Eemoji – A tiny CLI tool that adds emojis to your commit messages

Hacker News

Emojis can make it instantly apparent what a commit does. This package appends an emoji to your commit messages. How it is different from others: - Just works: one line install and that's it - Automatic: you don't actually need to use the CLI, this package operates with git hooks - Customizable: includes default config, but you can bring your own emojis and specify your own format Install it locally for NodeJS projects, or globally for any kind of project.

Visit product View on Hacker NewsJan 15, 2024

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

75%75% 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 · Missing: supports, reddit linkedin, podcasting

64%64% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

51%51% 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

37%37% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released

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

nativeThis product was originally launched on this platform.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

11%11% 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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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