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HISTORICAL RECORD2024–2026
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Discover this repository through its Hacker News conversations.

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49Distinct people
53Mentions
0Explicit recommenders
REPOSITORY AT A GLANCE

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What it is

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Where it is used

No documented product use has been verified yet.

What people are saying

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No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 8–Nov 15 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/15/2026, 4:00:59 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by month53 dated mentions

Observed mentions: 2024-07-16 07:12:23 UTC to 2026-10-30 20:27:56 UTC.

02462024-07-01 00:00:00 UTC to 2024-08-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 commentsJul 20242024-08-01 00:00:00 UTC to 2024-09-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2024-09-01 00:00:00 UTC to 2024-10-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2024-10-01 00:00:00 UTC to 2024-11-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2024-11-01 00:00:00 UTC to 2024-12-01 00:00:00 UTC (exclusive): 5 mentions; 2 submissions, 3 comments2024-12-01 00:00:00 UTC to 2025-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2025-01-01 00:00:00 UTC to 2025-02-01 00:00:00 UTC (exclusive): 6 mentions; 2 submissions, 4 comments2025-02-01 00:00:00 UTC to 2025-03-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-03-01 00:00:00 UTC to 2025-04-01 00:00:00 UTC (exclusive): 3 mentions; 2 submissions, 1 comments2025-04-01 00:00:00 UTC to 2025-05-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-05-01 00:00:00 UTC to 2025-06-01 00:00:00 UTC (exclusive): 3 mentions; 1 submissions, 2 comments2025-06-01 00:00:00 UTC to 2025-07-01 00:00:00 UTC (exclusive): 5 mentions; 4 submissions, 1 comments2025-07-01 00:00:00 UTC to 2025-08-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2025-08-01 00:00:00 UTC to 2025-09-01 00:00:00 UTC (exclusive): 2 mentions; 1 submissions, 1 commentsAug 20252025-09-01 00:00:00 UTC to 2025-10-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 comments2025-10-01 00:00:00 UTC to 2025-11-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2025-11-01 00:00:00 UTC to 2025-12-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2025-12-01 00:00:00 UTC to 2026-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2026-01-01 00:00:00 UTC to 2026-02-01 00:00:00 UTC (exclusive): 3 mentions; 3 submissions, 0 comments2026-02-01 00:00:00 UTC to 2026-03-01 00:00:00 UTC (exclusive): 3 mentions; 3 submissions, 0 comments2026-03-01 00:00:00 UTC to 2026-04-01 00:00:00 UTC (exclusive): 4 mentions; 1 submissions, 3 comments2026-04-01 00:00:00 UTC to 2026-05-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2026-05-01 00:00:00 UTC to 2026-06-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 comments2026-06-01 00:00:00 UTC to 2026-07-01 00:00:00 UTC (exclusive): 3 mentions; 1 submissions, 2 comments2026-07-01 00:00:00 UTC to 2026-08-01 00:00:00 UTC (exclusive): 2 mentions; 1 submissions, 1 comments2026-08-01 00:00:00 UTC to 2026-09-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2026-09-01 00:00:00 UTC to 2026-10-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2026-10-01 00:00:00 UTC to 2026-11-01 00:00:00 UTC (exclusive): 1 mentions; 1 submissions, 0 commentsOct 2026

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
Jul 20242024-07-01 00:00:00 UTC2024-08-01 00:00:00 UTC202
Aug 20242024-08-01 00:00:00 UTC2024-09-01 00:00:00 UTC101
Sep 20242024-09-01 00:00:00 UTC2024-10-01 00:00:00 UTC000
Oct 20242024-10-01 00:00:00 UTC2024-11-01 00:00:00 UTC101
Nov 20242024-11-01 00:00:00 UTC2024-12-01 00:00:00 UTC523
Dec 20242024-12-01 00:00:00 UTC2025-01-01 00:00:00 UTC101
Jan 20252025-01-01 00:00:00 UTC2025-02-01 00:00:00 UTC624
Feb 20252025-02-01 00:00:00 UTC2025-03-01 00:00:00 UTC000
Mar 20252025-03-01 00:00:00 UTC2025-04-01 00:00:00 UTC321
Apr 20252025-04-01 00:00:00 UTC2025-05-01 00:00:00 UTC000
May 20252025-05-01 00:00:00 UTC2025-06-01 00:00:00 UTC312
Jun 20252025-06-01 00:00:00 UTC2025-07-01 00:00:00 UTC541
Jul 20252025-07-01 00:00:00 UTC2025-08-01 00:00:00 UTC101
Aug 20252025-08-01 00:00:00 UTC2025-09-01 00:00:00 UTC211
Sep 20252025-09-01 00:00:00 UTC2025-10-01 00:00:00 UTC110
Oct 20252025-10-01 00:00:00 UTC2025-11-01 00:00:00 UTC000
Nov 20252025-11-01 00:00:00 UTC2025-12-01 00:00:00 UTC101
Dec 20252025-12-01 00:00:00 UTC2026-01-01 00:00:00 UTC000
Jan 20262026-01-01 00:00:00 UTC2026-02-01 00:00:00 UTC330
Feb 20262026-02-01 00:00:00 UTC2026-03-01 00:00:00 UTC330
Mar 20262026-03-01 00:00:00 UTC2026-04-01 00:00:00 UTC413
Apr 20262026-04-01 00:00:00 UTC2026-05-01 00:00:00 UTC101
May 20262026-05-01 00:00:00 UTC2026-06-01 00:00:00 UTC202
Jun 20262026-06-01 00:00:00 UTC2026-07-01 00:00:00 UTC312
Jul 20262026-07-01 00:00:00 UTC2026-08-01 00:00:00 UTC211
Aug 20262026-08-01 00:00:00 UTC2026-09-01 00:00:00 UTC101
Sep 20262026-09-01 00:00:00 UTC2026-10-01 00:00:00 UTC101
Oct 20262026-10-01 00:00:00 UTC2026-11-01 00:00:00 UTC110

