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Blog post details method to track LLM bot access to web content

A blog post details a method for analyzing web server logs to identify which large language model (LLM) crawlers are accessing specific files, such as "llms.txt" and "llms-full.txt". The process involves filtering Nginx access logs to isolate requests for these files, then grouping and counting the user agents to categorize them into known bots like GPTBot, ClaudeBot, PerplexityBot, and Googlebot, alongside a general "Other" category. This analysis provides direct insight into the traffic patterns of these AI-related bots without relying on dashboards. AI

IMPACT Provides a method for understanding which AI crawlers are accessing specific web content.

RANK_REASON Blog post explaining a technical method for analyzing web server logs.

Read on dev.to — LLM tag →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

Blog post details method to track LLM bot access to web content

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5 / 100
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Blog post explaining a technical method for analyzing web server logs.
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2 independent sources
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other
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Standard
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COVERAGE [2]

  1. Mastodon — fosstodon.org TIER_1 English(EN) · [email protected] ·

    Checking who touches llms.txt in practice /llms.txt and /llms-full.txt have been live on richardlemon.com for a while. The obvious next question: who, if anyone

    Checking who touches llms.txt in practice /llms.txt and /llms-full.txt have been live on richardlemon.com for a while. The obvious next question: who, if anyone, is actually requesting them? One way to approach that is to look at the web server logs directly. No dashboards, no vi…

  2. dev.to — LLM tag TIER_1 English(EN) · Richard Lemon ·

    Who actually reads my llms.txt?

    <h2>Checking who touches <code>llms.txt</code> in practice</h2> <p><code>/llms.txt</code> and <code>/llms-full.txt</code> have been live on richardlemon.com for a while. The obvious next question: who, if anyone, is actually requesting them?</p> <p>One way to approach that is to …