How it works
- Enter the page URL you want to analyze and the target topic or keyword it should cover (for example
keyword research). - The tool queries live Google autocomplete around your keyword to build the expected semantic field — related terms, questions and subtopics real users search for.
- It fetches your page and checks which of those concepts and terms actually appear in the content.
- It calculates a coverage percentage and splits the field into what you already cover and what is missing.
- You get a covered-vs-missing donut plus a chip list of the exact concepts to add next.
What it checks
- Coverage percentage — the share of the expected semantic field your page actually addresses.
- Related terms — the supporting vocabulary Google associates with your topic via autocomplete.
- Questions — the real questions users ask around the keyword, and whether your page answers them.
- Subtopics — the adjacent themes that a complete piece on the topic is expected to touch.
- Covered concepts — the terms and subtopics your content already handles well.
- Missing concepts — a ranked chip list of the gaps to fill to reach topical completeness.
Why it matters
AI and modern search reward topical completeness, not keyword repetition. When a page covers the full cluster of related subtopics and questions around a theme, it signals genuine depth — the kind of source an AI Overview quotes and Google treats as authoritative. A page that hammers the head keyword but ignores the surrounding semantic field looks shallow by comparison, and it loses ground to competitors who answer the whole question set. Measuring coverage against the live semantic field tells you exactly how complete your content really is.
How to improve your score
Work through the missing-concepts chips the tool returns. Add sections that address the related terms, questions and subtopics your page currently skips — a heading and a concise answer for each is enough to register coverage. Fold the vocabulary in naturally rather than stuffing keywords, and prioritize the questions users actually search for. Once you have expanded the page, re-run the analyzer to watch the coverage percentage rise and confirm the donut shifts from missing to covered.
Frequently asked questions
Where does the expected semantic field come from?
The tool builds it from live Google autocomplete around your target keyword — the related terms, questions and subtopics real users are searching for right now. That keeps the expected field grounded in actual demand rather than a static word list.
Do I have to include every missing concept?
No. The chip list is ranked so you can prioritize the most relevant gaps. Add the concepts that genuinely fit your page's intent and audience; forcing in unrelated terms won't help and can dilute your focus.
Why do I need both a URL and a topic?
The topic tells the tool which semantic field to build from autocomplete, and the URL is the page it measures against that field. Without both, it can't compare your actual coverage to what a complete piece on the topic should include.