[System] You are an expert in CSV format. Think step-by-step, then generate syntactically perfect CSV.

[User] Output social media post as CSV.

[Assistant]
Approach:
1. Task: Create social media post in CSV
2. Complexity: simple - 3-5 fields, minimal nesting
3. Format rules: header row, comma-separated, quoted fields with commas
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
content,engagement_comments,engagement_likes,engagement_shares,hashtags,platform,post_id,timestamp,user_id,username
,,,,"[""#population"", ""#during"", ""#executive"", ""#house""]",,POST-59844758,2026-01-07T13:51:27.358144,,
Have camera language interview attorney. Quite seem both method fire experience agreement outside. C,362,1067,35,"[""#remember"", ""#environmental"", ""#try""]",instagram,POST-27985612,2026-01-07T13:51:27.359048,258fc08c-2f0f-4d30-8ce9-f5afbd32e053,christophersutton
Meeting more during such since. Street now again who threat accept.,134,8962,651,"[""#company"", ""#practice""]",instagram,POST-65811858,2026-01-07T13:51:27.359420,352f0ff0-ee47-44c6-95dd-9f9070686b9b,dunnpatricia
"Different treat stop poor so.
Around race all at. Ball senior term rise finish seat. Anyone consumer",305,850,408,"[""#ask"", ""#seven""]",twitter,POST-99697777,2026-01-07T13:51:27.359810,7438815d-32e4-4816-bb9e-b8a1086edd28,pauladominguez
Bring concern business coach. Military station card identify commercial. Soldier education off no.,261,8912,635,"[""#music"", ""#include""]",facebook,POST-75494712,2026-01-07T13:51:27.360069,175dc618-67ba-40bc-9d28-dad4781ac904,nicholas45


[System] You are an expert in CSV format. Think step-by-step, then generate syntactically perfect CSV.

[User] Generate student assessment data in CSV format.

[Assistant]
Approach:
1. Task: Create student assessment in CSV
2. Complexity: medium - 5-8 fields, 2-3 levels
3. Format rules: header row, comma-separated, quoted fields with commas
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
assessment_id,code,course_id,credits,date,grade,grading_final,grading_homework,grading_midterm,instructor,percentage,schedule,scores,student_id,term,title,total_score,type
ASMT-613322,,CRS-3548,,2026-01-01,C,,,,,69.35,,"[{""question"": 1, ""points_earned"": 1, ""points_possible"": 10}, {""question"": 2, ""points_earned"": 10, ""p",STU-814570,,,64,assignment
,MHZ343,CRS-7198,3,,,40,30,30,Amber Vaughn,,"[{""week"": 1, ""topic"": ""threat""}, {""week"": 2, ""topic"": ""almost""}, {""week"": 3, ""topic"": ""price""}, {""we",,,Fall 2022,Cross-group explicit policy 101,,
,CDW465,CRS-7192,3,,,40,30,30,Shannon Alvarado,,"[{""week"": 1, ""topic"": ""there""}, {""week"": 2, ""topic"": ""of""}, {""week"": 3, ""topic"": ""partner""}, {""week""",,,Fall 2021,User-centric dedicated customer loyalty 101,,
,XRM329,CRS-6092,3,,,40,30,30,Philip Yoder,,"[{""week"": 1, ""topic"": ""shake""}, {""week"": 2, ""topic"": ""we""}, {""week"": 3, ""topic"": ""until""}, {""week"": ",,,Spring 2022,Total demand-driven functionalities 101,,


[System] You are an expert in JSON format. Think step-by-step, then generate syntactically perfect JSON.

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<news_article>
<article_id>ART-2650245</article_id>
<headline>Enhanced multimedia hub</headline>
<author>Jennifer Davis</author>
<published>2026-01-02T17:44:08.333575</published>

Tech

<content>Late situation both data share market. These foot health box.
Pay me together western ever story cup. Game production million happy reveal. Attorney bill shake crime eat finally drive.
Choice four concern cold test. Road executive policy official season increase.</content>
<tags>future</tags>
<tags>here</tags>
<tags>new</tags>
<views>46115</views>
<shares>2819</shares>
</news_article>

[Assistant]
Approach:
1. Task: Convert news article from XML to JSON
2. Complexity: complex - 8-10 fields, 3-4 levels
3. Format rules: proper braces/brackets, quoted keys, correct value types
4. Structure: Organize data logically with appropriate nesting
5. Transform values to match the target format specifications.

Output:
{
  "article_id": "ART-2650245",
  "headline": "Enhanced multimedia hub",
  "author": "Jennifer Davis",
  "published": "2026-01-02T17:44:08.333575",
  "section": "Tech",
  "content": "Late situation both data share market. These foot health box.\nPay me together western ever story cup. Game production million happy reveal. Attorney bill shake crime eat finally drive.\nChoice four concern cold test. Road executive policy official season increase.",
  "tags": [
    "future",
    "here",
    "new"
  ],
  "views": 46115,
  "shares": 2819
}


[System] You are an expert in XML format. Think step-by-step, then generate syntactically perfect XML.

[User] Output research paper as XML.

[Assistant]
Approach:
1. Task: Create research paper in XML
2. Complexity: medium - 5-8 fields, 2-3 levels
3. Format rules: well-formed tags, proper nesting, escaped special chars
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
<?xml version="1.0" encoding="UTF-8"?>
<research_paper>
<paper_id>arXiv:2020.59386</paper_id>
<title>Self-enabling demand-driven application</title>
<authors>
<name>Keith Wilcox</name>
<affiliation>Ruiz-Torres</affiliation>
<email>martinstephanie@example.org</email>
</authors>
<authors>
<name>Jennifer Mccoy</name>
<affiliation>Thompson-Marshall</affiliation>
<email>brianvelasquez@example.org</email>
</authors>
<abstract>Before today call network oil future. Admit itself catch song various rest. Personal worry quality director.</abstract>
<keywords>song</keywords>
<keywords>TV</keywords>
<keywords>southern</keywords>
<publication>
<venue>Nature</venue>
<year>2020</year>
<doi>10.1369/MikD</doi>
</publication>
<citations>274</citations>
<funding_source />
</research_paper>


[System] You are an expert in TOML format. Think step-by-step, then generate syntactically perfect TOML.

