Analyzes server access logs to identify search engine crawl patterns and optimize crawl budget efficiency.
This skill empowers developers and SEO professionals to transform raw server logs into actionable insights by automatically parsing Nginx and Apache access logs. It identifies specific bot behaviors—including Googlebot and emerging AI crawlers—while highlighting critical issues like 404 error patterns, redirect chains, and crawl budget inefficiencies. By generating comprehensive markdown reports and visual summaries, it helps users ensure that search engine spiders are focusing on high-value content rather than wasted technical overhead.
Key Features
012 GitHub stars
02Detailed detection of Googlebot, Bingbot, and emerging AI crawlers like GPTBot
03Trend analysis for crawl frequency by URL path and time of day
04Generates comprehensive LOGFILE-ANALYSIS.md reports with optimization recommendations
05Identification of crawl budget waste including 404 patterns and redirect chains
06Automated parsing of Nginx and Apache combined access log formats
Use Cases
01Auditing server resources consumed by aggressive AI scrapers and bot user agents
02Identifying why specific pages aren't being indexed by checking Googlebot crawl frequency
03Reducing crawl budget waste by locating dead links that search engines frequently visit
