Tool
What the Article Schema Generator does
Article Schema Generator: generates JSON-LD only from Headline, Author name and Publisher. Example: headline How to Choose a Mortgage in 2026, author name Jane Doe and publisher Example Media gives JSON-LD only { "@context": "https://schema.org", "@type": "Article", "headline": "How to Choose a Mortgage in 2026"….
JSON-LD only, derived from Headline, Author name, Publisher and Image URL. You can nudge a single number and watch the effect straight away.
Most people who open the Article Schema Generator are people publishing a page. Small on-page details decide whether a listing gets clicked or scrolled past.
There is no back end here. The calculation runs where you are sitting, not on a server somewhere.
If you want to check the arithmetic, the field table, the method and a worked example are further down.
What do the Article Schema Generator fields mean?
The Article Schema Generator uses 6 inputs. You do not have to fill everything in before seeing an answer; the starting values already produce one.
| Field | What to enter | Default |
|---|---|---|
| Headline | required | How to Choose a Mortgage in 2026 |
| Author name | required | Jane Doe |
| Publisher | required | Example Media |
| Image URL | required | https://example.com/article.jpg |
| Published (YYYY-MM-DD) | required | 2026-08-01 |
| Article URL | required | https://example.com/blog/choose-a-mortgage |
How does the Article Schema Generator work?
Each output is derived from the inputs above in a single pass; there is no hidden state carried between runs, so the same inputs always give the same generated output.
Values are checked first: an out-of-range or non-numeric entry names the offending field instead of returning nonsense.
Worked example
These are the values the Article Schema Generator loads by default, and the result it produces from them. This is the worked example the page starts from, reproduced here so you can check the arithmetic.
| Headline | How to Choose a Mortgage in 2026 |
|---|---|
| Author name | Jane Doe |
| Publisher | Example Media |
| Image URL | https://example.com/article.jpg |
| Published (YYYY-MM-DD) | 2026-08-01 |
| Article URL | https://example.com/blog/choose-a-mortgage |
| JSON-LD only | { "@context": "https://schema.org", "@type": "Article", "headline": "How to Choose a Mortgage in 2026"… |
|---|
What Google actually uses versus what Article schema allows
Google does not document a strict list of required Article properties, but headline, image, author and datePublished are the fields that consistently affect whether (and how) an article is treated differently in search.
Worth knowing
- A headline over roughly 110 characters risks being truncated in the interfaces that display it. Keep it closer to a normal title length than a full sentence.
- Google recommends images at least 1200px wide for the largest visual treatments, with a minimum of 696px. An image below that threshold may still validate while being excluded from the biggest visual formats.
- A missing or generic author, a shared "Admin" or "Staff" account rather than a named person or clearly identified organization, is a known weak point for the author-attribution and expertise signals Google has emphasised more heavily since its content-quality updates. That is a content-quality concern the schema can only report accurately, not fix.
- dateModified should reflect a genuine, substantive update. Google has warned against changing the date on unmodified content purely to appear fresh: the same trust concern that applies to sitemap lastmod dates.
How to use it
- Fill in Headline.
- Type Author name.
- Enter Publisher.
- Set Image URL.
- Put Published (YYYY-MM-DD).
- Key in Article URL.
- Type a value and the answer is already there by the time you stop.
- The panel reports JSON-LD only.
- Copy Link puts the current inputs in the URL, so bookmarking it brings the same numbers back.
What this tool does not do
- Search engines weigh hundreds of signals. No single on-page check predicts position.
- This inspects the markup you supply; it cannot see server headers or your live rankings.
- It cannot detect a typo that happens to fall inside the valid range.
Frequently asked questions
You need Headline, Author name, Publisher, Image URL, Published (YYYY-MM-DD) and Article URL. Every box already holds a working value, meaning you can explore the calculation before committing to real figures.
With the values loaded when the page opens, JSON-LD only comes out as { "@context": "https://schema.org", "@type": "Article", "headline": "How to Choose a Mortgage in 2026"…. The figure is derived from the inputs above, so it updates whenever they do.
No. The markup you paste is analysed locally, so unpublished pages stay unpublished.
No. There is no account, no usage cap and no trial period. The site is funded by advertising rather than by charging for the tools.
The generated output is exact for the method described above. Where a value is rounded for display, the underlying figure keeps full precision.