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