Machine Discoverability Glossary
A short glossary of the terms used consistently across Trocial and this site, for quick reference.
Terms
- AI visibility
- Whether an AI system mentions and correctly describes a brand when answering a relevant buyer-intent question.
- AI Recommendation Intelligence
- The discipline of measuring why an AI system recommends one brand over another, and turning that into a fix.
- Machine discoverability
- Whether crawlers, AI models, and agents can technically access a site and extract accurate, structured facts from it.
- Answer engine optimization (AEO/GEO)
- Structuring content and proof so AI answer engines can find, extract, and cite it accurately.
- Agent discoverability
- Whether autonomous AI agents - not just chat answer engines - can find and act on structured facts about a brand, often via a protocol like MCP.
- Buyer intent
- The underlying question or goal behind a search or prompt, e.g. comparing vendors or checking pricing, rather than the literal words used.
- Recommendation share
- The proportion of buyer-intent answers in which a brand is the one recommended, not merely named, versus competitors.
- Citation strength
- The quality and authority of the sources an AI system cites when it describes a brand.
- Brand accuracy
- Whether an AI system describes a brand’s product, pricing, and positioning correctly.
- Competitive position
- Where a brand ranks relative to the alternatives an AI system names in the same buyer-intent answers.
- BrandGraph
- The structured record of company facts, products, capabilities, markets, proof, citations, and competitive context Trocial builds from a scan.
- Schema markup
- Structured data embedded in a page (schema.org vocabulary) that lets machines parse meaning directly instead of inferring it from prose.
- llms.txt
- A plain-text file at a site’s root that gives AI systems a concise, factual summary of the site - proposed by the community as an AI-era counterpart to robots.txt.
- MCP (Model Context Protocol)
- An open standard that lets AI agents call external tools and data sources directly, instead of only reading static pages.