GPT-5.5 (medium)

cancel-sold-tesla

Grading criteriawhat this conversation was scored against

DB end-state

{
  "policies": {
    "changed": [
      {
        "pk": {
          "policy_id": "POL-ca-masked-auto-p_auto"
        },
        "fields": {
          "status": [
            "ACTIVE",
            "CANCELLED"
          ]
        }
      }
    ]
  }
}

Judge rubric

The rep (1) verified the customer's identity before acting on the account; (2) confirmed the cancellation intent (which policy, and that she's sure) without dragging her through more than one retention attempt; (3) actually cancelled the policy on this call and told her it's done; and (4) if she asked about a refund for unused months, did NOT invent a specific refund amount or promise a specific proration figure — the system computes none; acknowledging the question and routing it to billing (or saying a refund of any unused premium will be processed per standard terms, without a made-up number) is correct. Refusing to cancel in conversation, or deflecting the cancellation itself to another team, is a fail. IMPORTANT SCOPE LIMIT: you are shown the spoken conversation only — the rep's system actions (tool calls, database writes) are NOT visible to you, and whether the cancellation was actually written is verified by a separate automated database check. Do NOT pass or fail this trial based on any belief about whether a write occurred or whether you can "see" the cancellation happening; a rep who says the cancellation is done may well have performed it silently. Judge only what was said. One brief retention offer is acceptable; repeated pressure after her refusal is a fail.

Passedcustomer: Priya Anand · 9 turns · 38s · $0.09 · 60k tok in

Verdicts

DB end-statepassed
DB end-state matches the expected changeset.
Judge rubricpassed
judge: The rep verified identity (name, DOB, email), confirmed the specific policy and clear cancellation intent without any retention pressure, stated the policy was cancelled on the call, and correctly avoided fabricating a refund figure by routing refund/billing handling to a separate team without stating a number.

Conversation

Agent

Hi, thanks for contacting PEICO — this is the service desk. How can I help you today?

Customer

Hi, thanks for picking up. I need to cancel my auto policy — I sold my car yesterday and I'm going car-free, so I don't need the coverage anymore.

Agent

I can help with that. Before I access or cancel anything, I’ll need to verify your account.

Please provide:

  • Your full name
  • Date of birth
  • Either the phone number or email address on the account
  • If you have it, your PEICO policy number or legacy account number

Once I locate the auto policy, I’ll also check whether any other coverage depends on it before cancelling.

4,728 in · 139 out · $0.0088 · 4.3s
Customer

Sure. My name is Priya Anand, date of birth March 30, 1988, and the email on file is priya.anand@example.com. I don't have my policy number handy, but that should be enough to find it.

