Agent skill

Schema

by unifapi-agent in unifapi-agent/agents

When the user wants to add, fix, or optimize schema markup and structured data on their site.

MITAuto-check passedMarketing & SEO

Install Schema

skills CLI
$ npx skills add unifapi-agent/agents --skill schema -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install unifapi-agent/agents schema --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/unifapi-agent/agents.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/seo-agent/schema .claude/skills/schema && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
schema
GitHub stars
586
Token cost
~2.1k tokens
SKILL.md length
813 words
Files
3 (incl. references)
Skills in repo
47
Repo updated
First seen
Licence
MIT

At a glance

When the user wants to add, fix, or optimize schema markup and structured data on their site.

  • Works in 6 steps: Read context first. If… → Identify the page type and the rich… → Inventory existing markup. Note what… → …
  • Optimize schema markup and structured data on their site
  • SKILL.md covers Workflow, Core Principles, Common Schema Types and Quick Reference (required +…, plus 7 more sections
  • Reaches schema.org

What it does

Schema is an agent skill from unifapi-agent/agents. When the user wants to add, fix, or optimize schema markup and structured data on their site. Also use when the user mentions "schema markup," "structured data," "JSON-LD," "rich snippets," "schema.org," "FAQ schema," "product schema," "review schema," "breadcrumb schema," "Google rich results," "knowledge panel," "star ratings in search," or "add structured data." Use this whenever someone wants their pages to show enhanced results in Google. For broader SEO issues, see the seo-audit skill.

Its SKILL.md is about 2.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including reference files (for example `README.md` and `references/schema-examples.md`).

It sits in Marketing & SEO, covering Schema markup. The repository describes itself as: Open-source marketing agents for Claude, ChatGPT, Codex, OpenClaw & Hermes. One plugin: SEO audits, GEO / AI-visibility, local SEO, KOL pricing, social listening & competitive… The licence is MIT.

When your agent uses it

  • Optimize schema markup and structured data on their site
  • The user mentions schema markup
  • Structured data
  • Breadcrumb schema

Example prompts

  • “schema markup,”
  • “structured data,”
  • “JSON-LD,”
  • “/schema”

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. Read context first. If .agents/product-marketing.md (or .claude/product-marketing.md, or legacy product-marketing-context.md) exists, read…
  2. Identify the page type and the rich results it can earn — what is the primary content, and which enhanced result is realistically…
  3. Inventory existing markup. Note what schema (if any) is already present and whether it errors. To read JS-injected JSON-LD on the live…
  4. Choose the right types and properties — match each to its required and recommended fields (Quick Reference). When a page legitimately is…
  5. Generate valid JSON-LD for the page, accurately reflecting visible content (Output Format; full examples in references/schema-examples.md).
  6. Validate with the Rich Results Test and the Schema.org Validator, fix errors/warnings, then hand the markup to your own assistant to add…

What it can do on your machine

Read from SKILL.md and the folder at commit fb53247. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are json).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • schema.org

    Also links to:

    • search.google.com
    • validator.schema.org

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Schema loads about 2.1k tokens when it runs, and up to ~4.2k if it reads all its reference files. Until then it costs about 126 tokens; SKILL.md has 813 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~126
When it runs · the whole SKILL.md, loaded when a task matches
~2.1k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~4.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from unifapi-agent/agents at commit fb53247, republished under its MIT licence (© unifapi-agent). 813 words, ~2,119 tokens.

Download SKILL.mdSave it as .claude/skills/schema/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
schema
description
When the user wants to add, fix, or optimize schema markup and structured data on their site. Also use when the user mentions "schema markup," "structured data," "JSON-LD," "rich snippets," "schema.org," "FAQ schema," "product schema," "review schema," "breadcrumb schema," "Google rich results," "knowledge panel," "star ratings in search," or "add structured data." Use this whenever someone wants their pages to show enhanced results in Google. For broader SEO issues, see the seo-audit skill.
license
MIT
metadata.author
UnifAPI
metadata.version
1.0.0
metadata.adapted_from
https://github.com/coreyhaines31/marketingskills
metadata.adapted_author
Corey Haines

Schema Markup

You are an expert in structured data. Your goal is to pick the right schema.org types for a page, generate valid JSON-LD, and steer clear of the mistakes that get rich results disqualified — so search engines understand the content and the page becomes eligible for enhanced results.

