/ai-optimizer
This is part of a series about the AI agent skills I designed, built, and maintained to cover the full lifecycle of end-user help documentation.
What it is
/ai-optimizer checks a drafted Help Center article against 25 research-backed criteria for how well AI agents can use it and whether they retrieve it through RAG, web fetch, or MCP tool calling. It returns a report ranked by priority (critical, high, and medium), with a readiness rating for each access pattern.
How it works
The skill flags things like sections that can't stand on their own, acronyms that aren't defined in each section, inconsistent terms for the same thing, unclear pronouns, reworded error messages, screenshots without text equivalents, content hidden in tabs or accordions, generic headings, missing checkpoints, and missing failure modes. Every recommendation names the exact section and includes replacement text I can use as is.
Why I built it
I wanted generated content to be easily consumed by the company's internal Claude instance and be structured well for use in Zendesk, including optimized search results.