Brand protection amazon

Skill nexscope-ai/eCommerce-Skills/brand-protection/brand-protection-amazon

Amazon brand protection toolkit. Detect hijackers, counterfeits, and unauthorized sellers. Includes MAP violation monitoring, trademark abuse detection, complaint templates for Brand Registry, and test buy evidence collection guides. No API key required.From its SKILL.md

Install

npx -y skills add nexscope-ai/eCommerce-Skills --skill brand-protection-amazon

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

runs commandsInstructs the agent to run 5 commands, including `npx skills add nexscope-ai/eCommerce-Skills --skill brand-protection-amazon -g` and 4 more.

SKILL.md

3.2 KB, 713 tokens by cl100k_base, as published. Nobody here has run it

Brand Protection — Amazon 🛡️

Protect your brand from hijackers, counterfeits, and unauthorized sellers on Amazon.

Installation

npx skills add nexscope-ai/eCommerce-Skills --skill brand-protection-amazon -g

Features

Hijacker Detection — Find unauthorized sellers on your listings
Price Monitoring — MAP violation alerts
Counterfeit Signals — Review-based fake detection
Trademark Abuse — Title/keyword infringement detection
Complaint Templates — Brand Registry, C&D letters
Test Buy Guide — Evidence collection procedure

Detection Dimensions

Dimension	Method	Risk Level
Hijackers	Seller count monitoring	🔴 High
Price Violations	Below MAP detection	🔴 High
Counterfeit	Review keyword analysis	🔴 High
Trademark	Title pattern matching	⚠️ Medium

Risk Levels

Level	Description	Action
🔴 High	Immediate threat to brand	Take action within 24h
⚠️ Medium	Potential concern	Monitor and investigate
✅ Low	Normal activity	Continue monitoring

Input Configuration

{
  "brand_name": "YourBrand",
  "trademark_number": "US12345678",
  "brand_registry": true,
  "authorized_sellers": ["A1B2C3D4E5F6G7"],
  "protected_asins": ["B08XXXXXX1"],
  "min_price": 29.99
}

Usage

Hijacker Detection

python3 scripts/detector.py

Generate Complaint Templates

# Brand Registry complaint
python3 scripts/templates.py complaint

# Cease & Desist letter
python3 scripts/templates.py cease-desist

# Test buy guide
python3 scripts/templates.py testbuy

Output Example

🛡️ Brand Protection Report

Brand: YourBrand
ASINs Monitored: 5
Analysis Date: 2024-01-15

━━━━━━━━━━━━━━━━━━━━━━━━

🔴 HIGH RISK ALERTS

ASIN: B08XXXXXX1
├── 3 unauthorized sellers detected
├── Lowest price: $19.99 (MAP: $29.99)
└── Action: File Brand Registry complaint

━━━━━━━━━━━━━━━━━━━━━━━━

⚠️ COUNTERFEIT SIGNALS

Reviews mentioning "fake": 5
Reviews mentioning "not authentic": 2
Recommendation: Order test buy

Complaint Templates Included

Template	Use Case
Brand Registry	Report to Amazon
Cease & Desist	Direct seller contact
Test Buy Report	Evidence documentation
DMCA Takedown	Copyright infringement

Action Workflow

Monitor Listings
      ↓
Detect Violation
      ↓
Collect Evidence (Test Buy)
      ↓
Generate Complaint
      ↓
Submit to Amazon / Send C&D
      ↓
Track Resolution

Part of Nexscope AI — AI tools for e-commerce sellers.

What ships with it: 2 files

37.0 KB alongside SKILL.md, 2 of them executable

scripts/

detector.pyruns21.9 KB
templates.pyruns15.1 KB

Gives 0 of the 12 instructions most marketing audience skills give in 713 tokens

Counted across 690 of the 894 authors here whose files we hold, read 2026-08-07

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Use accent colors for non-text shapesin 38 of 690, across 3 files
Use RGB values for precise color matchingin 38 of 690, across 3 files
Use brand colors for primary text and backgroundsin 36 of 690, across 1 file
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Implement or generate appropriate JSON-LD structured datain 24 of 690, across 17 files
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Said here and by no other author read

detect unauthorized sellers
analyze reviews for counterfeit signals
generate seller complaint templates
monitor listings for violations
detect prices below MAP
match title patterns for trademark abuse

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.