It adds interpretation such as Rahul Sharma being the all-rounder and Mohan Vishe being a payment-risk red flag, rather than just listing rows.
What was measured
Business Insight
Does it explain what the result means?
decisive for this rankingtransformation
Explaining what the result means is part of making the database answer actually useful to a business user. (2 of 3 judges)
What was given, what came back
Test input: Best customers with unpaid-order and payment-method follow-ups · text · group: live-database-plain-english-queries
Input — what we sent
The exact prompt
Who are my best customers — the ones who order the most and spend the most? Follow-up 1: For the top 3 from that list — do any of them have unpaid orders? Follow-up 2: What payment methods do these top 3 usually use?
A conversational multi-table customer analysis with follow-up questions. It asks for the best customers by both order volume and spend, then drills into unpaid orders for the top 3 and their usual payment methods. Designed to test ranking logic, join-heavy analysis, and follow-up context retention.
Why this input is hard
- · ambiguous business term interpretation
- · multi-table joins
- · aggregation and ranking
- · follow-up context retention
- · scoping to a selected subset
- · payment behavior analysis
Output — unretouched
Also checked on this input — same tool, 5 other criteria
Ambiguity Handling✓ WorkedIt handles the ambiguous 'best customers' request by surfacing both order-count and spend rankings instead of silently choosing one metric.Follow-Up Context✓ WorkedIt preserves the selected top 3 across turns and reuses the earlier result set for the payment-method follow-up without issuing a new SQL query.Plain English Query Handling✓ WorkedIt can interpret informal ranking language like 'the ones who order the most and spend the most' and launch the analysis directly.Result Readability✓ WorkedIt presents the answer as clearly labeled ranking tables and customer-level payment summaries, with visual risk cues for unpaid or shipped orders.SQL Generation✓ WorkedIt can generate follow-up SQL constrained to exactly the top 3 customers, using hardcoded customer IDs in the WHERE clause.
Provenance
- Observation
- 239f04d5-19bb-454b-bebc-39db63df6c63
- Evidence run
- af2abc96-3311-484b-a19d-854a2fdd2bf3
- Study
- Query Live Databases Using Plain English with AI
- Research task
- 86b9y6c99
- Tested at
- not recorded
- Source
- first-party
- Evidence state
- verified
- Proof shown
- input + output shown
- Cost / latency
- not captured
- Repeat run
- not captured
- Tester
- not captured
The last three rows are honest blanks, not placeholders — our capture has no field for them yet.
Query this
get_evidence({
tool: "askyourdatabase",
scenario: "live-database-plain-english-queries"
})MCP · mcp.aidemos.com/api/mcp
Free with attribution.
Same input, same check — 7 other tools
measured on Business Insight
Basedash✓ WorkedIt explains what the numbers mean by naming Rahul Sharma as the best overall customer, Mohan Vishe as the most frequent, and Deepak Kulkarni as the biggest spender.BlazeSQL✓ WorkedIt explains the follow-up data in business terms, including that Rahul Sharma has 1 unpaid order worth $2,199 in CONFIRMED status while Deepak Kulkarni and Karan Joshi are fully paid up.camelAI◐ MixedIt gives a one-line business takeaway by naming Rahul Sharma as the strongest frequency-and-value combination, but it stops there without any deeper interpretation or recommendation.Definite✓ WorkedIt adds useful interpretation by flagging Rahul Sharma's unpaid $2,199 order, noting it had been confirmed but unpaid since April 2025, and linking his payment methods to the issue as likely an oversight rather than a pattern.Dot✓ WorkedIt adds interpretation instead of only listing rows: Rahul is framed as the strongest all-around customer, and the tool warns that Deepak and Karan's 'usual' payment method is not yet a stable preference because each has only one order.Draxlr⚠ StruggledIt produced query descriptions, but no after-the-table narrative that distilled the result into a takeaway like which top customer had unpaid orders.FutureSmart NL2SQL Agent◐ MixedThe payment-method follow-up gives a concise dominant-method insight for the top customers, but the result is incomplete as a business answer because it does not surface the full payment-method picture implied by the customer totals.
This evidence is published in
From the same study (page rebuilt from a later run)
Real inputs and real outputs, no retouching · every cell queryable via API & MCP · aidemos.com