Borrowing it
Nothing to install: this file belongs to textura-agency/ai-design-vault. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/textura-agency/ai-design-vault/main/.claude/skills/schema-markup/SKILL.mdgit clone --depth 1 https://github.com/textura-agency/ai-design-vaultWrote 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/textura-agency/ai-design-vault/schema-markup)<a href="https://agentmods.dev/skills/textura-agency/ai-design-vault/schema-markup"><img src="https://agentmods.dev/badge/skills/textura-agency/ai-design-vault/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/textura-agency/ai-design-vault/schema-markup"><img src="https://agentmods.dev/badge/skills/textura-agency/ai-design-vault/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 | $0.00081 | $0.00727 |
| Opus 5.5 | $0.00032 | $0.00291 |
| Sonnet 5.5 | $0.00016 | $0.00145 |
| Haiku 4.5 | $0.00008 | $0.00073 |
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 23d 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.
How it starts
The opening of the file, as written. The whole thing — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Structured data (JSON-LD)
Keep structured data in one typed builder module (e.g.
<paths.source>/utils/seo/structured-data.*) that composes an entity graph, and
render it once per page. Do not scatter inline
<script type="application/ld+json"> tags through components — that is how a
site ends up with three conflicting Organizations.
If no builder exists yet, create it; it is the first thing this skill installs.
Rules
- JSON-LD only — never microdata or RDFa (hard rule 10).
- Only describe what is on the page. Schema claiming content the page does not contain is spam, and search engines treat it that way.
- Reference, don't duplicate. Build the graph with
@idreferences between entities so the Organization is defined once and linked from everywhere. - Values come from the site config module and the page's own props — never hardcoded a second time.
- Validate: the JSON parses, required properties are present, URLs are absolute
(they need the site URL variable set — see
seo-audit).
Types worth adding, by page kind
| Page | Type | Required-ish properties |
|---|---|---|
| Home | Organization, WebSite |
name, url, logo, sameAs |
| Local business | LocalBusiness |
address, geo, openingHours, telephone |
| Blog post | Article / BlogPosting |
headline, image, datePublished, dateModified, author |
| Service page | Service |
serviceType, provider, areaServed |
| Product | Product + Offer |
name, image, description, price, availability |
| FAQ block | FAQPage |
mainEntity[] of Question/acceptedAnswer |
| Any nested page | BreadcrumbList |
itemListElement with position |
| Team page | Person per member |
name, jobTitle, image, worksFor |
FAQPage earns its place twice over: it is the format both featured snippets and
AI answer engines extract most reliably. If the page has a real FAQ section, mark
it up — but the questions must be visible on the page, not schema-only.
Pattern
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.
- 23d ago First seen · 59 lines · 81 tokens per session scan A ed675dcc8831
schema-markup is a skill published in the GitHub repository textura-agency/ai-design-vault (25 stars, last pushed 2mo ago), licensed Unlicense. It adds 81 tokens to every session and 727 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 2026-10-14.
schema-markup compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| schema-markuptextura-agency/ai-design-vault | Skill | 25 | 2mo ago | Unlicense | A | 81 | Claude Code |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 103 | Claude Code |