ReadMe Recipes

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ReadMe Recipes

Heya HN! I launched ReadMe here a few years ago as a Show HN (and even got the domain by randomly happening across someone giving it away here: https://news.ycombinator.com/item?id=6397526), so I figured this was a good place to post our newest feature, ReadMe Recipes. Here's the link: https://readme.com/recipes Most API documentation focuses on Reference Guides, which have the information you need about an API... all the parameters, endpoints, headers, query params, etc. They're really important! However, for a first-time user (or even someone more experienced), it's like handing someone a dictionary and telling them to learn the language. So, we built Recipes, which are interactive, use case-based code walkthroughs aimed at helping you get your users to solve specific problems. Recipes pair a common use case for your API or technical product with a snippet of code and then walk through the code explaining what everything does. Rather than focus on GETs and PUTs and POSTs, Recipes makes it easy to help your users accomplish the actual tasks they're looking to do. Many of you here already use ReadMe, so it's free with whatever plan you're on. And if you don't use ReadMe and your company has an API or other technical product, check us out :) If you wanna chat, either comment here or my email is in my profile! -Greg

Visit product View on Hacker NewsMar 26, 2021

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Product HuntOn track for Day 1 leaderboard · Strong signals: user, new, email · Missing: mac, agents, macos

73%73% 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: para · Missing: supports, reddit linkedin, podcasting

66%66% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

56%56% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue

13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency

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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