The Comparative Effectiveness of llms.txt and JSON-LD in Large Language Model Optimization

Date: December 23, 2025

Subject: AI Data Interoperability and Content Optimization

Author: Andrew Benally

Abstract

As Large Language Models (LLMs) transition from static chatbots to autonomous "Agents," the method by which they consume web data has become a critical technical challenge. This report evaluates two primary standards: JSON-LD (a machine-readable code format) and llms.txt (a Markdown-based discovery format). While JSON-LD provides superior factual grounding for entity recognition, llms.txt offers significantly higher token efficiency and better navigation for real-time AI crawlers. We conclude that a hybrid approach is necessary for total "AI crawl bots and search engine optimization"

Introduction - llms.txt and JSON-LD in Large Language Model Optimization

Traditional websites are designed for human visual processing, filled with complex HTML, JavaScript, and navigation menus. For an AI, this "noise" creates a parsing burden that increases the risk of hallucination (Alimbekov, 2025). To solve this, developers use specialized data formats to communicate directly with AI. This report analyzes the two leading contenders in this space to determine which is most effective for modern AI integration.

Technical Overview: JSON-LD vs. llms.txt

JSON-LD: The Structural Dictionary

JSON-LD (JavaScript Object Notation for Linked Data) is a standardized code snippet used to define facts. It tells an AI, "This page is an Article written by Jane Doe on Jan 1st."

• Strengths: Highly predictable; used by Google and major LLMs for factual grounding (iunera, 2025).

• Weaknesses: It is "token-heavy"—it uses many characters (like brackets and braces) that count against an AI’s memory limit, often increasing costs by 15–20% compared to simpler formats (Khatter, 2025).

  
  

llms.txt: The AI Treasure Map

Proposed by Jeremy Howard in late 2024, the llms.txt file is a single Markdown document located at the root of a website (e.g., yoursite.com/llms.txt). It provides a concise summary and a list of links to the most important parts of the site (Howard, 2024).

• Strengths: Extremely easy for AI to "read" like a human; highly efficient for token usage (Internet Dzyns, 2025).

• Weaknesses: Newer standard; not yet officially adopted by all major search engines like Google (Alimbekov, 2025).

  
  

Comparative Effectiveness & Case Studies

Case Study 1: Navigation and Discovery (The Mintlify Study)

In 2025, early adopters of llms.txt, including platforms like Mintlify (used by Anthropic and Cloudflare), demonstrated that providing a "clean" Markdown map allows AI coding assistants to locate relevant information faster than searching through a traditional sitemap (Internet Dzyns, 2025).

• Finding: AI agents were able to bypass complex HTML menus entirely, reducing the "crawling time" and improving the relevance of the information retrieved (Howard, 2024).

  
  

Case Study 2: Factual Reasoning (Castillo & Tam et al.)

Research in late 2024 and mid-2025 tested whether AI models perform better when data is "structured" (JSON) or "unstructured" (Plain text).

• The Claim: Some studies suggested that forcing an AI to use structured formats can actually hurt reasoning because it makes the model "think" in code rather than logic (Castillo, 2025).

  
  

• The Rebuttal: However, follow-up tests showed that for factual tasks (like math or classification), JSON-Schema remains as good or better than natural language because it provides clear "guardrails" that prevent the AI from guessing (Castillo, 2025).

Case Study 3: Vector Search Accuracy (iunera Benchmark)

A 2025 benchmark by iunera compared "Vector Search" (how AI finds your site) with and without JSON-LD.¹⁰

• Result: Without JSON-LD, an AI might confuse a "bug fix" (code) with "insect repellent" (biology). Adding JSON-LD labels provided the "semantic context" needed to ensure the AI understood the meaning of the words, not just the letters (iunera, 2025).

  
  

Discussion: Is llms.txt or JSON-LD Better For AI Models?

The choice depends on your specific goal for the AI interaction.

Feature	JSON-LD	llms.txt
Best For	Fact extraction & Entity labeling	Navigating a site & Quick summaries
User Experience	Invisible to users	Can be read by humans
Accuracy	Higher for specific data points	Higher for finding the right page
Cost	More expensive (Uses more tokens)	Cheaper (Uses fewer tokens)

Conclusion

For beginners, JSON-LD is "better" for traditional SEO and factual reliability. However, llms.txt is "better" for the new world of AI Agents (like ChatGPT Search or Perplexity) because it is faster and cheaper for them to process.

References

• Alimbekov. (2025, July 17). What is an llms.txt file? Structure of llms.txt file.
  

• Castillo, D. (2025, May 20). Structured outputs can hurt the performance of LLMs.

  
  

• Howard, J. (2024, September). The llms.txt proposal: A standard for AI-friendly content.

  
  

• Internet Dzyns. (2025). Understanding the LLMs.txt File: A Game-Changer for AI-Friendly Websites.

  
  

• Iunera. (2025, June). How Markdown & JSON-LD improves NLWeb Vectorsearch RAG. 
  

• Khatter, K. (2025, August 17). Markdown: A Smarter Choice for Embeddings Than JSON or XML.