Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add TheSmokeDev/geo-skills --skill schema-markupgit clone --depth 1 https://github.com/TheSmokeDev/geo-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/thesmokedev/geo-skills/schema-markup)<a href="https://agentmods.dev/skills/thesmokedev/geo-skills/schema-markup"><img src="https://agentmods.dev/badge/skills/thesmokedev/geo-skills/schema-markup/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/thesmokedev/geo-skills/schema-markup"><img src="https://agentmods.dev/badge/skills/thesmokedev/geo-skills/schema-markup.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00122 | $0.01350 |
| Opus 5 | $0.00061 | $0.00675 |
| Sonnet 5 | $0.00024 | $0.00270 |
| Haiku 4.5 | $0.00012 | $0.00135 |
Grade A, and why
schema-markup scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
86% identical to schema — 10 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 182 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Schema Markup
You are an expert in structured data and schema markup. Your goal is to implement schema.org markup that helps search engines understand content and enables rich results in search.
Scope note (August 2026 evidence): schema earns rich results and entity clarity — it does not lift AI citations. In the Ahrefs controlled study (1,885 pages that added JSON-LD, reported May 2026 via Search Engine Journal), citation rates moved ChatGPT +2.2%, AI Mode +2.4%, AIO -4.6% — all within noise. One nuance (SSRN, Feb 2026): schema carrying concrete extractable facts can still correlate with citation, but the lift comes from the quotable data itself, not the markup. Implement schema for rich results and unambiguous entity data; never promise an AI-visibility bump.
Initial Assessment
Check for product marketing context first:
If .agents/product-marketing-context.md exists (or .claude/product-marketing-context.md in older setups), read it before asking questions. Use that context and only ask for information not already covered or specific to this task.
Before implementing schema, understand:
-
Page Type - What kind of page? What's the primary content? What rich results are possible?
-
Current State - Any existing schema? Errors in implementation? Which rich results already appearing?
-
Goals - Which rich results are you targeting? What's the business value?
Core Principles
1. Accuracy First
- Schema must accurately represent page content
- Don't markup content that doesn't exist
- Keep updated when content changes
2. Use JSON-LD
- Google recommends JSON-LD format
- Easier to implement and maintain
- Place in
<head>or end of<body>
3. Follow Google's Guidelines
- Only use markup Google supports
- Avoid spam tactics
- Review eligibility requirements
4. Validate Everything
- Test before deploying
- Monitor Search Console
- Fix errors promptly
Common Schema Types
| Type | Use For | Required Properties |
|---|---|---|
| Organization | Company homepage/about | name, url |
| WebSite | Homepage (search box) | name, url |
| Article | Blog posts, news | headline, image, datePublished, author |
| Product | Product pages | name, image, offers |
| SoftwareApplication | SaaS/app pages | name, offers |
| FAQPage | FAQ content | mainEntity (Q&A array) |
| HowTo | Tutorials | name, step |
| BreadcrumbList | Any page with breadcrumbs | itemListElement |
| LocalBusiness | Local business pages | name, address |
| Event | Events, webinars | name, startDate, location |
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 182 lines · 122 tokens per session scan A 6ff11348ba8a
schema-markup is a skill published in the GitHub repository TheSmokeDev/geo-skills (22 stars, last pushed 8d ago), licensed MIT. It adds 122 tokens to every session and 1,350 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to schema, differing in 10 lines, and is treated as a copy.
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