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 kostja94/marketing-skills --skill schemagit clone --depth 1 https://github.com/kostja94/marketing-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/kostja94/marketing-skills/schema)<a href="https://agentmods.dev/skills/kostja94/marketing-skills/schema"><img src="https://agentmods.dev/badge/skills/kostja94/marketing-skills/schema/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/kostja94/marketing-skills/schema"><img src="https://agentmods.dev/badge/skills/kostja94/marketing-skills/schema.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00181 | $0.04788 |
| Opus 5 | $0.00090 | $0.02394 |
| Sonnet 5 | $0.00036 | $0.00958 |
| Haiku 4.5 | $0.00018 | $0.00479 |
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 7d 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
2 near-identical copies found in the catalogue:
- schema-markup — 100% identical, 0 lines differ
- schema-markup — 98% identical, 18 lines differ
How it starts
The opening of the file, as written. The whole thing — 321 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SEO On-Page: Schema / Structured Data
Guides implementation of Schema.org structured data (JSON-LD) for rich snippets, enhanced search results, and Generative Engine Optimization (GEO).
When invoking: On first use, if helpful, open with 1–2 sentences on what this skill covers and why it matters, then provide the main output. On subsequent use or when the user asks to skip, go directly to the main output.
Scope (On-Page SEO)
- Schema markup: Schema.org types for rich results, AI search visibility, and machine-readable content
- Schema.org vs. search engines: Schema.org defines 800+ types; each search engine supports only a subset for rich results
Schema.org vs. Search Engine Support
Schema.org and Google Structured Data are not fully aligned. Schema.org is an open vocabulary (800+ types); Google, Bing, and other engines each support only a curated subset for rich results.
| Engine | Support | Notes |
|---|---|---|
| Subset only | Only types in Google's search gallery generate rich results. Valid Schema.org markup not in Google's list won't produce enhanced snippets—even if technically correct. | |
| Bing | Subset; different | Supports JSON-LD, Microdata, RDFa, Open Graph. Some types (e.g., Product, Offer) have format-specific support. Check Bing Webmaster docs. |
| Other engines | Varies | Yandex, DuckDuckGo, AI search tools (Perplexity, etc.) may use Schema.org for understanding even when they don't display rich results. |
Practical implication: Implement Schema.org markup for your content type. If Google doesn't show rich results for that type, Bing or AI systems may still use it. Always verify against Google's developer docs for Google-specific rich result eligibility.
Rich Results: Google Support (2026)
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.
- 7d ago First seen · 321 lines · 181 tokens per session scan A 78262fdc41f5
schema-markup is a skill published in the GitHub repository kostja94/marketing-skills (963 stars, last pushed 3mo ago), licensed MIT. It adds 181 tokens to every session and 4,788 once invoked, about $0.0009 per session on Opus 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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