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Seo Analysis

Organization
infranodus
seo-analysis

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.

Overview

Publisherinfranodus
Repositoryskills
Skill nameseo-analysis
Stars
124
Forks
31
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by infranodus on GitHub. Read the source before you install it.

Installation

Install the Seo Analysis AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/infranodus/skills/tree/master/skill-seo-analysis
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/infranodus/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skill-seo-analysis .claude/skills/seo-analysis
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Seo Analysis in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Seo Analysis on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Seo Analysis is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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

ToolPurposeWhen to Use
analyze_google_search_resultsMap informational supplyTopic analysis Step 1
analyze_related_search_queriesMap search demandTopic analysis Step 2
search_queries_vs_search_resultsFind supply-demand gapsTopic analysis Step 3
generate_seo_reportFull content SEO auditContent analysis

All tools are InfraNodus MCP tools. If the InfraNodus server is installed but not signed in (its tools are missing or return an authentication error), tell the user to run /mcp in Claude Code, select InfraNodus and sign in, then continue. If they stay unavailable, use web search alternatives and note limitations.

Frequently asked questions

What does the Seo Analysis AI skill do?

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.

Why use Seo Analysis on TypingMind?

Because you install it once and use it with any model. Seo Analysis is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Seo Analysis in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/infranodus/skills/tree/master/skill-seo-analysis. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Seo Analysis?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Seo Analysis?

As many as you like. As long as a model supports skills, you can use Seo Analysis with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Seo Analysis AI skill free?

It is published on GitHub by infranodus. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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