AI Reviewer Template: Knowledge Base Article Reviewer

A reviewer designed for customer support and documentation teams who need knowledge base articles that actually solve customer problems and reduce support ticket volume. This template evaluates help content against self-service best practices including article findability through title and keyword optimisation, step-by-step accuracy, visual aid effectiveness, troubleshooting completeness, and measurable deflection potential. The goal is content that resolves customer issues without human intervention. The reviewer flags common knowledge base problems like titles that do not match how customers describe their problems, procedures with missing steps, screenshots that are outdated or unclear, articles that assume knowledge customers do not have, and content that ultimately directs users to contact support rather than solving their problem. It also evaluates whether articles are structured for both sequential reading and scanning, with clear headings and jump links. Whether you are building an internal wiki, customer-facing help centre, or product documentation portal, this reviewer helps create content that genuinely reduces support burden.