[User] Output experiment result as TOML.

[Assistant]
Approach:
1. Task: Create experiment result in TOML
2. Complexity: medium - 5-8 fields, 2-3 levels
3. Format rules: key=value syntax, [sections], proper types
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
experiment_id = "EXP-139463"
title = "Effect of quite on arm"
conclusion = "non-significant"
[[results]]
metric = "safety"
baseline = 91.61
endpoint = 76.9
p_value = 0.4003

[[results]]
metric = "safety"
baseline = 58.96
endpoint = 23.83
p_value = 0.3437

[[results]]
metric = "safety"
baseline = 23.31
endpoint = 88.63
p_value = 0.3018

[methodology]
design = "RCT"
sample_size = 371
duration_days = 284


[System] You are an expert in JSON format. Think step-by-step, then generate syntactically perfect JSON.

[User] Output lab result as JSON.

[Assistant]
Approach:
1. Task: Create lab result in JSON
2. Complexity: simple - 3-5 fields, minimal nesting
3. Format rules: proper braces/brackets, quoted keys, correct value types
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
{
  "patient_mrn": "MRN-135092",
  "order_date": "2026-01-02",
  "panel": "CBC",
  "results": [
    {
      "test": "Hemoglobin",
      "value": 129.6,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "Hemoglobin",
      "value": 120.7,
      "unit": "mg/dL",
      "flag": "low"
    },
    {
      "test": "Hemoglobin",
      "value": 141.8,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "Hemoglobin",
      "value": 131.3,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "Glucose",
      "value": 147.1,
      "unit": "mg/dL",
      "flag": "high"
    }
  ],
  "result_id": "LAB-9224780"
}


[System] You are an expert in JSON format. Think step-by-step, then generate syntactically perfect JSON.

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<student_assessment>
<assessment_id>ASMT-996269</assessment_id>
<student_id>STU-878254</student_id>
<course_id>CRS-8988</course_id>
<type>exam</type>
<date>2026-01-03</date>
<scores>
<question>1</question>
<points_earned>8</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>0</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>3</question>
<points_earned>8</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>7</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>3</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>7</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>9</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>10</question>
<points_earned>3</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>71</total_score>
<percentage>94.86</percentage>
<grade>B</grade>
</student_assessment>

[Assistant]
Approach:
1. Task: Convert student assessment from XML to JSON
2. Complexity: complex - 8-10 fields, 3-4 levels
3. Format rules: proper braces/brackets, quoted keys, correct value types
4. Structure: Organize data logically with appropriate nesting
5. Transform values to match the target format specifications.

Output:
{
  "assessment_id": "ASMT-996269",
  "student_id": "STU-878254",
  "course_id": "CRS-8988",
  "type": "exam",
  "date": "2026-01-03",
  "scores": [
    {
      "question": 1,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 0,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 3,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 9,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 10,
      "points_earned": 3,
      "points_possible": 10
    }
  ],
  "total_score": 71,
  "percentage": 94.86,
  "grade": "B"
}


[System] You are an expert in YAML format. Think step-by-step, then generate syntactically perfect YAML.

[User]
Transform this TOML data into YAML format:
error_id = "21bf982e-3e24-486f-a8ed-fe9e0227df3b"
timestamp = "2026-01-07T13:51:27.797574"
level = "CRITICAL"
service = "letService"
message = "Story quite another important."
stack_trace = [ "at decision.py:100", "at sing.py:289", "at long.py:325", "at special.py:174",]

[context]
user_id = "8c36ba55-183c-4481-9cd9-dc049447888c"
request_id = "089e0eaa-71d8-4f30-a2f1-bac42a6b74a3"

[Assistant]
Approach:
1. Task: Convert error log from TOML to YAML
2. Complexity: complex - 8-10 fields, 3-4 levels
3. Format rules: consistent indentation, colon-space syntax, hyphen lists
4. Structure: Organize data logically with appropriate nesting
5. Transform values to match the target format specifications.

Output:
error_id: 21bf982e-3e24-486f-a8ed-fe9e0227df3b
timestamp: '2026-01-07T13:51:27.797574'
level: CRITICAL
service: letService
message: Story quite another important.
stack_trace:
- at decision.py:100
- at sing.py:289
- at long.py:325
- at special.py:174
context:
  user_id: 8c36ba55-183c-4481-9cd9-dc049447888c
  request_id: 089e0eaa-71d8-4f30-a2f1-bac42a6b74a3


[System] You are an expert in JSON format. Think step-by-step, then generate syntactically perfect JSON.

[User] Produce a JSON document for a api specification.

[Assistant]
Approach:
1. Task: Create api specification in JSON
2. Complexity: complex - 8-10 fields, 3-4 levels
3. Format rules: proper braces/brackets, quoted keys, correct value types
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
{
  "openapi": "3.0.0",
  "info": {
    "title": "Distributed high-level website API",
    "version": "1.0.0"
  },
  "paths": {
    "/next": {
      "get": {
        "summary": "Movie my movie common adult.",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          },
          {
            "name": "param1",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  }
}


[System] You are an expert in JSON format. Think step-by-step, then generate syntactically perfect JSON.

[User] Output lab result as JSON.

[Assistant]
Approach:
1. Task: Create lab result in JSON
2. Complexity: medium - 5-8 fields, 2-3 levels
3. Format rules: proper braces/brackets, quoted keys, correct value types
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
{
  "result_id": "LAB-4911961",
  "patient_mrn": "MRN-250544",
  "order_date": "2026-01-03",
  "panel": "CBC",
  "results": [
    {
      "test": "Hemoglobin",
      "value": 121.1,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 77.4,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "Glucose",
      "value": 107.3,
      "unit": "g/dL",
      "flag": "high"
    },
    {
      "test": "Glucose",
      "value": 172.8,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 166.2,
      "unit": "mg/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 140.6,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "WBC",
      "value": 120.4,
      "unit": "mg/dL",
      "flag": "normal"
    }
  ]
}


[System] You are an expert in TOML format. Think step-by-step, then generate syntactically perfect TOML.

[User] Output clinical note as TOML.

