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Pullpo – Code review conversations on Slack

Hacker News

Pullpo – Code review conversations on Slack

Code review conversations on GitHub can be frustratingly slow, now you can have them on Slack. Features: - Each pull request (PR) on GitHub creates a Slack channel (public or private) with all involved parties (creator, assignees, and reviewers). - An auto-generated summary in English of what the PR does, making it easier for reviewers to enter the context. - Notifications of workflow results, new commits, new approvals... are sent in the channel. - Code comments with context are available. The initial review still takes place on GitHub, but messages are then transferred to Slack for smoother communication. Communication between GitHub and Slack is bidirectional, and messages are saved in both places.

Visit product View on Hacker NewsMar 31, 2023

Actual performance

23points

13comments

Made the leaderboard

Launch Intel predictions

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

88%88% 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: code review, io · Missing: https docs, excited, just released

54%54% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

34%34% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

33%33% predicted probability of success on AppSumo, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

23%23% 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

15%15% 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

6%6% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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