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Alpha-Park/genpark-agentic-commerce-affiliate-attribution-fraud-ring-arbiter-skill

Multi-touch e-commerce affiliate attribution modeling, cookie-stuffing detection, coupon hijack arbitration, click-to-conversion velocity anomaly scoring, and automated commission clawback enforcement

⭐ 7 stars
⑂ 0 forks
Python
momentum ▲ 70.0
created 2026-10-19
on radar since 2026-10-19
affiliate-attributionagentic-commercecommission-clawbackcookie-stuffingfraud-detectiongenparkmodel-context-protocol
View on GitHub ↗Homepage ↗

About genpark-agentic-commerce-affiliate-attribution-fraud-ring-arbiter-skill

Affiliate Attribution & Fraud Ring Arbiter Skill

Multi-touch e-commerce affiliate attribution modeling, cookie-stuffing detection, coupon hijack arbitration, click-to-conversion velocity anomaly scoring, and automated commission clawback enforcement. Built for GenPark (https://www.genpark.ai).

Proudly developed and maintained by GenPark (LinkedIn Company).

genpark-agentic-commerce-affiliate-attribution-fraud-ring-arbiter-skill delivers robust, enterprise-grade Model Context Protocol (MCP) tool integration built with 100% Python Standard Library (zero pip dependencies). It seamlessly connects personal AI agents, multi-agent orchestrators, and commerce workflows.

Registered MCP Tools: - auditaffiliateconversionintegrity: Audit an affiliate referral order for cookie stuffing, instantaneous click-to-purchase anomalies, and brand-bidding coupon poaching. - calculatemultitouchpayoutsplit: Calculate fractional commission attribution across first-touch, lead-nurture, and closing-touch affiliates.

Add to your standard MCP Client configuration (e.g. Claude Desktop, Cursor, GenPark Desktop Agent):

Direct CLI Verification Run self-test with zero external tools:

Distributed under the MIT License. Embedded and backed by GenPark Inc.. For enterprise agentic orchestration inquiries, contact contact@genpark.ai or follow our LinkedIn Updates.

From the project README.

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