How to Audit WordPress Structured Data with AI

Structured data is easy to generate and easy to misrepresent. An AI audit can parse JSON-LD, group recurring defects and compare markup with visible content. It cannot guarantee a rich result, and it must not recommend unsupported types simply because schema.org contains them.

SEO analysis is only as reliable as the supplied evidence. A language model does not independently know crawl status, indexation, rankings, canonical selection or page performance. Treat it as an evidence organizer and hypothesis generator, then verify every finding in the appropriate source system.

In one sentence: Audit the rendered markup against the visible page and the current Google feature documentation, then separate syntax, eligibility and content-consistency findings.

What this guide helps you accomplish

The result should identify which structured-data entities appear on each template, whether required and recommended properties are present, whether values match visible content and which findings are Google-specific versus general schema.org observations.

A useful result is not merely a polished answer. It must show which records or pages were examined, which evidence was unavailable, what the assistant inferred, what a human must decide and what actions remain prohibited.

What a successful output should contain

• Page- and template-level inventory of JSON-LD, Microdata or RDFa entities.
• Syntax and parsing findings.
• Google feature eligibility findings tied to current documentation.
• Visible-content mismatches and misleading markup risks.
• Duplicate or conflicting entity declarations.
• Prioritized remediation and test plan without appearance guarantees.

Evidence and inputs to prepare

Plugin settings do not prove what users and crawlers receive. Capture the final rendered markup and the visible page content it describes.

• Rendered HTML for representative pages and templates.
• Extracted structured-data blocks with page URLs.
• Rich Results Test or other validator results, dated.
• Visible names, prices, availability, dates, authors and other represented values.
• Current Google documentation for the intended feature.
• Schema.org validation when non-Google vocabulary is relevant.
• Template and plugin ownership information.

Record the date, source, scope and known omissions for every input. Remove credentials, personal information and customer data that are not required for the task.

Separate three kinds of validity

A block can be valid JSON but invalid schema. It can be valid schema but ineligible for a Google feature. It can be eligible in principle but misleading because it does not match visible content. Report these as separate dimensions.

Do not resurrect removed features

Google’s documentation changes. For example, FAQ rich results stopped appearing in May 2026 and the FAQ documentation was removed in June 2026. Revalidate every feature at implementation time instead of copying an old checklist.

A safe workflow

1. Select representative pages by template and content type.
2. Capture final HTML and visible content.
3. Extract all structured-data blocks and entity IDs.
4. Run current validators and retain raw results.
5. Ask the assistant to separate syntax, vocabulary, eligibility and consistency findings.
6. Trace recurring defects to template or plugin ownership.
7. Review misleading or business-critical values with owners.
8. Prepare template-level fixes and page exceptions.
9. Deploy to a test environment and rerun validation.

The workflow intentionally separates analysis from implementation. A later change stage should reference the approved output rather than quietly expanding the permissions of the analytical identity.

Prompt recipe

Before using this prompt, replace every value in square brackets. Do not paste passwords, API keys, private customer records or unrelated personal information into the instruction.

Audit the supplied rendered structured data and visible WordPress page content.

For each page or template, return:
- URL and template
- Structured-data format and entity types
- Syntax status
- Invalid or missing properties
- Intended Google feature and current documentation source
- Eligibility status: eligible, ineligible, not applicable, or unclear
- Visible-content mismatch
- Duplicate or conflicting entities
- Severity, confidence and likely owner
- Recommended validation step

Rules:
1. Do not promise rich-result appearance.
2. Do not recommend a Google feature absent from current documentation.
3. Do not mark up content that is hidden or absent from the page.
4. Distinguish schema.org validity from Google eligibility.
5. Do not modify WordPress or plugin settings.

Why this prompt is structured this way

The multi-dimensional status prevents a generic valid/invalid label from hiding the real issue. Current feature documentation is required for every eligibility claim.

Recommended access boundary

Use a Read Only identity. The assistant may inspect the WordPress records included in scope, but attempts to create, edit, delete or publish content should be refused.

The workflow can affect public meaning, search interpretation, conversion or product information. Require explicit review before any change is applied.

What must remain outside this task

• No rich-result guarantee.
• No generated markup for content not visible on the page.
• No reliance on plugin settings as rendered evidence.
• No assumption that all schema.org types are Google features.
• No production changes during the audit.

The access level is a starting recommendation, not a universal entitlement. The exact capabilities available to an identity must come from the installed product version and its published coverage.

How WP Agent Control fits

This is a general WordPress workflow, not a promise that Agent Control can edit every object or integration discussed here. For the guided path, start with public pages; plugin, theme, user, setting, file, deletion, WooCommerce, ACF and builder operations are not native guided tasks. Use separately qualified tools and permissions where required.

Get structured site information and inspect selected published pages after connecting. No temporary task is needed for this public reading. You can also browse public pages without the plugin; Agent Control adds structured access and a path toward authorized WordPress work.

Connect your AI: docs first profile · See features and compatibility: coverage

Verification checklist

• ☐ Rendered markup and visible content were captured together.
• ☐ Findings distinguish syntax, vocabulary, eligibility and consistency.
• ☐ Every Google feature links to current documentation.
• ☐ Template-level defects are not duplicated into hundreds of tickets.
• ☐ No appearance guarantee is made.
• ☐ No WordPress setting or markup changed.

Common failure modes

• Settings audit: Configured schema is assumed to be rendered correctly.
• Validity collapse: Syntax, schema vocabulary and Google eligibility are treated as one state.
• Hidden-content markup: Structured data describes facts users cannot see.
• Feature necromancy: Removed or obsolete rich-result tactics remain in the recommendation.

Advanced note

Maintain a template-to-entity contract with required visible fields and test fixtures. Build-time or deployment tests can then detect markup drift before an editorial audit is needed.

Related guides

• How to Run a Read-Only WordPress SEO Audit with AI
• How to Create a WordPress URL Inventory with AI
• How to Create Evidence-Based WordPress FAQs with AI
• How to Rewrite a WordPress Page with AI Without Publishing It

Next step

Use the URL inventory to sample templates and place approved fixes into a separate implementation brief rather than editing from the audit identity.