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seo-content

Automate SEO and content analytics with Python scripts for keyword and performance reporting.

1|Updated Mar 19, 2026
Search Tags:#analytics#content#seo#gsc#report-generation#decay-detection#keyword-tracking
One-click install
npx skills add https://github.com/weisberg/agile_agentic_analytics --skill seo-content-weisberg
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: seo-content
Source: https://github.com/weisberg/agile_agentic_analytics/tree/main/plugins/marketing-analytics/skills/seo-content
Command: npx skills add https://github.com/weisberg/agile_agentic_analytics --skill seo-content-weisberg

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, numpy, scipy, requests, google-auth, google-api-python-client, and includes scripts (resource) and references (resource) components.

What problem does it solve?

SEO and content performance tracking can be manual and siloed. This Skill automates data collection, analysis, and reporting to accelerate optimization.

Core Features & Use Cases

  • Google Search Console data extraction, keyword tracking, and content performance clustering.
  • Technical SEO audits (CWV, structured data validation, crawl health) with automated reporting.
  • AI-enabled visibility tracking (GEO) and competitive keyword gap analysis across organic search.

Quick Start

Run the seo-content pipeline on your workspace data to generate the content performance report.

Frequently Asked Questions about seo-content

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

FAQPage Schema
How do I automate Google Search Console data extraction and keyword tracking?▼

You can automate Google Search Console data extraction and keyword tracking using Python scripts that leverage the google-api-python-client to pull query data, cluster content performance, and generate automated reporting workflows.

What is content decay detection and how does it work for SEO?▼

Content decay detection identifies pages losing organic search traffic and keyword rankings over time. It works by analyzing historical Google Search Console data to score underperforming content and flag drops in freshness.

Can I track AI search visibility and perform competitive keyword gap analysis with Python?▼

Yes, you can track AI search visibility (GEO) and perform competitive keyword gap analysis by running end-to-end Python scripts that process content inventories and compare organic search keyword profiles.

Does this SEO analytics approach require pandas and scipy dependencies?▼

Yes, this SEO analytics approach requires pandas, numpy, and scipy dependencies to execute data extraction, calculate decay detection metrics, score content underperformers, and generate analytical reports.

What's the best way to score content freshness for technical SEO audits?▼

The best way to score content freshness for technical SEO audits is to apply automated Python scripts that evaluate historical performance metrics, detect keyword ranking decay, and validate structured data alongside crawl health.

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