This is an advice skill — UnifAPI is not called here. It recommends types and generates JSON-LD; your own assistant writes it into the site. (When you need to read the JS-injected JSON-LD already on a live page before changing it, the seo-audit skill does that via browser/html / browser/markdown — a static fetch can't see client-side-injected schema.)

Workflow

  1. Read context first. If .agents/product-marketing.md (or .claude/product-marketing.md, or legacy product-marketing-context.md) exists, read it before asking questions; only ask for what it doesn't cover.
  2. Identify the page type and the rich results it can earn — what is the primary content, and which enhanced result is realistically available (see Common Schema Types).
  3. Inventory existing markup. Note what schema (if any) is already present and whether it errors. To read JS-injected JSON-LD on the live page, hand off to seo-audit (browser/html / browser/markdown); a web_fetch/curl strips <script> tags and will miss it.
  4. Choose the right types and properties — match each to its required and recommended fields (Quick Reference). When a page legitimately is more than one thing, combine types under @graph rather than emitting separate disconnected blocks.
  5. Generate valid JSON-LD for the page, accurately reflecting visible content (Output Format; full examples in references/schema-examples.md).
  6. Validate with the Rich Results Test and the Schema.org Validator, fix errors/warnings, then hand the markup to your own assistant to add to the site.

Core Principles

  1. Accuracy first — markup must represent content that is actually on the page; don't mark up what isn't there; keep it in sync when content changes. Mismatched schema gets rich results revoked.
  2. Use JSON-LD — Google's recommended format; easiest to maintain. Place it in <head> or at the end of <body>.
  3. Follow Google's guidelines — only use types/properties Google supports for rich results; check eligibility requirements; avoid spammy markup.
  4. Validate everything — test before deploying; monitor Search Console Enhancements; fix errors promptly.

Common Schema Types

TypeUse ForRequired Properties
OrganizationCompany homepage/aboutname, url
WebSiteHomepage (sitelinks search)name, url
Article/BlogPostingBlog posts, newsheadline, image, datePublished, author
ProductProduct pagesname, image, offers
SoftwareApplicationSaaS/app pagesname, offers
FAQPageFAQ contentmainEntity (Q&A array)
HowToTutorialsname, step
BreadcrumbListAny page with breadcrumbsitemListElement
LocalBusinessLocal business pagesname, address
EventEvents, webinarsname, startDate, location

Full JSON-LD for each is in references/schema-examples.md.

  • Organization — req: name, url · rec: logo, sameAs (social profiles), contactPoint
  • Article/BlogPosting — req: headline, image, datePublished, author · rec: dateModified, publisher, description
  • Product — req: name, image, offers (price + availability) · rec: sku, brand, aggregateRating, review
  • SoftwareApplication — req: name, offers · rec: applicationCategory, operatingSystem, aggregateRating
  • FAQPage — req: mainEntity (array of Question/Answer) · only for genuine, visible Q&A
  • BreadcrumbList — req: itemListElement (each with position, name, item)
Show full SKILL.md (318 more words)Show less

Multiple Schema Types (@graph)

When a page is legitimately several things at once (e.g. a homepage that is an Organization and a WebSite and has breadcrumbs), combine them under a single @graph and cross-reference with @id so the entities link instead of floating as disconnected blocks:

json
{
  "@context": "https://schema.org",
  "@graph": [
    { "@type": "Organization", "@id": "https://example.com/#org", "name": "...", "url": "..." },
    {
      "@type": "WebSite",
      "@id": "https://example.com/#website",
      "url": "...",
      "publisher": { "@id": "https://example.com/#org" }
    },
    { "@type": "BreadcrumbList", "itemListElement": [] }
  ]
}

Validation and Testing

Common errors: missing required properties; invalid values (dates must be ISO 8601, URLs fully qualified, enumerations exact, e.g. https://schema.org/InStock); markup that doesn't match the visible page content.

Implementation Notes

  • Static sites — JSON-LD directly in the template; use includes/partials for reusable blocks.
  • Dynamic (React/Next.js) — a component that serializes data to JSON-LD, server-side rendered. See the Next.js example in the reference.
  • CMS/WordPress — Yoast / Rank Math / Schema Pro plugins (note: these inject via JS — see the live-detection caveat above), theme edits, or custom-field mapping.

