genpark-personal-agent-caffeine-adenosine-pharmacokinetics-skill

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

Simulates caffeine elimination pharmacokinetics, models adenosine receptor occupancy, and schedules intake windows to protect deep slow-wave sleep.

README.md

Personal Agent Caffeine Adenosine Pharmacokinetics Skill

OpenClaw Ecosystem
Dual-Org Sync
Zero Dependencies
Model Context Protocol
Production Grade

Zero-dependency two-compartment caffeine elimination pharmacokinetic modeler, adenosine A1/A2A receptor occupancy calculator, and sleep-architecture-safe intake scheduler.

Architecture

flowchart TD
    Doses[Dose Amount, Hour, CYP1A2 Phenotype] --> ClearanceModel[Two-Compartment Pharmacokinetic Engine]
    ClearanceModel --> BedtimeResidual[Circulating Bedtime Residual mg]
    BedtimeResidual --> AdenosineModel[Adenosine A1/A2A Receptor Occupancy]
    AdenosineModel --> SleepPenalty[Slow-Wave Deep Sleep Suppression %]
    SleepSchedule[Wake Time & Bedtime] --> CutoffScheduler[Optimal Intake Window & Cutoff Scheduler]

Quickstart

from client import PersonalAgentCaffeineAdenosinePharmacokinetics

agent = PersonalAgentCaffeineAdenosinePharmacokinetics()
res = agent.simulate_caffeine_clearance([{"hour": 8.0, "mg": 150.0}, {"hour": 14.0, "mg": 100.0}])
print(f"Bedtime Residual: {res['bedtime_circulating_residual_mg']} mg | SWS Penalty: {res['slow_wave_sleep_suppression_pct']}")

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