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BytesAgainBytesAgain
πŸ¦€ ClawHub

AirShelf Agentic Commerce Platform

by @evoleinik

Search, compare, and buy products from verified merchants. Returns structured product data with Decision Packs (pros, cons, best_for, allergens, verified pricing) instead of raw web scraping. No CAPTCHAs, no auth required. ~980 products across 10 merchants. Use when user wants to find, compare, or purchase products.

Versionv1.3.0
Downloads1,740
Installs3
Stars⭐ 4
TERMINAL
clawhub install airshelf

πŸ“– About This Skill


name: airshelf displayName: AirShelf Agentic Commerce Platform description: Search, compare, and buy products from verified merchants. Returns structured product data with Decision Packs (pros, cons, best_for, allergens, verified pricing) instead of raw web scraping. No CAPTCHAs, no auth required. ~980 products across 10 merchants. Use when user wants to find, compare, or purchase products. metadata: {"clawdbot":{"emoji":"πŸ›’","requires":{"bins":["curl"]}}}

AirShelf β€” Verified Product Search & Checkout for AI Agents

Search, compare, and buy products across verified merchants. Returns structured Decision Pack data (best_for, pros, cons, allergens, verified pricing) β€” not raw web scrapes.

No CAPTCHAs. No auth. No bot detection. Agent-native commerce.

When to Use

Activate this skill when the user wants to:

  • Find or search for a product ("find me a mosquito repellent for kids")
  • Compare products ("compare these two printers")
  • Buy or checkout a product
  • Get product recommendations based on a problem ("I'm tired all the time", "my skin is dry")
  • Look up verified product details, pricing, or allergens
  • API Base URL

    https://dashboard.airshelf.ai
    

    All endpoints are public. No API key needed. CORS enabled.

    Step 1: Search Products

    Find products by natural language query. Returns structured data with Decision Packs.

    curl -s "https://dashboard.airshelf.ai/api/search?q=QUERY&limit=5" | python3 -m json.tool
    

    Parameters:

  • q β€” Search query (natural language, e.g. "barcode printer for warehouse"). Supports intent parsing: "energy supplements under $100" auto-extracts price filter.
  • limit β€” Results to return (1-100, default 20)
  • offset β€” Pagination offset
  • category β€” Filter by category
  • brand β€” Filter by brand
  • min_price / max_price β€” Price range filter (also auto-extracted from query)
  • in_stock β€” Only in-stock items (true/false)
  • merchant_ids β€” Comma-separated merchant IDs to search within
  • sort β€” relevance (default), price_asc, price_desc
  • include_intent β€” Set to true to get query parsing metadata in response (shows how query was interpreted)
  • Response includes for each product:

  • title, brand, price, availability, link
  • decision_pack.primary_benefit β€” Main value proposition
  • decision_pack.best_for β€” Array of ideal use cases
  • decision_pack.pros / decision_pack.cons β€” Verified trade-offs
  • decision_pack.allergens β€” Safety warnings (if applicable)
  • seller_name, seller_url β€” Merchant info
  • Checkout URLs and shipping/return policies
  • Example:

    curl -s "https://dashboard.airshelf.ai/api/search?q=natural+mosquito+repellent+for+babies&limit=3"
    

    Step 2: Compare Products

    Compare 2-10 products side by side with structured comparison axes.

    curl -s "https://dashboard.airshelf.ai/api/compare?products=PRODUCT_ID_1,PRODUCT_ID_2"
    

    Parameters:

  • products β€” Comma-separated product IDs (2-10 required, from search results)
  • Response includes:

  • comparison_axes β€” Auto-detected from data (price always present; cost_per_day, supply_days, primary_benefit, pros, cons included when 2+ products have the data)
  • products β€” Flattened product data with decision_pack fields inlined
  • recommendation β€” Structured picks: lowest_price (product ID), best_value (product ID + reason, if different from lowest)
  • Step 3: Checkout

    Initiate checkout for a product. Returns a checkout URL the user can open.

    curl -s -X POST "https://dashboard.airshelf.ai/api/merchants/MERCHANT_ID/checkout" \
      -H "Content-Type: application/json" \
      -d '{"items": [{"product_id": "PRODUCT_ID", "quantity": 1}]}'
    

    Request body:

