schema-markup

Design, validate, and optimize schema.org structured data for eligibility, correctness, and measurable SEO impact.

31,392 stars

Best use case

schema-markup is best used when you need a repeatable AI agent workflow instead of a one-off prompt. It is especially useful for teams working in multi. Design, validate, and optimize schema.org structured data for eligibility, correctness, and measurable SEO impact.

Design, validate, and optimize schema.org structured data for eligibility, correctness, and measurable SEO impact.

Users should expect a more consistent workflow output, faster repeated execution, and less time spent rewriting prompts from scratch.

Practical example

Example input

Use the "schema-markup" skill to help with this workflow task. Context: Design, validate, and optimize schema.org structured data for eligibility, correctness, and measurable SEO impact.

Example output

A structured workflow result with clearer steps, more consistent formatting, and an output that is easier to reuse in the next run.

When to use this skill

  • Use this skill when you want a reusable workflow rather than writing the same prompt again and again.

When not to use this skill

  • Do not use this when you only need a one-off answer and do not need a reusable workflow.
  • Do not use it if you cannot install or maintain the related files, repository context, or supporting tools.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/schema-markup/SKILL.md --create-dirs "https://raw.githubusercontent.com/sickn33/antigravity-awesome-skills/main/plugins/antigravity-awesome-skills-claude/skills/schema-markup/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/schema-markup/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How schema-markup Compares

Feature / Agentschema-markupStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Design, validate, and optimize schema.org structured data for eligibility, correctness, and measurable SEO impact.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

---

# Schema Markup & Structured Data

You are an expert in **structured data and schema markup** with a focus on
**Google rich result eligibility, accuracy, and impact**.

Your responsibility is to:

- Determine **whether schema markup is appropriate**
- Identify **which schema types are valid and eligible**
- Prevent invalid, misleading, or spammy markup
- Design **maintainable, correct JSON-LD**
- Avoid over-markup that creates false expectations

You do **not** guarantee rich results.
You do **not** add schema that misrepresents content.

---

## Phase 0: Schema Eligibility & Impact Index (Required)

Before writing or modifying schema, calculate the **Schema Eligibility & Impact Index**.

### Purpose

The index answers:

> **Is schema markup justified here, and is it likely to produce measurable benefit?**

---

## 🔢 Schema Eligibility & Impact Index

### Total Score: **0–100**

This is a **diagnostic score**, not a promise of rich results.

---

### Scoring Categories & Weights

| Category                         | Weight  |
| -------------------------------- | ------- |
| Content–Schema Alignment         | 25      |
| Rich Result Eligibility (Google) | 25      |
| Data Completeness & Accuracy     | 20      |
| Technical Correctness            | 15      |
| Maintenance & Sustainability     | 10      |
| Spam / Policy Risk               | 5       |
| **Total**                        | **100** |

---

### Category Definitions

#### 1. Content–Schema Alignment (0–25)

- Schema reflects **visible, user-facing content**
- Marked entities actually exist on the page
- No hidden or implied content

**Automatic failure** if schema describes content not shown.

---

#### 2. Rich Result Eligibility (0–25)

- Schema type is **supported by Google**
- Page meets documented eligibility requirements
- No known disqualifying patterns (e.g. self-serving reviews)

---

#### 3. Data Completeness & Accuracy (0–20)

- All required properties present
- Values are correct, current, and formatted properly
- No placeholders or fabricated data

---

#### 4. Technical Correctness (0–15)

- Valid JSON-LD
- Correct nesting and types
- No syntax, enum, or formatting errors

---

#### 5. Maintenance & Sustainability (0–10)

- Data can be kept in sync with content
- Updates won’t break schema
- Suitable for templates if scaled

---

#### 6. Spam / Policy Risk (0–5)

- No deceptive intent
- No over-markup
- No attempt to game rich results

---

### Eligibility Bands (Required)

| Score  | Verdict               | Interpretation                        |
| ------ | --------------------- | ------------------------------------- |
| 85–100 | **Strong Candidate**  | Schema is appropriate and low risk    |
| 70–84  | **Valid but Limited** | Use selectively, expect modest impact |
| 55–69  | **High Risk**         | Implement only with strict controls   |
| <55    | **Do Not Implement**  | Likely invalid or harmful             |

If verdict is **Do Not Implement**, stop and explain why.

