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Generate docs from your public repos

Hacker News

Generate docs from your public repos

Hello HN, I’m Andrew from docs.dev ( https://docs.dev/ ), an AI powered docs assistant. With docs.dev you can generate your docs directly from your codebase, existing docs and other context sources. We don’t believe AI will replace technical writers—our goal is to make it easier for teams to get a solid first draft that they can review, edit, and improve. Think of it as a head start, not a finished product. More info on what we’ve built below but we wanted to release a quick, 1 minute, generate docs from your codebase tool. Try it out here: https://app.docs.dev/generate-docs-instantly . We built this page, so folks could generate some docs easily and quickly on some of their open source projects. It is still new so let us know if there are bugs but feel free to give it a try! It should work on any moderately sized public repo on GitHub. Why build another docs tool? We believe there are many great tools out there to help teams host their docs and make them look great, but that there aren’t enough tools to help teams manage the content that goes into them. We found that often there’s a disconnect between the devs shipping code and the teams managing the docs, often leading to delays in getting new features out the door or outdated docs. We kept hearing that the only thing worse than no docs is incorrect docs. So, we built tools to help you manage docs directly from your codebase—no special platforms or vendor lock-in required. With docs.dev you can not only generate first drafts of new docs, but also audit your existing docs in bulk, analyze them for effectiveness, and keep everything up to date as the product changes. docs.dev can: Work with any markdown-powered framework Generate clean markdown files synced with your GitHub repo Support existing markdown docs, your codebase, and even Slack threads as context More info at docs.dev ( https://docs.dev/ ) and on our docs page ( https://learn.docs.dev/ ) We’d love for you to check us out and welcome any feedback, criticism, suggestions, questions, or ideas! Thanks so much for reading!

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Actual performance

27points
11comments
Made the leaderboard

Launch Intel predictions

Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: slack, new, context · Missing: mac, agents, macos
97%97% 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: exist, open source, existing · Missing: https docs, excited, just released
76%76% 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
64%64% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform, host · Missing: plus, intuitive, reviews
38%38% 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
34%34% 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
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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