A New Terminal

Hacker News

A New Terminal

This project aims to create a terminal with functionalities that improve the experience of using terminals. Examples of useful functionalities would be autocomplete suggestion. The project uses technologies such as Svelte on the front-end, which offers flexibility regarding the implementation of the interface. The back end is implemented in Rust. The basic framework of the project is Tauri. At the moment the terminal has suggestions only for some commands (cd, ls, ...). To support more commands it is needed to add them in the Manter's "library" located at src/cli/library/library.ts. 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. See the link to the project in the comments section.

Visit product View on Hacker NewsFeb 24, 2023

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

80%80% 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 HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

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

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

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

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

46%46% 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

43%43% 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

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

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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