I built a Terms and Policies Generator to be done in a few minutes

Hacker News

As I work creating apps for myself and also for other people and companies, creating terms of use and privacy policy documents are always a pain in the ** and takes a lot of time. When it comes for something you are just testing out or validating, you just don't wanto to spend your time with that, but you have to or you might face some serious problems. That's why I created this tool called easyterms, so you (and also me) can create your terms and policies easily, just in a few minutes, by just filling a form using a easy to understand language. A perfect tool for solopreneurs, small business, new startups or validation/testing an idea. If you have any questions about how to use it, feel free to ask in the comments. Alex

Visit product View on Hacker NewsMar 21, 2025

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Did not reach leaderboard

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

75%75% 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: apps, new, using · Missing: mac, agents, macos

62%62% predicted probability of success on Product Hunt, 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

46%46% 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: apps, way · Missing: mobile apps, ios, personal

38%38% 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

36%36% 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

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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