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I've built a REST Test client in my spare time

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I've built a REST Test client in my spare time

Hi HN,<p>In my spare time (evenings and weekends) I've built 3 products which have been relatively successful even with little advertising (only google ads budgeted at $30 per day). The latest one is WcfStorm.Rest; which is a REST service test client. I built it because I found that the current tools did not have the features I wanted such as, intellisense when working with HTTP headers, syntax highlighting for JSON messages, etc.<p>I'm continually trying to improve these products and would very much love get your feedback. Every suggestion is welcome!<p>(My apologies for any grammatical mistakes. English is not my first language)

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Indie HackersFits the IH revenue-focused audience · Strong signals: mistakes · Missing: supports, reddit linkedin, podcasting
89%89% 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: google · Missing: mac, agents, macos
62%62% 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 · Missing: plus, platform, intuitive
32%32% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: google · Missing: mobile apps, ios, personal
23%23% 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
16%16% 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.

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