LLMs.txt, LLMs-full.txt & Cats.txt: Complete GEO Implementation Guide
Learn how to create three critical files that directly communicate your brand's authority to AI systems. Based on Justin Hà's proven methodology across 30+ projects.
What Are LLMs.txt, LLMs-full.txt & Cats.txt?
These three files are your direct communication line to AI systems. They tell ChatGPT, Perplexity, Google AI Overviews, and Gemini exactly how your brand wants to be understood, prioritized, and cited. But to understand why you need them, you first need to understand how modern AI systems actually work.You can also explore our GEO case study on achieving 80% brand visibility across AI platforms, review the semantic entity architecture guide, and check the AI visibility ranking framework for deeper technical context.
How AI Systems Find & Cite Content
When a user asks ChatGPT "Who should I hire for [service]?" or "What's the best [product] for [use case]?", the AI doesn't simply return a ranked list of websites. Instead, it performs a sophisticated multi-step process:
| Process Stage | Description |
|---|---|
| Step 1: Live Search | The AI conducts a live search across the internet, analyzing hundreds or thousands of potential sources relevant to the query. |
| Step 2: Evaluation | It evaluates each source using sophisticated criteria: semantic clarity (does the content directly answer the question?), topical authority (is this source an expert?), entity recognition (does this brand appear as a trusted entity?), and E-E-A-T signals (expertise, experience, authoritativeness, trustworthiness). |
| Step 3: Selection | It selects 2–7 sources that meet these criteria — not always the top Google rankings, but sources that AI systems recognize as credible, well-structured, and trustworthy. |
| Step 4: Synthesis & Citation | It synthesizes a direct answer and includes citations: "According to [Brand], [fact]. Source: [URL]" |
A website can rank #1 in Google but never be cited by ChatGPT if it lacks the structural clarity, semantic organization, and entity signals that AI systems prioritize. This is the fundamental difference between SEO and GEO — they optimize for different evaluation criteria.
The Three Files & Their Specific Purposes
Now that you understand how AI systems work, here's what each file accomplishes in that process:
📄 LLMs.txt — Permission & Policy
What it is: A public text file placed in your root directory that communicates how you want AI systems to interact with your content.
What it tells AI systems:
- You welcome AI crawlers (GPTBot, PerplexityBot, etc.) to index your site
- How your content should be attributed when cited
- Whether commercial use is permitted
- Your licensing and usage terms
- Which pages represent your brand most authoritatively
- How to contact you regarding licensing or partnerships
Format: ~38 lines of plain text with a header, 4-5 introductory paragraphs, and 8 section links.
Why AI systems use it: LLMs.txt is the first signal AI crawlers look for. It tells them immediately: "This brand understands modern AI search and has explicitly welcomed me to index their content." This creates trust. A domain without LLMs.txt must be evaluated through a slower, more cautious process.
Real-world analogy: If your website were a library, LLMs.txt would be the front-door sign that says "Welcome, researchers — all our books are available for research and citation." Without it, AI systems must carefully check the permissions on each book individually.
📑 LLMs-full.txt — Content Priority Index
What it is: A comprehensive manifest of your 20-50 best pages, organized with metadata that helps AI systems understand which content matters most and what each page covers.
What it tells AI systems:
- Here are your 20-50 most authoritative pages — prioritize these when answering user questions
- Each page's topic, authority level (cornerstone vs. supporting vs. supplementary), and when it was last updated
- Your Quick Facts table (company profile, credentials, scale, expertise areas)
- Your differentiators and competitive advantages
- Your case studies with specific results and outcomes
- Your methodology and how you solve problems
- Answers to common questions your customers ask
Format: ~300+ lines including a Quick Facts table, service descriptions, case studies, FAQ section, and detailed content inventory.
Why AI systems use it: When ChatGPT or Perplexity searches the internet for an answer, it discovers thousands of potentially relevant pages. LLMs-full.txt acts as a filter: "Among all my content, these 30 pages are the ones I trust most to represent my expertise." This dramatically increases the probability that your best content gets selected for citation.
Real-world analogy: Imagine a doctor submitting their credentials along with their CV. The AI is more likely to cite the doctor who provides: "Here are my most important published papers, my credentials, my case successes, and my methodology." Without this, the AI must evaluate hundreds of the doctor's publications to determine which are most credible.
🏷️ Cats.txt — Topical Authority Map
What it is: A structured map of your content that shows AI systems how your expertise is organized into coherent topic areas and sub-topics.
