Screensnap Screenshot – A extension for making polished screenshots

Hacker News

Hey HN, I've been working on a small side project called Screensnap, a suite of browser extensions designed to elevate your screen capture game. The first extension, Screensnap Screenshot, is now available and lets you take beautiful and polished screenshots with features like: - Custom backgrounds (gradients and images) - Adjustable padding & rounded corners - Shadow effect - Multiple formats: PNG, WebP, AVIF, JPEG - Save visible area, custom area or full page - Limit exported file size - YouTube video screenshot *Transparency Note:* Screensnap Screenshot is a paid extension. I've poured a lot of effort into making it a valuable tool, and I believe the features justify the cost. However, I'm very interested in your feedback! Let me know what you think about the concept, the features of Screensnap Screenshot, and even the pricing model. Is this something you'd find useful? Would you consider paying for it? *Here's what I'm especially interested in:* - Feedback on Screensnap Screenshot's features and functionality. - Thoughts on the pricing model for Screensnap Screenshot. I appreciate any insights you can offer! Below is the link to the extension, which is now supported on Google Chrome: https://chromewebstore.google.com/detail/screensnap-screensh...

Visit product View on Hacker NewsJan 16, 2025

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

83%83% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Strong signals: model, google · Missing: mac, agents, macos

80%80% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

49%49% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

28%28% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: paid · 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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