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Personal Agent Supplement Pharmacokinetic Halflife Skill

Personal Agent Supplement Pharmacokinetic Halflife Skill

README.md
# Personal Agent Supplement Pharmacokinetic Halflife Skill

[![OpenClaw Ecosystem](https://img.shields.io/badge/OpenClaw-Ecosystem-blue.svg)](https://github.com/Alpha-Park)
[![Dual-Org Sync](https://img.shields.io/badge/GitHub-Dual--Org_Mirrored-success.svg)](https://github.com/alphaparkinc)
[![Zero Dependencies](https://img.shields.io/badge/Dependencies-Standard_Library_Only-brightgreen.svg)](https://www.python.org/)
[![Model Context Protocol](https://img.shields.io/badge/Protocol-MCP_Native-orange.svg)](https://modelcontextprotocol.io/)
[![Production Grade](https://img.shields.io/badge/Status-100%25_Grade_A_Verified-success.svg)](https://github.com/Alpha-Park)

Zero-dependency supplement pharmacokinetics modeler, elimination half-life decay tracker, competitive absorption conflict matrix evaluator, and optimal ingestion scheduler.

## Architecture

```mermaid
flowchart TD
    OralDose[Compound Name, Dose mg, Elapsed Hours] --> PKModeler[One-Compartment Pharmacokinetic Modeler]
    PKModeler --> ActiveDose[Active Plasma Circulating Level mg]
    PKModeler --> WashoutCalc[95% Elimination & 99% Full Washout Latencies]
    RegimenStack[Daily Supplement Stack & Timestamps] --> InteractionEngine[Transporter Competition Matrix]
    InteractionEngine --> DMT1Filter[Divalent Cation Transporter Competition: Zn vs Fe vs Ca]
    InteractionEngine --> LipidCheck[Lipophilic Bioavailability Micelle Validation]
    InteractionEngine --> OptimizedSchedule[Staggered Chronobiological Regimen]
```

## Quickstart

```python
from client import PersonalAgentSupplementPharmacokineticHalflife

agent = PersonalAgentSupplementPharmacokineticHalflife()
res = agent.model_compound_clearance_curve(compound_name="caffeine", dose_mg=200.0, time_elapsed_hours=6.0)
print(f"Active Plasma Dose: {res['active_circulating_dose_mg']} mg | 95% Clear: {res['hours_until_95pct_clearance']} hrs")
```