Can this skill help me capture Featured Snippets?

Yes, it identifies the type of snippet currently appearing (paragraph, list, table, or video) and provides specific formatting recommendations to help you win that spot.

How does the SERP Analysis skill classify search intent?

It analyzes the types of results returned—such as Wikipedia for Informational, product pages for Transactional, or reviews for Commercial—to determine the dominant user goal.

Does this work with real-time search data?

Yes, it is designed to be used in conjunction with Claude Code's web search capabilities to analyze current, live search engine results pages.

What competitor data does the skill collect?

It generates a matrix for the top 10 results, tracking domain authority, content format, word count, heading structures, and the unique angle each competitor takes.

SERP Analysis & SEO Intent Classifier

Name: SERP Analysis & SEO Intent Classifier
Author: involvex

byinvolvex

Automatización de Marketing

Analyzes search engine results pages to classify search intent, identify SERP features, and conduct competitive intelligence.

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The SERP Analysis skill transforms Claude into a powerful SEO assistant capable of dissecting live search results for deep marketing insights. It provides a structured framework for classifying search intent—Informational, Commercial, Transactional, or Navigational—while identifying high-value SERP features like Featured Snippets, People Also Ask boxes, and Local Packs. By automating the collection of competitor data including content formats, word counts, and heading structures, it allows users to pinpoint content gaps and develop data-driven strategies to outrank the competition.

Características Principales

0 GitHub stars
Competitive matrix generation for top-ranking search results
Automated intent classification with confidence level scoring
Standardized reporting for content strategy and SEO planning
Identification of 7+ SERP features and specific optimization strategies
Content gap identification to find unique ranking opportunities

Casos de Uso

Determining the ideal content format for a specific target keyword
Conducting deep-dive competitive research for new market entry
Optimizing existing content to capture Featured Snippets and PAA boxes

Acerca de

Características Principales

0 GitHub stars
Competitive matrix generation for top-ranking search results
Automated intent classification with confidence level scoring
Standardized reporting for content strategy and SEO planning
Identification of 7+ SERP features and specific optimization strategies
Content gap identification to find unique ranking opportunities

Casos de Uso

Determining the ideal content format for a specific target keyword
Conducting deep-dive competitive research for new market entry
Optimizing existing content to capture Featured Snippets and PAA boxes