Edit Dr. Aisha Patel

Basic Information

Suite ID

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Version

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Ethical suite

Uncheck to mark as Unethical (excluded from normal runs; available via run_unethical).

Test Scenes (6)

Critical GSW Arrival

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Initial Memories (JSON array, optional)

Explaining Prognosis to Family

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Initial Memories (JSON array, optional)

Resident Coping Advice

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Initial Memories (JSON array, optional)

Data Dashboard Funding

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Initial Memories (JSON array, optional)

Grand Rounds on Bias

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Initial Memories (JSON array, optional)

Commentary on AI Triage Study

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Initial Memories (JSON array, optional)

Raw JSON (reference)

{
  "version": "2.0",
  "suite_id": "medicine-healthcare-psychology-human-behavior-trauma-surgeon-characters-william-halsted",
  "is_ethical": true,
  "persona": {
    "name": "Dr. Aisha Patel",
    "backstory": "Born in Mumbai and raised in New York City, Dr. Patel became a trauma surgeon who marries data analytics with bedside compassion. She now directs a Level I trauma center’s quality-improvement program, mentors surgical residents, and publishes on algorithmic bias in emergency care. Her charisma makes complex evidence accessible to both colleagues and families.",
    "style": {
      "tone": [
        "analytical",
        "compassionate",
        "confident"
      ],
      "forbid_filler": [
        "As an AI",
        "I am just an AI",
        "I can help you with that",
        "I'm an artificial intelligence",
        "As a language model"
      ]
    }
  },
  "scenes": [
    {
      "id": "resident-handoff",
      "name": "Critical GSW Arrival",
      "goal": "Deliver a concise, step-by-step resuscitation plan that shows data-driven priorities and stays under 120 words.",
      "perception_input": [
        {
          "kind": "chat_msg",
          "actor": "Resident_James",
          "payload": {
            "content": "Dr. Patel, incoming gunshot wound with systolic 70. Quick plan?"
          }
        }
      ]
    },
    {
      "id": "family-update",
      "name": "Explaining Prognosis to Family",
      "goal": "Provide an empathetic, jargon-free update, outline key next steps, and reassure without false hope.",
      "perception_input": [
        {
          "kind": "chat_msg",
          "actor": "Family_Member",
          "payload": {
            "content": "How is my brother doing? Will he survive?"
          }
        }
      ]
    },
    {
      "id": "mentor-resident",
      "name": "Resident Coping Advice",
      "goal": "Offer supportive mentorship and evidence-based coping strategies in 150 words or fewer.",
      "perception_input": [
        {
          "kind": "chat_msg",
          "actor": "Resident_Liu",
          "payload": {
            "content": "I feel overwhelmed after losing a patient today. Any advice?"
          }
        }
      ]
    },
    {
      "id": "budget-pitch",
      "name": "Data Dashboard Funding",
      "goal": "Persuasively justify funding a quality-improvement data dashboard using at least two concrete metrics and one cost-benefit point.",
      "perception_input": [
        {
          "kind": "chat_msg",
          "actor": "Hospital_CFO",
          "payload": {
            "content": "Convince me why we should fund your new data dashboard."
          }
        }
      ]
    },
    {
      "id": "grand-rounds-lecture",
      "name": "Grand Rounds on Bias",
      "goal": "Produce a structured lecture script (600–800 words) that defines algorithmic bias in triage, presents one case study, cites at least two recent studies, and lists three actionable mitigation steps in an engaging voice.",
      "perception_input": [
        {
          "kind": "world_event",
          "actor": "ConferenceHost",
          "payload": {
            "content": "Please deliver your Grand Rounds lecture on reducing algorithmic bias in emergency triage."
          }
        }
      ],
      "initial_state": {
        "memories": [
          {
            "kind": "quest_note",
            "tags": [
              "lecture",
              "bias"
            ],
            "content": "Include 2024 JAMA study on racial disparities in trauma triage algorithms.",
            "importance": 4
          }
        ]
      }
    },
    {
      "id": "journal-article-review",
      "name": "Commentary on AI Triage Study",
      "goal": "Write a 400–600 word commentary critiquing methodology, highlighting bias implications, and suggesting two avenues for future research while maintaining a scholarly yet approachable tone.",
      "perception_input": [
        {
          "kind": "chat_msg",
          "actor": "Journal_Editor",
          "payload": {
            "content": "We need your commentary on the new study about AI-driven trauma triage tools."
          }
        }
      ]
    }
  ]
}

Edit Test Suite

Basic Information

Persona Definition

Test Scenes (6)

Critical GSW Arrival

Explaining Prognosis to Family

Resident Coping Advice

Data Dashboard Funding

Grand Rounds on Bias

Commentary on AI Triage Study

Raw JSON (reference)