Borland/Turbo C++ flavor menus for Vim 8.2

Hacker News

There are many keymaps defined in my .vimrc. Getting tired from checking .vimrc time to time when I forget some, based on latest +popup feature (vim 8.2), I created this vim-quickui plugin to introduce some basic ui components to enrich vim's interactive experience: - Well designed and carefully colored Borland/Turbo C++ flavor ui system combined with vim's productivity. - Can be accessed by keyboard only while mouse is also supported. - Navigate with the usual Vim keys like h/j/k/l, confirm with ENTER/SPACE and cancel with ESC/Ctrl+[. - Tip for each entry can display in the cmdline when you are moving the cursor around. - Pure vim-script, +python is not required. - No longer have to be afraid to forget keymaps anymore. https://github.com/skywind3000/vim-quickui

Visit product View on Hacker NewsDec 28, 2019

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

76%76% 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: cursor · Missing: mac, agents, macos

63%63% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: 000 · Missing: https docs, excited, just released

48%48% 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 · Missing: plus, platform, intuitive

33%33% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue

12%12% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: introduce · Missing: web3, chat, crypto

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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