The GEO implementation checklist: crawlability, citability, structure, and governance

By licheo Research Team | | GEO Guides | 14 min read

This is the checklist we would use if we were handed a site and asked to improve its AI-search readiness without wasting weeks on speculation.

It is not a list of magic tricks. It is a list of the conditions that make citations and supporting links more likely by reducing crawl friction, ambiguity, and trust gaps.

If you want the conceptual version first, read our complete guide to generative engine optimization.

How to use this checklist

Do not try to score all 100 items at once.

Use it in three passes:

  1. Fix all blockers that keep important pages from being crawled, indexed, or surfaced.
  2. Improve the structure and evidentiary quality of your top commercial and informational pages.
  3. Build an update and measurement workflow so the work compounds instead of decaying.

Phase 1: crawlability and discovery

Robots and bot access

Check the following:

  • Your robots.txt file exists at the root and loads with a 200 response.
  • High-value directories are not accidentally blocked.
  • Search-specific bots are intentionally allowed or intentionally disallowed.
  • CDN, WAF, or bot-management rules are not stricter than the robots.txt policy you think you have.

For Google AI features, Google says Search access is managed through Googlebot. For ChatGPT Search, OpenAI says it is important to allow OAI-Searchbot. Anthropic separately documents ClaudeBot, Claude-User, and Claude-SearchBot.

A simple pattern looks like this:

User-agent: Googlebot
Allow: /

User-agent: OAI-Searchbot
Allow: /

User-agent: Claude-User
Allow: /

User-agent: Claude-SearchBot
Allow: /

Sitemap: https://example.com/sitemap.xml

Only use allow rules you actually intend to support. The point is not to allow every bot blindly. The point is to make sure your policy is deliberate and consistent across infrastructure.

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Sitemap health

Confirm:

  • the sitemap includes every page you actually want discovered
  • deleted or redirected pages are removed quickly
  • canonical URLs in the sitemap match your intended canonical targets
  • priority revenue pages are not buried in orphaned sections

If the site changes frequently, consider implementing IndexNow for participating engines so newly updated URLs are announced quickly.

Internal discovery

Review:

  • orphan pages
  • thin hub pages with no meaningful contextual links
  • overly deep content trees
  • pagination or JavaScript patterns that make important links hard to crawl

Generative systems do not rescue weak architecture. If your own site barely explains how pages relate, you should expect retrieval to be inconsistent.

Phase 2: indexing and eligibility

Indexability

For every priority page, verify:

  • no accidental noindex
  • the canonical URL resolves cleanly
  • there are no soft-404 behaviors
  • the rendered page contains the actual answer content
  • the page is available without login or fragile client-side hydration

For Google's AI features, the page must be indexed and eligible to show a snippet. That makes basic Search eligibility non-negotiable.

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Preview and snippet controls

Audit:

  • nosnippet
  • data-nosnippet
  • max-snippet
  • max-image-preview
  • noindex

Do not assume these tags are harmless defaults. If you over-restrict previews, you may limit what Search and AI surfaces can show from the page.

Use strict preview controls only when you truly mean it.

Duplicate and conflicting versions

Resolve:

  • HTTP versus HTTPS duplication
  • subdomain duplication
  • faceted URLs accidentally indexed
  • parameterized duplicates
  • near-identical versions competing for the same query space

AI retrieval is already probabilistic enough. Duplicating equivalent pages just gives the system more ways to misunderstand which URL matters.

Phase 3: structured understanding

Structured data

Implement the schema types that naturally fit the page:

  • Article or BlogPosting for editorial content
  • FAQPage for legitimate question-and-answer sections
  • Organization for company identity
  • BreadcrumbList for hierarchy
  • Product, Service, or SoftwareApplication where relevant

Guidelines:

  • make sure structured data matches visible content
  • prefer complete, accurate properties over bloated markup
  • validate with the Rich Results Test during development
  • use JSON-LD where possible, since Google recommends it

Do not add schema for content that is not really there. Bad structured data increases ambiguity rather than reducing it.

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Entity clarity

Review whether every important page clearly states:

  • who wrote it
  • what product, service, or topic it is about
  • what company owns it
  • when it was published
  • when it was updated

If you have to infer the entity, so does the machine.

