AI SEO workflow skill. Use this skill when the user needs Optimize content for AI search and LLM citations across AI Overviews, ChatGPT, Perplexity, Claude, Gemini, and similar systems. Use when improving AI visibility, answer engine optimization, or citation readiness and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
Instrucciones de origen · Vista previa de solo lectura
name
ai-seo-v2
description
AI SEO workflow skill. Use this skill when the user needs Optimize content for AI search and LLM citations across AI Overviews, ChatGPT, Perplexity, Claude, Gemini, and similar systems. Use when improving AI visibility, answer engine optimization, or citation readiness and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
This public intake copy packages plugins/antigravity-awesome-skills-claude/skills/ai-seo from https://github.com/sickn33/antigravity-awesome-skills into the native Omni Skills editorial shape without hiding its origin.
Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.
This intake keeps the copied upstream files intact and uses the external_source block in metadata.json plus ORIGIN.md as the provenance anchor for review.
AI SEO You are an expert in AI search optimization — the practice of making content discoverable, extractable, and citable by AI systems including Google AI Overviews, ChatGPT, Perplexity, Claude, Gemini, and Copilot. Your goal is to help users get their content cited as a source in AI-generated answers.
Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: Before Starting, How AI Search Works, AI Visibility Audit, Optimization Strategy, Content Types That Get Cited Most, Monitoring AI Visibility.
When to Use This Skill
Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.
Use when optimizing content to be cited by LLMs and AI search systems.
Use when the user asks about AI SEO, AEO, GEO, LLM visibility, or AI citations.
Use when traditional SEO alone is not the full question and AI-specific discoverability matters.
Use when the request clearly matches the imported source intent: Optimize content for AI search and LLM citations across AI Overviews, ChatGPT, Perplexity, Claude, Gemini, and similar systems. Use when improving AI visibility, answer engine optimization, or citation readiness.
Use when the operator should preserve upstream workflow detail instead of rewriting the process from scratch.
Use when provenance needs to stay visible in the answer, PR, or review packet.
Operating Table
Situation
Start here
Why it matters
First-time use
metadata.json
Confirms repository, branch, commit, and imported path through the external_source block before touching the copied workflow
Provenance review
ORIGIN.md
Gives reviewers a plain-language audit trail for the imported source
Workflow execution
references/content-patterns.md
Starts with the smallest copied file that materially changes execution
Supporting context
references/platform-ranking-factors.md
Adds the next most relevant copied source file without loading the entire package
Handoff decision
## Related Skills
Helps the operator switch to a stronger native skill when the task drifts
Workflow
This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.
Confirm the user goal, the scope of the imported workflow, and whether this skill is still the right router for the task.
Read the overview and provenance files before loading any copied upstream support files.
Load only the references, examples, prompts, or scripts that materially change the outcome for the current request.
Execute the upstream workflow while keeping provenance and source boundaries explicit in the working notes.
Validate the result against the upstream expectations and the evidence you can point to in the copied files.
Escalate or hand off to a related skill when the work moves out of this imported workflow's center of gravity.
Before merge or closure, record what was used, what changed, and what the reviewer still needs to verify.
Imported Workflow Notes
Imported: Before Starting
Check for product marketing context first:
If .agents/product-marketing-context.md exists (or .claude/product-marketing-context.md in older setups), read it before asking questions. Use that context and only ask for information not already covered or specific to this task.
Gather this context (ask if not provided):
1. Current AI Visibility
Do you know if your brand appears in AI-generated answers today?
Have you checked ChatGPT, Perplexity, or Google AI Overviews for your key queries?
What queries matter most to your business?
2. Content & Domain
What type of content do you produce? (Blog, docs, comparisons, product pages)
What's your domain authority / traditional SEO strength?
Do you have existing structured data (schema markup)?
3. Goals
Get cited as a source in AI answers?
Appear in Google AI Overviews for specific queries?
Compete with specific brands already getting cited?
Optimize existing content or create new AI-optimized content?
4. Competitive Landscape
Who are your top competitors in AI search results?
Are they being cited where you're not?
Examples
Example 1: Ask for the upstream workflow directly
Use @ai-seo-v2 to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.
Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.
Example 2: Ask for a provenance-grounded review
Review @ai-seo-v2 against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.
Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.
Example 3: Narrow the copied support files before execution
Use @ai-seo-v2 for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.
Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.
Example 4: Build a reviewer packet
Review @ai-seo-v2 using the copied upstream files plus provenance, then summarize any gaps before merge.
Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.
Best Practices
Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.
Keep the imported skill grounded in the upstream repository; do not invent steps that the source material cannot support.
Prefer the smallest useful set of support files so the workflow stays auditable and fast to review.
Keep provenance, source commit, and imported file paths visible in notes and PR descriptions.
Point directly at the copied upstream files that justify the workflow instead of relying on generic review boilerplate.
Treat generated examples as scaffolding; adapt them to the concrete task before execution.
Route to a stronger native skill when architecture, debugging, design, or security concerns become dominant.
Troubleshooting
Problem: The operator skipped the imported context and answered too generically
Symptoms: The result ignores the upstream workflow in plugins/antigravity-awesome-skills-claude/skills/ai-seo, fails to mention provenance, or does not use any copied source files at all.
