RankMath vs. EZY.ai: Why Your llms.txt Needs Engineering- What Gemini Said
Recently, a prospective client- a multinational tech company with 600 developers and $100M in ARR signed up to EZY.ai. They wanted our full suite of tools but planned to exclude our llms.txt generation. Their reasoning? "We already use RankMath to generate that file."
We love a challenge. So, we put it to the test.
We took the RankMath-generated file and the EZY.ai-generated file for the same domain and asked Google's Gemini Pro to rate them based on modern best practices for Large Language Models (LLMs).
The results were not close.
Here is what Google Gemini said for RankMath Vs EZY.ai
The Verdict: Google Gemini's Analysis
1.RankMath Version (The "Live" Site) Score: 32/100
The Diagnosis: "This is not an llms.txt file; it is a standard SEO Sitemap formatted as Markdown. Rank Math has simply taken their existing logic for Googlebot (a crawler) and applied it to an LLM (a reasoning engine). This is a fundamental misunderstanding of how LLMs work."
- The "Context Killer": The inclusion of generic terms like "Petty Cash," "Print Preview," and "Warehouse" is catastrophic for LLM optimization.
- Why it fails: Gemini noted, "An LLM has a limited 'attention span' (context window). By filling 50% of the file with definitions the AI already knows, you dilute the importance of the actual client-specific content."
- Zero Instruction: There is no "System Prompt" or "Key Notes" section. The file assumes the AI knows what to do with the links.
- Flat Architecture: The "Posts" section is a dump of 30+ mixed topics. The AI has to process "TikTok" next to "Warehouse" without knowing which is more important.
- The Result: The AI is less likely to see your "Best Products of 2026" because it is wading through definitions of "Inventory."
2. EZY.ai Version Score: 94/100
The Diagnosis: This is a Knowledge Graph designed for an AI agent. It is structured, prioritized, and instructional.
Instructional Layer: The "Key Notes" section is the most valuable part of the file. It tells the LLM how to behave (Citation Policy) and what to trust (Trust & Safety Signals).
Intent-Based Categorization: You moved away from "Posts vs. Pages" (technical structure) to "Core Guides vs. Strategy vs. Compliance" (semantic structure).
This allows the LLM to instantly route a user asking "Is [Client] safe?" to the Trust & Compliance section, rather than hallucinating based on a blog post.
Trust Signals: Explicitly citing ScamAdviser and the SFA (Supplier Fulfillment Agreement) is a master move for RAG (Retrieval-Augmented Generation). It gives the AI "proof" to defend the brand against skepticism.
Why Does This Matter? (The Business Case)
So one file is structured better. Why does that matter for my bottom line?
For AI Agents Answer Engines (ChatGPT, Google Gemini, Perplexity), your llms.txt can significantly help your brand's voice..
- Protect Your Reputation: A low score (32/100) means the AI is guessing. It might cite a random blog comment instead of your official policy. EZY's structure ensures the AI cites your Trust & Compliance documents first.
- Control the Narrative: When the AI "hallucinates," you lose customers. By using EZY.ai's "Instructional Layer," we explicitly tell the AI how to sell your product and what to ignore.
- Enterprise-Grade Security: We don't just list links; we provide Trust Signals. As Gemini noted, citing official documents explicitly is a "master move" that gives the AI "proof" to defend your brand against skepticism.
The takeaway: A plugin creates a map. EZY.ai creates a manual.
The EZY.ai Difference: PhD-Led Deterministic Logic
At EZY.ai, we don't rely on generic automated scripts. Our approach to AEO (Answer Engine Optimization) is built on deterministic logic.
Our team, led by PhDs in data science and AI architecture, engineers your llms.txt to function as a rigid set of instructions for fluid AI models. We don't hope the AI understands your business; we program the file structure to force it to understand.
When you use EZY.ai, you aren't just getting a text file. You are getting a semantic architecture designed to maximize your visibility and authority in the AI-driven future.
Control how AI explains your business.
Get Your Free LLM Scorecard; https://www.ezy.ai
Contact EZY.ai Sales; j@ezy.ai
Feature Comparison
| Feature | Rank Math (Live) | Your Version | Why Yours Wins |
|---|---|---|---|
| Philosophy | "Index Everything" | "Curate the Best" | LLMs need relevance, not volume. |
| Structure | Flat List | Semantic Hierarchy | Helps the AI understand relationships between topics. |
| Glossary | Bloated (Generic terms) | Removed (Focus on strategy) | Saves tokens for high-value content. |
| Instructions | None | Detailed "Key Notes" | Prevents hallucinations and sets citation rules. |
| Security | None | Explicit Trust Signals | Builds credibility with the AI. |
