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Octofriendly – Easiest way to follow all users of an org from GitHub

Hacker News

Octofriendly – Easiest way to follow all users of an org from GitHub

Hey HN! I built this simple tool to follow all users from a GitHub org. It uses the GitHub API to find users in the org, and then allows you to follow them with a single click. With this tool, you don't have to manually follow each user one by one. It saves time and effort for developers who need to follow all the users in their org. Let me know if you have any feedback or suggestions.

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Actual performance

1points
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
73%73% 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.
Product HuntOn track for Day 1 leaderboard · Strong signals: user, single · Missing: mac, agents, macos
72%72% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
63%63% 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: friendly, users · Missing: plus, platform, intuitive
46%46% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: users, way · Missing: mobile apps, ios, personal
36%36% 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, revenue
12%12% 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.

Incorrect prediction on native model

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