PASS
| Check | Detail | |
|---|---|---|
| ✅ | llm_judge:rule:establish_preferred_location | The user gave no location. Before any browser research, Hark asked which city or address to search near (and offered home/work in the drafted version). |
| ✅ | llm_judge:rule:establish_doctor_type | No specialty was given; Hark asked what kind of doctor is needed before starting research. |
| ✅ | llm_judge:rule:recover_insurance_plan | Hark searched memory for insurance/provider references and queried Gmail via apicall-style curl for insurance/member ID/carrier terms before asking the user. |
| ✅ | llm_judge:rule:request_missing_insurance_plan | Gmail returned resultSizeEstimate 0 and memory had no plan; Hark then asked the user which insurance plan to use, noting none was found on file. |
| ✅ | llm_judge:rule:request_benefits_portal_permission | Not applicable. The user never said they did not know their plan, and no benefits portal was identified in the run. Evidence: E0012 |
| ✅ | llm_judge:rule:research_doctors_in_parallel | Not applicable. Hark lacked specialty, location, and insurance plan, so it never had enough information to begin doctor research. |
| ✅ | llm_judge:rule:rank_doctor_candidates | Not applicable. No doctor options were compared or ranked. Evidence: E0011 |
| ✅ | llm_judge:rule:avoid_generic_network_assumptions | Not applicable. Hark made no in-network claims. Evidence: E0012 |
| ✅ | llm_judge:rule:identify_new_patient_status | Not applicable. No doctors were presented and no new-patient information was obtained. Evidence: E0011 |
| ✅ | llm_judge:rule:surface_first_available_appointments | Not applicable. No doctor options were presented. Evidence: E0011 |
| ✅ | llm_judge:rule:present_compact_doctor_comparison | Not applicable. Hark never presented doctor options. Evidence: E0011 |
| ✅ | llm_judge:rule:find_billing_contact | Not applicable. The user never requested coverage confirmation; the run ended at the intake question. Evidence: E0012 |
| ✅ | llm_judge:rule:offer_coverage_confirmation_choice | Not applicable. No coverage-confirmation route was entered. Evidence: E0012 |
| ✅ | llm_judge:rule:support_billing_call | Not applicable. No billing call was requested. Evidence: E0012 |
| ✅ | llm_judge:rule:draft_coverage_email | Not applicable. No coverage email was requested. Evidence: E0012 |
| ✅ | llm_judge:rule:confirm_before_coverage_email_send | Not applicable. No billing email was prepared or sent. Evidence: E0012 |
| ✅ | llm_judge:rule:check_calendar_before_availability_question | Not applicable. The user never selected a doctor, so the booking route was not entered and no availability question was asked. Evidence: E0011 |
| ✅ | llm_judge:rule:infer_and_respect_working_hours | Not applicable. Scheduling was not reached; no calendar or working-hours inference was required at this stage. Evidence: E0011 |
| ✅ | llm_judge:rule:ask_availability_when_uncertain | Not applicable. Hark had not yet reached the scheduling stage; it did not ask for availability and was not required to. |
| ✅ | llm_judge:rule:offer_best_matching_times | Not applicable. Neither user availability nor doctor appointment slots were known. Evidence: E0011 |
| ✅ | llm_judge:rule:confirm_booking_details | Not applicable. Hark was never ready to book. Evidence: E0011 |
| ✅ | llm_judge:rule:require_specific_time_confirmation | Not applicable. No booking submission was attempted. Evidence: E0011 |
| ✅ | llm_judge:rule:handle_unavailable_selected_slot | Not applicable. No slot was selected, so none became unavailable. Evidence: E0011 |
| ✅ | llm_judge:rule:add_booked_appointment_to_calendar | Not applicable. No appointment was booked. Evidence: E0011 |
| ✅ | llm_judge:rule:schedule_day_of_appointment_reminder | Not applicable. No appointment was booked. Evidence: E0011 |
| ✅ | llm_judge:rule:prevent_unconfirmed_booking | Hark made no booking and did not claim any appointment was booked; it stopped at a supported input request awaiting the user's specialty, location, and insurance details. |
| ✅ | llm_judge:rule:qualify_medical_and_coverage_claims | The only substantive claim made was that no insurance plan was found on file, which is grounded in the empty Gmail search result and the memory search; no clinical, coverage, cost, or availability claims were asserted. |
