Open Skills Logo
Open Skills

schema-markup

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.

Author

@sickn33

Category

Development Tools

Install

Hot:0

Download and extract to your skills directory

Copy command and send to OpenClaw for auto-install:

Download and install this skill https://openskills.cc/api/download?slug=sickn33-skills-schema-markup&locale=en&source=copy

Schema Markup - Structured Data and Schema Markup Expert

Skill Overview

Schema Markup is a specialized expert skill designed to design, validate, and optimize schema.org structured data. It helps you assess whether you should implement Schema markup, choose effective Schema types, and deploy JSON-LD code safely according to Google guidelines to qualify for rich result eligibility.

Use Cases

  • Add new Schema markup: When you add structured data to your website for the first time or extend existing Schema coverage, this skill evaluates the match between your content and Schema, rich result eligibility, and data completeness—ensuring you only implement markup that delivers real value.

  • Fix or audit existing Schema: When your Schema markup has errors, fails to show the expected rich results, or requires a comprehensive audit, this skill identifies technical issues, validates data accuracy, and checks compliance with Google policies.

  • Scale Schema deployment: When you need to implement Schema markup across multiple pages or templates, this skill designs a maintainable implementation approach—ensuring data stays in sync and avoiding the risk of over-markup.

    • Core Features

  • Eligibility and Impact Scoring Index: Computes an overall score from 0–100 across six dimensions (content match, rich result eligibility, data completeness, technical correctness, maintainability, and spam content risk). This determines whether Schema implementation is necessary and what benefits you can expect, helping you avoid ineffective or high-risk markup.

  • Schema type selection and validation: Supports major Schema types supported by Google, such as Organization, WebSite, Article, Product, SoftwareApplication, FAQPage, HowTo, and LocalBusiness—ensuring the selected types match content characteristics and Google’s rich result requirements.

  • JSON-LD implementation and deployment guidance: Provides specific implementation plans for static sites, React/Next.js frameworks, and the WordPress CMS. It generates JSON-LD code that follows standards, and includes placement guidance and a validation checklist.

    • Frequently Asked Questions

    Can Schema markup really improve SEO rankings?

    Schema markup itself is not a direct ranking factor, but it can indirectly affect rankings by improving click-through rate (CTR). Rich results—such as star ratings, price information, and breadcrumb navigation—can make your listings stand out more on search pages and attract more clicks. This skill uses the Eligibility and Impact Scoring Index to help you determine whether implementing Schema will deliver measurable value, avoiding the blind addition of markup that doesn’t produce real results.

    Why doesn’t my Schema markup show rich results?

    Rich result display depends on multiple factors: whether the Schema type is supported by Google, whether the page meets all eligibility requirements, whether the data is complete and accurate, and whether there are technical errors, among others. Even if everything is correct, Google does not guarantee that rich results will always be shown. This skill helps you verify the correctness of your Schema code, check compliance with Google documentation requirements, and identify common issues that may prevent rich results from appearing.

    How can I avoid Schema markup being judged as spam?

    Google has strict policies for structured data and prohibits false or misleading markup. This skill identifies potential issues through the “spam content/policy risk” dimension in the Eligibility and Impact assessment: ensuring Schema fully matches visible content, not adding content that exists only for Schema, avoiding over-markup, and not using fake data or placeholders. When evaluating certain Schema types, it will especially check whether they contain self-reviews, which Google explicitly prohibits.