Oculomotor Binocular Vergence Dynamics Skill

Zero-dependency sovereign personal agent skill for non-invasive evaluation of Binocular Vergence Dynamics peak convergence/divergence velocity, latency, and convergence insufficiency asthenopia.

flowchart TD
    BinocularDisparity["Step Binocular Disparity Jump (4-8 deg)"] --> SOA["Midbrain Supraoculomotor Area (SOA) Burst Neurons"]
    SOA --> MedialRecti["Bilateral Medial Rectus Inward Co-Activation (Convergence)"]
    SOA --> LateralRecti["Bilateral Lateral Rectus Outward Relaxation (Divergence)"]
    MedialRecti & LateralRecti --> VelocityRatios["Peak Velocity Kinetics & Conv/Div Ratio"]
    VelocityRatios --> AsthenopiaEngine["Convergence Insufficiency (CI) & Digital Eyestrain Score"]
    AsthenopiaEngine --> Agent["OpenClaw / Hermes Personal Agent Screen Distance Prescriptions"]

Features

• Deterministic Math: Pure Python standard library implementation with zero external dependencies.
• Oculomotor Neurophysiology Standards: Implements validated equations for step vergence velocities, main sequence ratios, and settling time constants.
• Digital Eyestrain & Convergence Fatigue Shield: Sensitive detection of binocular motor fusion breakdown during intense screen reading.
• Model Context Protocol (MCP): Native JSON-RPC tool integration for LLMs and autonomous agents.

Quickstart

from client import OculomotorVergenceDynamicsClient

client = OculomotorVergenceDynamicsClient()
result = client.evaluate_vergence_dynamics(
    step_disparity_deg=6.0,
    peak_convergence_velocity_deg_s=29.5,
    peak_divergence_velocity_deg_s=18.2
)
print("Conv/Div Ratio:", result["convergence_divergence_ratio"])
print("Vergence Score:", result["vergence_health_score"])
print("Classification:", result["classification"])

License

Apache-2.0