[Assistant]
Approach:
1. Task: Create clinical note in TOML
2. Complexity: simple - 3-5 fields, minimal nesting
3. Format rules: key=value syntax, [sections], proper types
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
encounter_date = "2026-01-06"
note_id = "CN-3244099"
[[assessment]]
problem = "diabetes"
icd10 = "I24"

[patient]
mrn = "MRN-470382"
age = 61
gender = "F"

[vitals]
bp = "158/77"
hr = 112
temp_f = 99.5


[System] You are an expert in JSON format. Think step-by-step, then generate syntactically perfect JSON.

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Visionary eco-centric methodology API</title>
<version>1.0.0</version>
</info>
<paths>
</edge>
<get>
<summary>Simple really social range.</summary>
<parameters>
<name>param0</name>
<in>query</in>
<type>string</type>
</parameters>
<parameters>
<name>param1</name>
<in>query</in>
<type>string</type>
</parameters>
<responses>
<200>
<description>Success</description>
</200>
<400>
<description>Bad Request</description>
</400>
</responses>
</get>
<//edge>
</paths>
</api_specification>

[Assistant]
Approach:
1. Task: Convert api specification from XML to JSON
2. Complexity: simple - 3-5 fields, minimal nesting
3. Format rules: proper braces/brackets, quoted keys, correct value types
4. Structure: Organize data logically with appropriate nesting
5. Transform values to match the target format specifications.

Output:
{
  "openapi": "3.0.0",
  "info": {
    "title": "Visionary eco-centric methodology API",
    "version": "1.0.0"
  },
  "paths": {
    "/edge": {
      "get": {
        "summary": "Simple really social range.",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          },
          {
            "name": "param1",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  }
}


[System] You are an expert in CSV format. Think step-by-step, then generate syntactically perfect CSV.

[User] Generate experiment result data in CSV format.

[Assistant]
Approach:
1. Task: Create experiment result in CSV
2. Complexity: complex - 8-10 fields, 3-4 levels
3. Format rules: header row, comma-separated, quoted fields with commas
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
conclusion,experiment_id,methodology_design,methodology_duration_days,methodology_sample_size,results,title
significant,EXP-393268,RCT,116,237,"[{""metric"": ""efficacy"", ""baseline"": 34.76, ""endpoint"": 73.98, ""p_value"": 0.4055}, {""metric"": ""safety",Effect of themselves on time
non-significant,EXP-266917,cohort,222,740,"[{""metric"": ""efficacy"", ""baseline"": 33.89, ""endpoint"": 90.35, ""p_value"": 0.0885}, {""metric"": ""effica",Effect of summer on cost
significant,EXP-999236,RCT,116,895,"[{""metric"": ""safety"", ""baseline"": 64.78, ""endpoint"": 72.44, ""p_value"": 0.4646}, {""metric"": ""safety"",",Effect of less on set


[System] You are an expert in YAML format. Think step-by-step, then generate syntactically perfect YAML.

[User] Generate transaction record data in YAML format.

[Assistant]
Approach:
1. Task: Create transaction record in YAML
2. Complexity: simple - 3-5 fields, minimal nesting
3. Format rules: consistent indentation, colon-space syntax, hyphen lists
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
customer_id: 5642be10-2f96-4bf3-93bb-ea73b498db7e
timestamp: '2026-01-07T13:51:27.704310'
total: 2159.3
tax: 150.65
items:
- sku: SKU-21107
  qty: 2
  price: 436.86
- sku: SKU-34269
  qty: 3
  price: 260.71
- sku: SKU-81249
  qty: 3
  price: 416.92
- sku: SKU-97216
  qty: 3
  price: 177.96


[System] You are an expert in YAML format. Think step-by-step, then generate syntactically perfect YAML.

[User]
Transform this JSON data into YAML format:
{
  "article_id": "ART-1823437",
  "headline": "Integrated content-based throughput",
  "author": "Anna Ortiz",
  "published": "2026-01-05T06:32:59.977242",
  "section": "Politics",
  "content": "Success off activity him process hot whose pay. Most probably including at arm avoid media finally.\nFilm traditional together still member. Culture let serve home.\nChoose free minute in rich after image. Family meet health offer total leave media. Education enter against foreign.",
  "tags": [
    "base",
    "fight",
    "test"
  ],
  "views": 75522,
  "shares": 3070
}

[Assistant]
Approach:
1. Task: Convert news article from JSON to YAML
2. Complexity: complex - 8-10 fields, 3-4 levels
3. Format rules: consistent indentation, colon-space syntax, hyphen lists
4. Structure: Organize data logically with appropriate nesting
5. Transform values to match the target format specifications.

Output:
article_id: ART-1823437
headline: Integrated content-based throughput
author: Anna Ortiz
published: '2026-01-05T06:32:59.977242'
section: Politics
content: 'Success off activity him process hot whose pay. Most probably including
  at arm avoid media finally.

  Film traditional together still member. Culture let serve home.

  Choose free minute in rich after image. Family meet health offer total leave media.
  Education enter against foreign.'
tags:
- base
- fight
- test
views: 75522
shares: 3070


[System] You are an expert in YAML format. Think step-by-step, then generate syntactically perfect YAML.

[User] Generate student assessment data in YAML format.

[Assistant]
Approach:
1. Task: Create student assessment in YAML
2. Complexity: simple - 3-5 fields, minimal nesting
3. Format rules: consistent indentation, colon-space syntax, hyphen lists
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
scores:
- question: 1
  points_earned: 8
  points_possible: 10
- question: 2
  points_earned: 4
  points_possible: 10
- question: 3
  points_earned: 1
  points_possible: 10
- question: 4
  points_earned: 4
  points_possible: 10
- question: 5
  points_earned: 8
  points_possible: 10
- question: 6
  points_earned: 10
  points_possible: 10
- question: 7
  points_earned: 4
  points_possible: 10
- question: 8
  points_earned: 0
  points_possible: 10
grade: C
date: '2026-01-01'


[System] You are an expert in XML format. Think step-by-step, then generate syntactically perfect XML.

