Re

Reunited My Cats in Code – yet another lightweight OpenClaw alternative

Hacker News

Reunited My Cats in Code – yet another lightweight OpenClaw alternative

# I Reunited My Cats in Code Pickle is yelling for food right now. She does this 8PM everyday. Cookie was her step-brother. The chill one. He lives somewhere else now. So I reunited them in code - Pickle handles the chat, Cookie handles the memories. They're still together. --- Okay, enough cat story. I built *pickle-bot* - yet another lightweight OpenClaw alternative. OpenClaw is incredible, but I wanted to understand how agents work. So I built my own: - Runs on Raspberry Pi - A clean and manageable codebase - Create agents, add skills, schedule crons - Chat via CLI, Telegram, Discord - Web Search, API server, all good stuff. *Chatting with "Pickle" while Pickle yells at me? Just so much fun.* Check the repo: [pickle-bot]( https://github.com/zane-chen/pickle-bot ) Pickle is mine. Bring your own cats :)

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Actual performance

2points
Did not reach leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, openclaw · Missing: mac, macos, cursor
94%94% 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 · Missing: supports, reddit linkedin, podcasting
61%61% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
37%37% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
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.
Hacker NewsMay not resonate with HN audience · Missing: https docs, excited, just released
26%26% 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
20%20% 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
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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