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A Simple Obisidan plugin to draw ASCII shapes like MS Paint

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A Simple Obisidan plugin to draw ASCII shapes like MS Paint

I like to draw things ascii on obsidian when I am working on projects but sometimes it's quite challanging for me because the line starts to shift as I edit some regions. I ended up building a ms paint like canvas experience for ascii so instead of thinking like it's text, we think like it's canvas but it still draws texts. Also, it supports embed on other notes and dynamic canvas size for your preference.

Visit productView on Hacker NewsFeb 25, 2026
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Actual performance

3points
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Launch Intel predictions

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Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
63%63% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntOn track for Day 1 leaderboard · Strong signals: notes · Missing: mac, agents, macos
61%61% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Strong signals: supports · Missing: reddit linkedin, podcasting, created
42%42% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
42%42% 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
37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.
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 · Missing: web3, chat, crypto
3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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