tlc-generative-engine-optimization
Generative Engine Optimization (GEO) specialist — the technical, on-page publishing work that makes a given page or site discoverable, understandabl…
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技能内容
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)
- Plan page structure: one topic, one H1, question-based H2s/H3s.
- Apply
templates/page-metadata.html(canonical, hreflang, meta description). - Add
templates/techarticle.jsonld(orfaqpage.jsonldfor FAQ pages). - Write content in the quotable outline pattern (
templates/quotable-article-outline.md): short direct answer → supporting detail → sources. - Update
robots.txtto allow AI crawlers (templates/robots-ai-crawlers.txt). - Add or update
llms.txtif the site wants to guide AI agents (templates/llms.txt). - Run the GEO page checklist (in
references/pillars-and-workflow.md).
Mode 2 — Audit (score an existing page or site)
- Crawl check: read
robots.txt— areOAI-SearchBotandBingBotallowed? - Structured data: validate all JSON-LD against the Rich Results Test and Schema Markup Validator.
- Pillar sweep: for each of the six pillars, mark pass / partial / fail.
- Produce a prioritized findings table (Pillar → Finding → Severity → Fix).
- Identify quick wins (metadata, schema, robots) vs. content rewrites.
Mode 3 — Improve (apply fixes)
- Apply fixes in severity order: blockers first (crawl access, broken schema), then quick wins (metadata, dates), then content improvements.
- Re-validate structured data after every schema change.
- 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.txtis 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.txtis the only authoritative crawler-control file.llms.txthas no effect on crawling.- Do not add
noindexorDisallowfor 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:
- Check
robots.txt→OAI-SearchBotis missing aDisallowbut also missing an explicitAllow— confirm default is allow. - Validate JSON-LD on the homepage →
datePublishedis missing,authorhas nourl. - Run pillar sweep → Trustworthy: partial (no author bio page); Quotable: fail (no FAQ schema on FAQ page).
- 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:
- Draft
<head>fromtemplates/page-metadata.html. - Generate
templates/techarticle.jsonldfilled with real title, author, dates. - Structure content using
templates/quotable-article-outline.md: direct-answer intro, H2/H3 sections, sources list. - Confirm
robots.txtallowsOAI-SearchBot. - 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:
- Inventory the three or four most useful pages for an AI agent.
- Apply
templates/llms.txtformat: H1 site name → blockquote description →## Key pageswith Markdown links → optional## Technical files. - Remind the user that
llms.txtis 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 |
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它属于哪个仓库
packages/skills-catalog/skills/(quality)/tlc-generative-engine-optimization/SKILL.md同一个仓库里的其他技能
- component-common-domain-detection
- component-flattening-analysis
- component-identification-sizing
- coupling-analysis
- decomposition-planning-roadmap
- domain-analysis
- domain-identification-grouping
- evolutionary-modular-architecture
- frontend-blueprint
- legacy-migration-planner
- modular-decomposition
- modular-design-principles