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Circumflex, browse HN in your terminal

Hacker News

Circumflex, browse HN in your terminal

Some two years ago, I found myself spending a lot of time in the terminal between learning vim and discovering new command line tools. I was surprised to see that the niche of HN clis was (relatively) small, and so I decided to write my own command line tool for browsing HN called `circumflex`(`clx`). `clx` is written in Go using Bubble Tea[1]. You can read the comment section or the linked article in reader mode in the pager `less`. Using `lesskey` to add custom keybindings, the replies can be collapsed and expanded in real-time (but not individual replies, only all replies at once). Behind the scenes I am appending invisible unicode characters to each line so that I can use the custom keybindings to filter them out. The same technique is used to allow for jumping between top-level comments. I spent a lot of time thinking about syntax highlighting and finding relevant bits to highlight while also not going overboard with colors. The end result is highlighting of things I find useful for providing context in the comment section, like indicating parent poster and original poster, coloring references, coloring indentations as well as formatting YC startups. Other quality of life features include adding submissions as favorites (it is stored as a pretty-printed json so you can check it into your vcs to allow for readable diffs). Submissions are marked as read and new comments are indicated with a bullet point. [1] https://github.com/charmbracelet/bubbletea

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Actual performance

180points
63comments
Made the leaderboard

Launch Intel predictions

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Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
72%72% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntOn track for Day 1 leaderboard · Strong signals: new, context, using · Missing: mac, agents, macos
70%70% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
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.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
46%46% 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
28%28% 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
12%12% 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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