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ProcrastiScan — Marc

A new approach to detecting procrastination.

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ProcrastiScan helps you stay focused and productive by continually checking if the content you're viewing aligns with what you actually want to be doing.

As you browse, a Relevance Score is calculated for every tab, based on how similar it is to your task and your descriptions of relevant/distracting content. If the score is higher than 0.5, content is considered relevant; lower scores indicate distractions. An averaged Focus Score reflects your current level of focus. If it falls below 0.5, ProcrastiScan assumes you're distracted and activates one of the interventions you’ve selected.

Features:
- Smart Distraction Recognition: All your browsing activity is scored in real-time based on meaning rather than just keyword matching
- Dashboard: See at which times you were focused or distracted
- Tab Blocking: Automatically detect distracting tabs and block them
- Chatbot: Engage in a focused conversation with an AI assistant to get back on track or reflect on why you got distracted (requires a local LLM connection, highly experimental)
- Procrastination List: Recognize and save distracting tabs for later

For a detailed manual and an optional server to score all programs instead of just your browser, check out the GitHub repository: https://github.com/Marc-Pk/ProcrastiScan
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Zahtevana dovoljenja:

  • dostopa do zavihkov brskalnika
  • dostopa do dejavnosti brskalnika med brskanjem

Neobvezna dovoljenja:

  • dostopa do vaših podatkov za localhost
Več informacij
Povezave dodatka
  • Domača stran
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  • E-naslov za podporo
Različica
2.1.0
Velikost
629,68 KB
Zadnja posodobitev
pred 4 meseci (28. mar. 2025)
Sorodne kategorije
  • Zaznamki
  • Opozorila in posodobitve
  • Zavihki
Licenca
Mozilla Public License 2.0
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Opombe ob izdaji 2.1.0
  • added tab blocking
  • renamed (averaged) similarity score to Relevance Score and Focus Score
  • dashboard now has red/green segments and dynamic colors for the Focus Score
  • intervention times and days can be selected
  • LLM prompt includes recent browsing
  • added support for thinking LLMs and made the API calls more robust
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