AI Visibility Scorecard
colourcoding.net · Technology
At 3.49/10, Colour Coding is near-invisible in AI search today. Most AI engines will not name it when asked about its category. The weakest signals are Structured Data, News & Press and Social Mentions. That is fixable, and the signals below show where to start.
AI engines read this profile 8 times
Claude · Apple Intelligence · Meta AI · ChatGPT
Top 10% in Technology for AI visibility
62
AI Naming Predictability
iRarely named · 62/100
Technology average 28
Top 9% of Technology
See what's behind this score →3.49
-
Network Authority
iNot connected yet
0 relationships on record. Businesses in Technology average 4. Claim your page and Engagemii is your first.
See what's behind this score →5
4
from our crawl and measurement
Colour Coding works in Technology. To AI engines like ChatGPT and Perplexity, though, it is barely visible: it scores 3.49 out of 10.
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 read this profile 8 times in our tracking, including ClaudeBot (Anthropic), Applebot (Siri) and Meta AI.
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
-
Not yet measured.
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 read your site and name it in answers. At 3.49/10, Colour Coding is near-invisible to AI engines today. That is 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).
ChatGPT doesn't crawl the web like Google does. When someone asks Claude about the best project management tools, the model isn't searching your website in real-time. It's pulling from training data that stopped months or years ago.
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Scored by Engagemii on November 9, 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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