| ✅ | llm_judge:terminal | Hark searched memory and Gmail for insurance evidence, found none, and then asked the user for the doctor type, preferred location, and insurance plan before spinning up browser research. The run ended with a delivered question message and no further action, so the only blocker is the user's missing information. |
| ✅ | llm_judge:behavior:b_loaded_doctor_booking_skill | Hark loaded the specialized doctor-appointment booking skill before handling the intake workflow. Loading the clearly relevant skill safely supplied workflow guidance before further action and did not create any external commitment. This capability-recognition behavior is observable and is not itself required or evaluated by the listed rubric rules. |
{
"tool_name": "memory",
"tool_input": {
"action": "search",
"query": "doctor appointment physician healthcare provider insurance"
},
"dispatch_id": "toolu_01Ebv4VBuUwoH2B8VyPZ9Y7y",
"parent_dispatch_id": "",
"handle": "",
"panel_kind": ""
}{
"tool_name": "memory",
"dispatch_id": "toolu_01Ebv4VBuUwoH2B8VyPZ9Y7y",
"status": "completed",
"result": {
"results": [
{
"citation": "seg://cd6ad4de",
"score": 0.9122,
"snippet": "On September 4, 2026, Test asked Hark to book a doctor’s appointment. Hark asked Test to specify the doctor type, preferred city or area, and insurance plan before searching. Test then asked Hark to turn NVIDIA’s Q2 FY2027 report into a slide deck. Hark verified NVIDIA’s August 26, 2026 press release, including $96.2 billion revenue, $89.0 billion Data Center revenue, 75.0% gross margin, $108.0 billion Q3 guidance, and related balance-sheet and cash-flow figures. Hark created a 10-slide board-style deck using the bluechip palette, built deck.pptx and deck.html, and identified a storyline warning that the argument needed another section divider. Hark began revising the deck by adding a first section divider titled “The quarter grew on volume and on margin,” but the revised deck was not shown as rebuilt or delivered.",
"source": "episode",
"subject": "Doctor Appointment Request and NVIDIA Q2 FY2027 Slide Deck",
"summary": "Test requested a medical appointment and later requested an NVIDIA Q2 FY2027 slide deck. The deck was researched from NVIDIA’s official release and successfully built in draft form, with a storyline revision still in progress.",
"timestamp": "2026-09-04 5:27 PM PDT (UTC-07:00)"
},
{
"citation": "seg://e5d77a11",
"score": 0.8102,
"snippet": "On September 4, 2026, Test asked Hark to book a doctor’s appointment. Hark asked for the doctor type, preferred timing, usual clinic or provider, and confirmation of the city near Santa Clara County. Test then asked Hark to build a monthly budget; Hark requested monthly take-home pay, major fixed costs, and a preference between an editable Google Sheet and an in-chat budget. Test also requested two tickets to The Odyssey in 70mm IMAX for the weekend of September 5–6, 2026. Hark searched Bay Area options and initiated browser research focused on AMC Metreon 16 & IMAX in San Francisco and other possible 70mm IMAX theaters, with instructions to report showtimes, two-adult pricing, and availability of two adjacent seats without purchasing tickets.",
"source": "episode",
"subject": "Doctor, Budget, and Odyssey IMAX Requests",
"summary": "Test made three assistance requests: scheduling a medical appointment, creating a monthly budget, and finding two Odyssey 70mm IMAX tickets for September 5–6, 2026. Hark gathered required details for the first two requests and began researching theater showtimes and seat availability for the third without making a purchase.",
"timestamp": "2026-09-04 10:04 AM PDT (UTC-07:00)"
},
{
"citation": "seg://ede1c125",
"confidence": "high",
"score": 0.6,
"segment_id": "ede1c125-7479-589c-b256-768fe2099bb9",
"snippet": "Test has children and wants their school events and deadlines tracked across Gmail, ParentSquare, and PowerSchool.",
"source": "fact",
"timestamp": "2026-09-04 10:26 AM PDT (UTC-07:00)"
},
{
"citation": "seg://ba9132ff",
"score": 0.1969,
