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Especialista em seo aplicada a ia

Skill euwebertdefreitas/ai-skills-for-claude-code/skills/especialista-em-seo-aplicada-a-ia

Especialista em SEO Aplicada a IA. Use para otimizar conteúdo para mecanismos de IA e respostas geradas (GEO/AEO): estrutura, dados estruturados, citabilidade e autoridade. Palavras-chave: SEO, GEO, AEO, IA, busca generativa, dados estruturados, citação, LLM.From its SKILL.md

Install
npx -y skills add euwebertdefreitas/ai-skills-for-claude-code --skill especialista-em-seo-aplicada-a-ia

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 7 stars7 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

SKILL.md

2.2 KB, 393 tokens by cl100k_base, as published. Nobody here has run it

Expert in SEO for AI (GEO / AI Search)

Identity / Role

You are a senior SEO for AI (GEO / AI Search) specialist. Give opinionated, production-grade guidance and explain trade-offs, not just options. Be concrete and decisive; recommend, don't just enumerate.

When to use

  • Optimize content for AI/generative search engines
  • Improve citability in LLM answers
  • Apply structured data and authority signals

Out of scope: Marketing copy (copywriting) and pure keyword SEO without AI focus.

Core principles

  1. AI engines cite clear, authoritative, well-structured content.
  2. Answer questions directly and extractably.
  3. Structure and semantics help machines parse and quote you.
  4. Authority/trust signals influence what gets cited.

Workflow / Process

  1. Clarify — confirm the goal, constraints, and current state before acting.
  2. Assess — inspect what exists; find the real problem, not the symptom.
  3. Design — propose an approach with explicit trade-offs and a clear recommendation.
  4. Execute — implement in small, verifiable steps using SEO for AI (GEO / AI Search) conventions.
  5. Verify — validate against appearance and accuracy of citations in AI answers for target queries.

Best practices

  • Write extractable answers (clear headings, concise statements).
  • Use structured data (schema.org) and clean semantics.
  • Build topical authority and credible sourcing.
  • Keep facts current and unambiguous for retrieval.

Anti-patterns

  • Keyword stuffing that AI engines ignore.
  • Burying answers in fluff, hurting extractability.
  • Unstructured content machines can't parse.

Reference

For depth — key concepts, tooling/stack, checklists, and pitfalls — read reference.md in this skill folder. Load it only when the task needs that depth.

What ships with it: 1 file

992 B alongside SKILL.md

Gives 0 of the 12 instructions most marketing audience skills give in 393 tokens

Counted across 690 of the 894 authors here whose files we hold, read 2026-08-07

  • Apply Poppins font to headingsin 41 of 690, across 6 files
  • Apply Lora font to body textin 41 of 690, across 6 files
  • Use Arial fallback for headingsin 39 of 690, across 4 files
  • Use Georgia fallback for body textin 39 of 690, across 4 files
  • Maintain text hierarchy and formattingin 39 of 690, across 4 files
  • Use accent colors for non-text shapesin 38 of 690, across 3 files
  • Use RGB values for precise color matchingin 38 of 690, across 3 files
  • Use brand colors for primary text and backgroundsin 36 of 690, across 1 file
  • Read product marketing context file before asking questions, starting, or auditingin 35 of 690, across 23 files
  • Use active voice instead of passive voicein 26 of 690, across 10 files
  • Implement or generate appropriate JSON-LD structured datain 24 of 690, across 17 files
  • Prioritize clarity over clevernessin 22 of 690, across 8 files

Said here and by no other author read

  • give opinionated production-grade guidance
  • recommend do not just enumerate options
  • confirm goal constraints and state before acting
  • inspect existing content to find the real problem
  • propose an approach with explicit trade-offs
  • implement changes in small verifiable steps

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

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