[
  {
    "collection_slug": "ai-readiness-glossary",
    "slug": "machine-readable-content",
    "term": "Machine-readable Content",
    "meta_title": "Machine-readable Content | AI Readiness Glossary",
    "meta_description": "Definition of machine-readable content and why the way a site structures pages and public data matters for AI understanding.",
    "summary": "Content whose structure, labels, and context are explicit enough that software systems can interpret it without guessing at the page's role.",
    "aliases": [
      "machine-readable publishing"
    ],
    "topics": [
      "ai-ready-websites",
      "ai-website-architecture"
    ],
    "definition": [
      "Machine-readable content is content that exposes enough structure for software to determine what the page is, what it covers, and how it relates to the rest of the site.",
      "That structure can come from routes, taxonomy, schema, field naming, heading logic, and public endpoint files that echo the same underlying content model."
    ],
    "practice": [
      "A glossary term with a named collection, a stable URL, related terms, and matching public JSON data is machine-readable in a way a loose blog post is not.",
      "The goal is not to write for robots. It is to remove ambiguity from the page architecture."
    ],
    "notes": [
      "Machine-readable does not mean unreadable to humans. The best implementation usually improves clarity for both audiences.",
      "The structure needs to stay aligned over time, which is why shared source data matters."
    ],
    "related_terms": [
      {
        "collection_slug": "ai-readiness-glossary",
        "slug": "llm-json"
      },
      {
        "collection_slug": "ai-readiness-glossary",
        "slug": "ai-sitemap"
      }
    ]
  },
  {
    "collection_slug": "ai-readiness-glossary",
    "slug": "llm-json",
    "term": "llm.json",
    "meta_title": "llm.json | AI Readiness Glossary",
    "meta_description": "Definition of llm.json and how it supports machine-readable site summaries for AI systems.",
    "summary": "A public JSON summary file that describes the site's identity, topics, key URLs, services, and other machine-readable reference points for AI systems.",
    "aliases": [
      "LLM site summary"
    ],
    "topics": [
      "ai-ready-websites",
      "ai-website-architecture"
    ],
    "definition": [
      "llm.json is a site-level machine-readable reference layer. It gives AI systems a quick summary of what the site is and what matters most.",
      "It should align with the same content records that drive the HTML pages wherever practical."
    ],
    "practice": [
      "A useful llm.json file includes site identity, primary sections, important URLs, service summaries, and other public references.",
      "It works best when it helps navigation and understanding rather than becoming a dumping ground for every possible detail."
    ],
    "notes": [
      "The file is public by design. If a value would be unsafe in public HTML, it should not be in llm.json either.",
      "A mismatched llm.json file can create confusion instead of clarity."
    ],
    "related_terms": [
      {
        "collection_slug": "ai-readiness-glossary",
        "slug": "machine-readable-content"
      }
    ]
  },
  {
    "collection_slug": "ai-readiness-glossary",
    "slug": "ai-sitemap",
    "term": "AI Sitemap",
    "meta_title": "AI Sitemap | AI Readiness Glossary",
    "meta_description": "Definition of an AI sitemap and how it differs from a standard XML sitemap.",
    "summary": "A machine-readable sitemap focused on the site's meaningful content graph ... important pages, content types, glossary collections, directory collections, and support files.",
    "aliases": [
      "AI-facing sitemap"
    ],
    "topics": [
      "ai-ready-websites",
      "ai-search-visibility"
    ],
    "definition": [
      "An AI sitemap is a machine-readable map of the site that focuses on semantic value rather than only URL discovery.",
      "It can include content types, topic relationships, glossary sets, directory collections, and public endpoint files."
    ],
    "practice": [
      "This can live alongside a traditional XML sitemap. The XML sitemap helps standard crawlers. The AI sitemap can add richer context about the site's architecture.",
      "It should emphasize what the site wants understood first."
    ],
    "notes": [
      "Do not confuse a richer JSON AI sitemap with a replacement for XML. Both can be useful.",
      "A sitemap that lists everything but prioritizes nothing is less helpful."
    ],
    "related_terms": [
      {
        "collection_slug": "ai-readiness-glossary",
        "slug": "llm-json"
      }
    ]
  },
  {
    "collection_slug": "ai-search-glossary",
    "slug": "citation-readiness",
    "term": "Citation Readiness",
    "meta_title": "Citation Readiness | AI Search Glossary",
    "meta_description": "Definition of citation readiness and why AI systems prefer pages with clear attribution and reusable explanation layers.",
    "summary": "The degree to which a page is clear, trustworthy, and attributable enough that AI systems can quote or summarize it with confidence.",
    "aliases": [
      "citation fitness"
    ],
    "topics": [
      "ai-search-visibility"
    ],
    "definition": [
      "Citation readiness is about whether a page looks safe and useful to cite. The more explicit the page is about its topic, authorship, and boundaries, the easier that becomes.",
      "Glossary definitions, FAQ pages, and clear article structures often improve citation readiness."
    ],
    "practice": [
      "A concise FAQ answer or glossary term often becomes easier to cite than a long generic landing page.",
      "Pages that state what they are and stay on topic tend to be easier for AI systems to reuse."
    ],
    "notes": [
      "Citation readiness is not only about schema. The underlying writing still has to be specific and worth pulling.",
      "Public data files can support citation readiness when they reinforce the same facts the page states."
