Ocular Cone Contrast Test (CCT) Skill

Cone Contrast Test (CCT) and Photoreceptor Contrast Sensitivity Analyzer based on Rabin cone isolation psychophysics.

flowchart TD
    A[Cone-Isolating Contrast Thresholds: L, M, S] --> B[Logarithmic Score Transformation: 0 - 100]
    B --> C[Compute Individual L, M, S Scores]
    C --> D{Score Threshold >= 75?}
    D -- All >= 75 --> E[Normal Trichromatic Photoreceptor Integrity]
    D -- S-cone < 60 --> F[Acquired Tritan / Macular / Glaucoma Defect]
    D -- L-cone < 60 --> G[Protan Selective Defect]
    D -- M-cone < 60 --> H[Deutan Selective Defect]

Features

• Zero PIP Dependencies: Implemented strictly with Python Standard Library (math, json, sys, typing).
• LMS Psychophysics: Separates L, M, and S photoreceptor channels to detect subclinical maculopathies.
• Rabin CCT Standardization: Maps raw thresholds to calibrated 0-100 diagnostic scores.
• Dual Architecture: Native Python import and Model Context Protocol (MCP) JSON-RPC 2.0 stdio server.

Quickstart

python example_usage.py

License

Apache-2.0