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A September 2026 report by Listwright found a dramatic discrepancy in Hacker News Search API comment counts: one 30-day query returned 34,795,481 hits but was marked non-exhaustive, while the author reported 317,984 comments from summing 30 one-day queries marked exhaustive. Those are the author’s measurements, not independently verified totals. A later correction is crucial: the non-exhaustive result changed sharply on rerun, so it should not be treated as an exact count.
What the reported counts do—and do not—show
Listwright’s report compared a query for Hacker News comments over a 30-day period, measured on September 23, 2026. Its results were:
| Measurement | Reported result | Scope and qualification |
|---|---|---|
| One 30-day query | 34,795,481 | Comment query; one response; exhaustiveNbHits: false; reported by Listwright on September 23, 2026. |
| Sum of 30 daily queries | 317,984 | Same reported 30-day period; each one-day response was reported as exhaustiveNbHits: true. The article does not reproduce all 30 raw responses. |
| Rerun of the 30-day query | 171,753 | Comment query; one response; exhaustiveNbHits: false; reported in Listwright’s correction roughly a day later. |
| Unfiltered comment query | 310,522 | Reported in the same correction; the article says this was lower than its 317,984 total for the recent 30-day subset. |
The table records what the author said the API returned, not a set of independently reproduced measurements. Listwright says the 30 daily windows were rerun and again returned the exhaustive flag, but the article page does not provide a complete raw-response archive or all daily values. That limits what readers can verify from the published page.
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Why the correction changes the interpretation
The post initially suggested that the very large, non-exhaustive result represented the whole index. Its correction withdraws that explanation. The corrected account reports that the 30-day value fell from 34,795,481 to 171,753 across runs, while a separate unfiltered comment query returned 310,522. Those values do not support treating a non-exhaustive hit count as a stable or comparable total.
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The narrower lesson is about the flag: according to the correction, exhaustiveNbHits: false means the engine stopped counting, so the returned nbHits value is not a dependable exact count. The figures illustrate the problem, but they do not establish why the engine stopped, nor do they constitute an official explanation from Algolia or Hacker News.
How the author counted comments across 30 days
Listwright’s reported method was to split the date range into 30 separate one-day windows, check that each response had exhaustiveNbHits: true, and add the daily counts. The resulting sum was 317,984 for the stated period.
- Choose the interval. Define the start and end of the 30-day period and the query’s comment scope.
- Divide it into daily windows. Run one query per day, using consistent boundaries so no date is omitted or counted twice.
- Inspect each response. Confirm
exhaustiveNbHitsis true for every daily count before treating it as an exact count under the API’s reported flag. - Sum the daily results. Add the 30 counts only after checking the flag and retaining the query scope and date boundaries.
This describes the author’s approach and reported result. The article does not establish that one-day windows will always be exhaustive, for every query or future period. If a daily response is non-exhaustive, the method has not established an exact total for that day.
Which Hacker News API is being discussed?
“Hacker News API” can refer to different interfaces. The official Hacker News API repository documents the Firebase-backed v0 API, including item IDs, story and comment types, timestamps, comment text, parent relationships, and a story’s descendants count. Its README describes the v0 API as “essentially a dump of our in-memory data structures.” That documentation does not describe or verify the Algolia-backed HN Search API results in Listwright’s report.
As a result, the official Firebase API documentation is useful context for the data model, but it cannot be used as independent confirmation of the Search API totals. The two sources should not be conflated.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What the discrepancy means for the report’s conclusions
Listwright used public-text queries to explore whether Hacker News discussions showed demand for product ideas. The article reports 1,104 Ask HN questions, 1,153 Stack Overflow questions, and 317,984 Hacker News comments in its September 2026 comparison; it says 278 Stack Overflow questions were closed, or 24.1%. It also reports 495 comments matching phrases expressing demand, with buyer-vocabulary matches of 1, 2, 5, and 1 across four product categories. These are the author’s counts and classifications, not independently verified results.
The author’s stated conclusion was that the public-text demand research did not validate the product hypothesis. That is a conclusion about the author’s selected source queries and keyword predicates—not proof that demand is absent from the market. The count discrepancy makes it especially important to distinguish a reported API hit count from evidence that a product category has, or lacks, customers.
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