Launch Platform

Score your Hacker News description

ML models trained on 151k+ real Hacker News launches. Get your probability score in seconds.

1.77%

of Show HN posts reach 100+ points

What the model looks for in Hacker News descriptions

Competition level: Low. Success criteria: 100+ points (top 1.77% of posts).

Technical implementation language (specific tech stack)
High-scoring Show HN posts explain how the product is built, not just what it does.
Open-source or developer-focused positioning
HN readers upvote tools they can inspect, extend, or self-host.
Honest limitations and rough-edge disclosures
Acknowledging what is missing builds trust with a skeptical technical audience.
No marketing speak or AI buzzwords
Promotional phrasing and vague AI claims correlate with lower point totals.

Our Hacker News model is trained on 151,383 real listings collected from the platform. Success is defined as: 100+ points (top 1.77% of posts).

151,383

Products in dataset

49.3%

Avg prediction score

100+ points rate

Step 1

Name, tagline, and full description.

Step 2

Instant probability and missing signals.

Step 3

Re-score after each edit.

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