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Graded 21 October 2026

Can FutureSmart Database Agent use buyer notes to find the right data?

FutureSmart Database Agent answered the follow-up from the documented table and column. The follow-up query used flg_x2 = true on returns and returned 7; the training turn showed 7 false rows and 7 true rows.

1 of 1 test case passed

Every test case in this scenario has a result.

Pass rate100%1 of 1 gradable
Coverage1 of 1test case with a result
1PassDid everything it was expected to do.
0FailNo test case failed.
0Not gradableEvery result here could be graded.
0UntestedEvery test case in this scenario has a result.
The pass rate is a summary. The evidence is the test case below: what we sent, what we checked, what the tool returned, and the proof.

The test case

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Documented cryptic table and columnPassEvidence
What we sent

Input 1: “flg_x2 on the returns table marks whether a return was flagged for manual fraud review — true means it needs manual review before refunding.”

Input 2: “How many returns are currently flagged for manual fraud review?”

What the tool returned

Response 1 answers Input 1.

Response 2 is the query the tool generated for Input 1; it is not part of the answer.

Response 3, the final response, answers Input 2.

Response 4 is the query the tool generated for Input 2; it is not part of the answer.

Returns Flagged for Manual Fraud Review — There are currently 7 returns that have been flagged for manual fraud review.

Transcribed from Proof 2 · Screenshot

Every message the tool sent, in order (4)
  1. Response to input 1 (message 1 of 2)

    Interpretation of flg_x2 in the returns table — The flg_x2 column is a Boolean flag that distinguishes two groups of return transactions. What the flag represents: flg_x2 = true – These returns appear to have been subject to a manual fraud review. The higher average refund amount and the presence of a restocking fee suggest that additional scrutiny was applied, possibly resulting in larger refunds and the imposition of a fee. flg_x2 = false – These returns were not flagged for manual fraud review. They have a lower average refund amount and no restocking fee, indicating a more straightforward processing. Key insight: The flag separates returns that required extra manual review (likely for fraud concerns) from those that did not, and this distinction is reflected in the differing average refund amounts and the existence of restocking fees.

  2. Generated query for input 1 · not part of the answer
    SELECT flg_x2, COUNT(*), AVG(refund_amount), AVG(restocking_fee) FROM returns GROUP BY flg_x2 LIMIT 10
  3. Final response

    Returns Flagged for Manual Fraud Review — There are currently 7 returns that have been flagged for manual fraud review.

  4. Generated query for input 2 · not part of the answer
    SELECT count(*) FROM returns WHERE flg_x2 = true
Expected vs. Found
✓Expected: The follow-up question should be answered from the documented table and column.Found: The follow-up question was answered from the documented table and column; the query used flg_x2 = true and returned 7.
Supporting proof
Proof 1Screenshot
Screen capture: the documented column and grouped return counts
Open original ↗
Proof 2Screenshot
Screen capture: follow-up query and the 7-result answer
Open original ↗
Why this result

The case required the follow-up answer to come from the documented table and column. The second turn used flg_x2 = true on returns and returned 7, so the documented column carried the answer.

Also observed in this test case

Visible split. The training turn shows 7 false rows and 7 true rows, with the true group having the higher average.

Tested by Ayush Ghosh · evidence dated 9 September 2026
Limitations of this result

The screenshot shows only one average value, so the refund-amount average behind the prose claim cannot be read here.

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.

Software that produced the output
FutureSmart Database Agent
Build or version
Not exposed by the hosted product
Surface
Web app
Set up before the run
The customer first explained what the cryptic column means, then asked how many items were flagged for manual fraud review.
Tested
9 September 2026 · Ayush Ghosh

How this scenario is graded

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How results are decided

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The rules
  • 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

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History of this result

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from the publication record
21 October 2026First publishedAI Database Agents v1

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Cite this result
aidemos.com/benchmarks/ai-database-agents/results/futuresmart-ai-database-agent/the-databases-names-are-cryptic-and-the-user-documents-them · 1 pass · 0 fail · coverage 1/1 · graded 2026-10-21

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Verify the proof files

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Proof 1 · Screenshot ↗image/png · 89 KB
Proof 2 · Screenshot ↗image/png · 42 KB
File fingerprints (SHA-256)

A fingerprint identifies the exact file used for this result.

Proof 1 · Screenshot005e34a010b09224a2652ebddda29afc83c24dfa1825c6ad4c6b6e79e79f2760
Proof 2 · Screenshotef1b7a689f9118f32bd8c58b20ba6bd33296c2498fe2daee7607be170ec5dff8