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genpark-seo-metadata-generator-skill

AI skill module: genpark-seo-metadata-generator-skill

Install / Use

claude mcp add alphaparkinc -- npx -y github:alphaparkinc/genpark-seo-metadata-generator-skill

If the server publishes to npm under a different name, use that package instead — check the repo README.

About this skill
🔌

MCP Server

Model Context Protocol server

Quality Score

67/100

Category

Marketing

Supported Platforms

Claude Code
Claude Desktop

AI SEO Metadata Generator Skill

An automated Python skill that takes product details—such as title, description, category, brand, price, and target keywords—and generates a complete, production-ready SEO metadata package.

Capabilities

  • Title Tag Generation: Constructs optimized <title> tags formatted as {product_name} | {brand} | {category} strictly capped at 60 characters with overflow truncation detection.
  • Meta Description Generation: Produces concise meta descriptions within 160 characters (truncating to 155 + ellipsis if needed).
  • Open Graph (OG) Tags: Generates structured OG metadata (og:title, og:description, og:type, og:site_name, product:price:amount, product:price:currency).
  • Schema.org Product JSON-LD: Creates structured JSON-LD data for Google Search rich snippets including product brand, category, keywords, and offer pricing details.
  • Canonical URL Slug: Converts raw product names into clean, lowercased, hyphenated web-safe slugs.
  • Validation Engine: Flags character limit overruns and minimum length warnings.

Directory Structure

genpark-seo-metadata-generator-skill/
├── skill.json             # Skill manifest (metadata, input/output schemas)
├── seo_metadata_agent.py  # Core SEOMetadataClient Python implementation
├── example_usage.py       # Executable usage example script
├── requirements.txt       # Skill dependencies (standard library only)
└── README.md              # Documentation and usage guide

Input Schema

| Parameter | Type | Required | Description | | :--- | :--- | :--- | :--- | | product_name | string | Yes | Name of the product | | description | string | Yes | Detailed product description | | category | string | Yes | Product category name | | brand | string | Yes | Brand or manufacturer name | | price | number | Optional | Product price | | keywords | array[string] | Optional | Target SEO keywords |


Output Schema

| Parameter | Type | Description | | :--- | :--- | :--- | | title_tag | string | SEO Title tag (<60 characters) | | meta_description | string | Meta description (<160 characters) | | og_tags | object | Open Graph tags dictionary | | schema_jsonld | string | Formatted Schema.org Product JSON-LD script string | | url_slug | string | Canonical URL slug | | validation | object | Object containing is_valid, warnings, and character counts |


Quick Start & Usage

1. Installation

No external dependencies are required as the client relies purely on the Python standard library (json, re, typing).

python -m pip install -r requirements.txt

2. Python Integration

from seo_metadata_agent import SEOMetadataClient

client = SEOMetadataClient()

result = client.generate(
    product_name="Roborock Q Revo",
    description="The Roborock Q Revo offers powerful 5500Pa suction, dual spinning mops, auto-mop washing and drying, and a multi-functional dock for seamless hands-free cleaning.",
    category="Robot Vacuums",
    brand="Roborock",
    price=799.99,
    keywords=["robot vacuum", "smart home", "roborock q revo"]
)

print("Title Tag:", result["title_tag"])
print("Meta Description:", result["meta_description"])
print("URL Slug:", result["url_slug"])
print("JSON-LD:", result["schema_jsonld"])

3. Run Example Script

python example_usage.py

Related Skills

View on GitHub
GitHub Stars9
CategoryMarketing
Updated1mo ago
Forks0

Languages

Python

Security Score

75/100

Audited on Jul 29, 2026

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