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 CraftOS-dev/CraftBot --skill schema-markupgit clone --depth 1 https://github.com/CraftOS-dev/CraftBotWrote 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/craftos-dev/craftbot/schema-markup)<a href="https://agentmods.dev/skills/craftos-dev/craftbot/schema-markup"><img src="https://agentmods.dev/badge/skills/craftos-dev/craftbot/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/craftos-dev/craftbot/schema-markup"><img src="https://agentmods.dev/badge/skills/craftos-dev/craftbot/schema-markup.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Output Handling · line 542 Model output is used without validation or sanitization. Unvalidated output injected into downstream contexts (SQL, shell, HTML) enables injection attacks and arbitrary code execution.Fix: Validate and sanitize all model output before using it in downstream contexts. Use parameterized queries for SQL, shell quoting for commands, and HTML encoding for web output.
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 | $0.00078 | $0.03475 |
| Opus 5.5 | $0.00031 | $0.01390 |
| Sonnet 5.5 | $0.00016 | $0.00695 |
| Haiku 4.5 | $0.00008 | $0.00347 |
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 1mo 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.
Copies of this mod
4 near-identical copies found in the catalogue:
- schema-markup — 100% identical, 0 lines differ
- schema-markup — 100% identical, 0 lines differ
- schema-markup — 98% identical, 3 lines differ
- tool-schema-markup — 97% identical, 8 lines differ
How it starts
The opening of the file, as written. The whole thing — 597 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.
Initial Assessment
Before implementing schema, understand:
-
Page Type
- What kind of page is this?
- What's the primary content?
- What rich results are possible?
-
Current State
- Any existing schema?
- Errors in current implementation?
- Which rich results are 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
Organization
Use for: Company/brand homepage or about page
Required properties:
- name
- url
Recommended properties:
- logo
- sameAs (social profiles)
- contactPoint
{
"@context": "https://schema.org",
"@type": "Organization",
"name": "Example Company",
"url": "https://example.com",
"logo": "https://example.com/logo.png",
"sameAs": [
"https://twitter.com/example",
"https://linkedin.com/company/example",
"https://facebook.com/example"
],
"contactPoint": {
"@type": "ContactPoint",
"telephone": "+1-555-555-5555",
"contactType": "customer service"
}
}
WebSite (with SearchAction)
Use for: Homepage, enables sitelinks search box
Required properties:
- name
- url
For search box:
- potentialAction with SearchAction
{
"@context": "https://schema.org",
"@type": "WebSite",
"name": "Example",
"url": "https://example.com",
"potentialAction": {
"@type": "SearchAction",
"target": {
"@type": "EntryPoint",
"urlTemplate": "https://example.com/search?q={search_term_string}"
},
"query-input": "required name=search_term_string"
}
}
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.
- 1mo ago First seen · 597 lines · 78 tokens per session scan A b43f80e20747
schema-markup is a skill published in the GitHub repository CraftOS-dev/CraftBot (400 stars, last pushed today), licensed MIT. It adds 78 tokens to every session and 3,475 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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