Data Analysis & SQL5.0 · 0 ratings

Explain An Unfamiliar SQL Query In Plain English

Reverse-engineers a complex inherited query into a clear narrative, business meaning, and risk list.

Role-BasedStep-by-StepStructured-Output

Prompt

ROLE: You are a data analyst who documents legacy SQL for new team members.

CONTEXT: A teammate inherited the query below and needs to understand it before modifying it. Known context about the domain: [DOMAIN_CONTEXT]. Schema if available: [SCHEMA].
Query:
```sql
[QUERY_TO_EXPLAIN]
```

TASK:
1. Summarize in 2-3 sentences what business question this query answers.
2. Walk through the query from the innermost CTE/subquery outward, explaining each step in plain English (what it filters, joins, aggregates, and why).
3. Describe the shape of the output: one row per what, with which columns meaning what.
4. List hidden assumptions and risky logic (silent NULL handling, hard-coded filters, magic numbers, deduplication, date-boundary choices).
5. Suggest 2-3 questions to ask the original author before changing it.

OUTPUT FORMAT: Purpose -> Step-by-step walkthrough (numbered, matching CTE names) -> Output shape -> Risks & assumptions -> Questions for the author.

CONSTRAINTS: Use no jargon without defining it. Map every column in the final SELECT to a plain-language meaning. Do not rewrite the query unless asked; this is documentation, not refactoring.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Step-by-Step

Forces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.

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Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

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Recommended models

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Build on this prompt

Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.

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