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genpark-personal-agent-blood-glucose-variability-auc-skill

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  • License — License: MIT
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SUMMARY

Personal agent Continuous Glucose Monitoring (CGM) glycemic variability modeler, computing Mean Amplitude of Glycemic Excursions (MAGE), incremental Area Under the Curve (iAUC), and Time in Range (TIR).

README.md

Personal Agent Blood Glucose Variability AUC Skill

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

Zero-dependency Continuous Glucose Monitoring (CGM) glycemic variability calculator, Mean Amplitude of Glycemic Excursions (MAGE) modeler, and postprandial iAUC stabilizer.

Architecture

flowchart TD
    CGMReadings[Time-Series Glucose Readings mg/dL] --> CGMAnalyzer[Glycemic Variability Engine]
    CGMAnalyzer --> CVMetric[Coefficient of Variation %CV: Target <= 36%]
    CGMAnalyzer --> MAGEMetric[MAGE Peak-to-Trough Amplitude]
    CGMAnalyzer --> TIRMetric[Time in Range % & iAUC Excursion Area]
    CVMetric & MAGEMetric --> ProtocolEngine[Glycemic Stabilization Protocol]
    ProtocolEngine --> Interventions[Food Sequencing & GLUT4 Postprandial Ambulation]

Quickstart

from client import PersonalAgentBloodGlucoseVariabilityAuc

agent = PersonalAgentBloodGlucoseVariabilityAuc()
res = agent.calculate_cgm_glycemic_variability([90.0, 110.0, 145.0, 160.0, 120.0, 95.0, 85.0])
print(f"CV: {res['coefficient_of_variation_pct']} | TIR: {res['time_in_range_70_140_pct']}")

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