Bo
Bookmarklet to get 12 month Gitlab contributions
Hacker NewsBookmarklet to get 12 month Gitlab contributions
javascript:alert(`${Array.from(document.querySelectorAll('rect.user-contrib-cell')).reduce((sum, node) => sum + (parseInt((node.getAttribute('title') || node.getAttribute('data-original-title') || '').split(' ')[0]) || 0), 0)} contributions in the last 12 mo.`);
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BetaListSuited for BetaList early-adopters · Missing: web3, chat, crypto62%62% predicted probability of success on BetaList, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
TrustMRRFits verified-revenue profile · Strong signals: month · Missing: mobile apps, ios, personal53%53% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released40%40% 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 · Missing: plus, platform, intuitive37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Strong signals: user · Missing: mac, agents, macos30%30% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: arr · Missing: mrr, revenue, profit21%21% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting18%18% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Correct prediction on native model
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