A MUD-server using lua coroutines

Hacker News

I recently finished a round of tweaks on my barebones mud-server and thought HN might be interested. https://github.com/endgame/MudCore It sits somewhere between socketmud and a full mud like tbamud in that it handles all the socket work and telnet negotiation, but it makes no assumptions about anything else. The other interesting thing is that it can talk to other services using ZeroMQ. I'm interested in reactions, particularly in terms of coding style, documentation quality and so on. It's my main "presentation piece" so far, in that it's some of the first code I actually feel proud to have on the internet. (Someone posted this 248 days ago, but it generated no discussion: http://news.ycombinator.com/item?id=2707979, I hope the repost is OK.)

Visit product View on Hacker NewsMar 3, 2012

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Hacker NewsStrong engagement from HN community · Strong signals: lua, io · Missing: https docs, excited, just released

78%78% 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: new, using, coding · Missing: mac, agents, macos

56%56% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

43%43% 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

32%32% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

26%26% predicted probability of success on Indie Hackers, 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 · Missing: web3, chat, crypto

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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