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genpark-personal-agent-ultradian-rhythm-phase-forecaster-skill

MCP

Enables forecasting of ultradian alertness peaks and troughs, modeling homeostatic sleep pressure against circadian drive to prescribe restorative nap durations that avoid sleep inertia.

@alphaparkinc · MIT License · updated today

SECURITY

B

SCORE

60

STARS

▲ 7

PLUG IN

git clone https://github.com/alphaparkinc/genpark-personal-agent-ultradian-rhythm-phase-forecaster-skill.git

See the README to configure this MCP server

README

genpark-personal-agent-ultradian-rhythm-phase-forecaster-skill

Tests License Python Dependencies Coverage

GenPark Personal Agent Ultradian Rhythm Phase Forecaster models 90-minute human biological oscillations and Borbely's classic Two-Process Sleep Regulation framework to predict alertness peaks, post-prandial energy dips, and optimal nap durations.

flowchart TD
    A[Wakeup Time & Planned Active Hours] --> B[90-Minute BRAC Cycle Harmonic Decomposer]
    B --> C[Peak Synthesis Windows & Trough Recovery Times]
    D[Hours Awake & Sleep Baseline] --> E[Two-Process S & C Alertness Model]
    E --> F[Net Cognitive Alertness & Fatigue Regime]
    F --> G[Sleep-Inertia-Free Nap Duration Prescriber]

Features

  • 90-Minute Cycle Decomposition: Maps continuous workdays into biological basic rest-activity cycles.
  • Borbely Two-Process Sleep Pressure: Models homeostatic sleep debt accumulation vs circadian phase drive.
  • Sleep Inertia Prevention: Strictly guides naps to 20 minutes (pre-SWS) or 90 minutes (full cycle).

Quickstart

from client import PersonalAgentUltradianPhaseForecaster

forecaster = PersonalAgentUltradianPhaseForecaster()
res = forecaster.forecast_ultradian_energy_windows("07:00", 12)
print("First Peak Window:", res["cycles"][0]["peak_phase_time"])

FastMCP Integration

python -m genpark-personal-agent-ultradian-rhythm-phase-forecaster-skill.mcp_server

License

MIT

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