I created a tool to generate handwritten signatures

Hacker News

At this time, I had to sign multiple documents (energy, gas, water, etc) for our new house. I'm using a Mac, and I have the option to create my own sign and reuse it multiple times, making it easy for me. I'm also exploring vibe coding, so I decided to try building a small web app to generate handwritten signatures, allowing me to have a cool-looking signature and for others to use it if they want. You can generate multiple signatures and only pay if you want to download your 7-signature pack. I decided to let the users pay for it (only $3), not to become rich obviously :D, but to maybe cover some operational costs, like the VPS and the domain. Since this is my first vibe-coded project, I'm also open to receiving feedback, so I can give some directions to my "virtual employee" :D Thanks in advance!

Visit product View on Hacker NewsDec 25, 2025

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Indie HackersFits the IH revenue-focused audience · Strong signals: created · 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: mac, user, new · Missing: agents, macos, agent

74%74% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

40%40% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

40%40% 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: users · Missing: mobile apps, ios, personal

36%36% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

11%11% 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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