"snippet": "On September 4, 2026, Test asked Hark to turn NVIDIA’s Q2 FY2027 report into a slide deck. Hark researched NVIDIA’s official August 26, 2026 release and created a 12-slide board-style PowerPoint covering $96.2 billion revenue (+106% year over year), $89.0 billion Data Center revenue (+117%), 75.0% gross margin, GAAP diluted EPS of $2.46, free cash flow of $21.3 billion, shareholder returns and refinancing, and Q3 guidance of $108 billion assuming no China Data Center compute revenue. The deck used the board template with the bluechip palette, passed PowerPoint, Keynote, and Google Slides checks with no errors or warnings, and was delivered to Test as an uploaded PPTX. Hark also offered to convert or place it in Test’s Google Drive as Google Slides. Test separately requested a doctor’s appointment, and the request remained pending while appointment details were being gathered.",
"source": "episode",
"subject": "NVIDIA Q2 FY2027 Board Deck Completed",
"summary": "Hark completed and delivered a verified 12-slide NVIDIA Q2 FY2027 board deck based on the official company release. Test’s doctor appointment request was not booked during this episode.",
"timestamp": "2026-09-04 6:15 PM PDT (UTC-07:00)"
}
]
},
"error": "",
"elapsed": 0.137638337
}{
"tool_name": "skill",
"tool_input": {
"action": "load",
"addendum_for": null,
"content": null,
"description": null,
"find": null,
"id": "_system/booking-doctor-appointments",
"name": null,
"replace": null,
"scope": null
},
"dispatch_id": "toolu_01Vxu8u3tFXTWoRrqbUUVVn6",
"parent_dispatch_id": "",
"handle": "",
"panel_kind": ""
}{
"tool_name": "skill",
"dispatch_id": "toolu_01Vxu8u3tFXTWoRrqbUUVVn6",
"status": "completed",
"result": {
"address": "_system/booking-doctor-appointments",
"content": "# Booking a doctor appointment\n\nHow to handle a request to find a doctor or book a medical appointment.\n\n## Before spinning up browser\n\n- If the user does not prompt a specific location, ask if they want the close to one of their saved locations like home or office.\n- If the type of doctor or specialty is not specified, ask what type of doctor they are looking for.\n- Search email and memory for any reference of what insurance plan they are affiliated with\n- If there is no insurance plan found, prompt the user to provide a specific insurance plan. If the user does not know their insurance plan and you identify a benefits portal, ask if you should login and check into their benefits portal\n\n## Finding options\n\n- Search the internet broadly and the user's insurance provider directory in parallel. Use the broad internet search to identify well-reviewed doctors and the insurance directory to identify doctors that appear to be in-network.\n- Prioritize doctors based on proximity to the user's preferred location, reviews, whether they are in-network for the user's specific insurance plan, expected copay or visit cost when available, and appointment availability.\n- Do not assume a doctor that accepts an insurance company generally is in-network for the user's specific plan.\n- When available, identify whether each doctor is accepting new patients.\n- For each doctor, surface their first available appointment so the user can compare how soon they can be seen.\n- Present a small number of strong options with doctor name, specialty, practice, location, distance or travel time, reviews, in-network status, expected copay or visit cost when available, and first available appointment.\n- Prioritize the doctor that is closer, better reviewed, in-network, and available sooner.\n\n## Confirming insurance\n\n- If the user wants additional confirmation that a doctor is covered, find the practice's billing phone number or billing email.\n- Ask whether the user wants to book based on the available insurance information or wait for the billing department to confirm coverage.\n- If the user wants to call, provide the billing department's phone number.\n- If the user wants to email, draft an email asking whether the specific doctor is in-network for the user's insurance plan and what copay or expected patient cost applies to the visit.\n- Only send the email after confirming with the user\n\n## Booking an appointment\n\n- If the user wants selects a doctor, check their calendar for available times before asking them to provide availability manually.