Mukette, a Markdown Pager for Unix-Based Systems

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I really apologize if I am submitting this twice. I am new to these fora. I just discovered Show HN. The other thread did not have Show HN so it did not get any traction. This is a useful little tool so I guess people will like it. You're eithre like me, and do all your work in the terminal emulator. If they literally replace my displays with a VT100 I won't complain (but have to watch Youtube on my phone -_-). The other kind of use is someone who uses X (I know emulators are X too!) extensively, and only often needs to use the terminal This can be useful for both groups. Imagine you wanna read the README.md file of a repository. This happened to me what I wanted to read PackCC's REAMDE. And I had to do a pipline from Pandoc to Philadelphia! This nifty little tool will page the markdown file. I want to improve it in the future. I have made some leeway to adding more features to it. I want people to execute the code listings (in a safe environment) by navigating to them. It's all right these in the code, I just got tired of picking at this like an old wound and releassed it. It's been rand through ASAN and Valgrind. Some errors were fixed. If anything remains that I missed please tell me. I always initialize pointer ssto NULL so it should not complain much? Anyways thanks.

Visit product View on Hacker NewsFeb 10, 2024

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

78%78% 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: new, code, plain · Missing: mac, agents, macos

76%76% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

65%65% 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

37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

29%29% 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

16%16% 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.

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