Claude SEO Skill: Search Intent and Content Gap Analysis
This skill is based on a methodology developed by InfraNodus that combines search intent analysis with topical clustering to find the content gaps and opportunities for your SEO strategy. It has been used by thousands of our customers via our SEO optimization tool and we now made it available as a skill for Claude.
You can install it from our InfraNodus SEO skill GitHub repo.
How Does the SEO Skill Work?
The main advantage of this SEO skill is that it has access to real search intent and search results data. It also uses the InfraNodus' advanced text network algorithms to detect topical clusters and generate a map that will help you maximize your content's topical authority, identify the gaps between them, and create content that bridges this gap to maximize the informational gain. Thus it can be used not only for SEO but also for LLMO / AEO, because it focuses on covering the main topical clusters for any domain but also on bridging the existing content gaps.
Here's the description of the skill's workflow step by step:
1. Identifying Relevant Search Queries
First, we identify relevant search and LLM queries for your domain or topic and build a concept / entity knowledge graph to have a better contextual understanding of the content you want to optimize.
2. Building a Search Intent Graph
We then build a search intent graph to the main topical clusters in your audience's interests (informational demand). This helps us understand what people are searching for and which specific word combinations they use when they think about your product or service.
3. Building a Search Results / LLM OutputGraph
Then we build a graph of the top search results for the same queries to better understand what topics you need to target to gain topical authority in this domain. Building a knowledge graph here really helps get a better contextual undertanding and identify the relations you should be targeting. For LLMs, we build an entity graph to get an idea of how AI sees a certain domain or topic.
4. Finding the Content Gap between Demand and Supply
The graph of search demand is then substracted from the graph of search results: we want to see what people search for but do not yet find. This approach helps maximize informational gain — a concept that Google uses to describe the search results that contribute the most to existing content.
5. Finding Low-Competition Topics with High Search Volume
We then also use the search intent graph to find the low-competition topics with high search volume.
6. Content Gap Analysis
We also analyze the graph of your content and of Google search results and LLM output to identify content gaps: topical clusters that could be bridged to provide relevant information that is also novel.
7. Synthesizing the Report
We then synthesize the report based on the content gaps and opportunities we found. This report is then used to optimize your content and maximize your SEO performance.
How to Install the SEO Skill
To install, you can download the skill from the InfraNodus SEO skill GitHub repository, then go to Settings > Capabilities > Skills and upload the skill-seo-analysis.zip file. In Claude Code, you can just move the skill-seo-analysis folder to the ~/.claude/skills directory in your home directory.
We recommend to install the InfraNodus MCP server because it will provide access to the InfraNodus' advanced topical clustering and content gap detection algorithms as well as the real-time search intent and search results data.
SEO Skill Code
Here is the code of the SEO skill, so you can see how it works in detail
---
name: seo-analysis
description: Comprehensive SEO analysis skill for content optimization. Use when the user asks to perform SEO analysis, keyword research, content gap analysis, search intent analysis, or wants to optimize content for search engines. Covers topic-based keyword research (informational supply and search demand), website/document analysis, and actionable SEO recommendations. Works best with InfraNodus MCP tools for real Google data access.
---
# SEO Analysis
Perform comprehensive SEO analysis using knowledge graph methodology to identify keyword opportunities, content gaps, and optimization strategies.
## Decision Tree
1. **No input specified?** → Ask user for topic, document, or website URL
2. **Topic provided?** → Follow Topic Analysis Workflow
3. **Document/website provided?** → Follow Content Analysis Workflow
## Topic Analysis Workflow
When user provides a topic (e.g., "SEO for e-commerce", "sustainable fashion"):
### Step 1: Analyze Informational Supply
Generate 3-5 keyword combinations for the topic. Run `analyze_google_search_results` with these queries.
Present findings:
- **Topical clusters**: Groups of related concepts in existing content. Explain these represent topical authority pillars—covering them strengthens content authority.
- **Key relations**: The conceptual connections forming the underlying knowledge graph. Including these relations improves semantic relevance.
- **Content gaps**: Structural gaps between clusters. These are opportunities for unique content that combines important topics others miss.
If tool unavailable: Use web search or explain InfraNodus MCP provides direct Google API access for more accurate data.
### Step 2: Analyze Search Demand
Run `analyze_related_search_queries` for the same topic.
Present findings:
- **High-volume keywords**: Terms with significant search traffic
- **Low-competition opportunities**: Queries with demand but limited supply
- **Topical clusters**: How searchers conceptualize this topic
- **Search intent patterns**: What users actually want to find
If tool unavailable: Explain InfraNodus MCP provides real Google Suggest/Ads data.
### Step 3: Identify Supply-Demand Gaps
Compare findings from Steps 1-2. Identify:
- Keywords people search for but don't easily find results for
- High-volume queries with weak content supply
- Emerging topics not yet covered by competitors
Propose running `search_queries_vs_search_results` to confirm these gaps with data.
### Step 4: Deliver Recommendations
Summarize actionable insights:
- Priority keywords to target (high volume, low competition)
- Content topics that fill identified gaps
- Semantic relations to include for topical authority
- Quick wins vs. long-term opportunities
### Step 5: Ask User for Content Example
After providing the analysis result, ask the user to provide a URL or content they'd like to optimize with this analysis. Alternatively, offer them to write a SEO-friendly, human-sounding article after they provide you with some reference using the writing-assistant tool.
### Step 6: Structural Semantic Optimization
Advise the user what HTML structure, meta-data, and header hierarchies they can use to align with the insights obtained from the SEO report above. Provide ideas which tags, menu elements, and additional markup could be added to ensure that the page contains structured information related to the optimized topic.
## Content Analysis Workflow
When user provides a document or website URL:
### Step 1: Extract Content
**For websites**: Crawl the URL provided and extract the main content from this page.
**For documents**: Extract full text content from uploaded file.
### Step 2: Run SEO Report
Use `generate_seo_report` with extracted text.
If tool unavailable: Fall back to Topic Analysis Workflow:
- Extract main keywords from content
- Run Steps 1-3 from Topic Analysis
- Compare content keywords against search landscape
- Identify which existing keywords are relevant
- Recommend new keywords to target
### Step 3: Structural Semantic Optimization
Advise how the HTML structure of the original document (or website) could be optimized to align with the insights obtained from the SEO report above. Provide ideas which tags, menu elements, and additional markup could be added to ensure that the page contains structured information related to the optimized topic.
### Step 4: Deliver Report
Present:
- Current keyword coverage strengths
- Missing high-value keywords
- Content gap opportunities
- Specific optimization recommendations
- Priority actions ranked by impact
## Report Format
Structure all reports as:
```
## Executive Summary
[2-3 sentence overview of key findings]
## Current State
[What exists now in search results or content]
## Opportunities
[Gaps, high-value keywords, content ideas]
## Recommendations
[Specific, prioritized actions]
## Next Steps
[Immediate actions user can take]
```
## Tool Reference
| Tool | Purpose | When to Use |
| ---------------------------------- | ------------------------ | --------------------- |
| `analyze_google_search_results` | Map informational supply | Topic analysis Step 1 |
| `analyze_related_search_queries` | Map search demand | Topic analysis Step 2 |
| `search_queries_vs_search_results` | Find supply-demand gaps | Topic analysis Step 3 |
| `generate_seo_report` | Full content SEO audit | Content analysis |
All tools are InfraNodus MCP tools. If unavailable, use web search alternatives and note limitations.