This skill analyzes Search Engine Results Pages to reveal what's working for ranking content, which SERP features appear, and what triggers AI-generated answers. Understand the battlefield before creating content.
claude skill add aaron-he-zhu-serp-analysisThe serp-analysis skill is designed to empower marketers, content creators, and SEO professionals by analyzing Search Engine Results Pages (SERPs). This skill reveals what content is ranking well, identifies which SERP features are present, and uncovers the triggers for AI-generated answers. By understanding the competitive landscape before creating content, users can make informed decisions that enhance their content strategy and improve visibility in search engines. One of the key benefits of using the serp-analysis skill is the time savings it offers. Instead of spending hours manually researching SERPs and analyzing competitors, this skill automates the process, allowing users to focus on content creation and strategy development. By gaining insights into what works for ranking content, users can quickly adapt their strategies to align with current trends and search behaviors, ultimately leading to more effective and efficient workflows. This skill is particularly beneficial for developers, product managers, and AI practitioners who are involved in content marketing or SEO. It provides valuable data that can inform decisions and streamline workflows, making it easier to create high-quality content that resonates with target audiences. For example, a content manager could use the insights from serp-analysis to refine their blog topics based on what is currently performing well in search results, saving time and increasing the chances of higher rankings. While the implementation difficulty and specific requirements for the serp-analysis skill are currently unknown, its integration into AI-first workflows is clear. By leveraging AI automation, users can enhance their content strategies with data-driven insights, ensuring they stay ahead in the competitive digital landscape. This skill is a vital addition for anyone looking to optimize their marketing efforts and improve their understanding of search engine dynamics.
1. **Gather Keywords:** Use tools like Ahrefs, SEMrush, or Google Keyword Planner to identify 5-10 high-value keywords for your niche. Focus on commercial intent or informational queries where ranking opportunities exist. 2. **Run the Analysis:** Copy the prompt template, replace [KEYWORD] with your target term, and specify [SEARCH_ENGINE] (e.g., 'Google UK'). Paste the prompt into your AI tool (e.g., Claude, ChatGPT) and generate the SERP analysis. 3. **Compare Competitors:** Repeat the analysis for 2-3 competitor keywords (e.g., '[COMPETITOR_KEYWORD]') to identify gaps in their content strategy. Look for patterns in their top-ranking pages (e.g., word count, backlink profiles). 4. **Extract Insights:** Use the output to inform your content brief. Prioritize opportunities where: - The AI Overview cites outdated or incomplete information. - SERP features (e.g., PAA, carousels) are underutilized by competitors. - There’s a clear content format mismatch (e.g., competitors use lists, but a guide or tool would perform better). 5. **Validate with Tools:** Cross-check the AI’s findings with tools like MozBar (for DA/backlinks) or AnswerThePublic (for PAA questions). Adjust your content plan based on data, not just AI suggestions. **Tip:** For local businesses, replace [SEARCH_ENGINE] with 'Google [COUNTRY]' and analyze the Local Pack SERP features. For e-commerce, focus on 'Product' and 'Review' schema opportunities.
No install command available. Check the GitHub repository for manual installation instructions.
Copy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
Analyze the Search Engine Results Page (SERP) for the keyword '[KEYWORD]' on [SEARCH_ENGINE] (e.g., Google US). Identify: 1) The top 3 ranking pages and their key ranking factors (e.g., word count, backlinks, featured snippets), 2) All SERP features present (e.g., People Also Ask, Local Pack, Videos, AI Overviews), 3) The content format and structure of the top results, and 4) Potential gaps or opportunities for new content. Compare this SERP to the results for '[COMPETITOR_KEYWORD]' to highlight strategic differences.
For the keyword 'best budget laptops 2024' on Google US, the SERP analysis reveals the following: **Top 3 Ranking Pages:** 1. **LaptopMag.com** (Position 1) – 2,500-word comprehensive guide with 1,200+ backlinks, featuring a comparison table, expert reviews, and a 'Buyer's Guide' section. The page includes schema markup for 'Product' and 'Review' types. 2. **PCMag.com** (Position 2) – 1,800-word article with 800 backlinks, structured as a 'Top Picks' list with ratings and a 'FAQ' section. Uses a 'How We Test' methodology visible in the snippet. 3. **TechRadar.com** (Position 3) – 2,200-word guide with 950 backlinks, including a 'Best Budget Laptops' carousel and a 'Pros and Cons' section for each model. **SERP Features Present:** - **AI Overview (Top of Page):** Generated by Google, summarizing key factors like 'minimum 8GB RAM' and 'under $600 price point' with citations from the top 3 pages. - **People Also Ask (PAA):** 8 questions, including 'What is the best budget laptop for students?' and 'Are Chromebooks good for budget laptops?' - **Local Pack:** Not present (irrelevant for this query). - **Videos:** 1 YouTube video from 'Laptop Mag' embedded in the results. - **Carousel:** 'Best Budget Laptops Under $500' with 5 product cards. - **Top Stories:** None for this query. **Content Gaps:** - No page in the top 3 includes a 'Price Tracker' tool or a 'Student Discounts' section, which could be a unique differentiator. - The AI Overview cites outdated models (e.g., 'Acer Aspire 5 from 2023'), suggesting an opportunity to create an updated '2024 Budget Laptop Guide' with fresh data. - The PAA questions reveal user intent around 'student-specific' and 'gaming-capable' budget laptops, which are not fully addressed by the top results. **Strategic Recommendations:** - Create a '2024 Budget Laptop Guide' targeting the AI Overview by including a 'Minimum Specs' checklist and citing recent reviews. - Develop a 'Student Budget Laptop Comparison' page with a 'Discounts' section to target PAA queries. - Add a 'Price Tracker' widget to the guide to improve dwell time and engagement, which could boost rankings.
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