genpark-checkout-ab-test-skill
GenPark AI Skill - Design, simulate, and analyze A/B tests for e-commerce checkout flows with statistical significance testing
Install / Use
claude mcp add alphaparkinc -- npx -y github:alphaparkinc/genpark-checkout-ab-test-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
Development & EngineeringSupported Platforms
Skill content
View source on GitHubgenpark-checkout-ab-test-skill
GenPark AI Agent Skill — Design, simulate, and analyze A/B tests for e-commerce checkout flows.
Features
- Two-proportion z-test for statistical significance
- Conversion lift and revenue impact calculation
- Statistical power estimation
- Sample size calculator (test design)
- Monte Carlo simulation for false positive rates
- Clear Ship / Continue / Revert recommendations
Quick Start
from client import ABTestClient
client = ABTestClient()
result = client.analyze(
control={"visitors": 10000, "conversions": 300, "avg_order_value": 80},
variant={"visitors": 10000, "conversions": 340, "avg_order_value": 82},
confidence_level=0.95,
monthly_traffic=40000,
)
print(result["recommendation"])
print(f"Revenue impact: ${result['revenue_impact_usd']:,.2f}/month")
Installation
python example_usage.py # No external dependencies
Built by GenPark | alphaparkinc
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