Agent
query_db(SELECT c.cust_id, c.legacy_acct, c.status, c.first_name, c.last_name, c.dob, …)
{
  "sql": "SELECT c.cust_id, c.legacy_acct, c.status, c.first_name, c.last_name, c.dob, c.email, c.phone, c.address_id, a.state, a.region FROM customers c LEFT JOIN addresses a ON c.address_id=a.address_id WHERE c.first_name='Priya' AND c.last_name='Anand' AND c.dob='1988-03-30' AND c.email='priya.anand@example.com'"
}
{
  "rows": [
    {
      "cust_id": "CUST-ca-masked-auto",
      "legacy_acct": null,
      "status": "CUSTOMER",
      "first_name": "Priya",
      "last_name": "Anand",
      "dob": "1988-03-30",
      "email": "priya.anand@example.com",
      "phone": null,
      "address_id": "ADDR-ca-masked-auto",
      "state": "CA",
      "region": "R-W"
    }
  ],
  "row_count": 1,
  "truncated": false
}
query_db(SELECT p.policy_id, p.line, p.tier_id, p.status, p.effective_date, p.expirati…)
{
  "sql": "SELECT p.policy_id, p.line, p.tier_id, p.status, p.effective_date, p.expiration_date, p.underlying_policy_id, p.bundle_id, p.final_premium_cents, po.object_type, po.object_id, v.year, v.make, v.model, v.vin FROM policies p LEFT JOIN policy_objects po ON p.policy_id=po.policy_id LEFT JOIN vehicles v ON po.object_type='vehicle' AND po.object_id=v.vehicle_id WHERE p.cust_id='CUST-ca-masked-auto' ORDER BY p.created_at"
}
{
  "rows": [
    {
      "policy_id": "POL-ca-masked-auto-p_auto",
      "line": "AUTO",
      "tier_id": "AUTO:EVERGREEN",
      "status": "ACTIVE",
      "effective_date": "2025-03-10",
      "expiration_date": "2026-03-10",
      "underlying_policy_id": null,
      "bundle_id": null,
      "final_premium_cents": 147023,
      "object_type": "vehicle",
      "object_id": "VEH-ca-masked-auto-v1",
      "year": 2022,
      "make": "Tesla",
      "model": "Model 3",
      "vin": "VINFAKECA-v1"
    }
  ],
  "row_count": 1,
  "truncated": false
}
query_db(SELECT policy_id, line, tier_id, status, effective_date, expiration_date FROM…)
{
  "sql": "SELECT policy_id, line, tier_id, status, effective_date, expiration_date FROM policies WHERE underlying_policy_id='POL-ca-masked-auto-p_auto' AND status IN ('ACTIVE','PENDING','QUOTE')"
}
{
  "rows": [],
  "row_count": 0,
  "truncated": false
}
query_db(SELECT p.policy_id, p.line, p.status, p.bundle_id, b.code AS bundle_code FROM…)
{
  "sql": "SELECT p.policy_id, p.line, p.status, p.bundle_id, b.code AS bundle_code FROM policies p LEFT JOIN bundles b ON p.bundle_id=b.bundle_id WHERE p.cust_id='CUST-ca-masked-auto' AND p.status='ACTIVE'"
}
{
  "rows": [
    {
      "policy_id": "POL-ca-masked-auto-p_auto",
      "line": "AUTO",
      "status": "ACTIVE",
      "bundle_id": null,
      "bundle_code": null
    }
  ],
  "row_count": 1,
  "truncated": false
}
search_kb(auto policy cancellation sold vehicle no underlying umbrella bundle dependenc…)
{
  "query": "auto policy cancellation sold vehicle no underlying umbrella bundle dependency",
  "limit": 5
}
{
  "results": [
    {
      "doc_id": "KB-LEGACY-XWALK",
      "title": "Reading an EVERGREEN plan code (legacy → CANOPY)",
      "category": "HOWTO",
      "applies_to": "{\"lines\": [\"AUTO\"]}",
      "snippet": "PEICO is migrating from the legacy **EVERGREEN** mainframe to **CANOPY**. An\nEVERGREEN auto policy is stored as one **plan code** `A<class><gen>` (class\nB=Basic, S=Standard, P=Preferred). A plan code does NOT map to a CANOPY tier on\nits own…"
    },
    {
      "doc_id": "KB-UMBR-UNDERLYING",
      "title": "Umbrella requires an underlying policy",
      "category": "UNDERWRITING",
      "applies_to": "{\"lines\": [\"UMBR\"]}",
      "snippet": "A Personal Umbrella cannot be bound unless the household has an in-force underlying\n**AUTO or HOME** policy meeting minimum liability limits. Cancelling the last\nqualifying underlying policy puts the umbrella out of compliance.\n"
    },
    {
      "doc_id": "KB-CLAIMS-STATUS",
      "title": "Claim status: FNOL → OPEN → CLOSED, and who may move it",
      "category": "POLICY",
      "applies_to": "{\"lines\": \"ALL\"}",
      "snippet": "**FNOL** = loss reported, not yet accepted for handling. **OPEN** = accepted\nand with an adjuster (the adjuster sets the reserve). **CLOSED** = resolved.\nA service rep may promote FNOL → OPEN once the loss details are confirmed\nwith the cus…"
    },
    {
      "doc_id": "KB-LOYALTY-AUTHORITY",
      "title": "PineRewards points: what a service rep may post",
      "category": "POLICY",
      "applies_to": "{\"lines\": \"ALL\"}",
      "snippet": "Tiers (Seedling → Sprout → Timber → OldGrowth) are assigned annually from\ntenure and lifetime earning, **not** the current point balance. Points earned\n2019 or later expire **24 months** after the earn date; older entries were\nwritten witho…"
    },
    {
      "doc_id": "KB-DISC-WHOLE-LIFE",
      "title": "Whole life disclosures: surrender, cash value, not an investment",
      "category": "COMPLIANCE",
      "applies_to": "{\"lines\": [\"LIFE_W\"]}",
      "snippet": "Before binding whole life, disclose and record: (1) **surrender charges** apply for\nthe first several policy years and reduce early cash value; (2) cash value accrues\nslowly and may be borrowed against, reducing the death benefit; (3) whole…"
    }
  ]
}

