This is an example report for a fictional business. Choose improvements and try the PDF export.
Overview
Request a quote
Agent Experience parameters
What an agent needs to read, understand and use this website.
Content accessibility
ExampleCan agents reach and read the website’s public information?
robots.txt: found. Sitemap: found. Review crawler restrictions in the evidence.
Strong
Structured data / JSON-LD
ExampleCan agents extract clear business, service and product facts?
0 JSON-LD blocks on the primary page. No schema types recorded there.
Needs improvement
Action readiness
ExampleAre the next steps and available interfaces clear to an agent?
API documentation: not observed. MCP signals: not observed. AGENTS.md: not observed.
Needs attention
Content negotiation
ExampleCan agents request Markdown or plain text, and find agent guidance?
Markdown/plain-text request: text/html. llms.txt: found.
Needs attention
Semantic HTML
ExampleDo headings, landmarks and page structure make the content understandable?
Strong
Metadata
ExampleDo page titles and descriptions explain what the page offers?
Needs improvement
Content clarity
ExampleAre the offer, prices and important details easy to understand?
Needs improvement
Agent interaction
ExampleDoes the website give agents useful guidance for interacting with it?
Needs improvement
The next service to offer your client
You help customers find the business.
Now help AI assistants use its website.
Your SEO, AEO and GEO services help clients get discovered by AI agents. Add Agent Experience as a service: improve structured data, content negotiation and customer journeys, or implement WebMCP where it helps. Your agency sets the scope and price.
Agent Experience findings
Specific findings from this scan, the Agent Experience improvements they point to, and the work your agency can offer.
Structured data · add Schema.org JSON-LD
Add Schema.org JSON-LD: structured business, service or product details that agents can read directly. Use the same names, prices and offers customers see on the page.
Observed in this scan: No JSON-LD blocks were observed on https://example.com.
Why it matters to the client
Clear details help an assistant understand what the business offers and compare the right options for a customer.
What your agency can offer
Schema.org / JSON-LD implementation and validation.
View technical details
Recorded evidence
No JSON-LD blocks were observed on https://example.com.
https://example.com/services: 0 JSON-LD blocks observed.
https://example.com/contact: 0 JSON-LD blocks observed.
Technical implementation
Select the schema types that match the actual page, such as Service, Product or Organization. Describe only facts present in the visible content; use explicit names, URLs and applicable offer details.
Context
Agents may need to infer the offering and its details from page text. Clear structured facts can make comparisons more consistent.
Verification instructions
Validate the markup, rescan the same pages, and compare extracted names and commercial details with the visible page. Presence alone does not establish correctness or ranking benefits.
WebMCP · verify detected browser tools
The scan found signs of WebMCP. Test the tools with a supported AI assistant before telling the client they are ready to use.
Observed in this scan: https://example.com/contact: declarative annotation for “request_quote” — Prepare a project quote request using the customer’s service requirements.
Why it matters to the client
A tool being listed on a page does not show that a customer’s task can be completed.
What your agency can offer
Test and improve the existing WebMCP setup.
View technical details
Recorded evidence
https://example.com/contact: declarative annotation for “request_quote” — Prepare a project quote request using the customer’s service requirements.
Technical implementation
Open the relevant page in a WebMCP-compatible browser and inspect document.modelContext.getTools(). Review names, descriptions and inputs. Test an agreed read-only scenario before proposing further actions.
Context
Source annotations suggest an agent interaction surface, but this scan does not establish that tools are available or that the journey works.
Verification instructions
Record browser/API version, page state and returned tool metadata. Keep registration evidence separate from any explicit task-execution result.
Action readiness · make forms usable by agents
Give the quote form clear field labels, required-field guidance, and a useful confirmation message.
Why it matters to the client
An assistant needs to know where each piece of customer information belongs and whether the enquiry succeeded.
What your agency can offer
Form accessibility and agent journey testing.
View technical details
Original finding
Give the quote form clear field labels, required-field guidance, and a useful confirmation message.
https://example.com ↗Recorded evidence
Model-generated recommendation from the stored AX analysis. Validate on the affected page before including it in the implementation scope.
Technical implementation
Give the quote form clear field labels, required-field guidance, and a useful confirmation message.
Context
Review whether this recommendation addresses a real barrier to: Request a quote. Commercial impact has not been measured.
Verification instructions
Confirm the issue manually on the relevant page, capture baseline evidence, and repeat the same scenario after implementation. Record an unresolved result if the barrier remains.
Content clarity · explain service and quote requirements
Explain the service scope and quote requirements beside the primary contact action.
Why it matters to the client
An assistant can help a customer prepare the right information before contacting the business.
What your agency can offer
Rewrite the service page and quote instructions.
View technical details
Original finding
Explain the service scope and quote requirements beside the primary contact action.
https://example.com ↗Recorded evidence
Model-generated recommendation from the stored AX analysis. Validate on the affected page before including it in the implementation scope.
Technical implementation
Explain the service scope and quote requirements beside the primary contact action.
Context
Review whether this recommendation addresses a real barrier to: Request a quote. Commercial impact has not been measured.
Verification instructions
Confirm the issue manually on the relevant page, capture baseline evidence, and repeat the same scenario after implementation. Record an unresolved result if the barrier remains.
