Does this tool execute JavaScript?

No. The Bulk Schema Checker reads server-rendered HTML only. For client-injected JSON-LD, use SSR or a prerender so markup is visible to the tool.

What structured data types are supported?

It reports any Schema.org types found across JSON-LD, Microdata, and RDFa. Rich result eligibility depends on search engine policies.

Why am I seeing JSON-LD parse errors?

Parse errors often come from invalid JSON such as trailing commas, comments, or unescaped characters. Validate and escape strings correctly.

How often should I run a structured data audit?

Run audits at least once per release on SEO-critical templates and schedule monthly checks to catch regressions early.

Bulk Schema (Structured Data) Checker

About the Bulk Schema (Structured Data) Checker

This tool inventories structured data on multiple URLs, including JSON-LD, Microdata, and RDFa. It lists detected types, counts entities, and flags basic issues like parse errors or missing markup.

Detects Schema.org types across JSON-LD, Microdata, RDFa
Counts JSON-LD blocks, entities, and Microdata/RDFa items
Exports full results to CSV
Does not execute JavaScript; checks HTML source only

Tip: Use Google’s Rich Results Test to validate eligibility for rich snippets after you spot issues here.

About the Bulk Schema (Structured Data) Checker

The SEOAegis Bulk Schema Checker scans many URLs at once for JSON-LD, Microdata, and RDFa. It inventories detected Schema.org types, counts entities, and flags basic issues such as missing markup or JSON-LD parse errors—so you can prioritize fixes that unlock richer search features.

What You’ll Get

Type inventory: All unique Schema.org types found per page (e.g., Organization, Article, Product).
Counts: Number of JSON-LD blocks, JSON-LD entities, Microdata items, and RDFa items.
Issue highlights: Quick notes when no structured data is found or JSON-LD fails to parse.
CSV export: One-click download for reporting or handing off to devs.

Common Schema Pitfalls the Tool Surfaces

No structured data on important templates (PLPs, PDPs, blogs, locations).
Multiple conflicting types on the same page (e.g., Article vs. Product).
Invalid JSON (trailing commas, comments) that breaks JSON-LD parsing.
Outdated or non-Schema.org vocabularies used with Microdata/RDFa.

Best Practices for Clean Structured Data

Prefer JSON-LD in the head or body; keep one primary entity per page.
Ensure properties reflect on-page content (name, price, rating, author, dates).
Avoid redundant or conflicting types; nest related entities (e.g., Article → Organization as publisher).
Validate rich result eligibility with Google’s Rich Results Test after bulk checks.
Automate QA on deploys—run this bulk check on key templates regularly.

Pro Tip: If you’re migrating from Microdata or RDFa, deploy JSON-LD in parallel, confirm parity, then remove legacy markup to reduce maintenance.

FAQs

Does this tool execute JavaScript?: No—it inspects the server-rendered HTML. For client-injected JSON-LD, ensure markup is SSR’d or provide a prerender.
What types of structured data are supported?: The scan reports any Schema.org types it finds across JSON-LD, Microdata, and RDFa. Eligibility for rich results depends on Google’s policies.
Why do I see JSON-LD parse errors?: Common causes include trailing commas, comments, or stray HTML entities inside JSON. Validate your JSON and escape strings properly.
How often should I run a bulk schema audit?: At least once per release on templates that affect SEO (product, article, category, location). Schedule monthly checks for safety.