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Serpapi core workflow b

Skill jeremylongshore/claude-code-plugins-plus-skills/plugins/saas-packs/serpapi-pack/skills/serpapi-core-workflow-b

425 plugins, 2,810 skills, 200 agents for Claude Code. Open-source marketplace at tonsofskills.com with the ccpi CLI package manager.

Install
npx -y skills add jeremylongshore/claude-code-plugins-plus-skills --skill serpapi-core-workflow-b

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

What its author says it does

Copied from the file, not written here

'Search Bing, YouTube, Google Shopping, Google News, and Google Maps with SerpApi.

The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.

SKILL.md

4.5 KB, ~1.1k tokens by cl100k_base, as published. Nobody here has run it

SerpApi Core Workflow B: Multi-Engine Search

Overview

SerpApi supports 15+ search engines beyond Google. Each engine has its own parameters and result structure. Key engines: YouTube (search_query), Bing (q), Google News, Google Shopping, Google Maps, Walmart, eBay, Apple App Store.

Instructions

Step 1: YouTube Search

import serpapi, os
client = serpapi.Client(api_key=os.environ["SERPAPI_API_KEY"])

# YouTube uses search_query (not q)
yt = client.search(engine="youtube", search_query="python asyncio tutorial")

for video in yt.get("video_results", []):
    print(f"{video['title']}")
    print(f"  Channel: {video.get('channel', {}).get('name')}")
    print(f"  Views: {video.get('views')}, Length: {video.get('length')}")
    print(f"  Link: {video['link']}")
    print(f"  Published: {video.get('published_date')}")

Step 2: Bing Search

bing = client.search(engine="bing", q="machine learning frameworks", count=10)

for r in bing.get("organic_results", []):
    print(f"{r['position']}. {r['title']}")
    print(f"   {r['link']}")
    # Bing has different snippet structure
    print(f"   {r.get('snippet', 'N/A')}")

Step 3: Google News

news = client.search(engine="google_news", q="artificial intelligence", gl="us", hl="en")

for article in news.get("news_results", []):
    print(f"{article['title']}")
    print(f"  Source: {article['source']['name']}")
    print(f"  Date: {article.get('date')}")
    print(f"  Link: {article['link']}")
    # News often has thumbnail
    if "thumbnail" in article:
        print(f"  Image: {article['thumbnail']}")

Step 4: Google Shopping

shopping = client.search(
    engine="google_shopping",
    q="mechanical keyboard",
    gl="us",
    hl="en",
)

for product in shopping.get("shopping_results", []):
    print(f"{product['title']}")
    print(f"  Price: {product.get('price')}")
    print(f"  Source: {product.get('source')}")
    print(f"  Rating: {product.get('rating')} ({product.get('reviews', 0)} reviews)")
    print(f"  Link: {product['link']}")

Step 5: Google Maps / Local

maps = client.search(
    engine="google_maps",
    q="pizza restaurants",
    ll="@30.2672,-97.7431,14z",  # Austin, TX coordinates + zoom
)

for place in maps.get("local_results", []):
    print(f"{place['title']} - {place.get('rating', 'N/A')} stars ({place.get('reviews', 0)} reviews)")
    print(f"  Address: {place.get('address')}")
    print(f"  Phone: {place.get('phone')}")
    print(f"  Type: {place.get('type')}")
    print(f"  Hours: {place.get('operating_hours', {}).get('monday')}")

Step 6: Cross-Engine Comparison

def multi_search(query: str) -> dict:
    """Search across multiple engines for the same query."""
    engines = [
        {"engine": "google", "q": query},
        {"engine": "bing", "q": query},
        {"engine": "youtube", "search_query": query},
        {"engine": "google_news", "q": query},
    ]
    results = {}
    for params in engines:
        result = client.search(**params)
        engine = params["engine"]
        key = "organic_results" if engine != "youtube" else "video_results"
        if engine == "google_news":
            key = "news_results"
        results[engine] = result.get(key, [])[:3]
    return results  # 4 API credits total

Error Handling

ErrorEngineSolution
search_query requiredYouTubeUse search_query not q
No shopping_resultsGoogle ShoppingQuery must be product-related
Empty local_resultsGoogle MapsAdd ll parameter with coordinates
count vs numBingBing uses count, Google uses num

Resources

Next Steps

For common errors, see serpapi-common-errors.

Keep looking

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