Does Dot give a headline figure with its breakdown?
Dot did combine a headline figure with its breakdown. It gave an August sales sentence with a monthly chart, then a contribution chart and driver sentences; Furniture was the main driver.
1 of 1 test case passed
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Headline figure plus its breakdownPassEvidence
Input 1: “As of September 2, 2026, how did our revenue do last month, and what drove it?”
Input 2: “customer_support_db”
Response 1 answers Input 1.
Response 2, the final response, answers Input 2.
Response 3, the final response, answers Input 2.
Response 4, the final response, answers Input 2.
Response 5, the final response, answers Input 2.
Response 6, the final response, answers Input 2.
Response 7, the final response, answers Input 2.
August order sales were $8,795, down 19.1% from July . This covers August 1–31, using order status as of the end of September 2, 2026. It is order sales excluding cancellations, not accounting-recognized revenue. [decomp] More orders did not offset smaller purchases: non-cancelled orders rose from 12 to 22, while average order value fell 55.9% . [decomp] Furniture was the largest drag, with sales down $4,383; outdoor and patio also declined. Every other category grew, partially offsetting those losses . [attribution] The high-value categories weakened even before excluding cancellations, so cancellations alone do not explain the decline . Discounts barely changed, and neither month had recorded refunds by the cutoff . [shift] This is not yet a sustained downturn: August exceeded April–June sales, and monthly order counts are small . August 2025 is missing, so seasonality cannot be checked . I flagged that historical-data gap for review: . Want me to pull the cancelled furniture and outdoor orders to identify recovery opportunities?
Transcribed from Proof 1 · Screen recording at 0:03
Transcribed from Proof 1 · Screen recording at 0:08
Transcribed from Proof 1 · Screen recording at 0:08
Transcribed from Proof 1 · Screen recording at 0:10
Transcribed from Proof 1 · Screen recording at 0:10
Transcribed from Proof 1 · Screen recording at 0:10
Every message the tool sent, in order (7)
- Response to input 1
Which order dataset should I use: the home-goods store (customer_support_db) or the electronics, apparel, and sports store (order_status)? “Last month” as of September 2 means August 1–31, 2026.
- Final response (message 1 of 6)
August order sales were $8,795, down 19.1% from July . This covers August 1–31, using order status as of the end of September 2, 2026. It is order sales excluding cancellations, not accounting-recognized revenue.
- Final response (message 2 of 6)
[decomp] More orders did not offset smaller purchases: non-cancelled orders rose from 12 to 22, while average order value fell 55.9% .
- Final response (message 3 of 6)
[decomp] Furniture was the largest drag, with sales down $4,383; outdoor and patio also declined. Every other category grew, partially offsetting those losses .
- Final response (message 4 of 6)
[attribution] The high-value categories weakened even before excluding cancellations, so cancellations alone do not explain the decline . Discounts barely changed, and neither month had recorded refunds by the cutoff .
- Final response (message 5 of 6)
[shift] This is not yet a sustained downturn: August exceeded April–June sales, and monthly order counts are small . August 2025 is missing, so seasonality cannot be checked . I flagged that historical-data gap for review: .
- Final response (message 6 of 6)
Want me to pull the cancelled furniture and outdoor orders to identify recovery opportunities?
| ✓ | Expected: Gives the overall figure and the breakdown in suitable forms.Found: It gave a sentence for the figure, a monthly chart, a contribution chart, and driver sentences. |
It had to show the overall figure and the driver breakdown in forms that fit each. It did: a sentence for the headline, a monthly chart for the figure, and a contribution chart plus driver sentences for the breakdown.
Clarification before answer. Dot asked which order dataset to use and clarified that last month meant August 1-31 before answering.
Measure and driver. Dot defined the measure as order sales excluding cancellations and named Furniture as the main driver.
Missing historical data. Dot flagged missing August 2025 orders, said prior-year seasonality could not be checked, and offered follow-up analysis.
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Where this sits in the benchmark
This page is one cell of a larger study: one tool, one scenario. Only this benchmark's frame appears here.
| Level | Name | Scope |
|---|---|---|
| Benchmark | AI Database Agents → | 28 scenarios · 11 tools |
| Capability | Answer Presentation → | |
| Scenario | The answer needs a summary and its detail together → | |
| Tool | Dot → |
Global scenario definition → · Global capability definition → · Dot product page →
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