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Agent Readiness Index

Victoria Green Agent Readiness Score

Partially Agent-Ready · Grade D · Scanned August 21, 2026

Victoria Green designs and creates award-winning, innovative, and stylish beauty bags, wash bags, and vanity cases for women to organize and protect their beauty products while traveling and in daily life.

Beauty Products
Travel Accessories
Brighton, United Kingdom
58
/ 100
Grade D
Six-dimension breakdown

Discoverability

Can an AI agent find sitemaps, llms.txt, and machine-readable entry points?

100

Content

Can agents consume content cheaply via markdown, schema.org, and structured data?

100

Access Control

Are crawl rules and AI bot permissions declared in robots.txt?

40

Capabilities

Does the site expose APIs, MCP endpoints, or agent-usable tools?

35

Commerce

Can agents discover pricing and initiate payments (x402, MPP, UCP)?

40

Quality

Performance, token efficiency, and trust signals beyond baseline checks.

65
Priority fixes

Capabilities (35/100)

Improve capabilities signals: llms.txt, robots.txt AI rules, structured data, MCP or OpenAPI endpoints, and agent-readable pricing where relevant.

Access Control (40/100)

Improve access control signals: llms.txt, robots.txt AI rules, structured data, MCP or OpenAPI endpoints, and agent-readable pricing where relevant.

Commerce (40/100)

Improve commerce signals: llms.txt, robots.txt AI rules, structured data, MCP or OpenAPI endpoints, and agent-readable pricing where relevant.

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How we score

StartupHub audits the full website across 50+ checks: discoverability, content negotiation, access control, capabilities (API/MCP), commerce (x402/MPP), and quality.

Unlike pricing-only indexes, we measure whether AI agents can find, read, and act on the entire site, not just the pricing page.

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