We built a tool that automatically generates API tests

Hacker News

Hi, this is Mish and Sebastian. We are working on Step CI - a fully automated API testing platform for developers. Step CI works programming-language independent and for different API paradigms (REST, GraphQL, XML). Our CLI and test runner are available on GitHub ( https://github.com/stepci ) under the MPLv2 license. Since our last launch, Step CI is now able to generate automated tests for your API based on your OpenAPI (Swagger) spec. This saves you a lot of time as you never have to write and maintain your tests again! We would like to invite you to try our tool and give us feedback! Please star us on GitHub, if you like what we are working on! We are very thankful for your attention and any feedback or suggestions we receive from you :) Mish and Sebastian from Germany

Visit product View on Hacker NewsOct 10, 2022

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

78%78% 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: open · Missing: mac, agents, macos

73%73% 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

57%57% 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: platform · Missing: plus, intuitive, reviews

31%31% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

29%29% 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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