{
  "client": "Ironclad Industrial",
  "date": "2026-04-22",
  "events": [
    {
      "kind": "baseline_fill",
      "at": "07:00",
      "role": "Electrician",
      "count": 5,
      "city": "Gary",
      "state": "IN",
      "shift_start": "07:00 AM",
      "scenario_note": "Gary IN has ZERO Electricians in the index. Local WILL fail this. Cloud should diagnose no-supply and recommend pivoting to Chicago IL (40min drive) or relaxing to 'Maintenance Tech'."
    },
    {
      "kind": "expansion",
      "at": "09:30",
      "role": "Safety Coordinator",
      "count": 8,
      "city": "Peoria",
      "state": "IL",
      "shift_start": "09:30 AM",
      "scenario_note": "Safety Coordinator is the rarest role overall (~4500 nationally). 8× in a mid-sized city with availability > 0.5 is genuinely tight. Cloud should either confirm or suggest multi-city sourcing."
    },
    {
      "kind": "emergency",
      "at": "11:45",
      "role": "Welder",
      "count": 3,
      "city": "Flint",
      "state": "MI",
      "shift_start": "12:00 PM",
      "deadline": "13:30",
      "scenario_note": "Flint MI has ZERO workers indexed — total data desert. Cloud must flag 'impossible supply' and recommend pivot (Detroit 60mi, Saginaw 40mi)."
    },
    {
      "kind": "expansion",
      "at": "14:00",
      "role": "Tool & Die Maker",
      "count": 4,
      "city": "Grand Rapids",
      "state": "MI",
      "shift_start": "14:00 PM",
      "scenario_note": "Tool & Die Maker is scarce (~9000 total). 4× in Grand Rapids, availability > 0.5 AND reliability > 0.75. Tight but solvable if playbook_memory has history; cloud should prioritize proven performers."
    },
    {
      "kind": "misplacement",
      "at": "15:30",
      "role": "Electrician",
      "count": 1,
      "city": "Gary",
      "state": "IN",
      "shift_start": "15:30 PM",
      "replaces_event": "07:00",
      "scenario_note": "Refilling 1× Electrician in Gary after a no-show. Same data desert as event 1 — cloud should recognize the repeat and recommend the SAME pivot it gave earlier, proving it learns within-run."
    }
  ]
}