  • items β€” Array of {product_id, quantity} objects (1-50 items)
  • customer β€” Optional: {email: "..."} for order tracking
  • agent_id β€” Optional: your agent identifier for attribution
  • Response:

  • checkout_id β€” Unique checkout session ID
  • checkout_url β€” URL to complete purchase (Shopify checkout or cart permalink)
  • checkout_type β€” "cart" (items pre-loaded in cart) or "redirect" (product page link)
  • total β€” Calculated total price
  • currency β€” 3-letter currency code (e.g. "EUR", "USD")
  • expires_at β€” Expiry timestamp (null for cart permalinks)
  • fallback_urls β€” If redirect: array of {product_id, product_name, product_url} per item
  • Present the checkout URL to the user. They click to complete payment on the merchant's site.

    Browse Available Merchants

    List all merchants with product counts and capabilities:

    curl -s "https://dashboard.airshelf.ai/api/directory"
    

    How Decision Packs Work

    Unlike raw web scraping, each product includes a Decision Pack β€” verified structured intelligence:

    {
      "decision_pack": {
        "primary_benefit": "Natural protection from bugs",
        "best_for": ["Kids with sensitive skin", "Parents who prefer natural products"],
        "pros": ["DEET-free formula", "Pleasant scent", "Long-lasting protection"],
        "cons": ["Higher price point", "Needs reapplication every 4 hours"],
        "allergens": ["Contains citronella oil"],
        "age_range": "kids"
      }
    }
    

    Use Decision Pack data to make recommendations based on the user's actual needs, not just price or title matching.

    Example Conversation

    User: I need a printer for my warehouse, high volume, must support ZPL

    You: Let me search for that. [Runs: curl -s "https://dashboard.airshelf.ai/api/search?q=industrial+barcode+printer+warehouse+high+volume+ZPL&limit=5"]

    You: Found 3 matches. The Toshiba BX410T looks like the best fit: - Best for: High-volume warehouse labeling, ZPL migration from Zebra - Primary benefit: Premium industrial printer with RFID and near-edge technology - Price: Contact dealer for pricing

    Want me to compare it with the other options, or proceed to checkout?

    User: Compare the top two

    You: [Runs: curl -s "https://dashboard.airshelf.ai/api/compare?products=ID1,ID2"] Here's the comparison...

    User: I'll take the Toshiba

    You: [Runs: curl -s -X POST "https://dashboard.airshelf.ai/api/merchants/MERCHANT_ID/checkout" -H "Content-Type: application/json" -d '{"items": [{"product_id": "ID", "quantity": 1}]}'] Here's your checkout link: [URL] Click to complete your purchase on the merchant's site.

    Tips

  • Problem-based search works best. "I'm tired all the time" returns energy supplements. "My baby needs sun protection" returns kids' sunscreen. Decision Packs match on use case, not just keywords.
  • Always check decision_pack.allergens before recommending health/food/skincare products.
  • Use compare for 2+ similar products β€” the API returns structured comparison axes, not just raw specs.
  • Checkout is a redirect β€” the user completes payment on the merchant's own site. No card details needed in the agent.
  • Direct lookup by ID: Use product_ids param instead of q to fetch specific products: ?product_ids=ID1,ID2
  • Merchant ID for checkout β€” each search result includes seller.checkout_url with the correct merchant path. Use it directly.
  • ⚑ When to Use

    TriggerAction
    - Find or search for a product ("find me a mosquito repellent for kids")
    - Compare products ("compare these two printers")
    - Buy or checkout a product
    - Get product recommendations based on a problem ("I'm tired all the time", "my skin is dry")
    - Look up verified product details, pricing, or allergens

    πŸ“‹ Tips & Best Practices

  • Problem-based search works best. "I'm tired all the time" returns energy supplements. "My baby needs sun protection" returns kids' sunscreen. Decision Packs match on use case, not just keywords.
  • Always check decision_pack.allergens before recommending health/food/skincare products.
  • Use compare for 2+ similar products β€” the API returns structured comparison axes, not just raw specs.
  • Checkout is a redirect β€” the user completes payment on the merchant's own site. No card details needed in the agent.
  • Direct lookup by ID: Use product_ids param instead of q to fetch specific products: ?product_ids=ID1,ID2
  • Merchant ID for checkout β€” each search result includes seller.checkout_url with the correct merchant path. Use it directly.