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BotMaD – an inetd-like bot manager for Slack

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BotMaD – an inetd-like bot manager for Slack

BotMadD is an unopinionated bot engine for Slack. It really has only one opinion... that a bot should be written to handle one conversation, and the bot manager (BotManD itself here) should manage the lifecycle of these bots, starting up instances for new conversations and shutting them down once the conversations are complete. BotManD bots are simple standalone executables which read input on stdin and respond on stdout. BotManD starts up your bot based on configured triggers (a separate instance is launched for each new conversation), and then gets out of you bot's way. For people who still remember inetd, think of this as inetd for bots. (Would, in fact, have named it botnetd but for some unfortunate associations the word evokes.) I wrote BotManD because I often need a simple way to run pre-determined commands on remote machines. I initially used small special-purpose scripts for these developed using one of the many Slack bot libraries, but each time I needed to add support something resembling a simple conversation, I ended up having to write code to manage state and keep track of conversations happening in multiple threads... a lot of plumbing work not related at all to the task I was trying to finish. This frustration led to the development of the initial prototype of BotManD, which I quickly found useful enough to justify reimplementing with a few more bells and whistles to support different types of bot interactions. The thing that sets BotManD apart from other bot toolkits is that it is designed from the ground up to handle conversations. There are, of course, other bot development tools which support conversations, like Botkit, but they all seem to need tool-specific conventions to implement complex logic involving conditionals or loops. BotManD bots, on the other hand, are simple executables written in the language of your choice. Assuming your language of choice is turing-complete, so is your bot. :) Of course, tools like Botkit do a lot of other things, not least of them being the ability to talk to a bunch of different messaging platforms. BotManD only supports Slack right now, though there are plans to support Teams and Discord some time soon. Check the GitHub repo for instructions on getting started with BotManD, as well as a bunch of examples, including a few real-world ones which do some interesting things using ChatGTP and OpenAI's API.

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Actual performance

1points
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: supports, started, para · Missing: reddit linkedin, podcasting, created
87%87% 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: mac, slack, new · Missing: agents, macos, agent
80%80% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io, including · Missing: https docs, excited, just released
70%70% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRFits verified-revenue profile · Strong signals: way, para · Missing: mobile apps, ios, personal
58%58% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform, soon · Missing: plus, intuitive, reviews
46%46% 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.

Incorrect prediction on native model

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