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seo-keyword-strategist

Analyze keyword density, identify entities, and generate LSI keywords for content optimization.

Updated Feb 21, 2026
Search Tags:#keyword research#content optimization#seo#semantic analysis#on-page seo#lsi keywords
One-click install
npx skills add https://github.com/HCMUTE-RTIC/fit-hcmute --skill seo-keyword-strategist-hcmute-rtic
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: seo-keyword-strategist
Source: https://github.com/HCMUTE-RTIC/fit-hcmute/tree/main/.agent/skills/seo-keyword-strategist
Command: npx skills add https://github.com/HCMUTE-RTIC/fit-hcmute --skill seo-keyword-strategist-hcmute-rtic

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps users optimize their content for search engines by analyzing keyword usage, suggesting improvements, and preventing over-optimization.

Core Features & Use Cases

  • Keyword Density Analysis: Calculates the frequency of primary and secondary keywords.
  • LSI Keyword Generation: Suggests semantically related keywords to improve topical relevance.
  • Entity Analysis: Identifies and suggests related entities to build topical authority.
  • Over-optimization Detection: Flags content that may be stuffing keywords unnaturally.
  • Use Case: A content writer can use this Skill to ensure their blog post about "sustainable gardening" naturally incorporates relevant terms like "organic compost," "eco-friendly pest control," and "water conservation techniques," while avoiding excessive repetition of "sustainable gardening."

Quick Start

Analyze the provided article text for keyword density and suggest LSI keywords.

Frequently Asked Questions about seo-keyword-strategist

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I check keyword density and prevent over-optimization in my content?▼

Keyword density analysis calculates the frequency of primary and secondary keywords to prevent over-optimization. It flags content that may be stuffing keywords unnaturally, ensuring your articles maintain natural language patterns for improved search engine rankings.

What are LSI keywords and how do they improve semantic relevance for on-page SEO?▼

LSI keywords are semantically related terms generated to improve topical relevance for on-page SEO. They help content creators naturally incorporate related vocabulary, building semantic relevance without repetitive keyword usage in blog posts and web copy.

How do I identify entities to build topical authority for search engine rankings?▼

Entity analysis identifies and suggests related entities within your article text to build topical authority. By focusing on semantic relevance and natural language patterns, it supports content specialists in refining web copy for better search engine rankings.

Can I use this semantic analysis tool to optimize any type of web copy?▼

Yes, semantic analysis supports content creators and SEO specialists in refining articles, blog posts, and web copy. It analyzes keyword usage and suggests improvements by focusing on semantic relevance and preventing over-optimization across various content formats.

What is the best way to generate related keywords for a blog post about sustainable gardening?▼

The best way to generate related keywords is through LSI keyword generation and entity analysis. This suggests semantically related terms like organic compost or eco-friendly pest control, ensuring natural incorporation while avoiding excessive repetition of primary keywords.

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