AI-Powered OpenAPI Spec Generator

Hacker News

Hi hn! I wanted to share a simple JS script I built that uses Anthropic's Claude AI to auto-generate OpenAPI specs from code. Keeping OpenAPI specs in sync is tedious and error-prone. I was wasting too much time manually updating YAMLs. To fix this, I created a script that leverages Claude to parse source code and produce OpenAPI specs, no annotations needed. It's a gist you can copy/paste into your project: https://gist.github.com/hotkartoffel/2d2ca5a5a4ace98ca7fe87f... Feed it your code and Claude handles inferring the OpenAPI objects. I've tested it on JavaScript and Python APIs, but it's framework-agnostic. If Claude understands the code, it can generate the spec. You need an Anthropic API key for Claude. But if you want to try the script, I'm happy to provide a small hosted demo - just ping me! Adding this to CI/CD means fresh OpenAPI specs on each code change, no manual updates required. Definitely a bit flimsy atm, but wanted to gather feedback.

Visit product View on Hacker NewsAug 10, 2023

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Product HuntOn track for Day 1 leaderboard · Strong signals: claude, code, apis · 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 · Strong signals: created · Missing: supports, reddit linkedin, podcasting

60%60% 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

38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

30%30% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

28%28% 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

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

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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