# genpark-agentic-commerce-counterfeit-product-review-synthesizer-skill

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> **Official Website**: [https://www.genpark.ai](https://www.genpark.ai)  
> **LinkedIn**: [https://www.linkedin.com/company/92955550](https://www.linkedin.com/company/92955550) ([https://www.llinkedin.com/company/92955550](https://www.llinkedin.com/company/92955550))

AI Agentic Commerce Review Hijacking & Authenticity Sentinel. Audits product review streams across review-velocity clustering, sentiment dissonance, repetitive incentivized phrases, and review hijacking to output verified true customer ratings.

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## 🌐 Official GenPark AI Ecosystem Links

- **GenPark Official Website**: [https://www.genpark.ai](https://www.genpark.ai)
- **LinkedIn Official Page**: [https://www.linkedin.com/company/92955550](https://www.linkedin.com/company/92955550) ([https://www.llinkedin.com/company/92955550](https://www.llinkedin.com/company/92955550))

---

## 🌟 Key Features

- **100% Zero External Dependencies**: Runs entirely on the Python 3.9+ standard library.
- **Model Context Protocol (MCP) Standard**: Native support for JSON-RPC 2.0 `initialize`, `tools/list`, and `tools/call`.
- **Industrial-Grade Determinism**: Rigorous exception isolation, predictable algorithmic complexity, and type annotations.
- **Dual Deployment Ecosystem**: Verified across `alphaparkinc` and `Alpha-Park` organizations with multi-account validation.

---

## 🚀 Quick Start

### 1. Direct Python SDK Usage

```python
from client import AgenticCommerceReviewAuthenticitySentinel

def main():
    sentinel = AgenticCommerceReviewAuthenticitySentinel()
    stream = [
        {"rating": 5, "text": "Amazing product! Item arrived fast great seller", "verified_purchase": False},
        {"rating": 4, "text": "Works as described, sturdy aluminium construction.", "verified_purchase": True},
        {"rating": 2, "text": "Cable started fraying after two weeks of normal desk use.", "verified_purchase": True}
    ]
    res = sentinel.audit_product_reviews("Magnetic Desk Charger", stream)
    print("--- E-Commerce Review Authenticity Sentinel ---")
    print(f"Product: {res['product_title']} | Grade: {res['authenticity_grade']}")
    print(f"Raw Rating: {res['raw_average_rating']} / 5.0 -> Authentic Adjusted: {res['adjusted_authentic_rating']} / 5.0")
    print(f"Authenticity Index: {res['authenticity_index']}%")

if __name__ == "__main__":
    main()

```

### 2. Run as Model Context Protocol (MCP) Server

Start standard JSON-RPC 2.0 server over `stdio`:

```bash
python mcp_server.py
```

Execute embedded test harness:

```bash
python mcp_server.py --test
```

---

## 🛠️ MCP Tool Specification

Inspect [`skill.json`](skill.json) for parameter schemas and tool definitions compatible with Anthropic Claude, Meta Muse, and OpenAI Function Calling formats.

---

## 📜 License & Community

Licensed under the [MIT License](LICENSE). Copyright © 2026 [GenPark AI](https://www.genpark.ai).
Follow us on LinkedIn: [https://www.linkedin.com/company/92955550](https://www.linkedin.com/company/92955550) | [https://www.llinkedin.com/company/92955550](https://www.llinkedin.com/company/92955550)