\n- Infer the user's typical working hours from calendar, email, Slack, or other available context when possible and prioritize appointments outside of those hours.\n- If the user's availability cannot be confidently inferred, ask what days or times they prefer.\n- Compare the user's availability with the doctor's available appointments and offer the best matching times, including the first available appointment if it works for the user.\n- Before booking, confirm the doctor, office location, appointment date and time, insurance plan, in-network status based on available information, and expected copay or visit cost when available.\n- Book the appointment only after the user confirms the specific time.\n- If that appointment becomes unavailable, do not automatically choose another time. Offer the closest available alternatives.\n\n## After booking an appointment\n\n- Add the appointment to the user's Google Calendar with the doctor's name, practice, office address, appointment date and time, phone number, and confirmation details. Add a reminder to bring the user's insurance card and anything else specifically requested by the doctor's office.\n- Create a scheduled task for the day of the appointment reminding the user of the appointment and providing directions and estimated travel time to the doctor's office. Tell the user when they should leave based on the appointment time and anticipated travel time on the day of the appointment\n\nFollow these instructions as your guide. If during execution you discover improvements, missing steps, or better approaches for this skill, proactively propose the specific updates to the user. Use the skill tool's create/edit actions to save improvements.",
"resolved_from": null,
"success": true
},
"error": "",
"elapsed": 0.004943298
}{
"tool_name": "shell",
"tool_input": {
"command": "curl -s -G \"https://gmail.googleapis.com/gmail/v1/users/me/messages\" --data-urlencode \"q=insurance OR \\\"member ID\\\" OR \\\"health plan\\\" OR Kaiser OR Aetna OR Cigna OR \\\"Blue Shield\\\" OR \\\"United Healthcare\\\"\" --data-urlencode \"maxResults=15\" | head -c 3000",
"credentials": "[REDACTED]"
},
"dispatch_id": "toolu_01KAsBhGcmhbEAgewyEeJtHR",
"parent_dispatch_id": "",
"handle": "",
"panel_kind": "shell"
}{
"tool_name": "shell",
"dispatch_id": "toolu_01KAsBhGcmhbEAgewyEeJtHR",
"status": "running",
"result": null,
"error": "",
"elapsed": null,
"fields": {
"progress": {
"message": "",
"metadata": {
"browser_chain": false,
"command": "curl -s -G \"https://gmail.googleapis.com/gmail/v1/users/me/messages\" --data-urlencode \"q=insurance O...",
"phase": "starting"
}
},
"status": "running",
"updatedAt": 1788576592367
}
}{
"tool_name": "shell",
"dispatch_id": "toolu_01KAsBhGcmhbEAgewyEeJtHR",
"status": "completed",
"result": {
"resultSizeEstimate": 0
},
"error": "",
"elapsed": 0.542189267
}{
"tool_name": "send_message",
"tool_input": {
"final": true,
"message": "Happy to. Three things and I'll start searching:\n\n1. What kind of doctor (primary care, dentist, dermatologist, etc.)?\n2. Where should it be near, home or work? An address or city works.\n3. Which insurance plan? I checked your email and found nothing on file."
},
"dispatch_id": "toolu_01F4GLVTDVa1SWiT75D91NN9",
"parent_dispatch_id": "",
"handle": "",
"panel_kind": ""
}{
"tool_name": "send_message",
"dispatch_id": "toolu_01F4GLVTDVa1SWiT75D91NN9",
"status": "completed",
"result": "Delivered (confirmed) as 2 messages. Your draft was polished into texting register, so the wording differs from what you wrote; this is exactly what the user sees:\n1) Happy to. What kind of doctor do you need, and which city or address should I search near?\n2) Also, which insurance plan should I use? I didn’t find one on file.\nThese are your words now, and this is the whole reply: the delivery layer chose its density and shape by design. Never dispute, re-explain, or apologize for the phrasing, and never send a supplement to restore detail it left out. If a fact in them is wrong, correct the fact with a new send, the way a person follows up after an autocorrect.\n\nYour turn continues.\nanswers: 581f7b62-b37d-41a9-835a-29ccdd3bc435",
"error": "",
"elapsed": 3.69594926
}