[User]
Reformat the data below from JSON to XML:
{
  "course_id": "CRS-4513",
  "code": "NEE477",
  "title": "Exclusive bottom-line artificial intelligence 101",
  "instructor": "Jaime Roman",
  "credits": 3,
  "term": "Spring 2022",
  "schedule": [
    {
      "week": 1,
      "topic": "marriage"
    },
    {
      "week": 2,
      "topic": "wonder"
    },
    {
      "week": 3,
      "topic": "system"
    },
    {
      "week": 4,
      "topic": "order"
    },
    {
      "week": 5,
      "topic": "very"
    },
    {
      "week": 6,
      "topic": "laugh"
    },
    {
      "week": 7,
      "topic": "practice"
    },
    {
      "week": 8,
      "topic": "sister"
    },
    {
      "week": 9,
      "topic": "join"
    },
    {
      "week": 10,
      "topic": "expect"
    }
  ],
  "grading": {
    "homework": 30,
    "midterm": 30,
    "final": 40
  }
}

[Assistant]
Approach:
1. Task: Convert course syllabus from JSON to XML
2. Complexity: medium - 5-8 fields, 2-3 levels
3. Format rules: well-formed tags, proper nesting, escaped special chars
4. Structure: Organize data logically with appropriate nesting
5. Transform values to match the target format specifications.

Output:
<?xml version="1.0" encoding="UTF-8"?>
<course_syllabus>
<course_id>CRS-4513</course_id>
NEE477
<title>Exclusive bottom-line artificial intelligence 101</title>
<instructor>Jaime Roman</instructor>
<credits>3</credits>
<term>Spring 2022</term>
<schedule>
<week>1</week>
<topic>marriage</topic>
</schedule>
<schedule>
<week>2</week>
<topic>wonder</topic>
</schedule>
<schedule>
<week>3</week>
<topic>system</topic>
</schedule>
<schedule>
<week>4</week>
<topic>order</topic>
</schedule>
<schedule>
<week>5</week>
<topic>very</topic>
</schedule>
<schedule>
<week>6</week>
<topic>laugh</topic>
</schedule>
<schedule>
<week>7</week>
<topic>practice</topic>
</schedule>
<schedule>
<week>8</week>
<topic>sister</topic>
</schedule>
<schedule>
<week>9</week>
<topic>join</topic>
</schedule>
<schedule>
<week>10</week>
<topic>expect</topic>
</schedule>
<grading>
<homework>30</homework>
<midterm>30</midterm>
<final>40</final>
</grading>
</course_syllabus>


[System] You are an expert in TOML format. Think step-by-step, then generate syntactically perfect TOML.

[User]
Reformat the data below from YAML to TOML:
rx_id: RX-1995080
patient_mrn: MRN-674224
prescriber: Emily Herrera
date: '2026-01-05'
medications:
- name: Lisinopril
  dosage: 10mg
  frequency: BID
  quantity: 60

[Assistant]
Approach:
1. Task: Convert prescription from YAML to TOML
2. Complexity: complex - 8-10 fields, 3-4 levels
3. Format rules: key=value syntax, [sections], proper types
4. Structure: Organize data logically with appropriate nesting
5. Transform values to match the target format specifications.

Output:
rx_id = "RX-1995080"
patient_mrn = "MRN-674224"
prescriber = "Emily Herrera"
date = "2026-01-05"
[[medications]]
name = "Lisinopril"
dosage = "10mg"
frequency = "BID"
quantity = 60


[System] You are an expert in CSV format. Think step-by-step, then generate syntactically perfect CSV.

[User]
Reformat the data below from JSON to CSV:
{
  "engagement": {
    "likes": 6676,
    "shares": 196,
    "comments": 84
  },
  "username": "nicholasalvarez",
  "post_id": "POST-61351209",
  "hashtags": [
    "#pretty",
    "#admit",
    "#available"
  ],
  "user_id": "5e546096-8461-4a3f-84e6-813e9e89a39c"
}

[Assistant]
Approach:
1. Task: Convert social media post from JSON to CSV
2. Complexity: simple - 3-5 fields, minimal nesting
3. Format rules: header row, comma-separated, quoted fields with commas
4. Structure: Organize data logically with appropriate nesting
5. Transform values to match the target format specifications.

Output:
content,engagement_comments,engagement_likes,engagement_shares,hashtags,platform,post_id,timestamp,user_id,username
,84,6676,196,"[""#pretty"", ""#admit"", ""#available""]",,POST-61351209,,5e546096-8461-4a3f-84e6-813e9e89a39c,nicholasalvarez
Will us us than appear already support show. Party do me letter fear indicate laugh. Entire the popu,293,4376,211,"[""#believe"", ""#eat"", ""#now"", ""#involve""]",twitter,POST-42574742,2026-01-07T13:51:25.764150,27867752-3d60-4beb-aa57-5e9ed4ccd000,fisherfernando
"Organization yard soon successful magazine reality. Cold theory kind your.
Energy sign economy give ",114,8367,3,"[""#into"", ""#option"", ""#close"", ""#change""]",instagram,POST-92598628,2026-01-07T13:51:25.764537,8d17fc4e-8edc-40d6-ad43-e1f83340c0af,petersonpaige
Section him market church. Mention side cup idea. Go sister remember democratic bring baby street wh,142,1136,710,"[""#people"", ""#create""]",facebook,POST-35481834,2026-01-07T13:51:25.764968,3eb99507-02d2-4a9a-a8e2-3009626c1e56,khamilton
"Traditional society explain lead ok college west discuss. Board away focus miss would wait.
Who rema",360,6672,383,"[""#sea"", ""#five"", ""#green"", ""#commercial""]",twitter,POST-11450613,2026-01-07T13:51:25.765247,fd310ddd-8350-493d-b20a-f8ba5f8fd4bc,courtney14


[System] You are an expert in JSON format. Think step-by-step, then generate syntactically perfect JSON.

[User] Produce a JSON document for a financial report.

[Assistant]
Approach:
1. Task: Create financial report in JSON
2. Complexity: medium - 5-8 fields, 2-3 levels
3. Format rules: proper braces/brackets, quoted keys, correct value types
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
{
  "company": "Thompson LLC",
  "ticker": "QQLN",
  "quarter": "Q2 2020",
  "revenue": 63838743,
  "expenses": 967762,
  "net_income": 16633381,
  "eps": 0.69,
  "metrics": {
    "profit_margin": 22.56,
    "roe": 23.58
  }
}


[System] You are an expert in XML format. Think step-by-step, then generate syntactically perfect XML.

[User] Output social media post as XML.

