · launched May 3, 2026 · 26 upvotes (top 22%) · 0 views

Niche: specialized analytics platforms · 141 launches, 4 in the last 7 days ▼ -60% · Explore this niche →

Category and tags

  • Horizontal
  • Analytics & BI
  • Prosumer
  • Not AI
  • Hobby / open-source project

Visit website ↗ Source listing ↗

Could you build this?

Yes The product analyzes post headlines/timing against a public Hugging Face dataset of HN posts using a standard pre-trained NLP/regression model accessible via a web UI wrapper.

Discussion

20 comments analyzed.

Concerns raised: Random factors make prediction unreliable despite model, LLM trend overcrowded /show with submissions, Shadowbanning and domain-related moderation issues, Success metric ambiguity (frontpage visibility vs. meaningful feedback)

Feature requests: Add parenthetical suggestions to title recommendations, Factor current event trends into predictions, Distinguish between frontpage metrics and discussion quality

Competitors

Other products that read as similar to this one : 238 launches clear the similarity bar, closest 8 shown.

Attention rank: #65 of 239 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 182 days after the earliest competitor.

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