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Agent Readiness Index

Reflection Agent Readiness Score

Partially Agent-Ready · Grade D · Scanned May 25, 2026

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EdTech
Personalized Learning
$2.0B raised
7 employees
San Francisco, United States
50
/ 100
Grade D
Six-dimension breakdown

Discoverability

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

91

Content

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

5

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?

27

Commerce

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

63

Quality

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

90
Priority fixes

Content (5/100)

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

Capabilities (27/100)

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.

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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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