Price Tracker
by @michael-laffin
Monitor product prices across Amazon, eBay, Walmart, and Best Buy to identify arbitrage opportunities and profit margins. Use when finding products to flip, monitoring competitor pricing, tracking price history, identifying arbitrage opportunities, or setting automated price alerts.
clawhub install price-trackerπ About This Skill
name: price-tracker description: Monitor product prices across Amazon, eBay, Walmart, and Best Buy to identify arbitrage opportunities and profit margins. Use when finding products to flip, monitoring competitor pricing, tracking price history, identifying arbitrage opportunities, or setting automated price alerts.
Price Tracker
Overview
Track product prices across multiple e-commerce platforms to identify arbitrage opportunities, profit margins, and optimal buying/selling windows. This skill enables automated price monitoring, historical tracking, and revenue-focused decision making.
Core Capabilities
1. Product Discovery & Monitoring
Search and Track Products:
Example Request: "Monitor iPhone 15 Pro prices across Amazon and eBay. Alert me if the price drops below $800 or if eBay listing is $150+ cheaper than Amazon."
2. Arbitrage Analysis
Cross-Platform Comparison:
Fee Structure Reference:
Example Request: "Find Nintendo Switch bundles where eBay price is 20%+ higher than Amazon, accounting for all fees and shipping costs."
3. Historical Price Tracking
Price History:
Example Request: "Show me the price history for AirPods Pro 2 over the last 60 days. Identify the best buying window."
4. Automated Alerts
Alert Configuration:
Example Request: "Set up alerts for all Sony TV models. Alert me if any model drops below $400 or has 25%+ arbitrage margin."
Quick Start
Track a Single Product
# Use scripts/track_product.py
python3 scripts/track_product.py \
--product "Apple iPhone 15 Pro 256GB" \
--platforms amazon,ebay \
--alert-below 800 \
--alert-margin 0.20
Bulk Monitor Products from CSV
# Use scripts/bulk_monitor.py
python3 scripts/bulk_monitor.py \
--csv products.csv \
--margin-threshold 0.25 \
--alert-frequency daily
Price Comparison Report
# Use scripts/compare_prices.py
python3 scripts/compare_prices.py \
--keyword "Sony WH-1000XM5" \
--platforms amazon,ebay,walmart,bestbuy \
--report markdown
Workflow
Arbitrage Opportunity Discovery
1. Search for products in high-demand categories (electronics, gaming, home goods)
2. Compare prices across all platforms using compare_prices.py
3. Calculate net profit after fees/shipping/taxes
4. Filter opportunities with 20%+ margin
5. Verify product condition and seller reliability
6. Execute or set monitoring for price drops
Price Drop Monitoring
1. Identify target products (wishlist, seasonally discounted items)
2. Set alert thresholds using track_product.py
3. Monitor historical patterns to predict optimal buy windows
4. Act when price drops below threshold
5. Repeat for seasonal shopping events (Prime Day, Black Friday)
Scripts
track_product.py
Track a single product across platforms with configurable alerts.Parameters:
--product: Product name/keyword--platforms: Comma-separated platforms (amazon,ebay,walmart,bestbuy)--alert-below: Alert when price drops below this amount--alert-margin: Alert when arbitrage margin exceeds this fraction (e.g., 0.20 = 20%)--frequency: Check frequency (hourly,daily,weekly)--output: Output format (json,csv,markdown)Example:
python3 scripts/track_product.py \
--product "Samsung Galaxy S24 Ultra 256GB" \
--platforms amazon,ebay,walmart \
--alert-below 900 \
--alert-margin 0.25 \
--frequency daily \
--output markdown
compare_prices.py
Compare prices for a product across all platforms.Parameters:
--keyword: Product search keyword--platforms: Comma-separated platforms (default: all)--report: Report format (markdown,json,csv)--sort-by: Sort by price, margin, or rating--min-rating: Minimum seller ratingExample:
python3 scripts/compare_prices.py \
--keyword "PlayStation 5 Slim" \
--platforms amazon,ebay,walmart,bestbuy \
--report markdown \
--sort-by margin \
--min-rating 4.5
bulk_monitor.py
Monitor multiple products from a CSV file.CSV Format:
product,platforms,alert_below,alert_margin
"Apple MacBook Air M3 256GB",amazon,ebay,walmart,899,0.20
"Sony PlayStation 5",amazon,ebay,399,0.25
"Dyson V15 Detect",amazon,walmart,bestbuy,500,0.18
Parameters:
--csv: Path to CSV file--margin-threshold: Minimum margin to report--alert-frequency: Frequency of alerts--output: Output file for alertsExample:
python3 scripts/bulk_monitor.py \
--csv products.csv \
--margin-threshold 0.20 \
--alert-frequency daily \
--output alerts.txt
price_history.py
Retrieve and analyze historical price data.Parameters:
--product: Product name/keyword--days: Number of days of history (default: 30)--platform: Specific platform (optional)--output: Output format (markdown,json,csv)--trend-analysis: Include trend analysis and predictionsExample:
python3 scripts/price_history.py \
--product "AirPods Pro 2" \
--days 60 \
--trend-analysis \
--output markdown
Best Practices
Arbitrage Profit Calculation
Always calculate net profit:
Net Profit = (Sell Price - Buy Price)
- Platform Fees
- Shipping Costs
- Payment Processing Fees
- Taxes
Recommended minimum margin: 20-25% to account for:
Risk Mitigation
1. Verify seller reliability - Check ratings and reviews 2. Check product condition - New, refurbished, or used 3. Factor in return windows - Platforms have different policies 4. Monitor price stability - Volatile prices increase risk 5. Stay within limits - Don't over-leverage on single opportunities
Seasonal Patterns
Automation Integration
Set Up Cron Jobs for Automated Monitoring
# Check prices every 6 hours
0 */6 * * * /path/to/price-tracker/scripts/bulk_monitor.py --csv products.csv --output alerts.txtDaily arbitrage scan
0 9 * * * /path/to/price-tracker/scripts/compare_prices.py --keyword "high-demand-products" --report markdown >> /path/to/reports.txt
Integration with Notifications
Combine with notification systems (email, Discord, Telegram) to receive real-time alerts when opportunities are detected.
Limitations
Revenue first. Track smart. Flip fast.
π‘ Examples
Track a Single Product
# Use scripts/track_product.py
python3 scripts/track_product.py \
--product "Apple iPhone 15 Pro 256GB" \
--platforms amazon,ebay \
--alert-below 800 \
--alert-margin 0.20
Bulk Monitor Products from CSV
# Use scripts/bulk_monitor.py
python3 scripts/bulk_monitor.py \
--csv products.csv \
--margin-threshold 0.25 \
--alert-frequency daily
Price Comparison Report
# Use scripts/compare_prices.py
python3 scripts/compare_prices.py \
--keyword "Sony WH-1000XM5" \
--platforms amazon,ebay,walmart,bestbuy \
--report markdown
π Tips & Best Practices
Arbitrage Profit Calculation
Always calculate net profit:
Net Profit = (Sell Price - Buy Price)
- Platform Fees
- Shipping Costs
- Payment Processing Fees
- Taxes
Recommended minimum margin: 20-25% to account for:
Risk Mitigation
1. Verify seller reliability - Check ratings and reviews 2. Check product condition - New, refurbished, or used 3. Factor in return windows - Platforms have different policies 4. Monitor price stability - Volatile prices increase risk 5. Stay within limits - Don't over-leverage on single opportunities