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Below the Root (1984 game) ported to JavaScript

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Below the Root (1984 game) ported to JavaScript

As a kid, I loved this relatively unknown game, Below the Root. The world-building of the original trilogy of novels from the 1970s, is lovingly carried through into this side-scrolling "platform-adventure". You can play the IBM PC port of this game online fairly easily, but the quality of the C64 version is much better (non-dithered graphics, better colors, polyphonic sound). However I found there was a lot of friction to just play the C64 version. So back in 2013, I tried restoring and packaging the C64 version of the game to make it just one step to play. I made a bootable x86 ISO with a Linux unikernel that only ran the VICE C64 emulator, pre-configured to launch the game from some .G64 disk images that a German hacker cracked for me. Took about 4 months of effort and the results were mid; the game would be running from VMWare boot in 5 seconds but it still required a whole VM, the sound was choppy, and save games were kind of a hassle. I made a basic webpage and shelved it as a beta experiment. Then, for some reason about a week ago I decided to try again. But this time I directed Fable and Astra in varying capacities to dissect and disassemble the original .G64 images, produce a spec, and produce a Javascript version equivalent to the original. They got about 75% mostly autonomously in a single evening. I've since spent a few tens of hours playing it through, getting bugs fixed, tweaking the interface, improvements, and writing the About page. I had to have some difficult conversations with Claude and I made some unpopular decisions, but after all that, this is the result and I'm kinda proud of it. It's not a major project, but then it never should have been. So I just wanted to share this game from my childhood and the process and the result. Hope other people remember this game fondly and enjoy playing it again!

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Indie HackersFits the IH revenue-focused audience · 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: claude, single · Missing: mac, agents, macos
56%56% 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
55%55% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform, interface · Missing: plus, intuitive, reviews
47%47% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: month · Missing: mobile apps, ios, personal
41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: arr · Missing: mrr, revenue, profit
14%14% 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.

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