Agent Readiness Index

Cato Institute Agent Readiness Score

Partially Agent-Ready · Grade D · Scanned August 16, 2026

A public policy think tank advocating for the principles of individual liberty, limited government, free markets, and peace.

Public Policy
Think Tank
124 employees
Washington, District of Columbia, 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?

28

Access Control

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

52

Capabilities

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

74

Commerce

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

50

Quality

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

16
Priority fixes

Quality (16/100)

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

Content (28/100)

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

Commerce (50/100)

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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