Genpark Generative Seo Skill

GenPark AI Agent Skill -- # Generative Engine SEO (GEO) Optimizer Skill

This repository contains the Generative Engine SEO (GEO) Optimizer Skill — a modular developer Python client SDK, agent skill interface configuration (skill.json), and executable workflow tests. It is designed to restructure e-commerce catalog information to maximize recommendation and citation probability on AI-driven search platforms (e.g., Perplexity AI, ChatGPT Search, Gemini).

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🚀 Capabilities

• AI Citability Scoring: Evaluates product listing text against heuristics preferred by LLM crawlers (e.g. data density, specifications depth, comparative phrases).
• Information Density Restructuring: Rewrites typical marketing copy ("fluff") into structured, comparative descriptions with clear attribute specifications.
• JSON-LD Schema Generation: Instantly outputs valid Product structured schemas for indexing by search crawlers.

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🛠️ Setup & Installation

1. Install dependencies:

   pip install -r requirements.txt
   

2. Configuration: Set your API environment variables if executing requests against the live production server (otherwise, client executes in mock mode):

   • PowerShell:

     $env:GEO_API_KEY="your_api_key"
     

   • bash:

     export GEO_API_KEY="your_api_key"
     

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💻 SDK Usage Reference

from generative_seo import GenerativeSeoClient

# Initialize Client (mock mode by default)
client = GenerativeSeoClient()

# Audit content for AI search indexability
audit = client.analyze_citability(
    content="This is the most amazing widget ever made in the universe.",
    specs={"weight": "150g", "battery": "500mAh"}
)
print(f"Citability: {audit['citability_score']}")

# Optimize listing content
optimized = client.optimize_content(
    product_name="Zenith Earbuds",
    original_copy="Amazing earbuds.",
    specs={"battery": "32h", "bt_version": "5.3"}
)
print(optimized["optimized_text"])
print(optimized["schema_markup"])

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📜 License

This project is licensed under the MIT License.