CopyTrack – un clipboard tracker invisibile e automatico per Windows

Hacker News

Hi HN I built CopyTrack, a tiny Windows tool that automatically logs everything you copy (Ctrl+C) into a plain .txt file on your desktop — with timestamps. It has no UI, no popups, no distractions — just runs quietly in the background. Set it and forget it. Main use cases: Keep track of code, messages, notes, etc. Recover text you copied and accidentally overwrote Simple and focused — does one thing only Features: Open-source (CC BY-NC 4.0) Fully offline Logs to CopyTrack.txt with timestamp Auto-start on boot No config needed, no GUI GitHub: https://github.com/loki3737/loki I made it for personal use but it surprisingly got 200+ downloads in just two days. Would love your thoughts and feedback — thanks for checking it out!

Visit product View on Hacker NewsJun 28, 2025

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: tiny, notes, code · Missing: mac, agents, macos

82%82% 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

72%72% 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, intuitive

48%48% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

43%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, io · Missing: https docs, excited, just released

41%41% 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

13%13% 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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