{
  "_type": "curated_open_data",
  "as_of": "2026-07",
  "links": {
    "canonical": "https://verticalmarketplace.ai",
    "docs_for_llms": "https://verticalmarketplace.ai/llms.txt",
    "sell_your_own": "https://verticalmarketplace.ai/api/marketplace/listings",
    "vertical_listings": "https://verticalmarketplace.ai/api/marketplace/listings?vertical=ai-prompts"
  },
  "records": [
    {
      "term": "System prompt",
      "category": "prompting",
      "reference": "provider docs",
      "definition": "Instruction that defines an assistant's role and behavior"
    },
    {
      "term": "Few-shot prompting",
      "category": "technique",
      "reference": "research literature",
      "definition": "Including a small number of demonstrations in the prompt"
    },
    {
      "term": "Zero-shot prompting",
      "category": "technique",
      "reference": "research literature",
      "definition": "Asking a model to perform a task with no demonstrations"
    },
    {
      "term": "Chain-of-thought",
      "category": "technique",
      "reference": "Wei et al. 2022",
      "definition": "Prompting a model to reason through intermediate steps"
    },
    {
      "term": "Token",
      "category": "concept",
      "reference": "provider docs",
      "definition": "Basic unit of text a model reads and generates"
    },
    {
      "term": "Temperature",
      "category": "parameter",
      "reference": "provider docs",
      "definition": "Sampling parameter controlling output randomness"
    },
    {
      "term": "top_p",
      "category": "parameter",
      "reference": "provider docs",
      "definition": "Nucleus sampling cutoff on cumulative probability"
    },
    {
      "term": "Context window",
      "category": "concept",
      "reference": "provider docs",
      "definition": "Maximum tokens a model can process at once"
    },
    {
      "term": "Retrieval-augmented generation (RAG)",
      "category": "technique",
      "reference": "Lewis et al. 2020",
      "definition": "Grounding responses with retrieved external data"
    },
    {
      "term": "Fine-tuning",
      "category": "technique",
      "reference": "provider docs",
      "definition": "Further training a model on task-specific data"
    },
    {
      "term": "Hallucination",
      "category": "failure mode",
      "reference": "research literature",
      "definition": "Model output that is fluent but not grounded in facts"
    },
    {
      "term": "Agent",
      "category": "concept",
      "reference": "provider docs",
      "definition": "An LLM system that plans steps and calls tools"
    },
    {
      "term": "Tool calling",
      "category": "capability",
      "reference": "provider docs",
      "definition": "A model invoking external functions or APIs"
    },
    {
      "term": "Embedding",
      "category": "concept",
      "reference": "provider docs",
      "definition": "Numeric vector representing the meaning of text"
    }
  ],
  "sources": [
    {
      "url": "https://platform.openai.com/docs/guides/prompt-engineering",
      "name": "OpenAI prompt engineering guide"
    },
    {
      "url": "https://arxiv.org/abs/2201.11903",
      "name": "Chain-of-thought paper (arXiv:2201.11903)"
    }
  ],
  "category": "glossary",
  "vertical": "ai-prompts",
  "data_note": "All records are public-domain facts compiled from the cited sources as of the asOf date. This content is authored and served by the platform itself — it is not seller data, so the marketplace's zero-storage promise about seller datasets is unaffected.",
  "record_count": 14,
  "what_this_is": "A platform-published open-data listing curated by Open Data Desk, the marketplace's in-house public-data seller. It is real free inventory: it counts in marketplace statistics and is purchasable for $0 through the normal purchase flow, which delivers this payload with an Ed25519-signed receipt.",
  "record_schema": {
    "term": "Prompting or agent term",
    "category": "Type of concept",
    "reference": "Where the term is described",
    "definition": "Plain-language meaning"
  },
  "buyer_use_cases": [
    "Onboard team members to prompt and agent terminology",
    "Standardize documentation for prompt libraries and agents",
    "Clarify sampling and technique terms during design reviews"
  ]
}