This skill guides you on how to query and analyze Google Trends keyword search interest data, helping users understand how keyword popularity changes over time across different regions.
Google Trends provides normalized search interest data (0-100 scale) reflecting how popular a given search term is relative to its peak popularity in the selected region and time range. A value of 100 represents peak popularity, 50 means the term is half as popular as its peak, and 0 means insufficient data.
Important language rule: Keywords must be in the language of the target country. For example, use English keywords for the US, German keywords for Germany, Japanese keywords for Japan. If the user provides keywords in the wrong language, translate them before querying.
| Parameter | Type | Required | Description |
|---|---|---|---|
| ----------- | ------ | ---------- | ------------- |
| keyword | string | Yes | The search keyword to analyze (max 100 characters). Must be in the target country's language. |
| region | string | No | Country/region code. Defaults to US. |
| dayRangeStart | string | No | Start date for the time range (format: YYYY-MM-DD, from 2004 onward). |
| dayRangeEnd | string | No | End date for the time range (format: YYYY-MM-DD, from 2004 onward). |
When both dayRangeStart and dayRangeEnd are provided, the custom time range takes priority.
US (United States), GB (United Kingdom), JP (Japan), CA (Canada), MX (Mexico), DE (Germany), FR (France), IT (Italy), ES (Spain), NL (Netherlands), AU (Australia), SG (Singapore), AE (United Arab Emirates), BR (Brazil), IN (India), TR (Turkey), PL (Poland), SE (Sweden)
Default region is US. Use US when the user doesn't specify a region.
This tool calls the LinkFox tool gateway API. See references/api.md for calling conventions, request parameters, and response structure. You can also execute scripts/google_trends_keyword.py directly to run queries.
dayRangeStart and dayRangeEnd.1. Basic Keyword Trend (Default Region & Time)
{"keyword": "wireless charger"}
Query the overall search interest trend for "wireless charger" in the US.
2. Keyword Trend in a Specific Region
{"keyword": "Ladekabel", "region": "DE"}
Query the search interest for "Ladekabel" (charging cable) in Germany.
3. Custom Date Range Analysis
{"keyword": "christmas gifts", "region": "US", "dayRangeStart": "2024-09-01", "dayRangeEnd": "2025-01-31"}
Analyze the seasonal trend of "christmas gifts" in the US from September 2024 through January 2025.
4. Year-over-Year Comparison
{"keyword": "sunscreen", "region": "AU", "dayRangeStart": "2023-01-01", "dayRangeEnd": "2025-12-31"}
Compare multi-year seasonality of "sunscreen" in Australia.
5. Regional Market Research
{"keyword": "yoga mat", "region": "GB"}
Check the popularity trend of "yoga mat" in the United Kingdom.
6. Emerging Trend Detection
{"keyword": "AI glasses", "region": "US", "dayRangeStart": "2024-01-01", "dayRangeEnd": "2025-12-31"}
Track the rise of "AI glasses" search interest over the past two years in the US.
chartOption, mention that visualization data is available and describe the trend shape.Applicable -- Queries about keyword search popularity trends:
| User Says | Scenario |
|---|---|
| ----------- | ---------- |
| "How popular is XX keyword on Google" | Basic trend lookup |
| "Is XX trending up or down" | Trend direction analysis |
| "When does XX peak in searches" | Seasonal peak detection |
| "Compare popularity of XX across months" | Seasonal pattern analysis |
| "Is XX gaining traction in Germany" | Regional trend check |
| "What's the search trend for XX over the past year" | Historical trend analysis |
| "Holiday search trends for XX" | Seasonal / event-driven analysis |
Not applicable -- Needs beyond Google Trends search interest data:
Boundary judgment: When users say "keyword research" or "market trend analysis", if it specifically relates to search interest popularity over time from Google's perspective, this skill applies. If they want absolute traffic numbers, advertising metrics, or e-commerce-platform-specific data, it does not apply.
Feedback:
Auto-detect and report feedback via the Feedback API when any of the following apply:
Call the feedback API as specified in references/api.md. Do not interrupt the user's flow.
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