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genpark-personal-agent-cutaneous-sebaceous-lipogenesis-sebum-excretion-rate-skill

mcp
Guvenlik Denetimi
Uyari
Health Uyari
  • License — License: NOASSERTION
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SUMMARY

Calculates photometric casual sebum level (CSL) and dynamic sebum excretion rate (SER) for epidermal lipid mantle barrier evaluation and seborrheic skin profiling.

README.md

Cutaneous Sebaceous Lipogenesis Sebumetry Personal Agent Skill

License: Apache-2.0
Python: 3.8+
Zero Dependencies
Model Context Protocol
Production Ready

Deterministic, zero-mock personal agent micro-skill for calculating Casual Sebum Level ($CSL$ in $\mu\text{g}/\text{cm}^2$) and Sebum Excretion Rate ($SER$ in $\mu\text{g}/(\text{cm}^2 \cdot \text{h})$) using photometric sebumetry to evaluate epidermal lipid barrier health.

Architecture

flowchart TD
    A[Photometric Sebumeter Tape Sampling] --> B[Measure Steady-State Casual Sebum Level CSL]
    B --> C[Post-Degreasing Sebum Accumulation Over Time]
    C --> D[Compute Sebum Excretion Rate SER = Delta S / Delta t]
    D --> E[Classify Alipic < 90 vs Eudermic vs Hyperseborrheic > 280]

Quickstart

from client import SebaceousLipogenesisClient

client = SebaceousLipogenesisClient()
result = client.evaluate_sebum_kinetics(
    casual_sebum_level_ug_cm2=145.0,
    reaccumulated_sebum_ug_cm2=2.3,
    accumulation_duration_hours=2.0
)
print(result)

License

Apache-2.0

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