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Zsh-AI – Natural language to shell commands in your terminal

Hacker News

Zsh-AI – Natural language to shell commands in your terminal

I built this lightweight plugin because I kept forgetting command syntax for things like finding processes on ports or batch file operations. It's been saving me time, so I'm sharing it in case others find it useful. How it works: Type `# kill process on port 3000` and you'll get `lsof -ti:3000 | xargs kill -9` - Single 5KB shell script, no Python/Node dependencies - Works with any shell that supports command substitution - Uses Anthropic's API (you need your own key) - Commands are suggested, not auto-executed, for safety See a demo at https://github.com/matheusml/zsh-ai This is a simple first version - I'd really appreciate feedback on what would make it more useful for your workflow!

Visit productView on Hacker NewsJun 27, 2025
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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: single · Missing: mac, agents, macos
63%63% 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: supports · Missing: reddit linkedin, podcasting, created
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
44%44% 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
35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: 000, io · Missing: https docs, excited, just released
31%31% 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
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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