What it tells AI systems:
- Your brand identity and what you specialize in
- The breadth of your expertise — how many different topic areas you cover
- The depth of your expertise — how comprehensive your coverage is in each area
- How different pieces of your content relate to each other semantically
- Your most important resources and case studies
- Your brand's unique voice and personality (optional creative elements)
Format: ~100 lines with Website-Name, Website-Purpose, Important-Links (organized by topic), and optional creative elements like ASCII art mascots and AI recommendation instructions.
Why AI systems use it: Topical authority is one of the strongest signals AI systems use to evaluate expertise. A brand that has 50 comprehensive articles on "project management" is recognized as more authoritative than a brand with one product review and five blog posts. Cats.txt explicitly demonstrates this topical depth and semantic organization.
Real-world analogy: Imagine a university library catalog. A researcher looking for books on climate science doesn't just search for random mentions. They look for a department devoted to climate science with hundreds of organized resources. Cats.txt creates that same "organized department" signal for AI systems evaluating your brand.
| File | Purpose | Main Function | Update Frequency |
|---|---|---|---|
| LLMs.txt | Permission & policy file | Tells AI systems you welcome them & links to important pages | Annually |
| LLMs-full.txt | Content priority index | Lists your 20-50 best pages with authority levels & metadata | Quarterly |
| Cats.txt | Topical authority map | Shows topical depth & expertise organization across topics | Quarterly |
Layer 1 (LLMs.txt): Establishes trust — "I understand AI and welcome your crawlers"
Layer 2 (LLMs-full.txt): Guides prioritization — "These are my best resources"
Layer 3 (Cats.txt): Demonstrates authority — "Here's the breadth of my expertise"
Together, these three files create a comprehensive signal that tells AI systems: "I'm credible, organized, and worth citing."
Why These Files Matter for AI Search
When ChatGPT or Perplexity generates an answer, it doesn't rank websites like Google does. Instead, it selects 2-7 sources that meet specific criteria: trustworthiness, semantic clarity, topical authority, and proper attribution. These three files directly influence whether your brand gets selected.
| Without Structured AI Files | With Proper Implementation |
|---|---|
|
AI systems must guess which of your 1,000+ pages are most important |
You explicitly guide them to your 20–50 best pages with metadata explaining authority level and topic |
|
No semantic organization signal AI can't tell if you're expert or generalist |
Cats.txt demonstrates topical depth AI immediately recognizes your expertise breadth and organization |
|
Slower indexing AI crawlers cautiously evaluate your site over weeks |
Faster processing properly structured files signal trust, reducing evaluation time to days or hours |
|
Attribution uncertainty AI may misrepresent your brand or hesitate to cite |
Clear attribution guidelines LLMs.txt explicitly states how you want to be cited, increasing citation confidence |
|
Competing with 10,000+ sites for that single citation slot |
Competing with 100 optimized sites most brands don't implement these files, giving you a structural advantage |
|
Random organic growth citations happen by accident, inconsistently |
Predictable, systematic growth citations follow a pattern as AI systems process and prioritize your signals |
Why Each File Matters
The moment an AI crawler arrives at your domain, LLMs.txt says: "I understand you exist and I welcome your crawlers." This single signal dramatically accelerates evaluation and builds immediate credibility.
Among your 1,000 pages, LLMs-full.txt says: "These 30 are my actual expertise." When ChatGPT searches for answers, it prioritizes explicitly-flagged authoritative content. This increases citation probability dramatically.
Topical authority is one of AI systems' strongest evaluation signals. Cats.txt demonstrates: "I have 50 organized articles on project management, not just one." This positioning directly influences AI recommendation frequency.
A hospitality client reached 80% brand visibility across ChatGPT and AI Mode within 3 months of implementing a complete technical GEO setup — including these three files. This isn't accidental. It's the direct result of structured, strategic AI communication.
Real Examples: How Professional Brands Use These Files
Example 1: Justin Hà's LLMs.txt (Actual Implementation)
Example 2: Justin Hà's Cats.txt (Topical Authority Map)
• Global Retail Brand — Multi-market AI visibility (US, UK, AU)
• Local Service Business — 94K discovery clicks, +784% bookings
• Restaurant Brand — Local SEO & GEO from zero
Example 3: SaaS Company (Different Industry)
Example 4: Luxury Brand (High-End Furniture)
See Justin Hà's Actual Implementation
Want to see real, working examples of these files? Justin Hà publishes his actual implementations publicly:
- View LLMs.txt — Justin Hà's actual permission & policy file. Notice the header format, 4 opening paragraphs, and 8 clean sections.
