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Card game where players write their own cards that get parsed into code

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Card game where players write their own cards that get parsed into code

Wordbots is a long-running side project I've been working on on-and-off for the past ~7 years that I finally feel comfortable enough with to share with the HN community. It's an online tactical card game (inspired by games like Hearthstone and Magic: the Gathering), where players write their own cards in natural language, that gets parsed down to JavaScript. The English-to-JavaScript translation is handled by a semantic parser operating on a hand-crafted CCG grammar – kind of an “old-school” approach in this age of LLMs but one that performs quite well on the very constrained language of Wordbots cards. The resulting game gets pretty wacky as players can create all sorts of cards, though there are some game formats that try to produce more balanced gameplay as well (e.g. one format in which both players shuffle their decks together, and various draft formats). If you're curious about how it all works, I made a write-up about it here: https://app.wordbots.io/how-it-works And if you want to chat about Wordbots beyond this thread, please don't hesitate to join our discord at https://discord.wordbots.io/ . I'd love to hear any and all feedback. -Alex

Visit productView on Hacker NewsMay 9, 2023
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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
93%93% 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: code · Missing: mac, agents, macos
70%70% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
56%56% 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.
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
14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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