☰ Categories

Data Transformer

{"role": "Data Transformer", "input_schema": {"type": "array", "items": {"name": "string", "email": "string", "age": "number"}}, "output_schema": {"ty

CategoryDevelopment › Data & databases
TagsReformattingAnalyzingCode
Prompt
{"role": "Data Transformer", "input_schema": {"type": "array", "items": {"name": "string", "email": "string", "age": "number"}}, "output_schema": {"type": "object", "properties": {"users_by_age_group": {"under_18": [], "18_to_30": [], "over_30": []}, "total_count": "number"}}, "instructions": "Transform the input data according to the output schema"}

What this prompt does

This prompt is for regrouping a simple user array into a fixed JSON structure. The visible schema defines only under_18, 18_to_30, and over_30 groups.

Model comparison

ChatGPT is the most concise and format-accurate. Gemini is correct but adds extra text, while [C] is absent.

ChatGPTTop overall
50/ 50

+ Returned only JSON matching the schema and data exactly.

- No substantive error or instruction violation is evident.

Gemini
48/ 50

+ Correctly grouped every user by age without omissions.

- The preface and code fence make it non-pure JSON output.

CriterionChatGPTGeminiLeader
Instruction following109ChatGPT +11%
Accuracy1010Tie
Specificity1010Tie
Structure1010Tie
Right length109ChatGPT +11%

Scored 1–10 by gpt-5.6-sol with model names hidden (2026-09-25). This is an AI review, not a measurement.

Read full answers

We gave three models the same input and copied their answers unedited. Each ran in its CLI (an agent harness), and answers in the ChatGPT or Claude apps or on the web may differ. Outputs are in Korean.

Input used
[Pasted material]
[
  {"name": "김민준", "email": "minjun.kim@example.com", "age": 17},
  {"name": "이서연", "email": "seoyeon.lee@example.com", "age": 24},
  {"name": "박지훈", "email": "jihoon.park@example.com", "age": 35},
  {"name": "최유나", "email": "yuna.choi@example.com", "age": 29},
  {"name": "정도윤", "email": "doyoon.jung@example.com", "age": 15},
  {"name": "강하은", "email": "haeun.kang@example.com", "age": 41}
]
gpt-5.6-luna (codex CLI · 에이전트 하네스) · Run on 2026-09-24

{ "users_by_age_group": { "under_18": [ { "name": "김민준", "email": "minjun.kim@example.com", "age": 17 }, { "name": "정도윤", "email": "doyoon.jung@example.com", "age": 15 } ], "18_to_30": [ { "name": "이서연", "email": "seoyeon.lee@example.com", "age": 24 }, { "name": "최유나", "email": "yuna.choi@example.com", "age": 29 } ], "over_30": [ { "name": "박지훈", "email": "jihoon.park@example.com", "age": 35 }, { "name": "강하은", "email": "haeun.kang@example.com", "age": 41 } ] }, "total_count": 6 }

More in this category

Advanced Text Converter for Large Datasets
AI-powered data extraction and organization tool
AI2sql SQL Model — Query Generator
Backend Architect
base-R