AI Visibility Scorecard
colourcoding.net · Technology
Somewhat visible. AI bots can read Colour Coding, but it is missing the structured signals that push citation rate above competitors.
AI engines read this profile 4 times
Claude · Apple Intelligence
#181,332 of 2,705,019 in Technology for AI visibility
6
AEO Visibility
iBorderline · 5.9/10
5
Muse Index Score
iAI agent readiness
Basic · 5/100
4
AI Adoption
iBasic · 4/100
from our crawl and measurement
Colour Coding works in Technology. To AI engines like ChatGPT and Perplexity it is partially visible, scoring 5.9 out of 10, readable in places and missing in others.
Our crawl found a sitemap and a readable heading structure. It is missing structured data describing the business and an llms.txt file.
AI crawlers have visited 3 times in our tracking, including ClaudeBot (Anthropic) and Applebot (Siri).
Strong · Good · Fair · Weak
Structured Data
Weak
Organization / LocalBusiness JSON-LD that AI can read.
Content Structure
Strong
Clear headings and answer-style content.
Entity Clarity
Fair
How clearly your brand identity reads to AI.
E-E-A-T Signals
Experience, Expertise, Authority, Trust
Fair
Experience, Expertise, Authority, Trust markers.
Technical AEO
Good
robots.txt, llms.txt, and AI-bot crawl access.
AI Discoverability
Strong
Sitemaps and entity links AI can follow.
How the web signals your brand to AI
Backlinks
Strong
Inbound links from other sites.
Domain Authority
Fair
Established authority for your domain.
Reference Presence
Weak
Not in AI knowledge graphs yet.
News & Press
Weak
No press coverage found yet.
Community
Fair
Forum and community discussion.
Social Mentions
Weak
No social discussion found yet.
Your AEO score measures whether AI search engines - ChatGPT, Claude, Perplexity, Gemini - can actually read your site and cite it in answers. Roughly two-thirds of sites are invisible to them. At 5.9/10, Colour Coding has a working base to build on - fixable, and the signals above are where to start.
What’s next?
So, honestly, I have no idea what’s next. I plan to merge down the rest of the existing PRs. Then, I plan to triage the open issue list. There’s an obvious argument to be made for making fetch the default implementation, and maybe changing the API to be more fetch-like.
What if I don’t want to use LLM code?
There are many good arguments for not wanting to rely on LLM code, and especially code that isn’t fully understood by a human. These arguments are valid. I admire and understand those taking a stand against AI slop. For the record, this blog post is entirely human-produced. However, the situation with cljs-ajax is, quite simply, absolutely nothing is likely to happen at all without it.
What Have We Seen and Unseen?
Hopefully I’ve made the point that this is a nuanced question. As Steve mentions, Tony Hoare regards introducing pervasive null references as a billion dollar mistake and I’m not going to argue with him. But the fact remains that it’s a mistake we live with, unless you’re a Rust programmer (and don’t use unsafe code).
Is this your brand?
The exact fixes for Colour Coding
Which AI engines already crawl you
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The search landscape has fundamentally shifted. While Google still dominates, millions of users now ask questions to ChatGPT, Gemini, and Claude instead of typing into a search bar.
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Scored by Engagemii on July 31, 2026. Methodology: engagemii.com/aeo/methodology
Source URL: https://engagemii.com/aeo/brands/colourcoding-net
Cite this score: Engagemii (2026). "AEO Score for Colour Coding." Retrieved from https://engagemii.com/aeo/brands/colourcoding-net
Licensed under CC BY 4.0. You may reuse this data with attribution: a visible link to engagemii.com.
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