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Ferrisume, a JSON Resume CLI Tool

Hacker News

Ferrisume, a JSON Resume CLI Tool

The goal of a JSON resume is to be able to store a resume in data and edit the data/theme autonomously and on-the-fly. No more battling Word anymore! There's an official resume-cli that doesn't get maintained anymore. The alternative is resumed, but I got a bit annoyed at how it was implemented. I ended up spending my weekend making my own in Rust + Handlebars. Currently I only have one mediocre theme, so if anyone wants to take a crack, feel free!

Visit product View on Hacker NewsJul 29, 2024

Actual performance

1points

2comments

Did not reach leaderboard

Launch Intel predictions

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

56%56% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

51%51% 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

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

Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos

30%30% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

29%29% 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

17%17% 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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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