Oa

OasRails – AutoGenerate Interactive API Docs in Rails with Yard and OAS

Hacker News

OasRails – AutoGenerate Interactive API Docs in Rails with Yard and OAS

I built OasRails, a Rails engine that automatically generates OpenAPI 3.1 documentation from YARD comments in your Rails controllers. It renders the docs using RapiDoc for a slick, interactive UI—no DSLs, no generators, and no dependency on RSpec or Grape. I was inspired by FastAPI’s interactive docs and wanted something similar for Rails. After not finding anything that met my needs, I built OasRails during downtime as a freelancing dev.

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Actual performance

3points
2comments
Did not reach leaderboard

Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
66%66% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: using, open · Missing: mac, agents, macos
60%60% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released
51%51% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
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
41%41% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue
19%19% 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
5%5% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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