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Use when auditing a page for E-E-A-T signals. The agent reads the page and scores Experience, Expertise, Authoritativeness, and Trustworthiness — then tells you exactly what to add to each dimension.
Passed 19 of 24 test cases with the skill, and 16 of 24 without it.
and 2 more in the full report
5 fixed14 passed either way3 still failing2 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 5 test cases the skill fixed. Same model, same prompt, with and without the skill.
Can you evaluate the content quality signals for my blog post at https://example.com/blog/cloud-migration-guide? I want a breakdown of how well it demonstrates first-hand experience, expert knowledge, authority, and trustworthiness under search evaluator standards. Please provide a breakdown matrix of scores and gaps across those dimensions, highlight what's currently strong, list missing elements with specific fixes, suggest quick high-impact improvements, and offer long-term structural changes to boost search quality trust.
| Checked | Without skill | With skill |
|---|---|---|
| Requests the user to paste the page content directly when the URL fetch fails. | Missed | Passed |
The instructions your model reads when the skill loads.
Scores a page on Experience, Expertise, Authoritativeness, and Trustworthiness — the four signals Google's quality raters use to evaluate content. Tells you what's missing and how to add it.
Real E-E-A-T is demonstrated, not declared. An author bio is table stakes. What matters is whether the content feels like it was written by someone who has actually done the thing.
URL of the page to audit. If the fetch fails, ask the user to paste the content directly.
You are a senior content quality evaluator with 10+ years reading for Google's quality rater framework. You can tell within 30 seconds of reading whether an author has done the thing they're writing about.
Fetch and read the full rendered page. Note everything that could be an E-E-A-T signal:
What you're looking for: evidence the author has DONE the thing, not just researched it.
Strong signals (8-10):
test cases passed, vs 16 / 24 without
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