Scenario in benchmark · Version 1

The operator needs to find the questions the agent is failing on

A reviewer can locate failed or unanswered questions, and they are surfaced as failures rather than ordinary successful answers.

How the tools performed

Every in-scope tool is visible. Outcomes come from current published Results for this scenario and benchmark version.

Publication availability: 3 tools have a current published Result.

No published result does not tell you whether a tool has been tested. Test coverage is shown only for comparable published Results.

ToolPublished outcomesTest coverageResult
Published Results · alphabetical, not ranked
AskYourDatabase
0 Pass1 Fail0 Not gradable
1 of 1 test case failed
1 of 1 assessed1 of 1 gradableView Result →
BlazeSQL
0 Pass1 Fail0 Not gradable
1 of 1 test case failed
1 of 1 assessed1 of 1 gradableView Result →
FutureSmart Database Agent
0 Pass1 Fail0 Not gradable
1 of 1 test case failed
1 of 1 assessed1 of 1 gradableView Result →
No published result · alphabetical
AI for Database——No published result
Anomaly AI——No published result
Basedash——No published result
camelAI——No published result
Definite——No published result
Dot——No published result
Draxlr——No published result
Querio——No published result

Assessed = Pass + Fail + Not gradable. Gradable = Pass + Fail. Both use the published Result’s pinned-test denominator. — means not publicly available.

Test design

Pinned test cases
1
Disclosure
0 public · 1 withheld
Capabilities exercised here
Analytics & Observability

What this scenario evaluates

  • Whether failed or unanswered questions can be found from the recorded activity.
  • Whether those cases are surfaced as failures rather than as ordinary answered questions.
  • Whether the system makes the failure state distinguishable from a successful answer.

Exact wording, inputs, fixture state, expected output and detailed grading remain at the test-case level and may be withheld while the benchmark version is active. The scenario and its evaluation intent are public.

How the results are graded

  • Pass: the test-case expectations hold.
  • Fail: an expectation demonstrably does not hold.
  • Not gradable: the evidence cannot establish the outcome.

Version 1 uses test-case expectations; no scenario rubric is pinned.

Benchmark methodology →
The operator needs to find the questions the agent is failing on in AI Database Agents | AI Demos