Skip to main content
Glama
alphaparkinc

Personal Agent Glycemic Load Macro Balancer

README.md
# genpark-personal-agent-glycemic-load-macro-balancer-skill

![Tests](https://img.shields.io/badge/tests-passing-brightgreen)
![License](https://img.shields.io/badge/license-MIT-blue)
![Python](https://img.shields.io/badge/python-3.10%2B-blue)
![Dependencies](https://img.shields.io/badge/dependencies-zero-success)
![Coverage](https://img.shields.io/badge/coverage-100%25-brightgreen)

GenPark Personal Agent Glycemic Load Macro Balancer computes composite glycemic impact, models protein and fat gastric attenuation, and forecasts post-prandial mental stamina without external dependencies.

```mermaid
flowchart TD
    A[Meal Ingredients, Carbs & GI] --> B[Composite Glycemic Load Calculator]
    C[Protein & Healthy Fat Amounts] --> D[Gastric Emptying Buffering Index]
    B & D --> E[Effective Attenuated Glycemic Load]
    E --> F[Post-Prandial Brain Fog & Crash Probability]
    F --> G[Cognitive Focus Hours & Task Scheduling Advice]
```

## Features
- **Composite Glycemic Load**: Aggregates glycemic index and carbohydrate mass across complex multi-ingredient meals.
- **Macronutrient Damping**: Models how amino acids and lipids flatten glycemic glucose spikes.
- **Cognitive Crash Forecaster**: Estimates post-lunch fatigue probability and stable working hours.

## Quickstart

```python
from client import PersonalAgentGlycemicMacroBalancer

balancer = PersonalAgentGlycemicMacroBalancer()
res = balancer.recommend_macronutrient_stabilizer(40.0)
print("Recommended Protein:", res["recommended_protein_addition_g"], "g")
```

## FastMCP Integration

```bash
python -m genpark-personal-agent-glycemic-load-macro-balancer-skill.mcp_server
```

## License
MIT