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A fan-made resource site for the Roblox game Grow a Garden

Hacker News

A fan-made resource site for the Roblox game Grow a Garden

Hello HN, We're a small team of developers and data analysts who are also avid players of the Roblox game "Grow a Garden". While playing, we found ourselves constantly switching between outdated wikis, sprawling spreadsheets, and Discord channels just to find reliable information on plant stats, pet abilities, and profit strategies. The data was scattered, often inaccurate, and it was taking the fun out of the game. To solve this for ourselves and the community, we built Bone-Blossom.org. It's a dedicated, fan-made resource site that brings all the essential information and tools for "Grow a Garden" into one place. Here’s what it offers: - __Plant Database:__ A complete database of all in-game plants with up-to-date prices, mutation chances, and rarity info. - __Profit Calculator:__ A tool to help you calculate potential earnings and optimize your garden layout for the best return. - __In-depth Guides:__ Detailed guides covering everything from beginner basics to advanced strategies for the pet system and in-game events. - __Community Hub:__ Links to community resources and a place to see fan creations. What makes it different from a standard wiki is that our tools are integrated directly with our data. For example, the profit calculator pulls live data from our plant database. We're also committed to keeping the information current, with a small team dedicated to tracking game updates. The project is built with Next.js, TypeScript, and Tailwind CSS. You can try it out right now at __< https://Bone-Blossom.org >__. There’s no sign-up required; all guides and tools are freely accessible. We just launched and would love to get your feedback. We're here to answer any questions you have!

Visit product View on Hacker NewsJul 22, 2025

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

95%95% 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.

AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive

50%50% 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

48%48% 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

41%41% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos

39%39% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

10%10% 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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