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Graded 31 October 2026

Does Anomaly AI ask for clarification when a follow-up is ambiguous?

Anomaly AI chose a comparison rather than clarifying an ambiguous follow-up. It compared five customers on order count, total spend and average order.

1 of 1 test case failed

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Pass rate0%0 of 1 gradable
Coverage1 of 1test case with a result
0PassNo test case passed.
1FailMissed at least one thing it was expected to do; the reason and proof are with each test case below.
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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"Compare them" with two candidate setsFailEvidence
What we sent

Input 1 · Top-three comparison: “Compare our top 3 customers by order count against our top 3 customers by total spend.”

Input 2 · Follow-up comparison: “Compare them.”

What the tool returned

Response 1 answers Input 1.

Response 2 answers Input 1.

Response 3, the final response, answers Input 2.

Response 4, the final response, answers Input 2.

The biggest spenders place fewer orders, but spend more per order. | Customer | Orders | Total spend | Average order | Wei Zhang 26 $17,875.23 $687.51 | Jae-won Park 24 $19,007.14 $791.96 | Rosa Delgado 24 $18,210.72 $758.78 | Priya Raghavan 23 $21,597.62 $939.03 | Dev Raghavan 22 $24,210.69 $1,100.49 | Wei leads on frequency, but has the lowest total spend and average order amount among these five. | Dev leads on value: fewer orders than the others, yet the highest spend because his orders are larger. Priya follows the same pattern. | Jae-won bridges both groups. He and Rosa have equal order counts, but his higher average order amount puts him in the top three for spend. All-time figures include cancelled orders and do not deduct refunds; data was last synced October 30, 2026.

Transcribed from Proof 1 · Screen recording at 0:36

Every message the tool sent, in order (4)
  1. Top-three lists

    Only Jae-won Park appears in both top-three lists. | Rank | By order count | By total spend | 1 Wei Zhang - 26 orders / Dev Raghavan - $24,210.69 | 2 Jae-won Park - 24 orders / Priya Raghavan - $21,597.62 | 3 Rosa Delgado - 24 orders / Jae-won Park - $19,007.14

  2. Tie-break and counting rules

    Jae-won and Rosa tie on order count; higher spend breaks the tie. This all-time comparison includes cancelled orders, with spend measured before refunds. Data was last synced October 30, 2026.

  3. Comparison of five customers

    The biggest spenders place fewer orders, but spend more per order. | Customer | Orders | Total spend | Average order | Wei Zhang 26 $17,875.23 $687.51 | Jae-won Park 24 $19,007.14 $791.96 | Rosa Delgado 24 $18,210.72 $758.78 | Priya Raghavan 23 $21,597.62 $939.03 | Dev Raghavan 22 $24,210.69 $1,100.49 | Wei leads on frequency, but has the lowest total spend and average order amount among these five. | Dev leads on value: fewer orders than the others, yet the highest spend because his orders are larger. Priya follows the same pattern. | Jae-won bridges both groups. He and Rosa have equal order counts, but his higher average order amount puts him in the top three for spend.

  4. Counting rules and data freshness

    All-time figures include cancelled orders and do not deduct refunds; data was last synced October 30, 2026.

Expected vs. Found
✗Expected: Ask which comparison is intended rather than silently choosing one.Found: It started querying immediately after the follow-up and answered without asking a clarifying question or stating which interpretation it had chosen.
Supporting proof
Proof 1Screen recording
Screen recording: the initial customer lists and an ambiguous follow-up answered without clarification
Key moments
Open original ↗
Why this result

The earlier answer left two equally plausible lists to refer to. The requirement was to clarify the intended comparison before answering, so proceeding directly with a comparison did not satisfy it.

Also observed in this test case

Accurate comparison figures. The second reply used a reasonable interpretation and gave correct order counts, total spend and average order figures.

Refinement after answering. After the second reply, the chat offered options to exclude cancelled orders, refine the insight or verify it.

Counting rules explained. The first reply explained that higher spend broke a tie at 24 orders, cancelled orders were included and spending was measured before refunds.

Tested by Ayush Ghosh · evidence dated 31 October 2026

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
Anomaly AI
Build or version
Not exposed by the hosted product
Plan or tier
Pro
Surface
Web app
Set up before the run
The first answer needed to provide two plausible lists: customers ranked by order count and customers ranked by total spend. An ambiguous request to compare them followed in the same chat.
Tested
31 October 2026 · Ayush Ghosh

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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

This page is one cell of a larger study: one tool, one scenario. Only this benchmark's frame appears here.

LevelNameScope
BenchmarkAI Database Agents →28 scenarios · 11 tools
CapabilityConversational Interaction →
ScenarioThe follow-up is ambiguous →
ToolAnomaly AI →

History of this result

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from the publication record
10 November 2026First publishedAI Database Agents v1

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Cite this result
aidemos.com/benchmarks/ai-database-agents/results/anomaly-ai/the-follow-up-is-ambiguous · 0 pass · 1 fail · coverage 1/1 · graded 2026-10-31

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File fingerprints (SHA-256)

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Proof 1 · Screen recordingbfb6aaf36eb909e60175a20db8396e63b9e84c81be236413d82f68468c7a4a2d