I built a tool to generate documentations using Notion as CMS

Hacker News

Hey HN. I'm a developer and solopreneur. A few months ago, I realized I was spending countless hours creating documentation websites for my projects. I kept repeating the same steps over and over: formatting, designing, and trying to make it look good, only to start all over again when something changed. So I built QuickDocs for 3 reasons: Save time by turning Notion pages into professional documentation websites in minutes. Eliminate headaches of dealing with design, hosting, or yet another CMS. Stay focused on building products instead of wasting time managing docs. I hope QuickDocs can be as helpful to you as it is for me. Whether you're launching a product, writing team docs, or managing guides, it's designed to keep things simple and efficient. Would love your feedback! Rudolfs

Visit product View on Hacker NewsDec 29, 2024

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Product HuntOn track for Day 1 leaderboard · Strong signals: using · Missing: mac, agents, macos

83%83% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

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

75%75% predicted probability of success on Indie Hackers, 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

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: month · 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 · Strong signals: host, efficient · Missing: plus, platform, intuitive

44%44% 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

18%18% 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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