Generate Walthroughs for GitHub Repos

Hacker News

Hey Everyone! A friend and I are working on tooling to help learn to code. We've converged on a simple tool that lets us provide a github url and behind the scenes we analyze it and generate a series of pages related to the implementation. Here's an example from OpenAI Swarm: https://www.notion.so/Open-AI-Swarm-161ee7a4c45780ef9715ccd7... Right now the process is fill out a form and we'll email you the doc once its completed. We're looking for any feedback on the final product so please send us any cool repos you know of!

Visit product View on Hacker NewsDec 20, 2024

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

78%78% 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: ide, io · Missing: https docs, excited, just released

55%55% 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 HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

51%51% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

24%24% 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

13%13% 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

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

Incorrect prediction on native model

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