Output Format

Return the JSON-LD block plus a testing checklist.

json
{
  "@context": "https://schema.org",
  "@type": "...",
  "// complete, valid markup populated from the actual page": "..."
}
text
Testing checklist
[ ] Validates in Rich Results Test
[ ] No errors or warnings
[ ] Every field matches visible page content
[ ] All required properties present
[ ] (multi-type) entities linked via @id under @graph

Guardrails

  • Advice + generation only ("eyes, not hands"): this skill produces JSON-LD and validation guidance; the operator's own assistant writes it into the site.
  • Accuracy over coverage: never mark up content that isn't on the page, and never invent ratings/prices/dates to qualify for a rich result — fabricated markup gets results revoked and risks a manual action.
  • Only claim a rich result is achievable when the type is Google-supported and the page meets its eligibility requirements; validate before declaring done.

References

  • references/schema-examples.md — complete JSON-LD for Organization, WebSite, Article, Product, SoftwareApplication, FAQPage, HowTo, BreadcrumbList, LocalBusiness, Event, @graph, and a Next.js implementation.
  • seo-audit (SEO Agent): overall SEO including reading the JS-injected schema already on a live page (browser/html / browser/markdown).
  • ai-seo (AI Visibility Agent): structured data helps AI engines extract and cite content.
  • programmatic-seo: templated schema generated at scale across many pages.
  • site-architecture: breadcrumb structure and navigation-schema planning.
  • unifapi: the shared data skill (only relevant via seo-audit, for reading live on-page markup).

© unifapi-agent, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files (references) in skills/seo-agent/schema of unifapi-agent/agents.

  • SKILL.md
  • README.md
  • references/schema-examples.md

Open the folder on GitHubat commit fb53247

Compare with similar skills

Schema next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Schema compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Schema this skillunifapi-agent/agents586—~2.1kAutomated safety check: PassMIT
SEO GeoReScienceLab/opc-skills1.8k4 repos~2.1kAutomated safety check: PassApache-2.0
GEO-First SEO Audit Toolzubair-trabzada/geo-seo-claude11k—~2.8kAutomated safety check: NotesMIT
SEO Audit with Search Consolenowork-studio/notfair-plugin3.9k1 repos~15kAutomated safety check: WarnMIT
Schema Markupfreekmurze/dotfiles1k14 repos~1.2kAutomated safety check: PassNone
SEO Optimizerailabs-393/ai-labs-claude-skills4541 repos~3.2kAutomated safety check: PassMIT

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Categories

Questions about Schema

What does Schema do?

When the user wants to add, fix, or optimize schema markup and structured data on their site. Schema is an agent skill from unifapi-agent/agents. When the user wants to add, fix, or optimize schema markup and structured data on their site.

When should I use Schema?

Schema fits situations like: optimize schema markup and structured data on their site; the user mentions schema markup; structured data; breadcrumb schema.

How do I install Schema in Claude Code?

Run `npx skills add unifapi-agent/agents --skill schema -a claude-code`. Or copy the skill folder (skills/seo-agent/schema in unifapi-agent/agents) into .claude/skills/schema in your project. Claude Code loads it when a task matches its description.

How do I install Schema in Codex?

Run `npx skills add unifapi-agent/agents --skill schema -a codex`. Or copy the skill folder (skills/seo-agent/schema in unifapi-agent/agents) into .agents/skills/schema in your project. Codex loads it when a task matches its description.

Can I use Schema in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add unifapi-agent/agents --skill schema -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/schema, .gemini/skills/schema, .github/skills/schema and .opencode/skills/schema in your project.

What does Schema need to run?

SKILL.md names no scripts, command-line tools or credentials: Schema is instructions for the agent only.

Does Schema access the network?

SKILL.md names 3 domains. In commands or code: schema.org; the agent is likely to contact it when it follows the instructions. As links in the text: search.google.com and validator.schema.org. This is read from the text; nothing was executed.

Is Schema safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Schema use?

Schema is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Schema use?

About 2.1k tokens (SKILL.md is roughly 8.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.1k tokens, read only when the agent opens those files.

What are the alternatives to Schema?

Skills that share tags, products or a category with Schema: SEO Geo (ReScienceLab/opc-skills, 1.8k stars), GEO-First SEO Audit Tool (zubair-trabzada/geo-seo-claude, 11k stars), SEO Audit with Search Console (nowork-studio/notfair-plugin, 3.9k stars) and Schema Markup (freekmurze/dotfiles, 1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Schema?

unifapi-agent (a GitHub organization) maintains it in unifapi-agent/agents, which has 586 GitHub stars. The repository holds 47 skills in this directory. The repository was last updated on September 5, 2026.

Source: unifapi-agent/agents on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.