Oi

Oidia – A simple no-judgement streak tracker for the terminal

Hacker News

Oidia – A simple no-judgement streak tracker for the terminal

Hey all! This is OIDIA, a terminal-based streak tracker I'm toying with. It's still fairly early days, but in terms of look and feel and working I think this is about where I want it. One of the main points I wanted to stick with was that it's "no judgement"; it tracks counts on days, and that's the lot. No shaming, no percentages, nothing like that. OTOH the data is held in a simple JSON file allowing anyone to have all the fun they'd like with what they accumulate.

Visit product View on Hacker NewsDec 17, 2022

Actual performance

2points

Did not reach leaderboard

Launch Intel predictions

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

79%79% 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 · Missing: mac, agents, macos

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

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

45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

38%38% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released

35%35% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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.

Correct prediction on native model

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