{
  "dataset": "glossary",
  "record": {
    "id": "token-economics",
    "term": "Token Economics",
    "category": "knowledge-memory",
    "short_def": "The cost structure of agent interactions, where every token of input and output is billed — making concise, structured content a direct cost saving.",
    "long_def": "Because agents pay per token, a markdown twin that is ~90% smaller than its HTML equivalent is not just faster but cheaper to consume. Agent-friendly design is partly an economic argument.",
    "see_also": [
      "markdown-twin",
      "content-negotiation"
    ],
    "etymology_origin": {
      "value": null,
      "verify_status": "verify-against-primary-at-build",
      "source_hint": "https://en.wikipedia.org/wiki/Large_language_model — 'token economics' here means LLM token billing/cost-structure, distinct from blockchain 'tokenomics'; no single coiner for the LLM sense"
    },
    "related_to": [
      "markdown-twin",
      "content-negotiation",
      "rag"
    ],
    "contrast_with": "Unlike blockchain 'tokenomics' (the supply and incentive design of a crypto token), token economics here means the per-token billing of LLM input and output — a content-cost argument, not a crypto one.",
    "example": "A markdown twin is roughly 90% smaller than its HTML equivalent in tokens, so serving it directly lowers the per-token cost an agent pays to read the page.",
    "source": "https://en.wikipedia.org/wiki/Large_language_model",
    "status": "active",
    "why_it_matters": "Token economics turns agent-readiness into a cost argument: leaner, structured content is literally cheaper for an agent to consume, which influences whether agents prefer your site.",
    "sameAs": [],
    "bridge_entity": "agent-readiness",
    "last_verified": "2026-06-15",
    "md_twin": "/glossary/token-economics.md"
  }
}