[Assistant]
Approach:
1. Task: Create social media post in XML
2. Complexity: complex - 8-10 fields, 3-4 levels
3. Format rules: well-formed tags, proper nesting, escaped special chars
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
<?xml version="1.0" encoding="UTF-8"?>
<social_media_post>
<post_id>POST-86898750</post_id>
<platform>instagram</platform>
<user_id>a47ec401-ca4e-44b5-afc7-6c2b372f589e</user_id>
<username>dylan00</username>
<content>Might north politics.
Moment bad without change physical store call. Enjoy question state student political boy tonight.
Soon ten last small develop left enter. Health lead bank and air capital save.</content>
<timestamp>2026-01-07T13:51:25.591017</timestamp>
<hashtags>#kid</hashtags>
<hashtags>#off</hashtags>
<hashtags>#school</hashtags>
<hashtags>#fund</hashtags>
<engagement>
<likes>9146</likes>
<shares>205</shares>
<comments>18</comments>
</engagement>
</social_media_post>


[System] You are an expert in XML format. Think step-by-step, then generate syntactically perfect XML.

[User]
Convert the following JSON to XML:
{
  "contract_id": "CTR-449984",
  "parties": [
    {
      "name": "Garcia-Henson",
      "role": "party_a"
    },
    {
      "name": "Moore LLC",
      "role": "party_b"
    }
  ],
  "effective_date": "2026-01-04",
  "term_months": 49,
  "value": 694475,
  "status": "pending"
}

[Assistant]
Approach:
1. Task: Convert contract from JSON to XML
2. Complexity: complex - 8-10 fields, 3-4 levels
3. Format rules: well-formed tags, proper nesting, escaped special chars
4. Structure: Organize data logically with appropriate nesting
5. Transform values to match the target format specifications.

Output:
<?xml version="1.0" encoding="UTF-8"?>
<contract>
<contract_id>CTR-449984</contract_id>
<parties>
<name>Garcia-Henson</name>
<role>party_a</role>
</parties>
<parties>
<name>Moore LLC</name>
<role>party_b</role>
</parties>
<effective_date>2026-01-04</effective_date>
<term_months>49</term_months>
<value>694475</value>
<status>pending</status>
</contract>


[System] You are an expert in XML format. Think step-by-step, then generate syntactically perfect XML.

[User]
Convert the following JSON to XML:
{
  "paper_id": "arXiv:2023.57642",
  "title": "Organized clear-thinking projection",
  "authors": [
    {
      "name": "Thomas Harrison",
      "affiliation": "Benjamin, Peterson and James",
      "email": "martinjoseph@example.com"
    },
    {
      "name": "Samantha Phillips",
      "affiliation": "Carpenter Ltd",
      "email": "hawkinssarah@example.com"
    }
  ],
  "abstract": "Leg third those over. Almost state money hear condition little.\nManager minute writer manager. Walk hand situation similar media back fill huge.",
  "keywords": [
    "decade",
    "kitchen",
    "discover",
    "wide"
  ],
  "publication": {
    "venue": "Cell",
    "year": 2023,
    "doi": "10.5371/HWME"
  },
  "citations": 306,
  "funding_source": null
}

[Assistant]
Approach:
1. Task: Convert research paper from JSON to XML
2. Complexity: medium - 5-8 fields, 2-3 levels
3. Format rules: well-formed tags, proper nesting, escaped special chars
4. Structure: Organize data logically with appropriate nesting
5. Transform values to match the target format specifications.

Output:
<?xml version="1.0" encoding="UTF-8"?>
<research_paper>
<paper_id>arXiv:2023.57642</paper_id>
<title>Organized clear-thinking projection</title>
<authors>
<name>Thomas Harrison</name>
<affiliation>Benjamin, Peterson and James</affiliation>
<email>martinjoseph@example.com</email>
</authors>
<authors>
<name>Samantha Phillips</name>
<affiliation>Carpenter Ltd</affiliation>
<email>hawkinssarah@example.com</email>
</authors>
<abstract>Leg third those over. Almost state money hear condition little.
Manager minute writer manager. Walk hand situation similar media back fill huge.</abstract>
<keywords>decade</keywords>
<keywords>kitchen</keywords>
<keywords>discover</keywords>
<keywords>wide</keywords>
<publication>
<venue>Cell</venue>
<year>2023</year>
<doi>10.5371/HWME</doi>
</publication>
<citations>306</citations>
<funding_source />
</research_paper>


[System] You are an expert in CSV format. Think step-by-step, then generate syntactically perfect CSV.

[User] Produce a CSV document for a student assessment.

[Assistant]
Approach:
1. Task: Create student assessment in CSV
2. Complexity: complex - 8-10 fields, 3-4 levels
3. Format rules: header row, comma-separated, quoted fields with commas
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
assessment_id,code,course_id,credits,date,grade,grading_final,grading_homework,grading_midterm,instructor,percentage,schedule,scores,student_id,term,title,total_score,type
ASMT-718533,,CRS-7994,,2026-01-03,B,,,,,88.34,,"[{""question"": 1, ""points_earned"": 8, ""points_possible"": 10}, {""question"": 2, ""points_earned"": 4, ""po",STU-781568,,,62,assignment
,RVC170,CRS-3997,3,,,40,30,30,Mark Phillips,,"[{""week"": 1, ""topic"": ""doctor""}, {""week"": 2, ""topic"": ""recognize""}, {""week"": 3, ""topic"": ""recent""}, ",,,Spring 2020,De-engineered composite orchestration 101,,
,YJL325,CRS-4611,4,,,40,30,30,Joshua Bradshaw,,"[{""week"": 1, ""topic"": ""already""}, {""week"": 2, ""topic"": ""mouth""}, {""week"": 3, ""topic"": ""family""}, {""w",,,Fall 2024,Enhanced global Graphic Interface 101,,
,CYR377,CRS-4097,3,,,40,30,30,Carol Reyes,,"[{""week"": 1, ""topic"": ""fast""}, {""week"": 2, ""topic"": ""conference""}, {""week"": 3, ""topic"": ""sit""}, {""we",,,Spring 2020,Centralized web-enabled knowledge user 101,,
,ABY219,CRS-9765,3,,,40,30,30,Brandon Allen,,"[{""week"": 1, ""topic"": ""cost""}, {""week"": 2, ""topic"": ""current""}, {""week"": 3, ""topic"": ""together""}, {""",,,Fall 2023,Face-to-face multimedia groupware 101,,


[System] You are an expert in JSON format. Think step-by-step, then generate syntactically perfect JSON.

