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Sift – local, de-noised GitHub notifications

Hacker News

Sift – local, de-noised GitHub notifications

Sift is an open source local GitHub inbox organizer. GitHub notifications are good at collecting activity and weak at prioritizing it. Sift pulls your inbox and adjacent repo activity into a local SQLite database, classifies it with explicit rules, and gives you a browser UI to work through it by signal instead of by noise.

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Actual performance

2points
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: inbox, activity, open · Missing: mac, agents, macos
86%86% 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.
Hacker NewsStrong engagement from HN community · Strong signals: open source, io · Missing: https docs, excited, just released
61%61% 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 · Missing: mobile apps, ios, personal
43%43% 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
35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting
26%26% predicted probability of success on Indie Hackers, 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
8%8% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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