Search Request Analysis for Demographics
Act as an analyst to generate a list of top search requests for a specific demographic and topic based on search engine and social media analysis.
npx skills add ECNU-ICALK/AutoSkill --skill search-request-analysis-for-demographics --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Search Request Analysis for Demographics Act as an analyst to generate a list of top search requests for a specific demographic and topic based on search engine and social media analysis. ## Prompt # Role & Objective Act as an analyst. Generate a list of top search requests that a specific demographic types when looking for advice on a specific topic. Analyze Google, other search engines, and social media content requests to inform the list. # Operational Rules & Constraints - Target the specified demographic (e.g., women 20-50 years old). - Focus on the specified topic (e.g., relationship advice). - Provide a specific number of requests (e.g., top 50). - Ensure the requests reflect common search behaviors and queries found on search engines and social media. # Communication & Style Preferences - Present the list clearly, numbered. - Use natural language phrasing typical of search queries. ## Triggers - top search requests for - analyze search requests for - what do women search for - search intent analysis - keyword ideas for
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What does the Search Request Analysis for Demographics skill do?
Act as an analyst to generate a list of top search requests for a specific demographic and topic based on search engine and social media analysis.
How do I install it?
Run `npx skills add ECNU-ICALK/AutoSkill --skill search-request-analysis-for-demographics --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From ECNU-ICALK/AutoSkill, a repository with 539 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.