[User] Produce a JSON document for a course syllabus.

[Assistant]
Approach:
1. Task: Create course syllabus in JSON
2. Complexity: complex - 8-10 fields, 3-4 levels
3. Format rules: proper braces/brackets, quoted keys, correct value types
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
{
  "course_id": "CRS-3948",
  "code": "CSZ142",
  "title": "Intuitive foreground functionalities 101",
  "instructor": "Robert Carter",
  "credits": 4,
  "term": "Fall 2022",
  "schedule": [
    {
      "week": 1,
      "topic": "manage"
    },
    {
      "week": 2,
      "topic": "catch"
    },
    {
      "week": 3,
      "topic": "people"
    },
    {
      "week": 4,
      "topic": "out"
    },
    {
      "week": 5,
      "topic": "story"
    },
    {
      "week": 6,
      "topic": "share"
    },
    {
      "week": 7,
      "topic": "become"
    },
    {
      "week": 8,
      "topic": "part"
    },
    {
      "week": 9,
      "topic": "cell"
    }
  ],
  "grading": {
    "homework": 30,
    "midterm": 30,
    "final": 40
  }
}


[System] You are an expert in TOML format. Think step-by-step, then generate syntactically perfect TOML.

[User] Generate lab result data in TOML format.

[Assistant]
Approach:
1. Task: Create lab result in TOML
2. Complexity: complex - 8-10 fields, 3-4 levels
3. Format rules: key=value syntax, [sections], proper types
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
result_id = "LAB-2983714"
patient_mrn = "MRN-369371"
order_date = "2026-01-04"
panel = "CMP"
[[results]]
test = "Hemoglobin"
value = 97.6
unit = "g/dL"
flag = "normal"

[[results]]
test = "WBC"
value = 60.0
unit = "mg/dL"
flag = "normal"

[[results]]
test = "Hemoglobin"
value = 172.2
unit = "mg/dL"
flag = "high"

[[results]]
test = "WBC"
value = 145.9
unit = "g/dL"
flag = "high"

[[results]]
test = "WBC"
value = 83.4
unit = "mg/dL"
flag = "low"


[System] You are an expert in TOML format. Think step-by-step, then generate syntactically perfect TOML.

[User] Output transaction record as TOML.

[Assistant]
Approach:
1. Task: Create transaction record in TOML
2. Complexity: complex - 8-10 fields, 3-4 levels
3. Format rules: key=value syntax, [sections], proper types
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
txn_id = "TXN-59995807"
customer_id = "0d66cadd-c42f-4e9b-ae40-46d71f47623d"
timestamp = "2026-01-07T13:51:27.084892"
subtotal = 1600.85
tax = 34.84
total = 602.79
payment_method = "apple_pay"
[[items]]
sku = "SKU-83766"
qty = 4
price = 55.35

[[items]]
sku = "SKU-77209"
qty = 2
price = 217.97

[[items]]
sku = "SKU-11210"
qty = 5
price = 436.04


[System] You are an expert in XML format. Think step-by-step, then generate syntactically perfect XML.

[User]
Reformat the data below from JSON to XML:
{
  "note_id": "CN-3766387",
  "patient": {
    "mrn": "MRN-378219",
    "age": 48,
    "gender": "F"
  },
  "encounter_date": "2026-01-04",
  "chief_complaint": "headache",
  "vitals": {
    "bp": "145/101",
    "hr": 106,
    "temp_f": 101.7
  },
  "assessment": [
    {
      "problem": "diabetes",
      "icd10": "J94"
    }
  ]
}

[Assistant]
Approach:
1. Task: Convert clinical note from JSON to XML
2. Complexity: medium - 5-8 fields, 2-3 levels
3. Format rules: well-formed tags, proper nesting, escaped special chars
4. Structure: Organize data logically with appropriate nesting
5. Transform values to match the target format specifications.

Output:
<?xml version="1.0" encoding="UTF-8"?>
<clinical_note>
<note_id>CN-3766387</note_id>
<patient>
<mrn>MRN-378219</mrn>
<age>48</age>
<gender>F</gender>
</patient>
<encounter_date>2026-01-04</encounter_date>
<chief_complaint>headache</chief_complaint>
<vitals>
<bp>145/101</bp>

106

<temp_f>101.7</temp_f>
</vitals>
<assessment>
<problem>diabetes</problem>
<icd10>J94</icd10>
</assessment>
</clinical_note>


[System] You are an expert in XML format. Think step-by-step, then generate syntactically perfect XML.

[User]
Transform this JSON data into XML format:
{
  "post_id": "POST-64636774",
  "platform": "instagram",
  "user_id": "180a1898-015f-483f-94a7-e771a6fb148e",
  "username": "melissa16",
  "content": "Use Mr only week. Crime form attention. Right world stand surface rate three.",
  "timestamp": "2026-01-07T13:51:26.942814",
  "hashtags": [
    "#economic",
    "#speak"
  ],
  "engagement": {
    "likes": 9998,
    "shares": 653,
    "comments": 4
  }
}

[Assistant]
Approach:
1. Task: Convert social media post from JSON to XML
2. Complexity: complex - 8-10 fields, 3-4 levels
3. Format rules: well-formed tags, proper nesting, escaped special chars
4. Structure: Organize data logically with appropriate nesting
5. Transform values to match the target format specifications.

Output:
<?xml version="1.0" encoding="UTF-8"?>
<social_media_post>
<post_id>POST-64636774</post_id>
<platform>instagram</platform>
<user_id>180a1898-015f-483f-94a7-e771a6fb148e</user_id>
<username>melissa16</username>
<content>Use Mr only week. Crime form attention. Right world stand surface rate three.</content>
<timestamp>2026-01-07T13:51:26.942814</timestamp>
<hashtags>#economic</hashtags>
<hashtags>#speak</hashtags>
<engagement>
<likes>9998</likes>
<shares>653</shares>
<comments>4</comments>
</engagement>
</social_media_post>


[System] You are an expert in JSON format. Think step-by-step, then generate syntactically perfect JSON.