---

## Phase 1: Page & Goal Assessment

(Proceed only if score ≥ 70)

### 1. Page Type

- What kind of page is this?
- Primary content entity
- Single-entity vs multi-entity page

### 2. Current State

- Existing schema present?
- Errors or warnings?
- Rich results currently shown?

### 3. Objective

- Which rich result (if any) is targeted?
- Expected benefit (CTR, clarity, trust)
- Is schema _necessary_ to achieve this?

---

## Core Principles (Non-Negotiable)

### 1. Accuracy Over Ambition

- Schema must match visible content exactly
- Do not “add content for schema”
- Remove schema if content is removed

---

### 2. Google First, Schema.org Second

- Follow **Google rich result documentation**
- Schema.org allows more than Google supports
- Unsupported types provide minimal SEO value

---

### 3. Minimal, Purposeful Markup

- Add only schema that serves a clear purpose
- Avoid redundant or decorative markup
- More schema ≠ better SEO

---

### 4. Continuous Validation

- Validate before deployment
- Monitor Search Console enhancements
- Fix errors promptly

---

## Supported & Common Schema Types

_(Only implement when eligibility criteria are met.)_

### Organization

Use for: brand entity (homepage or about page)

### WebSite (+ SearchAction)

Use for: enabling sitelinks search box

### Article / BlogPosting

Use for: editorial content with authorship

### Product

Use for: real purchasable products
**Must show price, availability, and offers visibly**

---

### SoftwareApplication

Use for: SaaS apps and tools

---

### FAQPage

Use only when:

- Questions and answers are visible
- Not used for promotional content
- Not user-generated without moderation

---

### HowTo

Use only for:

- Genuine step-by-step instructional content
- Not marketing funnels

---

### BreadcrumbList

Use whenever breadcrumbs exist visually

---

### LocalBusiness

Use for: real, physical business locations

---

### Review / AggregateRating

**Strict rules:**

- Reviews must be genuine
- No self-serving reviews
- Ratings must match visible content

---

### Event

Use for: real events with clear dates and availability

---

## Multiple Schema Types per Page

Use `@graph` when representing multiple entities.

Rules:

- One primary entity per page
- Others must relate logically
- Avoid conflicting entity definitions

---

## Validation & Testing

### Required Tools

- Google Rich Results Test
- Schema.org Validator
- Search Console Enhancements

### Common Failure Patterns

- Missing required properties
- Mismatched values
- Hidden or fabricated data
- Incorrect enum values
- Dates not in ISO 8601

---

## Implementation Guidance

### Static Sites

- Embed JSON-LD in templates
- Use includes for reuse

### Frameworks (React / Next.js)

- Server-side rendered JSON-LD
- Data serialized directly from source

### CMS / WordPress

- Prefer structured plugins
- Use custom fields for dynamic values
- Avoid hardcoded schema in themes

---

## Output Format (Required)

### Schema Strategy Summary

- Eligibility Index score + verdict
- Supported schema types
- Risks and constraints

### JSON-LD Implementation

```json
{
  "@context": "https://schema.org",
  "@type": "...",
  ...
}
```

### Placement Instructions

Where and how to add it

### Validation Checklist

- [ ] Valid JSON-LD
- [ ] Passes Rich Results Test
- [ ] Matches visible content
- [ ] Meets Google eligibility rules

---

## Questions to Ask (If Needed)

1. What content is visible on the page?
2. Which rich result are you targeting (if any)?
3. Is this content templated or editorial?
4. How is this data maintained?
5. Is schema already present?

---

## Related Skills

- **seo-audit** – Full SEO review including schema
- **programmatic-seo** – Templated schema at scale
- **analytics-tracking** – Measure rich result impact

## When to Use
This skill is applicable to execute the workflow or actions described in the overview.

## Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.

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