Cl
Claude Wrapped in the terminal, with a WASM raymarcher
Hacker NewsClaude Wrapped in the terminal, with a WASM raymarcher
Claude Code added a /stats command. The stats are cached in $HOME/.claude, so I made a fun program with Bun + WASM that pulls the stats (nonsensitive, nonidentifiable), posts them to a database, and lets you see where your usage lies. The code is here[^1] if anyone's interested in the rendering code or wants to make sure I'm not exfiltrating their credit card. [^1]: https://github.com/tspader/claude-wrapped/
Share cardActual performance
15points
2comments
Made the leaderboard
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Product HuntOn track for Day 1 leaderboard · Strong signals: claude, code · Missing: mac, agents, macos77%77% 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.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal43%43% 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 · Missing: https docs, excited, just released40%40% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting31%31% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive27%27% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue21%21% 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, crypto10%10% predicted probability of success on BetaList, based on ML models trained on real launch data.
Incorrect prediction on native model
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