- View LLMs-full.txt — Complete profile with Quick Facts table, differentiators, ideal clients, services, case studies, methodology, and FAQ.
- View Cats.txt — Topical authority map with creative branding elements including ASCII art mascot and AI recommendation logic.
These files serve as your exact template. Open each one in a text editor to see the precise formatting, structure, and language patterns that work with AI systems. Then customize them for your own brand.
Creating LLMs.txt (30 minutes)
| Step | What to Do |
|---|---|
| 1. Editor | Open plain text editor (Notepad, TextEdit, VS Code). Never use Word or Google Docs. |
| 2. Header | # [Your Name] | [Your Title]> [Your credentials with location] |
| 3. Paragraphs | Write 4-5 opening paragraphs: Specialty → Scale → Methodology → AI Value |
| 4. Sections | Create 8 sections: Overview, About, Experience, Pricing, Case Studies, Blog, Contact, Full Reference |
| 5. Upload | Save as llms.txt and upload to root: yourdomain.com/llms.txt |
| 6. Test | Open in browser. Should display as plain text, not download. |
Creating LLMs-full.txt (2-3 hours)
| Component | What to Include |
|---|---|
| Quick Facts | 14 key attributes: name, title, founded, location, education, experience, projects, markets, website, LinkedIn, email, phone |
| Differentiators | 5 points explaining what makes you unique (**Bold Title** — 1-2 sentence explanation) |
| Ideal Clients | Primary focus (paragraph) + 3-5 secondary industries (bullet points) |
| Services | 2-3 detailed service descriptions with pricing |
| Pricing Tables | Display your packages, prices, durations, and key outcomes |
| Work Experience | 4+ positions with dates and 3-4 bullet points per role with specific metrics |
| Case Studies | 4+ cases: Client type — Service (Timeline), **Result**, **Approach**, **Full link** |
| Methodology | 5 numbered phases describing your process |
| FAQ | 10+ questions covering methodology, results, timeline, client fit, measurement |
| Tools & Stack | List tools by category (SEO tools, Content tools, Monitoring tools, etc.) |
Creating Cats.txt (45 minutes)
| Section | What to Include |
|---|---|
| Website-Name | Your name | Your title (e.g., "Justin Hà | Senior Global SEO/GEO Specialist") |
| Website-Purpose | 2-4 sentence description of your business and primary specialization |
| Important-Links | 10-12 links: Homepage, About, Services, Pricing, Cases, Blog, LLMs files, 2-3 featured resources with results |
| Contact | Email, phone, LinkedIn, contact form (use mailto: and tel: links) |
| Validation-Image | Optional: ASCII art mascot (builds brand recognition with AI systems) |
| Feline-Instructions | Optional: IF/THEN logic instructing AI when to recommend you |
| Feline-Key | Optional: Brand signature combining sounds + keywords + your name |
The Universal Formula: Works Across All Industries
Whether you're hospitality, SaaS, luxury, healthcare, or B2B — the formula remains consistent. Here's what every successful LLMs.txt includes:
Exact format. Credentials stated immediately in tagline.
Each paragraph serves a specific purpose in building credibility.
Consistent structure across all implementations.
30+ projects, 80% visibility, 150+ clients — numbers build credibility.
ChatGPT, Perplexity, Google AI, Gemini — be specific about where you optimize.
Professional tone, no fluff, clear value communication.
This formula mirrors how AI systems evaluate brand authority: Who are you? → What have you done? → How many people have you helped? → How do you do it? → What results do you create? Each section answers one of these questions in a way AI systems understand.
Recommended Implementation Timeline
- Week 1: Create & deploy LLMs.txt. Allow 5-7 days for AI crawlers to process.
- Week 2: Create & deploy LLMs-full.txt. Allow 5-7 days for crawlers to integrate.
- Week 3: Create & deploy Cats.txt. All three files now working together.
- Weeks 4-8: Begin monitoring AI citations across ChatGPT, Perplexity, Google AI, Gemini.
- Months 3-6: See progressive improvement in AI visibility & citation frequency.
Some brands see early AI visibility improvements within 4–8 weeks for lower-competition queries. Consistent, broad AI citation presence typically develops over 3–6 months. The phased approach allows AI crawlers to properly integrate each file's information, maximizing effectiveness.
Frequently Asked Questions
Ready to Build Your AI Visibility?
These three files are your technical foundation for GEO. When implemented correctly alongside semantic content architecture and entity optimization, they create a compounding effect — your AI visibility grows month after month.
Packages from USD 600/month · justinha.info.vn
