I built a tool to help you quickly understand MBTI personality types

Hacker News

I'm excited to share a small project I built: easymbti.org. It's a simple tool designed to help you quickly understand the 16 MBTI personality types in the clearest, most straightforward way possible. I noticed that many existing MBTI resources are often full of jargon and lengthy descriptions, which can make it hard to grasp the core concepts. easymbti.org aims to solve that problem. What makes it different: Minimalist Design: I stripped away all unnecessary clutter to focus only on the essential information. You can find any type in seconds and see its key traits. Neutral Descriptions: The site offers objective, non-judgmental descriptions. I believe every personality type has unique strengths and challenges, and the tool reflects that. Focus on Key Points: Each type is summarized with a few core keywords, so you can immediately get a sense of its main characteristics. This was a fun, simple project to build, and I'd love to hear your thoughts. Whether you have feedback on the design, the content, or suggestions for new features, please share them in the comments below.

Visit product View on Hacker NewsAug 21, 2025

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

80%80% 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 · Missing: mac, agents, macos

71%71% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

55%55% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: excited, exist, existing · Missing: https docs, just released, lua

49%49% 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 · Strong signals: personal, way · Missing: mobile apps, ios, entrepreneurs

32%32% 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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