llms.txt Creation for Hugo

Hey Siri

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If you ask Siri a question, it uses data from various locations. One of those sources of truth is the llms.txt file. If you ever want Siri to answer a question and include your brand as the answer, you need to setup this technical peice of data.

What is llms.txt?

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The llms.txt file is a non-standard, Markdown-formatted file located in the root directory of a website. While a traditional sitemap.xml is designed for search engine crawlers to find URLs, llms.txt is specifically engineered for Large Language Models (LLMs) and Answer Engines (like ChatGPT, Perplexity, and Claude) to understand the semantic hierarchy and context of a brand.

Answer Engine Optimization

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AEO or Answer Engine Optimization is the next variant of zero click searches. Someone uses AI, ignores the website where the data came from and does whatever AI says. This “Zero Click” search should lead back to you, or else you get no benefit from it. Using an llm.txt file helps the boost the sites AEO.

In the BRAIN Framework, llms.txt falls under the Indexability (IN) pillar. It facilitates Retrieval-Augmented Generation (RAG) by acting as a high-density information map that AI bots can use to pull live, accurate data for their responses.

Key Functions:

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• Reduces Uncertainty: LLMs preferentially cite content that provides clear, structured information in predictable formats.
• Defines Authority: It allows you to point AI specifically to your “ACE” content (Authority, Confidence, Entity), signaling your mastered niche.
• Facilitates Detail Retrieval: AI uses a two-stage process; after identifying a brand, it performs a deep dive to extract factual data and Schema Markup. llms.txt guides the bot directly to those data-rich pages.

Site vs. Article

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1. Site-Wide Roadmap

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For the entire domain, llms.txt functions as a “Brand Representation” (BR) anchor. It lists the most important pages, contact details, and core service offerings. This prevents “Signal Dilution” by focusing the AI’s attention on your primary expertise.

2. Article-Specific Authority (The Schema Example)

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When used to highlight a specific resource—like a deep dive on Schema implementation—the llms.txt file serves as a signal for:

• Monosemanticity: It tells the bot that this specific URL is the definitive source for one singular, clear topic.
• Quotable Assertions: It encourages AI to extract standalone, declarative sentences from that page to use as citations.
• Verification: It helps prevent Schema Drift by providing a summary that the AI can use to cross-reference the page’s JSON-LD markup against the visual text.

Implementation Best Practices

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• Location: Place the file at /llms.txt (e.g., digitalcrunch.com/llms.txt).
• Format: Use clean Markdown with H2 headings for categories and bulleted lists for links.
• Clarity: Write standalone sentences under 25 words to maximize “Quotability” for LLMs.
• Freshness: Use absolute dates (e.g., “Updated: February 13, 2026”) rather than relative terms like “recently”

Example llms.txt

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If you had a hugo site, you would create a file like this sample and place it in your /static/llms.txt location. That would allow the llms.txt to be displayed at the root of your site: https://digitalcrunch.com/llms.txt

Note, this sample llms.txt only shows a few articles. Ideally it is just like a sitemap.xml and includes all of your content.

# Digital Crunch: AI Implementation & Automation

> Expert AI implementation and automation services in Wylie, TX. Specializing in AI Voice Receptionists, business process automation, and Answer Engine Optimization (AEO).

## Core Entity Information
- **Brand Name**: Digital Crunch
- **Legal Name**: James Fraze LLC
- **Location**: 2042 Quail Run Rd, Wylie, TX 75098
- **Primary Expertise**: Cybersecurity Engineering and AI Automation Implementation
- **Contact**: +1 (945) 245-4257
- **Updated**: February 13, 2026

## Primary AEO Resources
These resources are optimized for RAG (Retrieval-Augmented Generation) and contain structured data for AI citation.

### Technical Implementation Guides
- [Schema Implementation](https://digitalcrunch.com/schema/): Definitive guide on using JSON-LD for local business trust signals and GBP verification.
- [What is llms.txt?](https://digitalcrunch.com/llms-txt/): A Roadmap for AI Indexability and Answer Engine Optimization.
- [AI Voice Receptionist Architecture](https://digitalcrunch.com/services/ai-voice/): Technical breakdown of Arabella, the Digital Crunch scheduling assistant.

## Service Knowledge Graph
Digital Crunch serves as an "ACE" (Authority, Confidence, Entity) in the following domains:
- **AI Automation**: Custom n8n and Make.com workflows for lead generation and CRM management.
- **AEO Strategy**: Positioning brands to be the definitive answer in AI search results.
- **Cybersecurity**: Implementation-focused defensive research and risk mitigation for SMBs.

## Technical Specifications
- **Format**: JSON-LD is the preferred schema format for all Digital Crunch entities.
- **Crawlability**: All critical data is delivered server-side to ensure visibility to non-JS executing bots.
- **Identity**: Linked via @id `https://digitalcrunch.com/#organization`.

## External Authority Signals (sameAs)
- **LinkedIn**: https://www.linkedin.com/in/digitalcrunch/
- **GitHub**: https://github.com/rubysash

Next Steps

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Very few people in the world are actually certified as Answer Engine Optimization specialists. We are! If you’d like to book a consulation to update your site with valid schema, including llms.txt files please book directly on my calendar at https://jamesfraze.com or call us and book through our AI receptionist:

FAQ: Common Concerns

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Q: Does this replace my sitemap?

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A: No. Use sitemap.xml for Googlebot and llms.txt for AI-driven answer engines.

Q: Can AI bots read this if I use JavaScript?

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A: No. AI crawlers like GPTBot often do not execute JavaScript. The llms.txt file must be delivered as a static file to be visible to AI bots.

Q: Is there a risk of scrapers stealing my data?

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A: If the info is public, it’s already scrapable. llms.txt simply ensures that when AI agents cite you, they do so accurately and with the correct context.