Gait – A Command Line Tool for reviewing code changes

Hacker News

Hey HN, I wanted to share the open-source command line tool I built a while ago that allows you to review code changes in a git repository with chatGPT. My personal favorite is the gait pr command, it compares the HEAD with a remote branch and generates a PR review automatically. This means you can get preliminary review by GPT-4 before even opening an actual pull request, increasing your chances of approval. Currently it is just a prototype with minimal customization and with only a zero-shot prompt but I believe it has a huge potential, and I am open to your insights and contributions. Please feel free to try it out and give feedback! You can install it via pip: ``` pip install gait ```

Visit product View on Hacker NewsSep 11, 2024

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Actual performance

2points

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: chatgpt, code, open · 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.

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

55%55% 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

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

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

47%47% 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 · Strong signals: personal · Missing: mobile apps, ios, entrepreneurs

38%38% 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

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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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