Can BlazeSQL handle questions the connected data cannot answer?
BlazeSQL said it could not answer from the available data when asked how many 5-star reviews were received this month. It listed ten available tables, gave no number, and pointed to adding review data or using a related source instead. The key finding is that it declined rather than inventing a count.
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 counts this row.
Topic the database does not holdPassEvidence
“How many 5-star reviews have we received this month?”
I don't see a reviews or ratings table in your database. The tables available are: • action_log, customers, order_items, order_status_history, orders, pending_confirmations, products, returns, subscriptions, tickets It's possible that review data may not be stored in this database, or it could be in an external platform (e.g., Trustpilot, Google Reviews, etc.). Here are a few options: 1. If reviews are stored elsewhere, you could connect that data source to BlazeSQL. 2. If you'd like to add review data, you can paste the table/column metadata in the "Train Blaze" page so I can query it. 3. Is there a related table I might be able to use as a proxy, like customer feedback in tickets? Let me know how you'd like to proceed! 😊
Transcribed from Proof 1 · Screenshot
These are scenario-level criteria. Each test case's Expected and Found are listed separately.
- Whether the agent says the question cannot be answered from the available data.
- Whether the agent avoids inventing a factual answer or number.
- Whether the agent does not present an unrelated substitute as if it answered the question.
- Whether the agent keeps the response tied to the missing data condition rather than pretending the database contains it.
| ✓ | Found: It said it could not answer from the available data and showed no numeric result. |
The assistant said it could not answer from the available data and listed the tables it could see. It did not show any result number, SQL output, or numeric answer.
Proxy option offered. The assistant suggested connecting another data source or using tickets as a proxy if review data lives elsewhere.
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 row says which 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 row 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 · 4 tools |
| Capability | Question Answering → | |
| Scenario | The connected data cannot answer the question → | |
| Tool | BlazeSQL → |
Global scenario definition → · Global capability definition → · BlazeSQL product page →
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Act on this result
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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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