A terminal inbox for a GitHub repo PRs

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Inspired by an app with another material name (Graphite), here is my little take on a TUI for viewing and reviewing PRs in a repo! This is my first HN submission :) After a colleague decided to build his on web app clone of the original material-named service, I thought I would make my own take on it in the terminal, using the OpenTUI framework. I also use tmux and git worktrees quite a bit, so I added a handy "w" shortcut to create a worktree for a given PR, and open a new tmux window in that worktree. Btw, if you don't use tmux, the worktree just gets created in the background. Hope it can be as useful as the material-named services inspirations have been for me! And would love to hear some opinions :)

Visit product View on Hacker NewsSep 19, 2026

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

92%92% 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 · Strong signals: created · Missing: supports, reddit linkedin, podcasting

57%57% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

52%52% 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

41%41% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

37%37% 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

15%15% 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.

Incorrect prediction on native model

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