AgentScore: The New Standard for AI Agent Readability

AgentScore is a new open scoring framework that evaluates how well any AI product — website, app, or API — is structured to be understood and acted on by AI agents.

As AI agents increasingly browse, buy, and interact on behalf of humans, products that aren't "agent-readable" will be invisible in the emerging autonomous economy.

Creates a new AEO (Agent Engine Optimization) category that could grow as large as SEO within 3–5 years. Threatens incumbents whose legacy UX wasn't built for machine consumption.

• →Build an AgentScore audit SaaS for product teams
• →Integrate AgentScore into your CI/CD pipeline as a quality gate
• →Use high AgentScores as a competitive differentiator in pitches

• →Framework may fragment if competing standards emerge from OpenAI or Google
• →Gaming the score (AEO spam) could follow the same trajectory as black-hat SEO

Imagine your store has no labels and robots can't find anything. AgentScore tells you how robot-friendly your store is and how to fix it.

The web has been optimized for humans for three decades and for search engines for two. We're now entering a third era: optimization for AI agents. AgentScore formalizes this shift with a structured scoring rubric across five pillars: semantic clarity, structured data completeness, API accessibility, action affordance, and context anchoring. Each pillar is weighted based on how heavily modern agents rely on it. Semantic clarity carries the highest weight at 30%. Structured data follows at 25%. Builders who move first will have a structural advantage as agentic traffic becomes a meaningful acquisition channel within 18 months.