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seo-analysis

Audit codebases for SEO issues and generate fix prompts.

37|2|Updated Mar 25, 2026
Search Tags:#SEO#codebase#audit#search engine optimization#fix prompt
One-click install
npx skills add https://github.com/jpcaparas/skills --skill seo-analysis-jpcaparas
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: seo-analysis
Source: https://github.com/jpcaparas/skills/tree/main/skills/seo-analysis
Command: npx skills add https://github.com/jpcaparas/skills --skill seo-analysis-jpcaparas

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires python3, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill automates SEO audits on codebases, identifying issues and generating prompts for remediation.

Core Features & Use Cases

  • SEO Audit: Inspects codebases for SEO-related issues such as metadata, rendering, crawlability, canonicalization, structured data, and content quality.
  • Fix Prompt Generation: Produces detailed prompts for another session to implement fixes based on audit findings.
  • Use Case: If you have a codebase and want to ensure it's optimized for search engines, this Skill can analyze it and provide you with a specific set of instructions to improve its SEO.

Quick Start

Run the SEO Analysis Skill on your codebase with the command 'seo-analysis run-audit'.

Frequently Asked Questions about seo-analysis

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

FAQPage Schema
How do I perform an SEO audit on my codebase to find metadata and rendering issues?▼

To perform an SEO audit on your codebase, run a script that inspects metadata, rendering, canonicalization, and structured data. This process identifies search engine optimization issues and generates fix prompts for remediation.

What is a codebase SEO audit and how does it check AI-era search readiness?▼

A codebase SEO audit analyzes source code to evaluate search engine optimization factors like crawlability, content quality, and AI-era search readiness. It systematically reviews structured data and metadata to pinpoint issues blocking search visibility.

Do I need Python 3 to run a codebase SEO audit and generate fix prompts?▼

Yes, you need Python 3 installed to run the codebase SEO audit. The audit optionally benefits from command-line repository access, build tooling, and browser or HTTP tools to verify rendering and crawlability during the analysis.

How do I generate fix prompts for SEO issues found in my source code?▼

You generate fix prompts for SEO issues by running an automated audit that analyzes your codebase. The audit produces detailed instructions for a subsequent session to implement fixes for identified metadata and structured data problems.

Can I use this SEO audit approach for large codebases with complex rendering requirements?▼

Yes, you can audit large codebases with complex rendering by providing command-line repository access and build tooling. The audit evaluates rendering and canonicalization issues, but requires browser or HTTP tooling for complete verification.

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