Most on-page audits catch the obvious stuff: a missing title here, a duplicate meta description there. The thing that quietly costs you rich results is structured data that exists but is invalid, and most flat-list crawlers either skip it or bury it. Here is why it happens and how to catch it.

The problem, concretely

You add FAQ schema to a product page to win that expandable rich result in Google. You paste a JSON-LD block into the head, ship it, and move on. Six weeks later the rich result never showed up, and nobody knows why.

The usual culprits are small and silent:

• A @type that does not match the content (FAQPage with no mainEntity).
• A required property missing (acceptedAnswer without text).
• A trailing comma or a stray character that makes the JSON parse fail entirely.
• Schema that contradicts what is actually on the page, which Google can flag as spammy and ignore.

None of these throw a visible error. The page renders fine. The schema is just dead weight, and a standard "issues" crawl that only counts titles and headings walks right past it.

How to catch it

First, validate the JSON itself. A block that does not parse is invisible to search engines. Even a quick local check surfaces the dumb-but-fatal errors:

// Pull every JSON-LD block and check it parses + has a @type
const blocks = [...document.querySelectorAll(
  'script[type="application/ld+json"]'
)];

blocks.forEach((b, i) => {
  try {
    const data = JSON.parse(b.textContent);
    if (!data["@type"]) console.warn(`Block ${i}: missing @type`);
  } catch (e) {
    console.error(`Block ${i}: invalid JSON ->`, e.message);
  }
});

If that logs an error, the schema was never going to work, no matter how perfect the markup looked.

Second, check required properties for the specific type you are using. FAQPage needs mainEntity with Question items, each carrying an acceptedAnswer. Article needs headline, author, and datePublished. Validating "it parsed" is not the same as "it is complete."

Third, and this is the step people skip: do it across the whole site, not just the one page you remember adding schema to. Templates drift. A change to one component can break structured data on a thousand URLs at once, and you will never notice from a single spot check.

A repeatable checklist

When you audit a page or a site, run structured data through the same gate every time:

1. Does every JSON-LD block parse as valid JSON?
2. Does each block have a @type that matches the page content?
3. Are the required properties for that type present?
4. Does the schema agree with the visible content (no invented reviews, no fake ratings)?
5. Is it consistent across templated pages, not just the homepage?

Bake that into your audit and you stop shipping silently-dead schema.

Doing it without a spreadsheet

You can do all of this by hand, and the snippet above is a fine start for a single page. But across a site, manually opening dev tools on every URL gets old fast, and a heavyweight desktop crawler is more setup than the job needs when you just want a quick read.

This is the gap SEOScope fills. You paste a URL, it crawls the page or site, validates the structured data alongside the rest of the on-page checks, flags broken links and page weight, and returns one score with the fixes ranked by impact, so invalid schema shows up at the top instead of buried in row 240. It runs in the browser with nothing to install, and there is a free tier to point at a page and see what it flags.

Validate your schema before search engines silently decide to ignore it. That one habit catches more lost rich results than any other on-page check.

Full disclosure: I build SEOScope, an on-page SEO auditor that validates structured data, finds broken links and scores your pages. It is free to try at https://seoscope.dev.