Agent skill · marketing growth · sickn33
schema-markup
Design, validate, and optimize schema.org structured data for eligibility, correctness, and measurable SEO impact.
Why this skill is useful
Provides a structured methodology for evaluating schema markup effectiveness that the AI wouldn't reliably generate on its own.
What it needs
About 5k tokens when loaded. Last updated 2026-08-07. 44,571 stars on the source repository.
What this skill does
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. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills sickn33/schema-markup--b21071