AI Visibility Scorecard
zkbench.dev · Technology
Somewhat visible. AI bots can read ZK Bench, but it is missing the structured signals that push citation rate above competitors.
AI engines read this profile 12 times
Meta AI · Claude · Apple Intelligence
#102,299 of 2,707,789 in Technology for AI visibility
6
AEO Visibility
iVisible · 6.2/10
0
Muse Index Score
iAI agent readiness
Not agent-ready · 0/100
0
AI Adoption
iNone detected · 0/100
from our crawl and measurement
ZK Bench is one of the businesses we track in the Technology space. Its AI visibility score is 6.2 out of 10: the engines can find it, but they do not have much to hold on to.
Our crawl found a readable heading structure. It is missing structured data describing the business, an llms.txt file and a sitemap.
AI crawlers have visited 4 times in our tracking, including ClaudeBot (Anthropic) 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
Weak
How clearly your brand identity reads to AI.
E-E-A-T Signals
Experience, Expertise, Authority, Trust
Weak
Experience, Expertise, Authority, Trust markers.
Technical AEO
Fair
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
Weak
No community discussion yet.
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 6.2/10, ZK Bench has a working base to build on - fixable, and the signals above are where to start.
Which is the best framework?
There is no “best” framework. As you can see from the table above, there are a lot of caveats and trade offs. You should choose the framework that best meets your needs, which will depend on what kind of application you are building. In addition to what we have provided above, you should check the developer experience for each framework, and that the level of abstraction meets your needs.
X could be optimised further?
It probably can. In this case, it's probably one of two things: We did not write a fair benchmark - raise a PR The framework hasn't optimised for X yet, but it could theoretically be faster - I'm sure it could (everything can), but we're benchmarking things that exist today, because that's what a developer has available to them when they use a framework
What’s the difference between a STARK and a SNARK?
These are two different approaches to provable zero knowledge computation. You should prefix everything below with "in general" - there are always exceptions to the rule!
What are unbounded programs?
These are programs which have inputs or logic where the number of cycles or iterations is not known at compile time. For example, a program that iterates over a list of items and checks if each item is greater than 18. The number of items in the list is not known at compile time, so the program is unbounded. In general, SNARKs require a program to be bounded at compile time, whereas STARKs do not.
What is a ZK Recursive Proof?
A ZK recursive proof (often just called "recursion") is the ability to verify a proof, or many proofs, into another proof. There's nothing crazy going on here. Verification of proofs is simply a computation and ZK already enables proving of arbitrary computations.
Is this your brand?
The exact fixes for ZK Bench
Which AI engines already crawl you
Free AI bot monitoring: see every AI crawler that visits you
Your potential customers are asking ChatGPT, Gemini, and Claude questions about your product category. These AI models are giving answers without sending traffic to your website. You're not losing rank. You're losing visibility entirely.
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Scored by Engagemii on August 1, 2026. Methodology: engagemii.com/aeo/methodology
Source URL: https://engagemii.com/aeo/brands/zkbench-dev
Cite this score: Engagemii (2026). "AEO Score for ZK Bench." Retrieved from https://engagemii.com/aeo/brands/zkbench-dev
Licensed under CC BY 4.0. You may reuse this data with attribution: a visible link to engagemii.com.
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