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A chess analyzer that runs in the browser

Hacker News

A chess analyzer that runs in the browser

I play chess casually and usually struggle to figure out why Lichess analysis say my move is a blunder. Almost all the analysis tools will just suggest the best variant for a position, and you will have to follow the suggested engine lines, or play them out manually to analyze it better. So I built this tool to make that process easier for beginner players. Behind the scene: This app run Stockfish in your browser, at a position, the app will follow the engine's suggested lines, search for any meaningful situation like a check, a fork, a capture, material change, positional disadvantages,... and point that out with an explanation. You can see the app here: https://whyblunder.vercel.app and paste the PGN of your game. If you play on Lichess, you can also replace the lichess.org part in the browser URl with https://whyblunder.vercel.app/#<game-id> to quickly analyze, for example: https://whyblunder.vercel.app/#cBVQFX8l

Visit product View on Hacker NewsSep 16, 2026

Actual performance

2points

2comments

Did not reach leaderboard

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best fitHighest predicted score across all platforms for this description.

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

42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

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

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

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

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

28%28% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

18%18% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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