ozon-shopper

name

ozon-shopper

description

Use this skill whenever the user wants to search for products on Ozon (ozon.ru), analyze product listings, check for scams, validate technical specifications, or find the best deal on online marketplaces. Trigger on requests like: "найди ноутбук", "проверь этот товар", "сравни цены на мониторы", "is this a scam", "check this product", or any shopping/marketplace query involving Ozon or Russian e-commerce platforms.

Ozon Shopper — AI-Driven Product Search & Scam Detection

Overview

This skill enables searching Ozon for products, analyzing listings for scams, validating technical specs, and recommending the best options. The workflow is:

1. Search → collect product cards from Ozon
2. Analyze → deep-dive each product (specs, reviews, seller)
3. Validate → check for scam patterns and spec inconsistencies
4. Report → ranked list with trust scores and red flags

Prerequisites

pip install playwright
playwright install chromium

Scripts

All scripts live in scripts/ and accept --help for usage.

Script	Purpose	Key Args
ozon_search.py	Search Ozon, collect product cards	--query, --max-results, --output
ozon_product_page.py	Parse full product details	--url, --output
ozon_reviews.py	Extract and analyze reviews	--url, --max-reviews, --output
ozon_seller.py	Get seller information	--url, --output
helpers/reporter.py	Generate Markdown report from JSON data	--input, --output

Workflow

Step 1: Search

python scripts/ozon_search.py --query "ноутбук ASUS" --max-results 10 --output results.json

This produces a JSON file with product cards:

[
  {
    "title": "Ноутбук ASUS VivoBook 15...",
    "price": "45 990",
    "url": "https://www.ozon.ru/product/...",
    "rating": "4.8",
    "reviews_count": "1240",
    "image": "https://..."
  }
]

Step 2: Analyze Each Product

For each product from search results, run three analyses in parallel:

python scripts/ozon_product_page.py --url "https://www.ozon.ru/product/..." --output product.json
python scripts/ozon_reviews.py --url "https://www.ozon.ru/product/..." --max-reviews 30 --output reviews.json
python scripts/ozon_seller.py --url "https://www.ozon.ru/product/..." --output seller.json

Step 3: Validate Against Scam Patterns

After collecting data, read references/scam_patterns.md and references/specs_rules.md, then analyze each product against these checklists.

Key validation checks:

• Price anomaly (too low for the category/specs)
• Seller trust (rating, age on platform, number of products)
• Review authenticity (bot patterns, review velocity, rating distribution)
• Spec consistency (claimed specs vs realistic pricing)
• Brand verification (official vs third-party seller)

Step 4: Generate Report

python scripts/helpers/reporter.py --input results/ --output report.md

AI Analysis Guidelines

When analyzing products, follow these principles from references/scam_patterns.md:

Red Flags (immediate disqualification)

• Price 40%+ below market average for identical specs
• Seller account less than 3 months old with high-value electronics
• All reviews posted within 48 hours
• Vague specs (e.g., "Intel i7" without model number)
• Stock photos instead of real product images

Yellow Flags (investigate further)

• Price 20-40% below market average
• Mixed review sentiment despite high rating
• Seller has few products but many sales
• Specifications that look "too good to be true" for the price

Trust Signals (positive indicators)

• Official brand store on Ozon
• Consistent review timeline spanning months
• Detailed, specific reviews with photos
• Seller responds to negative reviews professionally
• Specs match manufacturer's official page

Decision Tree

User query → Is it a search or a specific URL?
├── Search → Run ozon_search.py → Collect results
│   └── For each result → Run product + reviews + seller analysis
│       └── Validate → Generate ranked report
│
└── Specific URL → Run product + reviews + seller analysis
    └── Validate → Generate single product analysis

Report Format

Always generate reports in this structure:

## Результаты поиска: "[query]"

### 1. [Product Name] — [Price]₽ ✅/⚠️/🔴 [Verdict]
- **Продавец**: [Name] (рейтинг [X], [Y] месяцев на Ozon)
- **Отзывы**: [N] отзывов, [X]% положительных
- **Характеристики**: [Key specs]
- **Оценка доверия**: [X]/10
- **Красные флаги**: [list or "Нет"]

Extending to Other Platforms

The skill is designed for easy extension:

1. Create wb_search.py, wb_product_page.py (Wildberries)
2. Create ali_search.py, ali_product_page.py (AliExpress)
3. Each script must follow the same CLI interface:
   • Accept --url or --query
   • Accept --output for JSON file path
   • Print JSON to stdout if no --output
4. Update SKILL.md with platform-specific selectors

Quick Reference

Task	Command
Search Ozon	python scripts/ozon_search.py --query "..."
Check product	python scripts/ozon_product_page.py --url "..."
Read reviews	python scripts/ozon_reviews.py --url "..."
Check seller	python scripts/ozon_seller.py --url "..."
Generate report	python scripts/helpers/reporter.py --input results/
Help on any script	python scripts/ozon_search.py --help