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StaleSweeper – Get rid of stale GitHub Discussions without any effort

Hacker News

StaleSweeper – Get rid of stale GitHub Discussions without any effort

If you as me suffers from OCD, its a problem when the GitHub Discussion raisers are not closing their discussions and the GitHub Discussion Space gets all cluttered. In my opinion, repository owners should not close GitHub Discussions - no matter if they're answered or not. I strongly believe it should be the raiser of the discussion to decide if its acceptable answered and can be closed - Thats why I leave them open - now - what to do? StaleSweeper is a open-source GitHub Action to de-clutter your GitHub Discussion Space gracefully and with plenty of options.

Visit productView on Hacker NewsMar 17, 2024
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Actual performance

3points
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Launch Intel predictions

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Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
66%66% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntOn track for Day 1 leaderboard · Strong signals: open · Missing: mac, agents, macos
65%65% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
35%35% 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
22%22% 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
21%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, podcasting
12%12% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
11%11% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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