Contributors page for your open-source project

Hacker News

I’m Pranav, co-founder of Chatwoot (https://github.com/chatwoot/chatwoot), an open-source alternative to Intercom and Zendesk. What started as a passion project in 2019, gained a lot of momentum recently. This was possible because of all the contributions and love we got from the community. We’ve created a page (https://contributors.chatwoot.com) to showcase our contributors’ work and give them a platform to share their contributions with the world. We open-sourced this little project too. We’ve made our repo for other open-source projects to use it as a template and build their own contributions page. It is built on Next.js and runs on Github Pages with Github Actions updating the data regularly. Check out the project and let us what you think about the project. https://github.com/chatwoot/contributors

Visit product View on Hacker NewsMay 9, 2022

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: open · Missing: mac, agents, macos

89%89% 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.

Indie HackersFits the IH revenue-focused audience · Strong signals: created, started · Missing: supports, reddit linkedin, podcasting

69%69% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

67%67% 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

38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews

31%31% 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

14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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