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πŸ¦€ ClawHub

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.

Versionv1.0.0
Downloads4,169
Installs22
Stars⭐ 6
TERMINAL
clawhub install price-tracker

πŸ“– 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:

  • Search products by keyword across Amazon, eBay, Walmart, Best Buy
  • Add products to monitoring lists
  • Set target price thresholds
  • Configure alert frequency (hourly, daily, weekly)
  • 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:

  • Compare identical product prices across platforms
  • Calculate profit margins after fees and shipping
  • Identify flip-worthy opportunities (20%+ margin after costs)
  • Factor in platform fees, shipping costs, and taxes
  • Fee Structure Reference:

  • Amazon: ~15% referral fee
  • eBay: ~13% final value fee + listing fees
  • Walmart: ~8-15% referral fee
  • 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:

  • Track price changes over time (30, 60, 90 days)
  • Identify seasonal pricing patterns
  • Detect price manipulation or flash sales
  • Export historical data for analysis
  • 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:

  • Price drop alerts (below threshold)
  • Arbitrage opportunity alerts (margin threshold)
  • Competitor price alerts (when competitor lowers price)
  • Bulk product monitoring
  • 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 rating
  • Example:

    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 alerts
  • Example:

    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 predictions
  • Example:

    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:

  • Unexpected shipping delays
  • Returns/refunds
  • Market price fluctuations
  • Time value of money
  • 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

  • Q4 (Oct-Dec): Holiday sales, best for electronics
  • January: Post-holiday clearance
  • Prime Day (July): Amazon-specific deals
  • Black Friday/Cyber Monday: Cross-platform discounts
  • Back-to-School (Aug-Sep): Laptops, tablets, accessories
  • 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.txt

    Daily 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

  • Platform API rate limits may affect search frequency
  • Real-time prices may have slight delays
  • Some platforms restrict scraping (comply with ToS)
  • Seller inventory changes rapidly

  • Revenue first. Track smart. Flip fast.

    πŸ’‘ 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
    

    πŸ“‹ 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:

  • Unexpected shipping delays
  • Returns/refunds
  • Market price fluctuations
  • Time value of money
  • 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

  • Q4 (Oct-Dec): Holiday sales, best for electronics
  • January: Post-holiday clearance
  • Prime Day (July): Amazon-specific deals
  • Black Friday/Cyber Monday: Cross-platform discounts
  • Back-to-School (Aug-Sep): Laptops, tablets, accessories