Quantitative Pupillary Light Reflex (PLR) Skill

Zero-dependency sovereign personal agent skill for non-invasive calculation of Pupillary Light Reflex (PLR) dynamics, autonomic tone, and central nervous system alertness.

flowchart TD
    PupilCam["Infrared Pupillometry / Optical Sensor"] --> Dynamics["Pupil Diameter Tracking Over Time"]
    Dynamics --> Extraction["Kinetic Metric Extraction (Latency, MCV, %CA, RDV)"]
    Extraction --> ScoreEngine["Autonomic Pupillary Resilience Engine"]
    ScoreEngine --> Agent["OpenClaw / Hermes Personal Agent Actions"]

Features

• Deterministic Math: Pure Python standard library implementation with zero external dependencies.
• Pupillometric Standard Metrics: Implements validated equations for constriction velocity, amplitude percentage, and redilation rate.
• Autonomic Tone Assessment: Quantifies balance between cholinergic parasympathetic and adrenergic sympathetic branches.
• Model Context Protocol (MCP): Native JSON-RPC tool integration for LLMs and autonomous agents.

Quickstart

from client import PupilLightReflexClient

client = PupilLightReflexClient()
result = client.evaluate_pupillary_dynamics(
    baseline_diameter_mm=4.3,
    minimum_diameter_mm=2.6,
    constriction_latency_ms=225.0,
    constriction_velocity_mm_s=4.9,
    redilation_velocity_mm_s=1.85
)
print("Constriction Amplitude:", result["constriction_amplitude_mm"], "mm")
print("Classification:", result["classification"])

License

Apache-2.0