LLM.txt & AI Crawler Setup Guide for News websites
An authoritative technical manual for configuring your news website's architecture to selectively allow, route, and optimize data ingestion by specialized LLM news crawlers.
High Priority
Deploy /news-crawl.txt Protocol
Establish a machine-readable summary of your entire news site hierarchy specifically for AI news agents.
Create a text file at /news-crawl.txt with a brief intro of your news publication's focus and editorial standards.
Include markdown-style links to your most important content verticals (e.g., Politics, Business, Technology) and investigative journalism archives.
Add a 'FAQ' section in the file to answer common training bot queries directly regarding sourcing, fact-checking protocols, and author credentials.


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High Priority
News Bot Selective Indexing
Fine-tune which sections of your news website should be ingested by AI news crawlers (e.g., Google's Search Generative Experience, Perplexity).
User-agent: News-Agent Allow: /breaking-news/ Allow: /investigations/ Disallow: /opinion-pieces/ Disallow: /sponsored-content/
Verify your crawler permissions using a simulated bot checker tool.
Monitor crawl frequency in your server logs to ensure AI news bots are accessing relevant, high-value content sections and not just evergreen archives.
Medium Priority
Semantic Article Structure
Utilize HTML5 semantic elements to help LLM news scrapers understand the hierarchy and context of your news articles.
Wrap your main news content within `<article>` tags to signal its primary importance.
Use `<section>` with descriptive 'aria-label' attributes for different thematic parts of an article (e.g., 'Background', 'Key Quotes', 'Expert Analysis').
Ensure all data tables (e.g., election results, financial reports) use proper `<thead>` and `<tbody>` tags for structured data extraction.
High Priority
RAG-Friendly Article Snippet Optimization
Structure your news articles so they can be easily 'chunked' and retrieved by Retrieval-Augmented Generation (RAG) pipelines for AI-generated summaries and Q&A.
Keep conceptually related information within distinct paragraphs or sub-sections, ideally under 500 words per logical unit.
Avoid ambiguous references; ensure pronouns clearly refer to named entities (people, organizations, locations) within the text.
Explicitly state the primary subject or event being reported at the beginning of each significant paragraph or section to aid context retention.
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