Agent skill

pricing-tracker

Tracks current pricing and availability across multiple retailers with price comparison. Use when user asks about 'price', 'how much', 'where to buy', 'pricing comparison', 'best deal', 'availability', or when orchestrator needs current market pricing data. Checks Amazon and category-specific retailers.

View SKILL.md on GitHub Repository
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Install this agent skill to your Project

npx add-skill https://github.com/lola69160/claude-product-comparison/tree/main/skills/pricing-tracker

SKILL.md

Pricing Tracker

Mission

Collecter prix actuel et disponibilité depuis multiples retailers (Amazon, sites spécialisés selon catégorie).

Outils de Scraping

Priorité 1: MCP Apify (Recommandé)

Outil Usage
mcp__apify__call-actor avec apify/amazon-product-scraper Prix Amazon structuré (inclut prix, stock, shipping)
mcp__apify__apify-slash-rag-web-browser Prix autres retailers (Decathlon, Darty, etc.)

Priorité 2: Fallback

Outil Usage
WebFetch Si MCP échoue ou timeout (>2 min)

Avantages MCP Apify:

  • Amazon: Prix exact, stock, shipping en JSON structuré
  • RAG Browser: Recherche + extraction prix en une seule requête

Quick Summary

  1. Amazon: MCP apify/amazon-product-scraper (ou WebFetch fallback)
  2. Autres retailers: MCP rag-web-browser (ou WebFetch fallback)
  3. Extract: prix, disponibilité, shipping, promos actives
  4. Save comparison table JSON + cache 7j

Inputs

  • product_name: Nom produit
  • category: Catégorie (pour sélectionner retailers appropriés)
  • amazon_url: URL Amazon (optionnel)

Outputs

  • pricing.json: Tableau prix par retailer
  • Cache 7j

Dependencies

  • data/category_specs.yaml (retailers par catégorie)
  • Load helpers/retailers.yaml when scraping for patterns

Workflow

1. Load retailers

javascript
retailers = category_specs.yaml[category].retailers
// Example velo: ["decathlon.fr", "alltricks.fr", "probikeshop.fr"]

2. Scrape Amazon (if in retailers)

javascript
**PRIMARY: MCP Apify**
mcp__apify__call-actor({
  actor: "apify/amazon-product-scraper",
  step: "call",
  input: {
    categoryOrProductUrls: [amazon_url],
    maxItems: 1
  }
})

mcp__apify__get-actor-output({
  datasetId: result.datasetId,
  fields: "title,price,availability,delivery"
})
→ Returns: { price: 549, availability: "In Stock", delivery: "Livraison gratuite" }

**FALLBACK: WebFetch** (if MCP fails)
WebFetch product page + extract with retailers.yaml selectors

3. Scrape other retailers (2-3)

javascript
For each retailer:
  query = "{product_name} prix site:{retailer}"

  **PRIMARY: MCP Apify RAG Web Browser**
  mcp__apify__apify-slash-rag-web-browser({
    query: query,
    maxResults: 1,
    outputFormats: ["markdown"]
  })

  Parse Markdown:
  "Extract pricing information:
   - Current price (number only)
   - Stock availability
   - Shipping cost
   - Active promotions
   Return as JSON."

  **FALLBACK: WebFetch**
  WebFetch product page + extract with retailers.yaml selectors

4. Build comparison table

javascript
{
  "product": product_name,
  "timestamp": now,
  "retailers": [
    {
      "name": "Amazon",
      "price": 549,
      "availability": "in_stock",
      "shipping": "Gratuit",
      "promo": null
    },
    {
      "name": "Decathlon",
      "price": 549,
      "availability": "in_stock",
      "shipping": "Gratuit en magasin",
      "promo": "-10% membres"
    }
  ],
  "best_price": 494.10,  // Decathlon with promo
  "best_retailer": "Decathlon"
}

5. Save + cache

  • Save: data/research_{timestamp}/{product}/pricing.json
  • Cache: data/cache/pricing/{cache_key}.json (7j TTL)

Error Handling

  • Retailer unavailable → Skip, continue with others
  • Price not found → Mark as "N/A"
  • Out of stock → Mark availability = false
  • MCP timeout → Fallback to WebFetch automatically

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