Automated summary
Designs, validates, and optimizes schema.org structured data for rich result eligibility and measurable SEO impact.
Strengths
- Rigorously evaluates markup relevance via an eligibility index.
- Prevents misleading or non-compliant markup per Google guidelines.
- Produces correct, maintainable JSON-LD.
Limitations
- Does not guarantee rich results.
- Requires prior understanding of page content.
- Impact score is subjective and context-dependent.
When you need to add, audit, or fix schema.org markup to improve search result appearance.
For pages with no clear structured content (e.g., error pages) or if markup offers no probable SEO benefit.
Security analysis
SafeThe skill uses only read-only tools (Read, Glob, Grep) and provides advisory guidance on structuring JSON-LD markup for webpages. It does not instruct or enable any file modification, command execution, network requests, or destructive actions. No security risks are present.
No concerns found
How this analysis is madeExamples
Audit the schema.org markup on this product page. Check for errors, eligibility for rich results, and suggest improvements.Design JSON-LD for a recipe page that includes ingredients, cooking time, and nutrition info. Ensure compliance with Google's recipe rich results guidelines.Should I add FAQ schema to this page? Calculate the Schema Eligibility & Impact Index and recommend whether to implement.name: schema-markup description: > Design, validate, and optimize schema.org structured data for eligibility, correctness, and measurable SEO impact. Use when the user wants to add, fix, audit, or scale schema markup (JSON-LD) for rich results. This skill evaluates whether schema should be implemented, what types are valid, and how to deploy safely according to Google guidelines. allowed-tools: Read, Glob, Grep
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
{
"@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)
- What content is visible on the page?
- Which rich result are you targeting (if any)?
- Is this content templated or editorial?
- How is this data maintained?
- 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
From the file to a first result
The download contains exactly the content displayed on this page. This copy may differ from the latest version in the source repository.
View the source and supporting filesThis download contains SKILL.md only. Any scripts, references, templates and dependencies are not included. Get the required files from the source, preserving their directory structure, before continuing.
1. Download the file
Download SKILL.mdFrom the root of a test project, save the file as .skill-downloads/schema-markup-structured-data-mma3jrvj/SKILL.md, or use the command below. This folder is for inspecting the skill before installation.
Command for macOS/Linux or WSL: requires a POSIX shell and curl. On Windows without WSL, use the download button and create the folder manually.
mkdir -p '.skill-downloads/schema-markup-structured-data-mma3jrvj' && curl --fail --show-error --location 'https://skills-guides.com/api/skills/schema-markup-structured-data-mma3jrvj/download' --output '.skill-downloads/schema-markup-structured-data-mma3jrvj/SKILL.md.part' && mv '.skill-downloads/schema-markup-structured-data-mma3jrvj/SKILL.md.part' '.skill-downloads/schema-markup-structured-data-mma3jrvj/SKILL.md'2. Check prerequisites
Read SKILL.md before using it. If it references scripts or external services, inspect them and prepare the required access in your test environment.
Tools declared by the author (check availability in your agent): Read, Glob, Grep
No recognized prerequisites section in this file. This does not mean it is self-contained: libraries, tools and access requirements may be mentioned elsewhere in the content or source repository.
The platforms on this page are catalog indications. The paths below follow tool documentation; they do not prove this skill has been run in those tools. No minimum tool version is confirmed for this listing.
3. Load the skill
After inspection, copy the complete folder into your project using one of the commands below, then open a new tool session. The command stops if a folder with the same name already exists: compare the files before replacing it.
Claude Code
test -f '.skill-downloads/schema-markup-structured-data-mma3jrvj/SKILL.md' && test -s '.skill-downloads/schema-markup-structured-data-mma3jrvj/SKILL.md' && mkdir -p '.claude/skills' && test ! -e '.claude/skills/schema-markup' && cp -R '.skill-downloads/schema-markup-structured-data-mma3jrvj' '.claude/skills/schema-markup'Cursor
test -f '.skill-downloads/schema-markup-structured-data-mma3jrvj/SKILL.md' && test -s '.skill-downloads/schema-markup-structured-data-mma3jrvj/SKILL.md' && mkdir -p '.cursor/skills' && test ! -e '.cursor/skills/schema-markup' && cp -R '.skill-downloads/schema-markup-structured-data-mma3jrvj' '.cursor/skills/schema-markup'OpenSkills
OpenSkills must already be installed. The local install/read procedure is checked with OpenSkills 1.5.0, which requires Node.js ≥ 20.6.0. Catalog slugs are not resolved automatically.
Official OpenSkills installationopenskills install './.skill-downloads/schema-markup-structured-data-mma3jrvj'openskills read 'schema-markup-structured-data-mma3jrvj'Reading should display the installed file content and its base directory. It does not run the skill or install its dependencies.
For an agent that reads AGENTS.md, then sync the index. This command changes AGENTS.md: review the diff before using it.
openskills syncManual method or another tool: attach SKILL.md to a conversation, or open it in an agent that can read files. Include any required supporting resources. No universal folder is recognized by every tool.
4. Try a first task
Use a short, synthetic input: an API endpoint, a small document or an interface brief. In a new conversation, attach the file or give the agent its path, then adapt this request:
Read .skill-downloads/schema-markup-structured-data-mma3jrvj/SKILL.md and apply its instructions to this example: [describe a test input]. Identify any missing files, dependencies or access. Produce the result requested by the skill without inventing data or running unreviewed scripts.Expected result: output matching the skill instructions, or a precise list of missing prerequisites. A read confirmation alone does not validate a first use. If an external resource is unavailable, that path remains untested.
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