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Merunit – Visual-first unit test generator (waitlist)

Hacker News

Merunit – Visual-first unit test generator (waitlist)

Hi HN, I’ve been frustrated with how repetitive and tedious writing unit tests can be, especially when you’re just trying to ship fast. So I’m building Merunit, a visual-first unit test generator that helps you create and export tests without boilerplate or syntax. You define test cases with inputs/outputs, and it generates framework-ready test code. It runs locally in the browser, no uploads or sync. The MVP is focused on devs who are tired (or afraid) of repeating logic just to test it. Would love feedback or ideas from the community. Join the waitlist here: https://merunit.io

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
62%62% 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.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
48%48% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: visual, code · Missing: mac, agents, macos
47%47% 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
25%25% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
20%20% 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
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
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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