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Skills Artificial Intelligence Generative Engine Optimization Specialist

Generative Engine Optimization Specialist

v20260704
tlc-generative-engine-optimization
A technical specialization focused on Generative Engine Optimization (GEO). This skill ensures that specific web pages are structured, documented, and optimized for modern AI answer engines (Google AI Overviews, ChatGPT, Bing Copilot). It focuses on technical elements like structured data (JSON-LD), semantic HTML, and robust metadata to maximize discoverability, trustworthiness, and quotability for AI consumption, rather than traditional SEO ranking.
Generative AI SEO Structured Data Web Optimization Discoverability
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Overview

GEO Specialist

Expert in Generative Engine Optimization — making pages discoverable, understandable, trustworthy, quotable, and fresh for AI answer engines.

Philosophy

Treat GEO as documentation quality, not a trick. AI engines cite pages they can parse, trust, and quote. The work is the same as writing clearly for humans: correct metadata, honest structured data, authoritative prose, stable URLs. Never promise rankings or AI citations — those are engine decisions outside your control. Do the technical work well; citations follow as a byproduct.

When to use / not use

Use this skill when the goal is making a specific page or site more visible, citable, or understandable to AI answer engines — technically and at the page level.

Do NOT use for:

  • AI-driven content strategy or programmatic pages at scale → use ai-seo
  • Classic keyword/SERP ranking work → use seo
  • Accessibility audits → use web-accessibility
  • Multi-area site health audits → use web-quality-audit

The Six GEO Pillars

Load references/pillars-and-workflow.md for the full deep-dive. Summary:

# Pillar Core check
1 Discoverable robots.txt allows AI crawlers; sitemap exists; canonical tags correct; HTTPS
2 Understandable Semantic HTML; page title matches H1; language declared; one topic per page
3 Useful Content answers a specific question; content in static HTML (not JS-only)
4 Trustworthy Author bio; citations/sources linked; publication + update dates visible; HTTPS
5 Quotable One answer per section; short-answer paragraph before elaboration; FAQ schema
6 Fresh dateModified in JSON-LD and meta; content reviewed when topic changes

Operating Modes

Mode 1 — Create (new GEO-ready page)

  1. Plan page structure: one topic, one H1, question-based H2s/H3s.
  2. Apply templates/page-metadata.html (canonical, hreflang, meta description).
  3. Add templates/techarticle.jsonld (or faqpage.jsonld for FAQ pages).
  4. Write content in the quotable outline pattern (templates/quotable-article-outline.md): short direct answer → supporting detail → sources.
  5. Update robots.txt to allow AI crawlers (templates/robots-ai-crawlers.txt).
  6. Add or update llms.txt if the site wants to guide AI agents (templates/llms.txt).
  7. Run the GEO page checklist (in references/pillars-and-workflow.md).

Mode 2 — Audit (score an existing page or site)

  1. Crawl check: read robots.txt — are OAI-SearchBot and BingBot allowed?
  2. Structured data: validate all JSON-LD against the Rich Results Test and Schema Markup Validator.
  3. Pillar sweep: for each of the six pillars, mark pass / partial / fail.
  4. Produce a prioritized findings table (Pillar → Finding → Severity → Fix).
  5. Identify quick wins (metadata, schema, robots) vs. content rewrites.

Mode 3 — Improve (apply fixes)

  1. Apply fixes in severity order: blockers first (crawl access, broken schema), then quick wins (metadata, dates), then content improvements.
  2. Re-validate structured data after every schema change.
  3. After changes, point to measurement tools (see references/measurement-and-tools.md) so the user can track AI visibility over time.

Guardrails

  • Never promise that changes will cause a specific AI engine to cite the page. Citation is an engine decision.
  • Structured data must match visible page content exactly. Mismatches violate Google's policies and can suppress the page.
  • llms.txt is optional. It is a community convention, not a crawler-control file, and not a citation guarantee. Recommend it only when the site wants to guide AI agent navigation.
  • robots.txt is the only authoritative crawler-control file. llms.txt has no effect on crawling.
  • Do not add noindex or Disallow for AI crawlers unless the user explicitly wants to block AI indexing.
  • Prefer primary platform documentation (Google Search Central, Bing Webmaster Tools, Schema.org) over third-party summaries.

Examples

Example 1 — Audit request

User: "Can you audit my blog for AI search visibility?"

Actions:

  1. Check robots.txt → OAI-SearchBot is missing a Disallow but also missing an explicit Allow — confirm default is allow.
  2. Validate JSON-LD on the homepage → datePublished is missing, author has no url.
  3. Run pillar sweep → Trustworthy: partial (no author bio page); Quotable: fail (no FAQ schema on FAQ page).
  4. Return findings table with three priority tiers.

Result: Prioritized list: fix techarticle.jsonld, add author bio, add FAQPage schema. Clear, actionable, no ranking promises.

Example 2 — Create request

User: "Create a new GEO-optimized article page for my Next.js blog."

Actions:

  1. Draft <head> from templates/page-metadata.html.
  2. Generate templates/techarticle.jsonld filled with real title, author, dates.
  3. Structure content using templates/quotable-article-outline.md: direct-answer intro, H2/H3 sections, sources list.
  4. Confirm robots.txt allows OAI-SearchBot.
  5. Run checklist — all eight items pass.

Result: Ready-to-deploy page with correct metadata, valid schema, and citation-ready prose.

Example 3 — llms.txt request

User: "Write an llms.txt for my documentation site."

Actions:

  1. Inventory the three or four most useful pages for an AI agent.
  2. Apply templates/llms.txt format: H1 site name → blockquote description → ## Key pages with Markdown links → optional ## Technical files.
  3. Remind the user that llms.txt is not a crawler-control file and doesn't guarantee citations.

Result: A concise, standards-compliant llms.txt with honest caveats.

Troubleshooting

Symptom Likely cause Fix
Rich Results Test shows no schema JSON-LD is in a JS-rendered <script> tag loaded after DOMContentLoaded Move JSON-LD to a static <script type="application/ld+json"> in server-rendered HTML
Schema validation error: "required property missing" datePublished, author, or headline absent Add all required fields; check Schema.org/TechArticle for the full list
OAI-SearchBot not crawling User-agent: * Disallow: / in robots.txt blocks all bots Add explicit Allow: / for OAI-SearchBot above the wildcard rule
llms.txt not picked up by agents File not at https://example.com/llms.txt (must be root) Move file to domain root; verify it returns Content-Type: text/plain
Content visible in browser but not cited Content rendered by client-side JS only Render content server-side so crawlers receive it in the initial HTML response

References and Templates

Load these files on demand — only when the task requires the detail.

File Load when
references/pillars-and-workflow.md You need the full pillar deep-dive, four-step page workflow, or the eight-item GEO page checklist
references/measurement-and-tools.md User asks how to measure GEO results, which tools to use, or what to track after publishing
templates/page-metadata.html Creating or fixing <head> metadata (canonical, hreflang, meta description, open graph)
templates/techarticle.jsonld Adding TechArticle structured data to an article page
templates/faqpage.jsonld Adding FAQPage structured data to a FAQ section
templates/robots-ai-crawlers.txt Updating robots.txt for AI crawler controls (OAI-SearchBot, GPTBot, BingBot)
templates/llms.txt Writing or updating the site's llms.txt
templates/quotable-article-outline.md Structuring article content for AI citation
Info
Category Artificial Intelligence
Name tlc-generative-engine-optimization
Version v20260704
Size 12.84KB
Source tech-leads-club/agent-skills
Updated At 2026-07-06
Language
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English