structured-data
Skill2 starsChanged 5 months agoMITView on GitHub
Add the JSON-LD structured data that helps answer engines parse content and recognize entities — Organization, Article, Person, FAQPage, Product, and related schema, applied and validated correctly. Works for any business, B2B or B2C, product or service. Use when the request is to add schema or structured data for AI, implement JSON-LD, mark up FAQs or articles or an organization, improve machine-readability for AI search, or validate schema. Reference the shared schema cookbook; pairs with answer-engineering and entity-optimization.
8 other projects use a version of this.
Adopted by
Most recently taken up by
- Zmoki/zmoki-astro-startertheir own version, first seen Oct 27, 2026
- afeezadebayo/technical-seo-skillstheir own version, first seen Oct 20, 2026
- MYehia565/google-seo-agent-skillstheir own version, first seen Oct 13, 2026
- cognyai/claude-code-marketing-skillstheir own version, first seen Oct 12, 2026
- nirholas/AuditKittheir own version, first seen Oct 11, 2026
- moh-obaida/ReadyVibe-Skillstheir own version, first seen Oct 8, 2026
Used with
Projects with it also use core-web-vitals.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
vijpatel7Skillcore-web-vitals
Optimize Core Web Vitals (LCP, INP, CLS) for better page experience and search ranking. Use when asked to "improve Core Web Vitals", "fix LCP", "reduce CLS", "optimize INP", "page experience optimization", or "fix layout shifts".
Also in 3 projects that use this
Other versions8 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 8
- huifer/claude-code-seo★ 110same name
- cognyai/claude-code-marketing-skills★ 106same name
- nirholas/AuditKit★ 19same name
- Zmoki/zmoki-astro-starter★ 4same name
- afeezadebayo/technical-seo-skills★ 2same name
- moh-obaida/ReadyVibe-Skills★ 2same name
- Piyush8296/claude-workspace★ 2same name
- MYehia565/google-seo-agent-skills★ 1same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository26 other files it gives its agents.
- aeo-foundationSkill
- ai-capability-signalingSkill
- ai-crawler-accessSkill
- ai-referral-analyticsSkill
- ai-retrievabilitySkill
- ai-visibility-auditSkill
- ai-visibility-trackingSkill
- answer-engineeringSkill
- author-authoritySkill
- chatgpt-optimizationSkill
- claim-accuracySkill
- claude-optimizationSkill
- community-and-reviewsSkill
- comparison-contentSkill
- competitor-ai-analysisSkill
- content-freshnessSkill
- crawler-log-analysisSkill
- digital-prSkill
- entity-optimizationSkill
- evidence-and-citationsSkill
- gemini-optimizationSkill
- google-ai-overviews-optimizationSkill
- llms-txtSkill
- multimodal-aeoSkill
- perplexity-optimizationSkill
- prompt-researchSkill
The file
We split this skill into the rules it gives an agent
4 rules. 0 are common, 3 are distinctive, and 1 is very specific to this project.
0
Common
Most of the 7 edited versions we read keep these.
3
Distinctive
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 36
Read aeo-foundation.md for the entity facts (for Organization schema) and the content types in play.
- Distinctive: line 48
Validate before shipping: Always run markup through a schema validator and a rich-results test.
- Distinctive: line 72
Validate: Run every page's markup through a validator and rich-results test.
- Distinctive: line 102
Only mark up content that is visible on the page, then validate with a rich-results test.
“Common” is measured: kept by at least 6 in 10 of the 7 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Structured Data
This skill adds the machine-readable markup that helps answer engines parse a page, understand its entities, and extract answers with confidence. Structured data does not force a citation, but it consistently improves how reliably engines interpret content and recognize the brand — and it is one of the higher-leverage technical moves. It works for any business, B2B or B2C.
Ready-to-adapt JSON-LD recipes live in the shared schema cookbook; this skill is the strategy, workflow, and validation around them.
When to use this skill
- Adding schema to content meant to be cited or to define the brand entity.
- Marking up FAQs, articles, authors, products, or the organization.
- Auditing and validating existing structured data.
- Reinforcing answer-engineering and entity work with markup.
Before you start
Read aeo-foundation.md for the entity facts (for Organization schema) and the content
types in play. If it is missing, point to the aeo-foundation skill.
Principles
- JSON-LD, in a script tag — the format engines handle most reliably (not microdata or RDFa).
- Mark up what is true and visible. Schema describes on-page content; it does not replace it, and marking up content that is not on the page is a quality risk.
- Connect the entities. Article references its author (Person); Person is affiliated with the Organization. These links help engines verify credibility and build the entity graph.
- Validate before shipping. Always run markup through a schema validator and a rich-results test.
Priority types for AEO
- Organization — anchors the brand entity, with
sameAs(pairs with entity-optimization). - Article / BlogPosting — content type, author, publish/modified dates.
- Person — author identity and credentials (pairs with author-authority).
- FAQPage — Q&A pairs engines can lift directly (pairs with answer-engineering).
- Product, Review / AggregateRating, HowTo, BreadcrumbList — as relevant to the page.
Workflow
- Audit existing markup. Inventory which pages have schema, which types, and what is missing or invalid.
- Map types to pages. Assign the right schema per template: Organization on the home/about page; Article + Person on content; FAQPage where genuine Q&A appears; Product/Review on commercial pages.
- Implement JSON-LD from the cookbook, filling real values and connecting author/publisher entities.
- Keep dates honest.
datePublished/dateModifiedshould reflect real updates (ties to content-freshness). - Validate. Run every page's markup through a validator and rich-results test; fix errors and warnings.
- Cover broadly. Aim for consistent schema across the relevant page templates, not a one-off.
Output format
- A schema audit: coverage and gaps by page type.
- The JSON-LD to add per template, with entity connections in place.
- A validation note confirming each block passes.
(assumption)tags on any entity facts to confirm.
Common pitfalls
- Marking up content that is not actually on the page — a quality and trust risk.
- Orphan schema: Article with no linked author or publisher.
- Inaccurate
dateModifiedused to fake freshness. - Shipping invalid JSON-LD that silently fails — always validate.
- Treating schema as a silver bullet; it aids interpretation, it does not replace good, corroborated content.
Tool
Generate and lightly validate JSON-LD from a small config (Organization, Article, FAQPage, Person):
python scripts/generate_schema.py --sample organization # example input
python scripts/generate_schema.py --input org.json # emit a <script> block + warningsOnly mark up content that is visible on the page, then validate with a rich-results test.
Optional. The script only automates this step; it needs
python3(standard library only, no install). No Python? Just follow the steps above manually.
Related Skills
- entity-optimization — Organization/
sameAsmarkup that anchors the brand entity. - author-authority — Person schema for credentialed authors.
- answer-engineering — FAQPage and structure that schema reinforces.
- ai-retrievability — ensures the marked-up content is actually crawlable.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
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Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