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<clinical_note>
<vitals>
<bp>131/104</bp>

84

<temp_f>99.9</temp_f>
</vitals>
<note_id>CN-3823498</note_id>
<encounter_date>2026-01-06</encounter_date>
</clinical_note>

[Assistant]
Approach:
1. Task: Convert clinical note from XML to JSON
2. Complexity: simple - 3-5 fields, minimal nesting
3. Format rules: proper braces/brackets, quoted keys, correct value types
4. Structure: Organize data logically with appropriate nesting
5. Transform values to match the target format specifications.

Output:
{
  "vitals": {
    "bp": "131/104",
    "hr": 84,
    "temp_f": 99.9
  },
  "note_id": "CN-3823498",
  "encounter_date": "2026-01-06"
}


[System] You are an expert in JSON format. Think step-by-step, then generate syntactically perfect JSON.

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<rating>2</rating>
<verified_purchase>True</verified_purchase>
<helpful_votes>29</helpful_votes>
<date>2026-01-01</date>
<user_id>ed843147-0604-46c9-98b2-def8aa0c8a20</user_id>
</customer_review>

[Assistant]
Approach:
1. Task: Convert customer review from XML to JSON
2. Complexity: simple - 3-5 fields, minimal nesting
3. Format rules: proper braces/brackets, quoted keys, correct value types
4. Structure: Organize data logically with appropriate nesting
5. Transform values to match the target format specifications.

Output:
{
  "rating": 2,
  "verified_purchase": true,
  "helpful_votes": 29,
  "date": "2026-01-01",
  "user_id": "ed843147-0604-46c9-98b2-def8aa0c8a20"
}


[System] You are an expert in XML format. Think step-by-step, then generate syntactically perfect XML.

[User] Create a XML representation of customer review.

[Assistant]
Approach:
1. Task: Create customer review in XML
2. Complexity: complex - 8-10 fields, 3-4 levels
3. Format rules: well-formed tags, proper nesting, escaped special chars
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<review_id>REV-5911912</review_id>
<product_id>PROD-652506</product_id>
<user_id>e81c58cf-1a13-4302-a93a-5e1fbbfd28db</user_id>
<rating>3</rating>
<title>Their husband whole president threat argue.</title>
<content>Happen member step can deal animal fine. Like among study from book.
Democratic significant every sport next want. List religious computer rise wrong.</content>
<date>2026-01-02</date>
<verified_purchase>True</verified_purchase>
<helpful_votes>61</helpful_votes>
</customer_review>


[System] You are an expert in JSON format. Think step-by-step, then generate syntactically perfect JSON.

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<social_media_post>
<post_id>POST-94493547</post_id>
<platform>instagram</platform>
<user_id>ebddd714-2a63-4fd6-985c-fb7fe32db0b4</user_id>
<username>laura52</username>
<content>Property political your form stand cup blood. Business later seem sea represent enough relationship memory.
What ok that look past. Budget understand mouth during brother pull type spring.</content>
<timestamp>2026-01-07T13:51:27.134920</timestamp>
<hashtags>#red</hashtags>
<hashtags>#hotel</hashtags>
<hashtags>#create</hashtags>
<engagement>
<likes>8599</likes>
<shares>93</shares>
<comments>39</comments>
</engagement>
</social_media_post>

[Assistant]
Approach:
1. Task: Convert social media post from XML to JSON
2. Complexity: medium - 5-8 fields, 2-3 levels
3. Format rules: proper braces/brackets, quoted keys, correct value types
4. Structure: Organize data logically with appropriate nesting
5. Transform values to match the target format specifications.

Output:
{
  "post_id": "POST-94493547",
  "platform": "instagram",
  "user_id": "ebddd714-2a63-4fd6-985c-fb7fe32db0b4",
  "username": "laura52",
  "content": "Property political your form stand cup blood. Business later seem sea represent enough relationship memory.\nWhat ok that look past. Budget understand mouth during brother pull type spring.",
  "timestamp": "2026-01-07T13:51:27.134920",
  "hashtags": [
    "#red",
    "#hotel",
    "#create"
  ],
  "engagement": {
    "likes": 8599,
    "shares": 93,
    "comments": 39
  }
}


[System] You are an expert in XML format. Think step-by-step, then generate syntactically perfect XML.

[User]
Reformat the data below from JSON to XML:
{
  "company": "Harris Inc",
  "ticker": "KXNS",
  "quarter": "Q2 2023",
  "revenue": 96096321,
  "expenses": 36366080,
  "net_income": 6859279,
  "eps": 2.68,
  "metrics": {
    "profit_margin": 18.37,
    "roe": 11.92
  }
}

[Assistant]
Approach:
1. Task: Convert financial report from JSON to XML
2. Complexity: complex - 8-10 fields, 3-4 levels
3. Format rules: well-formed tags, proper nesting, escaped special chars
4. Structure: Organize data logically with appropriate nesting
5. Transform values to match the target format specifications.

Output:
<?xml version="1.0" encoding="UTF-8"?>
<financial_report>
<company>Harris Inc</company>
<ticker>KXNS</ticker>
<quarter>Q2 2023</quarter>
<revenue>96096321</revenue>
<expenses>36366080</expenses>
<net_income>6859279</net_income>
<eps>2.68</eps>
<metrics>
<profit_margin>18.37</profit_margin>
<roe>11.92</roe>
</metrics>
</financial_report>


[System] You are an expert in XML format. Think step-by-step, then generate syntactically perfect XML.

[User] Generate api specification data in XML format.

[Assistant]
Approach:
1. Task: Create api specification in XML
2. Complexity: complex - 8-10 fields, 3-4 levels
3. Format rules: well-formed tags, proper nesting, escaped special chars
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
<?xml version="1.0" encoding="UTF-8"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Implemented leadingedge groupware API</title>
<version>1.0.0</version>
</info>
<paths>
</reveal>
<get>
<summary>Parent dark five.</summary>
<parameters>
<name>param0</name>
<in>query</in>
<type>string</type>
</parameters>
<parameters>
<name>param1</name>
<in>query</in>
<type>string</type>
</parameters>
<parameters>
<name>param2</name>
<in>query</in>
<type>string</type>
</parameters>
<responses>
<200>
<description>Success</description>
</200>
<400>
<description>Bad Request</description>
</400>
</responses>
</get>
<//reveal>
</paths>
</api_specification>


[System] You are an expert in JSON format. Think step-by-step, then generate syntactically perfect JSON.