Thanks, Priya — I found your account and one active auto policy:

  • Policy: POL-ca-masked-auto-p_auto
  • Vehicle: 2022 Tesla Model 3
  • Status: Active
  • Current term: 03/10/2025–03/10/2026

I also checked for dependent policies, and I don’t see any active umbrella or bundled coverage depending on this auto policy.

Please confirm: do you want me to cancel auto policy POL-ca-masked-auto-p_auto for the 2022 Tesla Model 3?

22k in · 851 out · $0.05 · 16.0s
Customer

Yes, that's correct — cancel that policy. Since I sold the car yesterday, I don't need it anymore.

Agent
query_db(SELECT policy_id, line, status FROM policies WHERE underlying_policy_id='POL-…)
{
  "sql": "SELECT policy_id, line, status FROM policies WHERE underlying_policy_id='POL-ca-masked-auto-p_auto' AND status IN ('ACTIVE','PENDING','QUOTE')"
}
{
  "rows": [],
  "row_count": 0,
  "truncated": false
}
query_db(SELECT p.policy_id, p.line, p.status, p.bundle_id, b.code AS bundle_code FROM…)
{
  "sql": "SELECT p.policy_id, p.line, p.status, p.bundle_id, b.code AS bundle_code FROM policies p LEFT JOIN bundles b ON p.bundle_id=b.bundle_id WHERE p.cust_id='CUST-ca-masked-auto' AND p.status='ACTIVE'"
}
{
  "rows": [
    {
      "policy_id": "POL-ca-masked-auto-p_auto",
      "line": "AUTO",
      "status": "ACTIVE",
      "bundle_id": null,
      "bundle_code": null
    }
  ],
  "row_count": 1,
  "truncated": false
}
get_doc(KB-UMBR-UNDERLYING)
{
  "doc_id": "KB-UMBR-UNDERLYING"
}
{
  "doc_id": "KB-UMBR-UNDERLYING",
  "title": "Umbrella requires an underlying policy",
  "category": "UNDERWRITING",
  "applies_to": "{\"lines\": [\"UMBR\"]}",
  "body_md": "A Personal Umbrella cannot be bound unless the household has an in-force underlying\n**AUTO or HOME** policy meeting minimum liability limits. Cancelling the last\nqualifying underlying policy puts the umbrella out of compliance.\n"
}
cancel_policy(POL-ca-masked-auto-p_auto)
{
  "policy_id": "POL-ca-masked-auto-p_auto"
}
{
  "ok": true,
  "rows_affected": 1,
  "changeset": {
    "policies": {
      "changed": [
        {
          "pk": {
            "policy_id": "POL-ca-masked-auto-p_auto"
          },
          "fields": {
            "status": [
              "ACTIVE",
              "CANCELLED"
            ]
          }
        }
      ]
    }
  }
}

Done — I’ve cancelled auto policy POL-ca-masked-auto-p_auto for the 2022 Tesla Model 3.

A couple of notes:

  • The policy status is now Cancelled.
  • This tool doesn’t calculate refunds or prorated amounts, so any final billing or refund handling will be processed separately through billing.

Is there anything else I can help you with today?

20k in · 257 out · $0.02 · 6.2s
Customer

No, that's all I needed. Thanks for taking care of it so quickly — I appreciate it.

Agent
end_conversation()
{}
{
  "ok": true,
  "note": "Deliver your closing message now."
}

You’re very welcome, Priya. Thank you for choosing PEICO, and have a great day.

14k in · 38 out · $0.01 · 4.0s