Twinonyms: The Word Game

Hacker News

Hey Hackers, I came up with an idea for a word game, and created it using v0. Here is the gist: Twinonyms is a fun, addictive word game that challenges your vocabulary and lateral thinking. Each round presents you with two synonyms, and your task is to guess the word that connects them both (e.g., "final" + "endure" = "last", or "falsehood" + "recline" = "lie"). Features: Three difficulty levels (Easy, Medium, Hard) Hint system for when you're stuck Skip option to move on Score tracking Built with Next.js 16, TypeScript, Tailwind CSS, and shadcn/ui components. The dictionary was AI-generated (ChatGPT) and human quality-checked. Deployed on Vercel.

Visit product View on Hacker NewsNov 22, 2025

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Actual performance

3points

Did not reach leaderboard

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

82%82% 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.

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

46%46% 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 HuntUnlikely to reach the leaderboard · Strong signals: chatgpt, using · Missing: mac, agents, macos

44%44% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

38%38% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

34%34% 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

13%13% 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

5%5% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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