Can Basedash find and inspect an exchange a user complains about?
Basedash made the complained-about exchange findable and inspectable. The chat list led to the question and full answer, and also opened two chats from another member.
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.
Find a complained-about exchangePassEvidence
“How many complaints have we received on social media this month?”
I can't determine the number of social-media complaints for October 2026 from the connected data. There's no social-media source or channel field identifying where complaints came from. The support-ticket data contains no tickets created this month; the latest is dated August 28, 2026. That does not establish that you received zero social-media complaints—those may not be captured here.
Transcribed from Proof 2 · Screenshot
| ✓ | Expected: The specific exchange can be found and inspected, including the question and response.Found: The complaints exchange opened with its question and both paragraphs of the answer visible. Two chats from another member also opened with their questions and complete replies. |
The exchange had to be found and inspected. It was reached through the chat list, with the question and whole answer visible. The complained-about chat belonged to the admin’s account; the same list also opened two chats from another member.
Search missed the chat. Searching for complaints returned no results even while the social media complaints chat was visible in the sidebar. A shorter search returned members, but no chats.
No person or date. No person or date filter. Finding a chat means scanning the list by title: workable at the roughly 30 chats in this workspace, but slow in a busy one.
Reported analysis time. Above the social media complaints reply, Basedash reported an analysis time of 54 seconds.
Context in the reply. The social media complaints reply described the available support-ticket data and cautioned that it did not establish there were zero complaints.
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
How we decide Pass, Fail and Not gradable. The same rules apply to every tool tested on this scenario.
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 | Analytics & Observability → | |
| Scenario | A user reports a bad answer and the operator has to find it → | |
| Tool | Basedash → |
Global scenario definition → · Global capability definition → · Basedash product page →
History of this result
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Act on this result
Nothing filed here edits the run or the grade. A challenge opens a review, and a review can produce a new run or a re-grade — which becomes the current result and leaves this one in the history.
You run the same kind of test against your own setup and get the same behaviour.
Agree →Yours behaves differently. Tell us what you got, with a screenshot if you have one.
Disagree →Something here is wrong — a reference value, a transcription, a grade.
Report an issue →Tell us what changed and we schedule a rerun of the failing test case. The old result stays as history.
Vendor notice →The same record is available as structured data through the AI Demos MCP server, with the counts, the coverage and every per-test-case reason carried as fields.
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File fingerprints (SHA-256)
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