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I Made Fleschkey – Non-AI Text Editor with Readability Insights

Hacker News

I Made Fleschkey – Non-AI Text Editor with Readability Insights

Hello, HN! After weeks of being frustrated with bloated software and AI writing tools, I decided to make something different—something simpler. That's how I created Fleschkey, my privacy-first, AI-free text editor. Fleschkey is for writers who want their work to be clear. It gives instant feedback with a readability score based on the Flesch-Kincaid formula, made in 1975—a system that's been used in many ways since then. To me, privacy means more than opting in or out. It means no one can see or take your data unless there's a good reason. That’s why everything stays on your device—no cloud, no AI, no data collection, no worries. By the way, the text above received the following scores: Flesch-Kincaid Grade Level: 7.16 Flesch Reading Ease Score: 67.55 Reading Level: 7th grade (Plain English) Average Words per Sentence: 13.38 Average Syllables per Word: 1.49 Sentences: 8 Words: 107 Characters (including spaces): 639

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Actual performance

5points
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: created, including · Missing: supports, reddit linkedin, podcasting
77%77% 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.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io, including · Missing: https docs, excited, just released
57%57% 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: plain · Missing: mac, agents, macos
50%50% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal
48%48% 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
27%27% 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
21%21% 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.

Incorrect prediction on native model

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