IDE Like Terminal

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IDE Like Terminal

Terminal built with Tauri (Rust+Svelte). I got this idea of creating a terminal that is more user friendly having autocomplete suggestions. I couldn’t create a suggestions engine that would work for all commands. But I defined a structure (a state machine in src/cli/library/library.ts) that can be used to determine the next suggestions. The good part with this approach is that it is possible to have custom script based suggestions. For example if we write in the terminal “git checkout” and after we press Space, a dropdown will appear with all available branches. The bad part is that it will take some time to add more supported commands in this “library”. Another feature is that in the bottom bar of the terminal we can have custom script based information. In .manter.json we can define a script that will generate this information. The script will be executed each time the prompt appears. On the front-end are used web technologies which offer a flexibility to add any feature and style that we want. Repository: https://github.com/iondodon/manter

Visit product View on Hacker NewsFeb 2, 2023

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, user · Missing: agents, macos, agent

85%85% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

66%66% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

47%47% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

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

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

42%42% 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 · Missing: web3, chat, crypto

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

Correct prediction on native model

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