Analyse server logs for crawler visits

Prompt that reads crawler visits from server logs and shows neglected pages and wasted crawl paths. Paste it into an AI tool of your choice, which then analyses the crawler visits.

Topic: SEO & website copy
Type: Prompt
Level: Intermediate
Time: about 15 min

Results depend on the tool, the model and what you enter.

Result preview

Example: written by our editors, not real AI output.

| Page type | Visits | Share 200 | | Filter addresses | 4,820 | 98% | | Product pages | 1,140 | 91% | | Old redirects | 960 | – | Neglected: 38 new categories, no visit in 14 days Measure 1: block sort and filter parameters Measure 2: link new categories from the menu

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WebsiteWhat kind of website?

QuestionWhat do you want to find out?

LogsWhich logs do you have?

Your prompt

Help me analyse server logs for search engine crawler visits.
Website: [Website]
Question: [Question]
Logs: [Logs]
Approach: 1. Filter the lines for known search engine crawlers and explain how to verify that a visitor really is one. 2. Count visits per page type, status code and day. 3. Find important pages that crawlers rarely or never visit. 4. Find crawl time spent on redirects, errors, parameter addresses and pages without value. 5. Compare the most visited pages with the pages that should rank. 6. Propose changes in the order of their effect, such as internal links, blocking parameters or fixing error pages.
Output: summary table by page type and status code, list of neglected important pages, list of wasted crawl paths and sorted measures.

Take particular care to verify crawlers, protect personal data and sort measures by effect.

Before you answer, check: Are all instructions met? If key information is missing or a placeholder in square brackets is still in the text, ask instead of guessing. Mark assumptions as assumptions.

Help me analyse server logs for search engine crawler visits.
Website: [Website]
Question: [Question]
Logs: [Logs]
Approach: 1. Filter the lines for known search engine crawlers and explain how to verify that a visitor really is one. 2. Count visits per page type, status code and day. 3. Find important pages that crawlers rarely or never visit. 4. Find crawl time spent on redirects, errors, parameter addresses and pages without value. 5. Compare the most visited pages with the pages that should rank. 6. Propose changes in the order of their effect, such as internal links, blocking parameters or fixing error pages.
Output: summary table by page type and status code, list of neglected important pages, list of wasted crawl paths and sorted measures.

Take particular care to verify crawlers, protect personal data and sort measures by effect.

Before you answer, check: Are all instructions met? If key information is missing or a placeholder in square brackets is still in the text, ask instead of guessing. Mark assumptions as assumptions.

This is an instruction for an AI, not the result itself.

Where this prompt works

These AI tools are a good fit for this prompt:

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How to use it

Fill in the fields or tap a suggestion. Leave out names, addresses and other personal data.
Copy the finished prompt into an AI tool of your choice.
Paste a sample of log lines with IP addresses shortened or removed; keep date, address, status code and user agent.

Why does this work?

Search tools show what crawlers report; server logs show what they actually did. The gap between the two often explains slow indexing.

Tips

Logs can contain personal data; shorten IP addresses and remove query strings with personal values before analysis.

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Analyse server logs for crawler visits

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