    ],
    "related_terms": [
      {
        "collection_slug": "ai-search-glossary",
        "slug": "entity-clarity"
      },
      {
        "collection_slug": "ai-search-glossary",
        "slug": "retrieval-surface-area"
      }
    ]
  },
  {
    "collection_slug": "ai-search-glossary",
    "slug": "entity-clarity",
    "term": "Entity Clarity",
    "meta_title": "Entity Clarity | AI Search Glossary",
    "meta_description": "Definition of entity clarity and how it helps AI systems connect a site to a stable subject, business, or person.",
    "summary": "How clearly a site defines who it is, what it covers, and how its pages relate to the same subject or business entity.",
    "aliases": [
      "subject clarity"
    ],
    "topics": [
      "ai-search-visibility",
      "ai-website-monetization"
    ],
    "definition": [
      "Entity clarity is the opposite of sending mixed signals about who the site is or what it is about.",
      "It comes from consistent naming, topic clustering, related definitions, and a content model that shows relationships across the library."
    ],
    "practice": [
      "A site with consistent glossary language, clear service names, and portfolio-style directory pages gives AI systems stronger entity clues.",
      "A site with disconnected pages and no visible relationship model looks more generic."
    ],
    "notes": [
      "Entity clarity supports both AI retrieval and future internal portfolio management.",
      "A glossary can improve entity clarity because it defines the site's vocabulary in its own terms."
    ],
    "related_terms": [
      {
        "collection_slug": "ai-search-glossary",
        "slug": "citation-readiness"
      }
    ]
  },
  {
    "collection_slug": "ai-search-glossary",
    "slug": "retrieval-surface-area",
    "term": "Retrieval Surface Area",
    "meta_title": "Retrieval Surface Area | AI Search Glossary",
    "meta_description": "Definition of retrieval surface area and why a connected library creates more entry points for AI systems.",
    "summary": "The total number of useful, public, and semantically clear entry points a site offers to retrieval systems.",
    "aliases": [
      "AI surface area"
    ],
    "topics": [
      "ai-search-visibility",
      "ai-website-monetization"
    ],
    "definition": [
      "Retrieval surface area is the breadth of public content and support files that AI systems can encounter and understand.",
      "Articles, FAQ pages, glossary terms, directory listings, and endpoint files all expand that surface when they are connected coherently."
    ],
    "practice": [
      "A library that includes one article, one definition page, one FAQ, and one directory listing about the same topic creates multiple retrieval opportunities.",
      "More pages only help if they add clarity instead of duplication."
    ],
    "notes": [
      "Surface area without quality becomes noise. The useful version is structured and purposeful.",
      "This concept becomes commercial when those surfaces reinforce services or product categories."
    ],
    "related_terms": [
      {
        "collection_slug": "ai-search-glossary",
        "slug": "citation-readiness"
      }
    ]
  },
  {
    "collection_slug": "agent-web-glossary",
    "slug": "agent-action-surface",
    "term": "Agent Action Surface",
    "meta_title": "Agent Action Surface | Agent Web Glossary",
    "meta_description": "Definition of agent action surface and why pages need explicit next-step information for future assistants.",
    "summary": "The visible set of information a page gives an assistant so it can determine what action is possible next.",
    "aliases": [
      "action surface"
    ],
    "topics": [
      "agent-ready-websites"
    ],
    "definition": [
      "An agent action surface is the part of a page that exposes what can be done next, how it is done, and under what constraints.",
      "Without that surface, an assistant has to guess whether the page supports comparison, contact, download, or purchase."
    ],
    "practice": [
      "Service pages with scope, deliverables, timeline, and next-step instructions create a stronger action surface than pages built only around persuasion.",
      "FAQ and glossary support layers reduce the amount of guessing needed."
    ],
    "notes": [
      "This concept becomes more important as assistants move from summarizing to acting.",
      "A clear action surface benefits human readers too."
    ],
    "related_terms": [
      {
        "collection_slug": "agent-web-glossary",
        "slug": "delegation-ready-page"
      }
    ]
  },
  {
    "collection_slug": "agent-web-glossary",
    "slug": "delegation-ready-page",
    "term": "Delegation-ready Page",
    "meta_title": "Delegation-ready Page | Agent Web Glossary",
    "meta_description": "Definition of a delegation-ready page and how it supports AI assistants making use of the page on someone else's behalf.",
    "summary": "A page structured so an assistant can evaluate it and pass it along or act on it with minimal ambiguity.",
    "aliases": [
      "assistant-ready page"
    ],
    "topics": [
      "agent-ready-websites"
    ],
    "definition": [
      "A delegation-ready page is a page that can survive second-hand use. An assistant can summarize it, compare it, or recommend it without losing the core meaning.",
      "That requires clear language about who the page is for, what it offers, and what the next step should be."
    ],
    "practice": [
      "Pages that separate summary, details, pricing logic, FAQ, and next actions are easier to delegate than pages where everything is implied.",
      "Supporting glossary terms and endpoint files improve consistency when an agent checks the site at multiple layers."
    ],
    "notes": [
      "Delegation-ready does not mean robotic. It means clear enough that a system can reuse the page responsibly.",
      "As with all AI-ready structures, clarity beats cleverness."
    ],
    "related_terms": [
      {
        "collection_slug": "agent-web-glossary",
        "slug": "agent-action-surface"
      }
    ]
  }
]