genpark-user-persona-generator-skill
AI skill module: genpark-user-persona-generator-skill
Install / Use
claude mcp add alphaparkinc -- npx -y github:alphaparkinc/genpark-user-persona-generator-skillIf the server publishes to npm under a different name, use that package instead — check the repo README.
MCP Server
Model Context Protocol server
Quality Score
Category
AutomationSupported Platforms
Skill content
View source on GitHubAI User Persona Generator Skill
An agentic skill that synthesizes 2-3 structured, highly actionable buyer persona profiles based on product attributes, category, price tier, key features, and target region.
Capabilities
- Multi-Category Archetypes: Built-in template banks covering
Service,AI Gadgets,Robots,Fashion,Electronics, andCrypto. - Price Tier Segmentation: Distinct persona archetypes tailored to
budget,mid,premium, andluxurypricing models. - Dynamic Feature Tailoring: Integrates key product capabilities directly into pain points, motivations, and messaging angles.
- Geographic & Demographic Channel Mapping: Assigns priority marketing channels (e.g. TikTok, LinkedIn, WeChat, Reddit) based on demographic age brackets and target market (
us,europe,asia,global).
Directory Layout
genpark-user-persona-generator-skill/
├── skill.json # Skill manifest file
├── persona_generator_agent.py # Main Python agent implementation class
├── example_usage.py # Runnable usage example script
├── requirements.txt # Python dependencies (standard library only)
└── README.md # Documentation and usage guide
Input Schema (skill.json)
| Field | Type | Description | Options |
|---|---|---|---|
| product_name | string | Name of the product or service | e.g. "Unitree G1 Humanoid Robot" |
| category | string | Product vertical | Service, AI Gadgets, Robots, Fashion, Electronics, Crypto |
| price_tier | string | Price tier positioning | budget, mid, premium, luxury |
| key_features | array | Unique selling points & capabilities | e.g. ["23 DoF", "3D LiDAR"] |
| target_market | string | Geographic market region | global, us, asia, europe |
Output Schema
| Field | Type | Description |
|---|---|---|
| personas | array | Array of 2-3 persona objects containing name, age_range, occupation, pain_points, motivations, objections, messaging_angle, and priority_channels |
| summary | string | Executive overview of synthesized persona landscape |
Quick Start / Usage
Run the included example script:
python example_usage.py
Python API Integration
from persona_generator_agent import UserPersonaGeneratorClient
agent = UserPersonaGeneratorClient()
result = agent.generate(
product_name="Unitree G1 Humanoid Robot",
category="Robots",
price_tier="premium",
key_features=[
"23 to 43 Degrees of Freedom (DoF)",
"3D LiDAR and Depth Camera Sensing",
"Force-controlled humanoid manipulation"
],
target_market="us"
)
print(result["summary"])
for persona in result["personas"]:
print(persona["name"], persona["messaging_angle"])
License
MIT License
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Security Score
Audited on Jul 29, 2026
