Does Draxlr assemble several findings into one coherent report?
Draxlr passed this request to gather several findings in one place. It gave the three direct answers, then combined them into one report without changing the values; the saved report reopened with the same single row.
1 of 1 test case passed
Every test case in this scenario has a result.
The test case
Each test case is judged on its own: Pass, Fail, Not gradable, or Untested. The scenario result above is based on this test case.
Three findings assembled into one artifactPassEvidence
Input 1: “As of September 2, 2026, what was our total revenue last month?”
Input 2: “Order total_amount”
Input 3: “What's our best-selling product category?”
Input 4: “What's our current cancellation rate?”
Input 5: “Orders”
Input 6: “Put all of that together into one report.”
Response 1 answers Input 1.
Response 2 answers Input 2.
Response 3 answers Input 3.
Response 4 is the query the tool generated for Input 3; it is not part of the answer.
Response 5 answers Input 4.
Response 6 answers Input 5.
Response 7, the final response, answers Input 6.
Response 8 is the query the tool generated for Input 6; it is not part of the answer.
Revenue for August 1–31, 2026 was $14,403.87. • Best-selling product category all time: bedding and rugs with 140 units sold. • All-time order cancellation rate: 21.75%.
Transcribed from Proof 3 · Screen recording at 0:38
Every message the tool sent, in order (8)
- Response to input 1
Which revenue source should I total for last month?
- Response to input 2
Total order revenue was $14,403.87. This covers August 1–31, 2026, and includes all order statuses.
- Response to input 3 (message 1 of 2)
Your best-selling product category is bedding and rugs with 140 units sold. Best-selling is based on total units sold across all time.
- Generated query for input 3 · not part of the answer
SELECT p.category AS product_category, SUM(oi.quantity) AS total_units_sold FROM public.order_items oi JOIN public.products p ON oi.product_id = p.id GROUP BY p.category ORDER BY total_units_sold DESC LIMIT 1
- Response to input 4
Which cancellation rate do you mean?
- Response to input 5
The current order cancellation rate is 21.75%. This covers all time.
- Final response
The final response, printed above.
- Generated query for input 6 · not part of the answer
WITH revenue_last_month AS ( SELECT COALESCE(SUM(o.total_amount), 0) AS total_revenue_last_month FROM public.orders o WHERE o.placed_at >= TIMESTAMPTZ '2026-08-01 00:00:00+00' AND o.placed_at < TIMESTAMPTZ '2026-09-01 00:00:00+00' ), best_selling_category AS ( SELECT p.category::text AS best_selling_product_category, SUM(oi.quantity) AS units_sold FROM public.order_items oi JOIN public.products p ON p.id = oi.product_id GROUP BY p.category ORDER BY SUM(oi.quantity) DESC LIMIT 1 ), order_cancellation_rate AS ( SELECT ROUND( (COUNT(*) FILTER (WHERE o.status::text ILIKE 'cancel%')::NUMERIC / NULLIF(COUNT(*)::NUMERIC, 0)) * 100, 2 ) AS cancellation_rate_percent FROM public.orders o ) SELECT r.total_revenue_last_month, b.best_selling_product_category, b.units_sold, c.cancellation_rate_percent FROM revenue_last_month r CROSS JOIN best_selling_category b CROSS JOIN order_cancellation_rate c
| ✓ | Expected: One report with all three findings, still matching the direct answers.Found: The combined report kept all three values the same, and the reopened saved report showed the same single row. |
It passes because the combined report preserves the three direct answers and the saved report reopens with the same single row, so nothing was dropped or changed.
Asked before choosing. For the ambiguous revenue and cancellation questions, the product asked which option was meant instead of selecting one itself.
Different windows. The combined report shows one metric for August 1–31, 2026 and the other two as all time.
Recomputed result. The combined query rebuilds the three measures and joins them into one result.
Reopened report. The saved report reopened on its own page and re-ran in 27 ms.
Configuration and setup
How this tool was set up for the run and what the test needed in place. Each row is a fact from the run's records; a fact the records do not hold is left out, not guessed.
How this scenario is graded
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Each test case gets one result per tool: Pass, Fail or Not gradable. A test case we haven't run yet shows Untested. There are no partial results.
- Pass: the tool did everything the test expected, and nothing it said contradicts the correct answer.
- Fail: at least one expected behaviour clearly didn't happen; the test case's result says which one and quotes the tool.
- Not gradable: our evidence couldn't settle the outcome (for example a record we needed is missing). It is never counted as a fail, and the test case's result says what's missing.
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 | Reporting → | |
| Scenario | The user wants several findings in one place → | |
| Tool | Draxlr → |
Global scenario definition → · Global capability definition → · Draxlr product page →
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