GitHub.com scored 80/100 in the latest probe on August 22, 2026, ranking 6th among 10 well-known sites. This score reflects strong visibility, with 4 out of 5 core signals passing, indicating readiness for AI-generated answers.
How does GitHub's score compare within the panel?
In the context of our panel, GitHub ranks 6th out of 10 with a score of 80/100. The panel's average score is 77.3, with a median of 90. This positions GitHub slightly above average but below the median. Top performers like Cloudflare, Stripe, and Vercel achieved perfect scores of 100, highlighting areas where GitHub could improve.
What did the probe observe about GitHub's AI readiness?
The probe indicates strong AI readiness for GitHub. The homepage is accessible to AI crawlers, returning HTTP 200 with approximately 7,129 characters of server-rendered text. Major AI crawlers like GPTBot and ClaudeBot can access key pages, and the presence of a well-formed /llms.txt file ensures AI engines have a map to the content. However, the homepage lacks a JSON-LD schema, which could enhance entity recognition by AI engines.
How has GitHub's score fluctuated over time?
Our probe history for GitHub shows a range of scores from 35 to 80 since July 13, 2026. Recent readings display a pattern of fluctuation, with scores alternating between 80 and 70, and a notable dip to 35 on August 19. This variability suggests that while GitHub maintains strong visibility, there are occasional lapses that impact its score.
What can other business sites learn from GitHub's performance?
GitHub's performance highlights the importance of AI readiness for maintaining strong visibility. Ensuring AI crawlers can access key pages and providing a well-structured /llms.txt file are critical steps. However, the absence of a JSON-LD schema on GitHub's homepage underscores a common oversight. Business sites should prioritize implementing structured data to enhance AI engines' understanding of their content.
What are common challenges in the panel?
The panel reveals that AI-crawler reachability, GPTBot/ClaudeBot access, and /llms.txt implementation are common challenges, with all 10 sites passing these signals. This suggests a growing recognition of the importance of AI readiness across the industry. However, structured data like JSON-LD remains an area for improvement, as evidenced by GitHub's failure in this aspect. Addressing these challenges can help sites improve their scores and visibility in AI-generated content.
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