geo/aeoplaybooks

wikipedia.org ranks 9 of 10 in panel, score 65/100

On 2026-10-13, wikipedia.org scored 65/100, ranking 9th in a panel of 10 sites.

How this note was made: an LLM drafted it automatically from our own probe logs (the hourly GEO Pulse data), and it was published without line-by-line human editing. Every number comes from those logs; the method is on the methodology page.

GEO & AEO Playbooks wikipedia.org ranks 9 of 10 in panel, score 65/100 geo/aeo playbooks · independent GEO lab

Wikipedia.org scored 65/100 in our latest probe on 2026-10-13, placing it 9th in a panel of 10 well-known sites. The domain shows partial visibility, with key areas needing improvement to enhance its presence in AI-generated answers.

How does wikipedia.org compare to the panel?

In the current panel of 10 sites, wikipedia.org ranks 9th with a score of 65/100. The panel's average score is 80.3, and the median score is 90/100, indicating that most sites perform significantly better in visibility metrics. High performers like cloudflare.com, stripe.com, and vercel.com achieve perfect scores of 100/100, setting a strong benchmark for others. Wikipedia.org's position highlights room for improvement, especially in areas where other sites excel.

65/100wikipedia.org score
80.3/100panel average score
9 of 10panel rank

What does OUR PROBE HISTORY reveal?

Our probe history for wikipedia.org shows two recorded assessments since 2026-09-25, with scores ranging from 20 to 65 out of 100. The most recent readings indicate an improvement from an initial score of 20 to 65, suggesting some progress in addressing visibility issues. However, the current score still reflects partial visibility, indicating that more work is needed to reach the panel's average performance.

What did the probe see on 2026-10-13?

The latest probe identified several key findings. The homepage is reachable by AI crawlers, returning an HTTP 200 status with approximately 8,764 characters of server-rendered text, ensuring retrieval bots can access content. Major AI crawlers like GPTBot, ClaudeBot, and PerplexityBot have access to key pages, as there is no blanket disallow for these bots. However, the absence of a /llms.txt file means engines lack a curated map to the best content, forcing them to guess. Additionally, the homepage lacks a JSON-LD schema, making it difficult for engines to identify the type of entity represented.

What should a normal business site learn from this?

Business sites aiming to improve AI visibility should ensure their pages are accessible to AI crawlers and major bots. Implementing a /llms.txt file can guide engines to your best content, enhancing visibility in AI-generated answers. Adding a JSON-LD schema on the homepage can clarify the site's entity type, improving search engine understanding. These steps can help achieve scores closer to the panel's average and improve overall visibility.

Run the same 5-signal probe on your own domainThis note came out of the hourly GEO Pulse board. The free checker runs the identical probe on any site, and Monitor re-runs it every month.

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