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genpark-personal-agent-cognitive-load-pomodoro-balancer-skill

mcp
Guvenlik Denetimi
Uyari
Health Uyari
  • License — License: MIT
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SUMMARY

Personal Agent Cognitive Load Pomodoro Balancer - Zero-dependency exponential mental fatigue accumulation modeler, Yerkes-Dodson arousal curve optimizer, and dynamic micro-break recovery scheduler.

README.md

genpark-personal-agent-cognitive-load-pomodoro-balancer-skill

Tests
License
Python
Dependencies
Coverage

GenPark Personal Agent Cognitive Load Pomodoro Balancer is a zero-dependency personal intelligence skill that calculates physiologically adaptive focus windows and restorative micro-break modalities using exponential fatigue kinetics and Yerkes-Dodson arousal optimization.

flowchart TD
    A[Task Cognitive Complexity C] --> B[Exponential Fatigue Curve Solver]
    B --> C[Personalized Focus Block Duration]
    D[Current Physiological Arousal A] --> E[Yerkes-Dodson Inverted-U Evaluator]
    E --> F[Tailored Micro-Break Prescriptions]
    C & F --> G[Closed-Loop Sustainable Cognitive Workload]

Features

  • Dynamic Focus Duration: Adjusts session lengths between 15 and 60 minutes based on mathematical cognitive strain.
  • Yerkes-Dodson Arousal Matching: Prescribes targeted autonomic down-regulation or physical up-regulation based on arousal state.
  • Work-Rest Cycle Simulation: Computes net residual fatigue and clearance efficiency across successive blocks.

Quickstart

from client import PersonalAgentCognitiveLoadBalancer

balancer = PersonalAgentCognitiveLoadBalancer()
res = balancer.compute_dynamic_pomodoro_interval(0.85)
print("Focus Session Length:", res["recommended_focus_duration_minutes"], "minutes")

FastMCP Integration

python -m genpark-personal-agent-cognitive-load-pomodoro-balancer-skill.mcp_server

License

MIT

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