Observed Signal · Sep 6, 2026 · Technical Release · Source: DEV Community · Impact: 1/5 · Sentiment: Positive
Infrastructure Market: Static Site Auto-Updates via Python and GitHub Actions
PD.Radar is a side project that automatically ranks resources mentioned in Hacker News 'Ask HN' threads by citation count, not upvotes. Running on GitHub Actions with pure-stdlib Python, the engine re-mines flagship threads and discovers new qualifying threads daily via the Algolia API, publishing leaderboards without manual intervention. An 'honesty gate' uses intent keywords and rant patterns to filter out low-quality threads, ensuring only genuine recommendations are published. The static site is hosted on GitHub Pages at zero cost, with commit history acting as a changelog of autonomous decisions. The first successful run produced five leaderboards from 1,551 comments and 66 ranked resources, demonstrating a scalable, zero-infrastructure approach to automated content aggregation and editorial filtering.
A niche side-project technical guide; low relevance to AdTech/MarTech/AI industry.
Key Takeaways & Evidence Grounding
- PD.Radar ranks resources in Ask HN threads by distinct commenter citations, not upvotes.
- The auto-update engine is a ~300-line pure-stdlib Python script that runs daily on GitHub Actions, discovering new threads via the Algolia API.
- The honesty gate uses intent keywords and rant patterns to filter out low-quality threads, rejecting those with fewer than 5 resources or 3 citations and remembering them for 45 days.
- The first run produced five leaderboards from 1,551 comments and 66 ranked resources, successfully rejecting off-topic threads.
- The project costs $0 per month, using GitHub Pages for hosting and GitHub Actions for automation.
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