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I created a simple and fast Broken Link Checker for WordPress
Hacker NewsI created a simple and fast Broken Link Checker for WordPress
There aren't any reliable free broken link checkers out there, so I decided to create one. Right now, it is a Python script that can be run on any platform. It is multi-threaded and has a lot of room for improvement. Feel free to check out the code and point out the mistakes or leave suggestions. I am newbie programmer :)
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Indie HackersFits the IH revenue-focused audience · Strong signals: created, mistakes · Missing: supports, reddit linkedin, podcasting88%88% 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 · Missing: https docs, excited, just released51%51% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews48%48% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal46%46% 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, revenue18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: new, code · Missing: mac, agents, macos17%17% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto3%3% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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