
deal-hunt
by tavily-ai
Official Tavily plugin for Claude Code
SKILL.md
name: deal-hunt description: "Find the best current deals/coupons for a specific product. Searches web for deals and returns raw results for analysis."
Deal Hunt
Search for deals on any product. Returns raw Tavily search results - Claude analyzes them to find the best prices.
Prerequisites
Tavily API Key Required - Get your key at https://tavily.com
Add to ~/.claude/settings.json:
{
"env": {
"TAVILY_API_KEY": "tvly-your-api-key-here"
}
}
Usage
# Search entire web (default - no domain filter)
python scripts/deal_hunt.py "Dyson V15"
# Multi-query search (max 3, runs in parallel, deduplicates results)
python scripts/deal_hunt.py "AirPods Pro" --queries "AirPods Pro deal,AirPods Pro coupon,AirPods Pro discount"
# Limit to specific sites
python scripts/deal_hunt.py "MacBook Air" --domains amazon.com,walmart.com,bestbuy.com
# Custom single query
python scripts/deal_hunt.py "Nintendo Switch" --query "Nintendo Switch OLED bundle deal"
# Fresh deals only
python scripts/deal_hunt.py "PS5" --time-range day
CLI Parameters
| Option | Short | Default | Description |
|---|---|---|---|
product | - | Required | Product name |
--query | -q | {product} deal price | Single custom search query |
--queries | None | Comma-separated queries (max 3), runs in parallel with dedup | |
--domains | -d | None (search all) | Optionally limit to specific domains |
--max-results | -n | 10 | Number of results per query |
--time-range | -t | week | day, week, month, year, none |
--search-depth | -s | advanced | basic, advanced, fast, ultrafast |
Output
Returns JSON with results:
{
"meta": {
"product": "AirPods Pro",
"queries": ["AirPods Pro deal", "AirPods Pro coupon"],
"domains": null,
"time_range": "week",
"search_time": "2026-01-13T...",
"total_results": 15
},
"results": [
{
"title": "...",
"url": "https://...",
"content": "...",
"score": 0.95
}
]
}
When using --queries, results are deduplicated by URL (highest score kept, content merged).
Output Schema for Analysis
After running the search, Claude should analyze results and structure findings as:
{
"product": "Sony WH-1000XM5",
"best_deal": {
"price": 279.99,
"original_price": 399.99,
"discount": "30% off",
"retailer": "Amazon",
"url": "https://amazon.com/...",
"condition": "new",
"in_stock": true
},
"all_deals": [
{
"price": 279.99,
"retailer": "Amazon",
"url": "https://...",
"notes": "Prime shipping"
},
{
"price": 169.99,
"retailer": "eBay via Slickdeals",
"url": "https://...",
"notes": "Refurbished"
}
],
"coupons": [
{
"code": "AUDIO10",
"discount": "10% off",
"retailer": "Best Buy",
"expires": "2026-01-31"
}
],
"summary": "Best new price is $279.99 at Amazon (30% off). Refurbished available for $169.99."
}
Claude extracts prices from content, compares deals, and presents the best options with purchase links.
Score
Total Score
Based on repository quality metrics
SKILL.mdファイルが含まれている
ライセンスが設定されている
100文字以上の説明がある
GitHub Stars 100以上
3ヶ月以内に更新がある
10回以上フォークされている
オープンIssueが50未満
プログラミング言語が設定されている
1つ以上のタグが設定されている
Reviews
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