{
  "title": "Toy manufacturing data for AI set and tracking identity",
  "source_page": "https://fiund.com/industries/toy-set-part-tracking-identity-data",
  "authorship": "Original fictional Fiund editorial exercise. No actual operating records or third-party source assets are included.",
  "example": {
    "title": "Track the unique shapes, not just the bag count",
    "context": "A self-authored geometric paper set has labeled parts and a fictional bag manifest.",
    "records": [
      [
        "1",
        "Set manifest",
        "One T triangle, one C circle, one S square."
      ],
      [
        "2",
        "Bag photo",
        "Two T shapes and one C; all marks readable."
      ],
      [
        "3",
        "Counter",
        "Three pieces present."
      ]
    ],
    "question": "What should the bag discrepancy say?",
    "answer": "Record 2 shows one extra T and a missing S relative to record 1, while C matches. Record 3's total is correct but does not establish completeness by part. Keep the duplicate and missing variant as separate inventory findings.",
    "failureModes": [
      "Checking piece count without unique identities",
      "Ignoring a duplicate because one expected shape is present"
    ],
    "fields": [
      [
        "part_code",
        "Identifies each distinct shape"
      ],
      [
        "expected_multiplicity",
        "Defines required counts"
      ],
      [
        "visible_multiplicity",
        "Measures discrepancies by part"
      ]
    ],
    "holdout": "Add a shape rotated into an unfamiliar silhouette and use its printed ID before counting it as missing.",
    "boundary": "Original paper shapes only; no licensed characters, child data, safety testing or age-grade claims."
  }
}