Helpful additions:

  • author bio with expertise
  • reviewer where appropriate
  • organization page
  • contact and policy pages that prove the site is real
  • consistent brand naming across the site

Phase 4: content architecture

Answer-first structure

Each priority page should pass this test:

  • could a reader identify the direct answer within the first screen?
  • is the scope obvious?
  • do major subheadings map to real follow-up questions?
  • are comparisons and definitions easy to extract?

Good GEO pages reduce the amount of inference required.

Heading hierarchy

Check for:

  • one clear H1
  • meaningful H2s that reflect subtopics or user questions
  • H3s used for drill-down, not decoration
  • headings that describe the section content honestly

Avoid vague headings like "Why this matters" if ten different pages on the site use them to mean ten different things.

Text availability

Important details should exist in text, not only in:

  • images
  • tabs that never render server-side
  • accordions with inaccessible markup
  • PDFs without supporting HTML summaries
  • video-only explanations

Google explicitly advises making important content available in textual form.

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FAQ blocks

Use FAQs when they are real.

Good FAQ sections:

  • answer common objections or clarifications
  • add precise wording users actually ask
  • reduce ambiguity around scope, pricing, implementation, or edge cases

Bad FAQ sections:

  • repeat the same keyword three ways
  • answer invented questions nobody asks
  • exist only to stuff markup onto the page

Phase 5: evidence and trust

Source quality

For every important page, ask:

  • Are there named sources?
  • Are dates provided?
  • Is the scope of each claim clear?
  • Is the page honest about what is sourced versus what is interpretation?

The Princeton GEO paper found that citations, statistics, and quotations can improve visibility in generative responses. That should not surprise anyone. Sourced claims are safer to quote than unsupported assertions.

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Originality

Check whether the page adds anything beyond a generic summary.

Stronger assets include:

  • internal process detail
  • firsthand examples
  • original screenshots
  • implementation checklists
  • unique comparisons
  • proprietary data
  • expert commentary tied to real experience

If the page could be replaced by a competent AI summary with no loss of value, your GEO problem is not technical. It is editorial.

Freshness and maintenance

For pages that compete on recency, confirm:

  • update timestamps are visible
  • stale references are replaced
  • broken citations are removed
  • major platform changes trigger review

Freshness is not universal, but decay is real. An unmaintained guide becomes a bad citation candidate over time.

Phase 6: commercial and local completeness

For product, service, and local-intent pages, verify:

  • pricing or pricing logic is clear where appropriate
  • business profile details are current
  • merchant or ecommerce data is current where relevant
  • contact information is consistent
  • location and service-area details are explicit

Google specifically calls out keeping Merchant Center and Business Profile information up to date for AI features.

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Phase 7: measurement and operations

Search Console

Use Search Console to monitor:

  • clicks and impressions for priority pages
  • branded versus non-branded query changes
  • changes after major content rebuilds

Google says AI-feature traffic is included in Search Console's overall Web search reporting, so do not expect a separate neat bucket that solves attribution for you.

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Citation tracking

Create a recurring prompt set for your most important categories, then track:

  • whether your brand appears
  • which page gets cited
  • what type of page wins
  • whether the answer includes a supporting link
  • how often the same competitor appears instead

You are not looking for perfection. You are looking for patterns.

Governance

Assign owners for:

  • technical controls
  • source review
  • update cadence
  • high-value prompt library
  • reporting

GEO becomes unreliable fast when content, engineering, and analytics each assume someone else owns it.

The minimum viable GEO scorecard

If you need a simple starting scorecard, track:

  • percent of priority pages fully crawlable
  • percent of priority pages fully indexable
  • percent with relevant structured data
  • percent with author, update, and source sections
  • answer-engine citation coverage across priority prompts
  • assisted conversions on pages rebuilt for GEO

That is enough to move from opinion to operating discipline.

Final reminder

Most GEO failures are not caused by a missing AI trick.

They are caused by:

  • blocked bots
  • unclear pages
  • weak sourcing
  • derivative content
  • no operational follow-through

Fix those first.

Sources and further reading