Content negotiation · offer Markdown to agents
Check whether the website can serve Markdown or plain text when an agent requests it, while keeping HTML for people. Add this option where it helps the target agent read the page.
Why it matters to the client
Clear text can make it easier to find service details without getting lost in the page layout.
What your agency can offer
Content negotiation and Markdown response setup.
View technical details
Recorded evidence
An Accept: text/markdown, text/plain request returned text/html.
Technical implementation
First review the existing HTML with the target agent. If parsing is a barrier, offer an equivalent Markdown response for content pages and preserve canonical URLs and commercial details.
Context
A simpler representation may reduce parsing work for compatible agents. Semantic, accessible HTML remains useful on its own.
Verification instructions
Request both HTML and Markdown, compare facts and links, and set Vary: Accept correctly if negotiation is implemented.
An additional service your agency can offer
WebMCP & agent tools
WebMCP lets a website expose browser tools that compatible AI agents can call. Tool descriptions and JSON inputs make the intended action clear: find a product, check availability or prepare a quote request.
What this scan found
Signs of a setup found · needs testingRecorded on the inspected pages
Whether registration was inspected
No completed-journey result recorded
request_quoteSource annotationPrepare a project quote request using the customer’s service requirements.
https://example.com/contact ↗Find a product
Help an assistant search for options that fit a customer’s needs.
Check available times
Let an assistant read the available appointments before a customer chooses.
Prepare an enquiry
Explain what information is needed for a quote or contact request.
Offer WebMCP setup and testing
Choose one useful task with the client, add the connection, and test it with a supported assistant. You can price this as a separate project alongside your SEO or AEO work.
WebMCP is still developing and support varies. It is optional, and this scan has not tested whether an assistant can complete these actions.
Implementation options for your agency
Choose the interfaces that fit the client’s workflow. Each integration needs its own validation.
JSON schemas & structured outputs
Define the inputs a tool accepts and the results it returns. Consistent JSON helps an agent interpret product details, available times and errors. Validate responses with the target agent.
MCP & API integrations
Connect agents to business tools and data through an MCP server or documented API. This is a separate integration from WebMCP tools exposed by a page in the browser.
CLI & continuous checks
Use command-line checks in your delivery workflow to spot changes after website updates. Combine those results with a test of the actual customer journey.
View WebMCP technical details
- Source / registration status
- detected
- Runtime inspection
- not-tested
- Task execution
- Not tested by this report
request_quote · declarative
Prepare a project quote request using the customer’s service requirements.
https://example.com/contact
Pages and states inspected
https://example.com/contact
Initial public quote form
Illustrative form annotation. Registration and task completion have not been tested.
WebMCP is an experimental enhancement and does not affect this AX score.
Source detection, runtime registration and successful task execution are separate evidence levels. WebMCP does not affect the core rating.
Your client work plan
Choose the improvements to deliver, add your estimate, and agree the work with your client.
Work item 1
Structured data · add Schema.org JSON-LD
Schema.org / JSON-LD implementation and validation.
How to check the improvement
Ask an assistant to describe the offer and compare its answer with the website.
View technical details
Recorded evidence
No JSON-LD blocks were observed on https://example.com.
https://example.com/services: 0 JSON-LD blocks observed.
https://example.com/contact: 0 JSON-LD blocks observed.
Technical implementation
Select the schema types that match the actual page, such as Service, Product or Organization. Describe only facts present in the visible content; use explicit names, URLs and applicable offer details.
Context
Agents may need to infer the offering and its details from page text. Clear structured facts can make comparisons more consistent.
Verification instructions
Validate the markup, rescan the same pages, and compare extracted names and commercial details with the visible page. Presence alone does not establish correctness or ranking benefits.
After the work is done, run a fresh scan and test the customer’s task. Marking an item as updated does not confirm that the task works.
What we checked
We checked the website’s information, page structure and signs of support for AI assistants. Some suggestions come from AI review and need a person to confirm them.
Website
example.com
Date checked
1 Sept 2026
Bookings, enquiries and purchases
Not tested by this scan
View all technical evidence
Original model assessment
The core service pages are readable, with opportunities to make commercial facts and the quote journey clearer. Start with the observable content gaps, then verify the structured action in a compatible browser. This report uses illustrative data.
Original rating parameters
Content accessibility · 88/100
Core content is available in the initial page.
Content clarity · 72/100
The offering is readable; quote requirements need clarification.
Structured information · 64/100
The service facts need a more explicit representation.
Action readiness · 48/100
Quote requirements and confirmation guidance need clarification.
Semantic HTML · 80/100
Page headings and landmarks provide a readable structure.
Meta Tags Quality · 78/100
Titles describe the services; some descriptions could be more specific.
Agent Interaction · 64/100
Agent guidance is available; interaction requirements need more detail.
Content Negotiation · 50/100
llms.txt is available, but requests for Markdown return an HTML page.
- robots.txt
- Observed
- Crawler policy
- Named agents permitted
- JSON-LD blocks
- 0
- Sitemap
- Observed
- Markdown response
- text/html
- API / server MCP
- Not observed
- llms.txt
- Observed
Scan coverage
https://example.com
https://example.com/services
https://example.com/contact
Checked: 2026-09-01T10:00:00Z. Other pages, sessions and states may differ.