Thumbly – Generate dynamic social media thumbnails for your website

Hacker News

Hello HN community, happy Thursday! I’m excited to share something I’ve been working on over the past few weeks: Thumbly. You’ve probably seen those dynamic social media thumbnails when you share a GitHub repository on Twitter or other social media. Thumbly can bring that same functionality to your website. With Thumbly, you can generate dynamic social media thumbnails for every page of your site. These thumbnails can automatically change based on the parameters you set, so each page has its own unique design. No need to manually create or upload different thumbnails every time you publish new content. I originally built Thumbly for one of my own side projects because I wanted dynamic, GitHub-style thumbnails for social media shares. I’d love to share it with others who might find it useful. So this is basically a side-project of a side-project. There’s no signup page yet, but feel free to reach out to me via email. I’ll be happy to help you integrate Thumbly into your website or even set it up on your own server. I’m actively using Thumbly myself, so I’ll continue to improve and add features. Your feedback and ideas would mean a lot as I refine it! And if you are not happy with the pricing, I'd be happy to discuss something that fit your requirements and site's workload.

Visit product View on Hacker NewsDec 19, 2024

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Product HuntOn track for Day 1 leaderboard · Strong signals: new, email, using · Missing: mac, agents, macos

84%84% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Strong signals: para · Missing: supports, reddit linkedin, podcasting

69%69% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

56%56% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: excited, ide, io · Missing: https docs, just released, exist

42%42% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: para · Missing: mobile apps, ios, personal

30%30% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue

14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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