Cluescall – A virtual escape room I built for friends

Hacker News

A while back I invited friends for a Saturday game night. But instead of the usual board games, I decided to build a treasure hunt / escape room challenge for them to play. Several of my friends are developers, so i wanted to have some form of coding as part of the game. The first clue was a long string of numbers with embedded patterns that was somewhat obvious to the naked eye, but wasn't easy to extract with a pen and paper, forcing them to code :). Anyway a few clues and few hours later there was a winning group. I was initially hesitant, but decided to productionize a version of the virtual room, sans the coding sections and certain parts simplified. I have a lot of different clue ideas, but wanted to release an MVP first. The game is setup to be primarily laptop friendly. Feel free to leave feedback at hello@cluescall.com

Visit product View on Hacker NewsJan 19, 2023

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

80%80% 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 NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

62%62% 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: coding, code · Missing: mac, agents, macos

54%54% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

50%50% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Strong signals: way · 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

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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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