Solution: Re-open metadata.json, ORIGIN.md, and the most relevant copied upstream files. Check the external_source block first, then restate the provenance before continuing.
Problem: The imported workflow feels incomplete during review
Symptoms: Reviewers can see the generated SKILL.md, but they cannot quickly tell which references, examples, or scripts matter for the current task.
Solution: Point at the exact copied references, examples, scripts, or assets that justify the path you took. If the gap is still real, record it in the PR instead of hiding it.
Problem: The task drifted into a different specialization
Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better.
Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.
Imported Troubleshooting Notes
Imported: Common Mistakes
Ignoring AI search entirely — ~45% of Google searches now show AI Overviews, and ChatGPT/Perplexity are growing fast
Treating AI SEO as separate from SEO — Good traditional SEO is the foundation; AI SEO adds structure and authority on top
Writing for AI, not humans — If content reads like it was written to game an algorithm, it won't get cited or convert
No freshness signals — Undated content loses to dated content because AI systems weight recency heavily. Show when content was last updated
Gating all content — AI can't access gated content. Keep your most authoritative content open
Ignoring third-party presence — You may get more AI citations from a Wikipedia mention than from your own blog
No structured data — Schema markup gives AI systems structured context about your content
Keyword stuffing — Unlike traditional SEO where it's just ineffective, keyword stuffing actively reduces AI visibility by 10% (Princeton GEO study)
Blocking AI bots — If GPTBot, PerplexityBot, or ClaudeBot are blocked in robots.txt, those platforms can't cite you
Generic content without data — "We're the best" won't get cited. "Our customers see 3x improvement in [metric]" will
Forgetting to monitor — You can't improve what you don't measure. Check AI visibility monthly at minimum
Related Skills
@00-andruia-consultant - Use when the work is better handled by that native specialization after this imported skill establishes context.
@00-andruia-consultant-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.
@10-andruia-skill-smith - Use when the work is better handled by that native specialization after this imported skill establishes context.
@10-andruia-skill-smith-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.
Additional Resources
Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.
Resource family
What it gives the reviewer
Example path
references
copied reference notes, guides, or background material from upstream
references/content-patterns.md
examples
worked examples or reusable prompts copied from upstream
examples/n/a
scripts
upstream helper scripts that change execution or validation
scripts/n/a
agents
routing or delegation notes that are genuinely part of the imported package
agents/n/a
assets
supporting assets or schemas copied from the source package
Traditional SEO gets you ranked. AI SEO gets you cited.
In traditional search, you need to rank on page 1. In AI search, a well-structured page can get cited even if it ranks on page 2 or 3 — AI systems select sources based on content quality, structure, and relevance, not just rank position.
Critical stats:
AI Overviews appear in ~45% of Google searches
AI Overviews reduce clicks to websites by up to 58%
Brands are 6.5x more likely to be cited via third-party sources than their own domains
Optimized content gets cited 3x more often than non-optimized
Statistics and citations boost visibility by 40%+ across queries
Imported: AI Visibility Audit
Before optimizing, assess your current AI search presence.
Step 1: Check AI Answers for Your Key Queries
Test 10-20 of your most important queries across platforms:
Query
Google AI Overview
ChatGPT
Perplexity
You Cited?
Competitors Cited?
[query 1]
Yes/No
Yes/No
Yes/No
Yes/No
[who]
[query 2]
Yes/No
Yes/No
Yes/No
Yes/No
[who]
Query types to test:
"What is [your product category]?"
"Best [product category] for [use case]"
"[Your brand] vs [competitor]"
"How to [problem your product solves]"
"[Your product category] pricing"
Step 2: Analyze Citation Patterns
When your competitors get cited and you don't, examine:
Content structure — Is their content more extractable?
Authority signals — Do they have more citations, stats, expert quotes?
Freshness — Is their content more recently updated?
Schema markup — Do they have structured data you're missing?
Third-party presence — Are they cited via Wikipedia, Reddit, review sites?
Step 3: Content Extractability Check
For each priority page, verify:
Check
Pass/Fail
Clear definition in first paragraph?
Self-contained answer blocks (work without surrounding context)?
Statistics with sources cited?
Comparison tables for "[X] vs [Y]" queries?
FAQ section with natural-language questions?
Schema markup (FAQ, HowTo, Article, Product)?
Expert attribution (author name, credentials)?
Recently updated (within 6 months)?
Heading structure matches query patterns?
AI bots allowed in robots.txt?
Step 4: AI Bot Access Check
Verify your robots.txt allows AI crawlers. Each AI platform has its own bot, and blocking it means that platform can't cite you:
GPTBot and ChatGPT-User — OpenAI (ChatGPT)
PerplexityBot — Perplexity
ClaudeBot and anthropic-ai — Anthropic (Claude)
Google-Extended — Google Gemini and AI Overviews
Bingbot — Microsoft Copilot (via Bing)
Check your robots.txt for Disallow rules targeting any of these. If you find them blocked, you have a business decision to make: blocking prevents AI training on your content but also prevents citation. One middle ground is blocking training-only crawlers (like CCBot from Common Crawl) while allowing the search bots listed above.
