I kept noticing great posts dying in /new while some mediocre ones hit front page at the right time. So I built a tool that analyzes your post and suggests optimal posting windows based on historical HN data. Also if provides general feedback based on data + similar posts.
From the tech side of it, both the fe and the HN API are open source here:
- Frontend: https://github.com/desplega-ai/ai-toolbox/tree/main/willitfr... - SQL API: https://github.com/desplega-ai/ai-toolbox/tree/main/hn-sql
The backend is done with a simple python script that fetches data into parquet files, and then queries them using duckdb, which work fine so far. The latencies go from ms to few seconds depending on the query.
PS: I haven't finished the full sync yet (~85% done).
zahlman•1mo ago
Why is the post content relevant to the "optimal posting windows"? What aspects of it does the model identify as being relevant?
tarasyarema•1mo ago
1. Relevance to HN (e.g. OSS, relevant tech articles, etc.) 2. Similar posts matching (e.g. if it's repeated, or low-impact ones) 3. Provides recommendations on title, description
To be fair, it's pretty "dumb" now, as it does a mix of deterministic queries to the database + LLM analysis to build the report.
You can see the plan for the idea tester here https://github.com/desplega-ai/ai-toolbox/blob/main/willitfr...