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System-info-now – Aggregate system debug data for LLM troubleshooting

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System-info-now – Aggregate system debug data for LLM troubleshooting

system-info-now is a lightweight command-line utility that aggregates your system’s debugging data into a well-structured JSON snapshot. It scans your computer for a comprehensive set of details—from OS and hardware specifications to network configurations, running processes, and even language-specific diagnostics for Python and JavaScript. Currently, it supports macOS only, but Linux and Windows support are coming soon. By unifying all this information into one JSON file, system-info-now creates an ideal input for LLM-driven analysis. This structured snapshot enables you to leverage advanced AI tools—even running offline with local models—to correlate real-time system metrics with historical logs, accelerating troubleshooting and enhancing system administration. Whether you're streamlining debugging workflows or setting up proactive network support, this tool makes it easier to prepare your environment for intelligent, AI-assisted diagnostics. Check it out and let me know what you think!

Visit productView on Hacker NewsFeb 16, 2025
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Launch Intel predictions

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Indie HackersFits the IH revenue-focused audience · Strong signals: supports · Missing: reddit linkedin, podcasting, created
69%69% 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.
Product HuntOn track for Day 1 leaderboard · Strong signals: mac, macos, model · Missing: agents, agent, cursor
68%68% predicted probability of success on Product Hunt, 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
48%48% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: soon · Missing: plus, platform, intuitive
40%40% 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
27%27% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue
16%16% 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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