What Is Agentic Ready Score and How Does It Measure AI Agent Readiness?
Agentic Ready Score is a proprietary metric that evaluates how well a website or online store is prepared to interact with AI agents, using a scale from 0 to 100.
The score is calculated by Agentic Ready Checker, a tool built from scratch by Delante’s technical team. It automatically scans a domain and evaluates the technical elements that determine whether AI agents can discover the website, understand its offerings, and interact with its content and functionalities.
Agentic Ready Score is not an AI visibility metric. It doesn’t measure how frequently a brand appears in responses generated by ChatGPT, Gemini, or Perplexity. Instead, it assesses how well a website meets the technical requirements relevant to AI agent interactions, from making product information accessible and understandable to enabling automated data retrieval and access to APIs.
How Is Agentic Ready Score Determined?
Agentic Ready Checker analyzes website elements that may affect different stages of interaction with an AI agent, from discovering the website and understanding its offerings to accessing data and functionalities needed to complete tasks.
It checks whether an AI agent can:
- discover the website and access files intended for AI systems,
- understand the website’s offerings through structured data and content,
- interact with machine-readable interfaces, such as APIs, to check availability or perform specific actions,
- identify signals that support the website’s trustworthiness.
Each element addresses a potential technical barrier that an AI agent might encounter when attempting to complete a shopping-related task independently.
What Does Agentic Ready Checker Analyze?
Agentic Ready Checker evaluates a range of technical elements grouped into five categories.
Discovery and access files:
- Presence of an agents.md file containing instructions for shopping agents.
- AI bot access permissions in robots.txt, including GPTBot, ClaudeBot, and PerplexityBot.
- XML sitemaps and /api or /agent endpoints.
- .well-known files related to AI agents and MCP.
- RSS/Atom feeds that provide information about updates without requiring a full website crawl.
- Presence of an llms.txt file and validity of its links (HTTP 200 responses).
Structured data:
- JSON-LD markup, including Product, Organization, and FAQPage schemas,
- completeness of ContactPoint markup, enabling agents to route inquiries to sales or support,
- a canonical company facts page where AI models can source authoritative brand information.
Machine interfaces (APIs):
- public OpenAPI/Swagger documentation,
- an agent card or manifest located in the /.well-known/ directory.
Content and readability:
- server-side rendering (SSR) of core content rather than client-side JavaScript execution,
- semantic HTML: heading hierarchy, text density, and image alt attributes,
- capability to serve content in Markdown format,
- content freshness signals,
- a smoke test verifying whether an agent can locate the price, target audience, and checkout path.
Trust:
- presence of a security.txt file.
Some of the evaluated solutions, such as llms.txt and agent manifests, are emerging practices rather than universally adopted requirements for AI systems. Agentic Ready Score is a proprietary technical readiness assessment based on Delante’s methodology, not an official certification issued by AI providers.
How is the Agentic Ready Score calculated?
Each category receives a partial score on a scale from 0 to 100.
The final Agentic Ready Score is calculated as a weighted average of these category scores.
Agentic Ready Score = Weighted Average of Discovery, Schema, API, Content, and Trust Scores
Each category contributes differently to the final result, according to the methodology developed by Delante.
How to Interpret Agentic Ready Score?
A numerical score alone provides limited insight without context.
To understand what the result means, it should be analyzed:
- across individual categories rather than as a single number,
- in comparison with competitors operating in the same industry,
- over time, following technical improvements and implementations.
For example, in Delante’s study of 15 Polish electronics and home appliance retailers, the average Agentic Ready Score was approximately 33/100, with individual results ranging from 4/100 to 67/100.
Within this sample, a score of 50/100 would be considerably higher than the average, although it would still indicate opportunities for further technical improvements.
The study also revealed that business size does not automatically translate into AI agent readiness. Some smaller online stores achieved higher scores than major retail chains.
Agentic Ready Score reflects a website’s technical condition at the time of the scan. Changes to access files, structured data, or content rendering can affect subsequent results.
Agentic Ready Score vs. Agentic Commerce
Agentic Commerce is a model of digital commerce in which AI agents actively participate in selecting and purchasing products on behalf of users.
Agentic Ready Score evaluates how well an online store is technically prepared to support this emerging model.
In simple terms:
Agentic Commerce: a shift in how people shop.
Agentic Ready Score: a measure of a store’s readiness for that shift.
