This is an example of an agent you can build with Sylvie: point it at a draft, a URL or a whole content library and it grades how ready each piece is to be pulled into and cited by AI answer engines like AI Overviews, ChatGPT and Perplexity, then hands back the score with the exact fixes that raise it. It runs on your brand brain, so it checks the facts an engine would extract against what is actually true for your product, and judges every page against your priority topics and the way you should be named. Sylvie does not ship it pre-built; your team assembles it on the brain you already own.
Sylvie does not ship this agent pre-built. It is an example of an agent your team can build with Sylvie, powered by your brand brain, so it runs your workflow the way you actually run it.
The AI Readiness Score agent is an example of what a marketing team can build on Sylvie: a diagnostic that puts a number on how likely a given piece of content is to be surfaced and quoted in an AI answer, and returns the prioritized changes that move that number up. It is not a one-off audit you commission and file away; it is an agent your team runs on demand, wired to the one brain that knows what this brand sells and how it needs to show up.
Search is collapsing into a single generated answer, and that answer is assembled from content the engine can parse, trust and cite. Most teams have no way to tell whether a page clears that bar until they notice they are missing from the answer entirely. An agent built on your brand brain turns that guesswork into a score: it reads a page the way an answer engine would, checks the structure, the coverage and the facts, and tells you precisely what to change so the next crawl can lift you into the response.
Before it grades anything, the agent reads the brand brain: your priority topics and the questions buyers actually ask, the product facts an engine might extract so it can check them for accuracy, and the positioning and entities that define how you should be named in an answer. Because the brain is permission-aware, it scores only against what this brand is cleared to use, and one client's topics or facts never leak into another's report.
Then it runs the scoring end to end inside Sylvie: it examines how the content is structured for extraction, whether it answers the target questions directly, how completely it covers the topic, how current and citable its sources are, and whether the facts match your brain, then returns a score with a ranked list of fixes. You act on them in the same place, and because the agent lives next to your other agents, the same brain that found the gap can feed the one that rewrites the page, so you re-score and watch the number climb.
AI readiness stops being a vague worry and becomes a number you can put on a page, so 'is this good enough for AI search?' has an answer before you publish.
Every score comes back with the specific changes that raise it, ordered by what they are worth, so your team works the edits that lift you into the answer instead of a flat best-practice checklist.
It reads the facts an engine would extract and checks them against what is actually true for your product, so a page never scores well while quietly stating something outdated or wrong.
Run a draft through the score before it goes live, so content is built to be citable from day one rather than audited and patched months after it stops getting pulled.
Re-run the score after every fix and watch it climb, so AI readiness becomes a metric you report on quarterly rather than a one-time audit you file and forget.
Because it runs on the brand brain, each page is scored against your topics, your positioning and how you should be named, so the grade reflects how this brand needs to show up, not a generic ideal.
A few of the jobs a team builds this agent to handle, each page graded against your brand brain rather than a generic rulebook. The outcome is the same every time: you can see the number, see exactly what is holding a page back, and fix it before it costs you the AI answer.
A writer finishes a page destined to own a key buying question. The agent scores the draft and lists what is missing before it goes live, so the page ships already built to be quoted instead of getting patched months later once you notice it never surfaces.
You have hundreds of older pages and no idea which ones are dragging you down in AI search. The agent scores them all and sorts by readiness, so your team fixes the high-value, low-score pages first instead of guessing where to start.
One of your most important articles never shows up in a generated answer and no one can say why. The agent grades it and pinpoints the structural and coverage gaps, so you ship targeted fixes and start appearing in the response within a refresh cycle.
A junior writer does not yet know what AI engines reward. Running their drafts through the score turns every submission into a lesson with a number attached, so the whole team's content clears the AI bar without a senior editor reviewing each one by hand.
A site migration or redesign quietly changed your markup and structure. Re-scoring the key pages afterward catches any drop in extractability, so a design refresh does not silently knock you out of answers you already won.
Your CMO wants to know if the content investment is paying off in AI search. A recurring readiness score across your priority pages gives the review a hard before-and-after, so the conversation is about a trend line rather than a gut feeling.
A traditional audit grades you for ranking in a list of blue links; this grades how ready a page is for the AI answer that increasingly sits above them, checking extractability, direct question-answering and factual coverage rather than keyword density and backlinks. Because you build it on your brand brain, it also verifies the facts an engine would pull against what is true for your product, so the score reflects both AI readiness and accuracy.
You build it. Sylvie does not ship a finished AI Readiness Score agent; this page is an example of what a team assembles on the platform. Sylvie helps you wire it to your brand brain, your priority topics and your real product facts, so the score measures the pages and questions you actually care about.
You build it around the signals AI answer engines reward: how the content is structured for extraction, whether it answers your target questions directly, how completely it covers the topic, how current and citable its sources are, and whether the facts line up with your brain. Because it runs on your positioning, a high score means the page is ready to represent this brand correctly, not just formatted to a generic standard.
Before scoring, it reads the parts of the brain that define how you should show up: priority topics, the questions your buyers ask, product facts it can check for accuracy, and the entities and positioning that say how you should be named. It is permission-aware, so it scores only against what this brand is cleared to use, and nothing crosses over from another account.
It returns ranked fixes with each score, and because you build it alongside your other agents in Sylvie, the same brain that flagged the gap can feed the agent that rewrites the page. You close the loop in one place and re-score to confirm the number actually moved.
Every brand brain is isolated and permission-aware, so one client's topics, facts and scored pages never appear in another's report, and each person sees only what they are cleared to. The agent grades on top of your brain inside Sylvie; your brand knowledge stays yours and is never pooled into a shared model.
Book a demo and we will map the workflows worth turning into agents, and show how each one runs on your brand brain.
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