Provides OKN gain, retinal slip, and visual-motion sickness scoring to support Hermes personal agent UI animation moderation and visual stabilization.
This server does not currently have a deployable release on Glama. Follow the repository's setup instructions to install and configure it for your MCP client, including any required credentials and local dependencies.
Zero-dependency sovereign personal agent skill for non-invasive evaluation of Optokinetic Nystagmus (OKN) slow-phase velocity gain, retinal slip velocity, and visual-vestibular motion stabilization.
flowchart TD
LargeFieldMotion["Full-Field Visual Motion Drift (20-60 deg/s)"] --> NOT_AOS["Nucleus of the Optic Tract (NOT) & Accessory Optic System"]
NOT_AOS --> SlowPhase["Slow-Phase Eye Smooth Pursuit Velocity (Vslow)"]
SlowPhase --> RetinalSlip["Retinal Slip Velocity (Vstim - Vslow)"]
NOT_AOS --> FastPhaseReset["Saccadic Fast-Phase Reset Beats (1.8-3.5 Hz)"]
RetinalSlip & FastPhaseReset --> OKNScore["Optokinetic Gain & Visual Motion Sickness Engine"]
OKNScore --> Agent["OpenClaw / Hermes Personal Agent UI Animation Moderation"]Deterministic Math: Pure Python standard library implementation with zero external dependencies.
Visual Neurophysiology Standards: Formulates OKN slow-phase gain, retinal slip speed, and directional symmetry ratios.
Screen Vertigo & Simulator Sickness Shield: Detects early breakdown of wide-field visual tracking during rapid desktop screen interaction.
Model Context Protocol (MCP): Native JSON-RPC tool integration for LLMs and autonomous agents.
Related MCP server: vor-gain
from client import OcularOptokineticNystagmusClient
client = OcularOptokineticNystagmusClient()
result = client.evaluate_okn(
stimulus_velocity_deg_s=30.0,
slow_phase_velocity_deg_s=27.2,
fast_phase_frequency_hz=2.6
)
print("OKN Gain:", result["okn_gain"])
print("Optokinetic Score:", result["optokinetic_score"])
print("Classification:", result["classification"])Apache-2.0
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