blog-analyze

To audit a blog post, you can use a 5-category 0-100 scoring rubric that evaluates content quality, SEO, E-E-A-T signals, technical elements, and AI citation readiness. This process detects AI-written risk signals like burstiness, flagged phrases, and vocabulary diversity to produce structured reports with prioritized fixes.

Burstiness and vocabulary diversity, measured as Type-Token Ratio (TTR), are metrics used to detect AI-written text. Burstiness evaluates sentence variation, while TTR assesses lexical richness, together flagging AI phrase patterns and low diversity that indicate automated generation.

Yes, you can perform batch directory analysis to audit multiple blog posts simultaneously. The skill supports single-post reviews, URL-based audits, and batch processing, outputting structured reports with category breakdowns and prioritized improvement recommendations.

An E-E-A-T quality audit evaluates blog content by scoring Experience, Expertise, Authoritativeness, and Trustworthiness signals alongside technical and SEO elements. It generates a 0-100 score across five categories, providing critical and high-priority recommendations to improve content readiness.

You can export blog audit reports in Markdown, JSON, or table formats. These optional exports include category breakdowns, citation readiness evaluations, and cognitive-load heatmaps, allowing seamless integration into downstream content pipelines.