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Daggerheart Game Master Tool

Hacker News

Daggerheart Game Master Tool

Hey everyone, I have been looking into Daggerheart (a new TTRPG currently in open beta) since the playtest and I am loving it. I ran a few combat simulations and I enjoyed the variety. However I noticed as a GM in combat, there is a lot to keep track of. I have ADHD so I struggled a lot. I hope Demiplane releases an encounter builder for daggerheart soon. For now, I built myself a small digital tool to help with this when I will run a game for friends soon.hese are the features at the moment: - Action tokens tracking - Fear Tokens tracking - Countdown tracking - Monsters statblocks (only the ones from the quick start adventure) with attack and damage rolls built in. - Responsive UI on a wide range of screens including mobile devices - A quick overview of the GM moves rules + combat tips - Client side app, everything happens in the browser and will be lost once you close the tab. It's purely tailwindcss and stimulus js to keep it simple. the codebase is a html file sprinkled with some styling and a small js file. deployed the app via Github pages. I'd appreciate feedback about UX, design, bugs, or responsiveness issues. Thanks!

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Actual performance

1points
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: including · Missing: supports, reddit linkedin, podcasting
84%84% 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: new, code, open · Missing: mac, agents, macos
70%70% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Strong signals: soon, builder · Missing: plus, platform, intuitive
54%54% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: adhd, ide, io · Missing: https docs, excited, just released
45%45% 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 · Missing: mobile apps, ios, personal
38%38% 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
12%12% 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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