serpapi-core-workflow-b
Search Bing, YouTube, Google Shopping, Google News, and Google Maps with SerpApi. Use when scraping non-Google engines, building multi-engine search, or extracting video/news/shopping/maps data. Trigger: "serpapi youtube", "serpapi bing", "serpapi news", "serpapi shopping".
Best use case
serpapi-core-workflow-b is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Search Bing, YouTube, Google Shopping, Google News, and Google Maps with SerpApi. Use when scraping non-Google engines, building multi-engine search, or extracting video/news/shopping/maps data. Trigger: "serpapi youtube", "serpapi bing", "serpapi news", "serpapi shopping".
Teams using serpapi-core-workflow-b should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/serpapi-core-workflow-b/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How serpapi-core-workflow-b Compares
| Feature / Agent | serpapi-core-workflow-b | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Search Bing, YouTube, Google Shopping, Google News, and Google Maps with SerpApi. Use when scraping non-Google engines, building multi-engine search, or extracting video/news/shopping/maps data. Trigger: "serpapi youtube", "serpapi bing", "serpapi news", "serpapi shopping".
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# 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
```python
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
```python
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
```python
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
```python
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
```python
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
```python
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
| Error | Engine | Solution |
|-------|--------|----------|
| `search_query` required | YouTube | Use `search_query` not `q` |
| No `shopping_results` | Google Shopping | Query must be product-related |
| Empty `local_results` | Google Maps | Add `ll` parameter with coordinates |
| `count` vs `num` | Bing | Bing uses `count`, Google uses `num` |
## Resources
- [YouTube Search API](https://serpapi.com/youtube-search-api)
- [Bing Search API](https://serpapi.com/bing-search-api)
- [Google News API](https://serpapi.com/google-news-api)
- [Google Shopping API](https://serpapi.com/google-shopping-api)
- [Google Maps API](https://serpapi.com/google-maps-api)
## Next Steps
For common errors, see `serpapi-common-errors`.Related Skills
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