What Hacker News says

3 sources
OmarBrikaa·Mar 29, 2025Submission

Show HN: Create presentations with smart animations using Excalidraw

I often create presentations where elements need to move (animate) from one slide to the next. This is great for explaining algorithms, workflows, or anything that benefits from dynamic visuals. I used to rely on Figma prototypes with smart animations for this, but I wanted a way to do it in Excalidraw—maybe even more conveniently. So I made an Excalidraw fork which helps you present "frames" and interpolates animations between them. Video demo (detecting cycles in a graph): https://github.com/user-attachments/assets/62033fca-03ca-489... Instructions, tips, and current limitations: https://github.com/excalidraw-smart-presentation/excalidraw-... Try it: https://excalidraw-smart-presentation.github.io/ Personal plug: I'm also currently looking for a full-time job. If you know of any opportunities or can refer me, I'd really appreciate it.
12 points · Open discussion
jimniels·Mar 27, 2025
Cool! Made me want to try building it in Quadratic because you can tie the live data source into the spreadsheet. I didn’t use the more comprehensive dataset in big query [1] and I didn't use the firebase API [2] either because it's so much data to go through. Instead I used the Algolia search API [3] because it was easy ha. The resulting charts [4] are, if nothing else, interesting to look at and on first glance similar to what I see in the og google sheet. Disclosure: I work on Quadratic and this was a good exercise in using the product (and finding bugs). The spreadsheet is available to look at publicly [5] [1] https://console.cloud.google.com/bigquery?p=bigquery-public-... [2] https://github.com/HackerNews/API?tab=readme-ov-file [3] https://hn.algolia.com/api [4] https://github.com/user-attachments/assets/a97ba432-d6dd-4d1... [5] http
Read the rest
s://app.quadratichq.com/file/033d2fa7-b205-4c27-9fce-247...
In The Website Hacker News Is Afraid to Discuss
joshleitzel·Mar 25, 2025Submission

Show HN: I built a Reddit MCP server for faster and better research in Claude

tl;dr: I built a Reddit MCP server to make LLM-based research tasks faster and more accurate — especially for use cases where up-to-date or subreddit-specific info matters. I’ve been bouncing between LLMs for "deep research" tasks lately — trend discovery, digging into niche use cases, finding the right community for topic <X>. Reddit usually has the best signal for these, but getting reliable results from an LLM is tricky. A few recurring issues: - Hallucinated subreddits: even with simple questions like “What’s the best subreddit for <X>?”, models often return made-up names. - Knowledge cutoffs: LLMs miss recent or trending content and topics, even when it’s easy to find on Reddit (try asking Claude what MCP is…) - Slow web tools: ChatGPT’s “Deep Research” and similar products can work to get up to date info, but they’re slow — often ta
Read the rest
king 5+ minutes to answer anything but the most trivial queries. To make this faster and more consistent, I built a plug-and-play MCP server that connects directly to the Reddit API. It exposes a small set of structured tools (search, fetch, browse) that LLMs can use to retrieve Reddit posts and comments in real time. It’s read-only for now to prevent any unintended side effects, but I might add write access in the future. Here’s a demo showing a request that a regular LLM without any tools simply could not complete at all, and a tool like ChatGPT Deep Research will take >5 mins and return worse results: asking the model to find highly upvoted comments in niche LLM subreddits. Demo video (sped up ~3x to reduce file size): https://github.com/user-attachments/assets/a2e9f2dd-a9ac-453... The model runs a toolchain with a set of structured queries first to identify “niche” subreddits, then looks for promising posts and comments, and iterates on this until it thinks it’s satisfied the original request. It then returns a grounded answer — all in <2.5 minutes. You can run this locally with Claude Desktop or any other MCP client (I actually use it with AutoGen -- example in the repo) — just plug in your Reddit API keys and go. There’s more in the README if you want to try it out, and I’m happy to provide any help as the MCP ecosystem is… not mature yet. Despite being a professional software engineer, building an MCP server was a total PITA so happy to pay it forward and help anyone in need of some guidance for anything they’re building. Would love feedback — especially if you’ve been working on research tools, using MCP in novel ways, have a use case for this, or things you want to see in this space.
3 points · Open discussion

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