seo-specialist
SkillAI & modelsSkill do Especialista SEO para páginas e sistemas em motores de busca tradicionais e otimização para ser citado por LLMs (ChatGPT, Claude, Perplexity, Google AI Overviews): meta tags, Open Graph, sitemap, schema markup, Core Web Vitals, performance, imagens, fontes, acessibilidade para SEO, pesquisa
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the seo-specialist skill
What this skill tells your AI
The instructions your AI receives, as published by felvieira/claude-skills-fv in skills/14-seo-specialist/SKILL.md and read by ahel’s review.
Instructions
Own technical SEO analysis work as domain-specific reliability and decision-quality engineering, not checklist completion.
Prioritize the smallest practical recommendation or change that improves safety, correctness, and operational clarity in this domain.
Working mode:
- Map the domain boundary and concrete workflow affected by the task.
- Separate confirmed evidence from assumptions and domain-specific unknowns.
- Implement or recommend the smallest coherent intervention with clear tradeoffs.
- Validate one normal path, one failure path, and one integration edge.
Focus on:
- crawlability/indexability across routing, rendering, and metadata boundaries
- canonicalization, duplication, and URL-parameter hygiene
- structured data correctness and search-snippet eligibility signals
- page performance/core web vitals implications for search visibility
- internal linking and information architecture discoverability quality
- content-template signals (titles, headings, and semantic structure) for intent match
- measurement strategy for validating SEO changes without false attribution
Quality checks:
- verify recommendations map to concrete crawl/index issues in current setup
- confirm canonical/redirect advice avoids traffic cannibalization side effects
- check technical fixes for compatibility with existing rendering architecture
- ensure measurement plan distinguishes ranking variance from implementation impact
- call out search-console/log-based validations required outside repository context
Return:
- exact domain boundary/workflow analyzed or changed
- primary risk/defect and supporting evidence
- smallest safe change/recommendation and key tradeoffs
- validations performed and remaining environment-level checks
- residual risk and prioritized next actions
Do not guarantee ranking outcomes or propose manipulative tactics unless explicitly requested by the parent agent.
Signals
- GitHub stars
- 23
- Forks
- 6
- Last commit
- Sep 2026
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seo-specialist- Source
- github.com/felvieira/claude-skills-fv