🌟 Executive Overview

As autonomous AI agents evolve from conversational advisors into active shopping proxies (inspired by recent 2026 milestones in Meta Muse and Stripe Link Agent Wallet), platforms like GenPark.ai require rock-solid safeguards, mathematical cart optimization, anti-spoof review intelligence, and community-driven trend discovery.

This repository implements 4 flagship features designed to scale GenPark's agentic commerce ecosystem:

🚀 Quick Start

Installation

git clone https://github.com/alphaparkinc/genpark-next-features.git
cd genpark-next-features
npm install

Run Tests

Zero external dependencies required (uses Node.js native test runner):

npm test

Interactive CLI

# Test Agent Wallet Guard (auto-approval vs human escalation)
node bin/genpark-cli.js wallet 45 GenPark-Direct
node bin/genpark-cli.js wallet 250 GenPark-Direct

# Test Cross-Store Basket Optimizer
node bin/genpark-cli.js basket mechanical-keyboard,desk-mat,usb-c-hub

# Test Product TruthGuard Review Audit
node bin/genpark-cli.js audit

# Test Circle Trend Radar & Article Synthesizer
node bin/genpark-cli.js radar

📦 Feature Deep-Dive

1. 🛡️ Agent Wallet Guard (src/wallet-guard/)

Autonomous shopping agents cannot be given unrestricted credit cards. AgentWalletGuard implements:

• Budget Policy:
  • maxPerOrder ($150 default): Purchases exceeding this threshold trigger a cryptographic confirmation challenge.
  • dailyAllowance ($500 default): Rolling 24-hour spend cap.
  • minMerchantTrustScore (0.75 default): Low-reputation merchants automatically require human approval.
  • Prohibited categories: Blocks automated agent purchases of restricted goods.
• HMAC-SHA256 Challenge Flow:
  • Generates timed challenge tokens with a 15-minute TTL.
  • Validates approval signatures before releasing funds.
• Virtual Receipt Ledger:
  • Generates a SHA-256 tamper-evident digital receipt verifiable via GenPark protocol.

2. 🛒 Cross-Store Basket Optimizer (src/basket-optimizer/)

When a user or agent builds a multi-item wishlist, buying everything from a single seller is rarely the cheapest option, but splitting across too many sellers incurs high shipping fees.

The solver computes:

• $\min \left( \sum \text{Price}_i + \sum \text{Shipping}(\text{Merchant}_j) \right)$
• Applies free-shipping qualification triggers (e.g. Free shipping when cart $\ge $50$).
• Outputs 3 distinct strategies:
  1. Cheapest Net Cost Plan
  2. Single-Store Consolidated Plan (minimal package count)
  3. Fastest Delivery Plan

3. 🔍 Product TruthGuard (src/truth-guard/)

E-commerce is plagued by incentivized reviews and generic LLM-generated boilerplates. ProductTruthGuard:

• Calculates Type-Token Ratio (TTR) and lexical burstiness.
• Flags cliché bot phrases ("game-changer", "exceeded all my expectations", "in conclusion...").
• Identifies Rating Incongruence (5-star ratings with severe defect complaints).
• Isolates verified negative feedback into structured flaw categories:
  • Durability & Build Quality
  • Sizing & Ergonomics
  • Battery & Electronics
  • Customer Service & Shipping
• Produces an adjusted Authentic Rating and Trust Grade (A, B, C, D, F).

4. 📡 Circle Trend Radar (src/circle-radar/)

GenPark's social community Circle is where shoppers share insights. CircleTrendRadar:

• Ingests discussion streams, calculating engagement velocity and acceleration.
• Ranks emerging items (STEADY, RISING, VIRAL).
• Automatically synthesizes editorial-grade Circle Insights (洞见) in Markdown with community quotes and direct purchase links.

🤖 MCP (Model Context Protocol) Integration

This package includes a production-ready stdio MCP server for OpenClaw, Claude Desktop, and Antigravity:

node mcp/server.js

Available MCP Tools:

• genpark_wallet_checkout: Safely evaluate and execute orders with budget guard.
• genpark_optimize_basket: Solve multi-item cart allocation.
• genpark_audit_reviews: Audit reviews and extract real flaws.
• genpark_circle_trend_radar: Analyze discussions and draft Circle insights.

📄 License

MIT © 2026 GenPark (AlphaPark Inc). Built for the GenPark and OpenClaw agent ecosystem.