Pream-team A TUI app that list PRs on multiple GH repos from your team

Hacker News

My team touches multiple repositories, it is difficult to get an overview of all open PRs for my team. It helps me prioritise reviewing team PRs, since my inbox gets full of GitHub notifications and I can miss new pull requests until someone pings me. This TUI app attempts to solve that issue. It caches the GitHub api responses so that you can open and close it often without loosing the previously fetched PR list (fetching a list of PRs can be slow due to GH search api rate limit). It displays the timestamp of the fetched PRs so you know if you would like to refresh to prevent the list from being too outdated. Any suggestions on how to improve the code or UX are more than welcome!

Visit product View on Hacker NewsFeb 19, 2024

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

87%87% 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.

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

46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

42%42% 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: io · Missing: https docs, excited, just released

36%36% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

22%22% 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

21%21% 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

5%5% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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