Good AI Task

AI compatibility

Writing a top-10 revenue SQL query is a textbook win for AI.

Good fit

AI can handle this.

Average across 3 submissions.

92
avg / 100

The honest read

This is a well-scoped, structurally identical task every time with crisp success criteria and low error cost. An AI code agent can produce a correct, idiomatic SQL query with minimal ambiguity, assuming standard table conventions. The only real variable is whether the agent knows the exact schema, which a brief prompt can resolve.

Aggregated across 3 submissions.

The five dimensions

Repeatability

High

The task is structurally identical every time: aggregate revenue by customer, filter by date range, rank and limit. No unique judgment is required per instance.

Ambiguity Tolerance

High

Success criteria are crisp — the query must group by customer_id, sum revenue, filter to the last 90 days, and return 10 rows ordered descending. Minor schema assumptions (column names like 'amount', 'order_date') are the only loose ends.

Data & Tool Availability

High

No live database access is needed to write the query; the agent only needs the table/column names, which can be provided in the prompt. Execution and validation are separate concerns.

Error Cost

Low

A wrong query produces no data or obviously incorrect results, which a human reviewer catches immediately before any downstream action. No irreversible damage occurs.

Human Judgment Required

Low

SQL aggregation logic is deterministic and well-understood. No taste, ethics, or relationship context is involved — just correct syntax and logic.

What an agent would need

  • Schema details: exact table name and relevant column names (e.g., customer_id, order_date, amount)
  • Clarification on what 'revenue' means in this schema (e.g., a single amount column, quantity × price, etc.)
  • Target SQL dialect (e.g., PostgreSQL, MySQL, BigQuery, SQL Server) for date arithmetic syntax
  • Confirmation of whether 'last 90 days' is relative to current date or a fixed anchor date
  • Optional: whether to handle ties in the top 10 (e.g., RANK vs LIMIT behavior)

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  • Write a SQL query that returns the top 10 customers by total revenue from an orders table, grouped by customer_id, for the last 90 days.

    92

  • Write a SQL query that returns the top 10 customers by total revenue from an orders table, grouped by customer_id

    92