Editorial Quality Control: The Pre-Publishing AI Content Verification Checklist

Google's Search Quality Rater Guidelines and AdSense Publisher Policies evaluate content based on E-E-A-T (Experience, Expertise, Authoritativeness, and Trustworthiness). Publishing raw, unedited AI output without human verification frequently leads to factual errors, generic repetition, algorithmic penalties, and AdSense rejection.

This editorial checklist provides a rigorous quality assurance framework to ensure every article published on your website provides original value, accurate citations, and engaging human readability.

The 7-Step Quality Assurance Framework

1. Factual Verification & Citation Audit: Verify all statistics, dates, software version numbers, and research claims against primary sources. Never publish an unverified numerical claim.
2. Original Insight & Experience Injection: Add proprietary case studies, real-world examples, screenshots, or firsthand testing notes that generic AI models cannot replicate.
3. Elimination of AI Clichés: Scan for and remove overused AI phrases such as "In today's fast-paced digital world", "Delve into", "Testament to", "Tapestry", and "Game-changer".
4. Structural Readability: Ensure clear typography hierarchy with descriptive H2 and H3 subheadings, bullet points, callout quotes, and summary tables.
5. Actionable Utility: Every article must solve a tangible problem for the reader and include copy-ready templates or direct step-by-step instructions.
6. Compliance & Policy Review: Confirm full compliance with AdSense guidelines—zero pirated media mentions, no dangerous content, and strict transparency.
7. Metadata & Structured Schema: Ensure valid OpenGraph tags, JSON-LD schema, canonical URLs, and mobile-responsive formatting.