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HackerNews Monitor + Auto-Tagger

Search and monitor HackerNews stories, Show HN, Ask HN, polls, jobs, comments by keyword and date range. Auto-tag every post with your custom keyword list. Built on the official Algolia public API — no auth, no rate-limit headaches, full historical archive.

What it does

• Multi-query search (run several keywords in one execution, results grouped by query)
• Filter by post type: story, comment, Show HN, Ask HN, poll, job, front_page
• Date range filter (any time window since HN inception)
• Sort by popularity (best matches) or date (newest)
• Min points / min comments thresholds
• Auto-tag every post with a keyword list — perfect for trend monitoring across multiple themes

Use cases

Tech market intelligence — Track every Show HN launch in your category to spot competitors and adjacent products.

AI trend detection — Monitor "RAG", "agent", "fine-tuning" to catch emerging topics before they go mainstream.

Founder lead-gen — Find Ask HN posts asking for tools in your space, reach out before they buy elsewhere.

LLM training data — Curate high-quality HN discussions as a corpus for fine-tuning domain-specific models.

Content marketing — Find high-engagement HN stories (>100 points, >50 comments) for blog post inspiration.

Input

{
"queries":["RAG","LLM agents","AI infrastructure"],
"postType":"story",
"sortBy":"popularity",
"dateFrom":"2026-04-01",
"dateTo":"2026-04-29",
"minPoints":5,
"minComments":0,
"maxResultsPerQuery":50,
"tagKeywords":["RAG","Llama","fine-tuning","agent","embedding","vector-db","evaluation"]
}

Output

One dataset item per matching post:

{
"query":"RAG",
"objectID":"47955083",
"type":"story",
"title":"Production RAG: what I learned from processing 5M+ documents",
"url":"https://example.com/blog/rag-lessons",
"hnUrl":"https://news.ycombinator.com/item?id=47955083",
"author":"user1",
"points":551,
"numComments":114,
"createdAt":"2026-04-15T13:42:00.000Z",
"createdAtEpoch":1745000000,
"storyId":null,
"tags":["RAG","evaluation"]
}

Pricing

Currently FREE during the launch preview — no per-result charges, no monthly cap.

When paid pricing rolls out (notice will be posted at least 14 days in advance):

Cost examples (post-launch):

• 100 posts: ~$0.11
• 1.000 posts: ~$1.01
• 10.000 posts: ~$10.01

Limits

• Source: HackerNews Algolia public search API (no auth required)
• Coverage: full HN archive (2007 onwards)
• Rate limit: ~10 req/sec (politely paced internally with 0.3s sleep)
• Max results per query: 1.000 per run
• Comment text not included by default (use HN item URL for full thread)

Source attribution

Data comes from the HackerNews Algolia public API, maintained by Algolia in partnership with Y Combinator. Subject to YC's terms.

Author

Polara Data — niche scrapers for Italy, EU & global markets.