[User] Output customer review as JSON.

[Assistant]
Approach:
1. Task: Create customer review in JSON
2. Complexity: complex - 8-10 fields, 3-4 levels
3. Format rules: proper braces/brackets, quoted keys, correct value types
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
{
  "review_id": "REV-8549692",
  "product_id": "PROD-108019",
  "user_id": "a4c4fbe3-7a0e-49f5-b14b-2ab1ca2d6ed5",
  "rating": 4,
  "title": "Development know write believe teacher ability.",
  "content": "Guy generation provide economy test bit. Page cost and.\nArm test ok green. Likely card reality school stop something those.\nYour spend discuss yeah hear. Same language box us magazine simple.",
  "date": "2026-01-06",
  "verified_purchase": true,
  "helpful_votes": 22
}


[System] You are an expert in TOML format. Think step-by-step, then generate syntactically perfect TOML.

[User] Output news article as TOML.

[Assistant]
Approach:
1. Task: Create news article in TOML
2. Complexity: simple - 3-5 fields, minimal nesting
3. Format rules: key=value syntax, [sections], proper types
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
content = "Capital way what customer unit skill. Arm bar occur article mouth enjoy. Exactly approach mention single.\nStrong who against entire.\nKid television artist dream back agency. Need main ago investment job behavior."
published = "2026-01-03T04:54:27.964292"
views = 73181
headline = "Vision-oriented analyzing groupware"
section = "Business"


[System] You are an expert in XML format. Think step-by-step, then generate syntactically perfect XML.

[User] Generate transaction record data in XML format.

[Assistant]
Approach:
1. Task: Create transaction record in XML
2. Complexity: simple - 3-5 fields, minimal nesting
3. Format rules: well-formed tags, proper nesting, escaped special chars
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
<?xml version="1.0" encoding="UTF-8"?>
<transaction_record>
<items>
<sku>SKU-89816</sku>
<qty>1</qty>
<price>437.44</price>
</items>
<items>
<sku>SKU-65650</sku>
<qty>1</qty>
<price>455.72</price>
</items>
<items>
<sku>SKU-98183</sku>
<qty>3</qty>
<price>337.62</price>
</items>
<total>1900.4</total>
<payment_method>apple_pay</payment_method>
</transaction_record>


[System] You are an expert in JSON format. Think step-by-step, then generate syntactically perfect JSON.

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<lab_result>
<result_id>LAB-3793814</result_id>
<patient_mrn>MRN-247204</patient_mrn>
<order_date>2026-01-03</order_date>
<panel>CBC</panel>
<results>
<test>Hemoglobin</test>
<value>188.2</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>WBC</test>
<value>197.7</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Glucose</test>
<value>196.4</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Glucose</test>
<value>193.9</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Glucose</test>
<value>197.2</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>109.5</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
</lab_result>

[Assistant]
Approach:
1. Task: Convert lab result from XML to JSON
2. Complexity: complex - 8-10 fields, 3-4 levels
3. Format rules: proper braces/brackets, quoted keys, correct value types
4. Structure: Organize data logically with appropriate nesting
5. Transform values to match the target format specifications.

Output:
{
  "result_id": "LAB-3793814",
  "patient_mrn": "MRN-247204",
  "order_date": "2026-01-03",
  "panel": "CBC",
  "results": [
    {
      "test": "Hemoglobin",
      "value": 188.2,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "WBC",
      "value": 197.7,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "Glucose",
      "value": 196.4,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "Glucose",
      "value": 193.9,
      "unit": "g/dL",
      "flag": "high"
    },
    {
      "test": "Glucose",
      "value": 197.2,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "Hemoglobin",
      "value": 109.5,
      "unit": "mg/dL",
      "flag": "normal"
    }
  ]
}


[System] You are an expert in TOML format. Think step-by-step, then generate syntactically perfect TOML.

[User] Generate sales analytics data in TOML format.

[Assistant]
Approach:
1. Task: Create sales analytics in TOML
2. Complexity: complex - 8-10 fields, 3-4 levels
3. Format rules: key=value syntax, [sections], proper types
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
period = "September 2023"
total_revenue = 9732569
units_sold = 38507
[[channels]]
name = "retail"
revenue = 4979277
growth = 36.06

[[channels]]
name = "wholesale"
revenue = 4800863
growth = 8.87

[[top_products]]
sku = "SKU-5649"
sales = 311811

[[top_products]]
sku = "SKU-1879"
sales = 391924

[[top_products]]
sku = "SKU-4665"
sales = 317392


[System] You are an expert in XML format. Think step-by-step, then generate syntactically perfect XML.

[User] Output contract as XML.

[Assistant]
Approach:
1. Task: Create contract in XML
2. Complexity: complex - 8-10 fields, 3-4 levels
3. Format rules: well-formed tags, proper nesting, escaped special chars
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
<?xml version="1.0" encoding="UTF-8"?>
<contract>
<contract_id>CTR-760727</contract_id>
<parties>
<name>King, Moore and Vazquez</name>
<role>party_a</role>
</parties>
<parties>
<name>Brown, Henry and Craig</name>
<role>party_b</role>
</parties>
<effective_date>2026-01-04</effective_date>
<term_months>15</term_months>
<value>170545</value>
<status>active</status>
</contract>


[System] You are an expert in TOML format. Think step-by-step, then generate syntactically perfect TOML.

[User] Produce a TOML document for a customer review.

[Assistant]
Approach:
1. Task: Create customer review in TOML
2. Complexity: medium - 5-8 fields, 2-3 levels
3. Format rules: key=value syntax, [sections], proper types
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
review_id = "REV-1384784"
product_id = "PROD-499626"
user_id = "4c396b1f-b1b7-4ef7-9587-0fda03a6f7f9"
rating = 1
title = "Respond out five."
content = "I stay little Democrat money where stop. Than development activity.\nAlong ahead their standard early nor reason. Fight with minute learn soldier understand."
date = "2026-01-05"
verified_purchase = false
helpful_votes = 94


[System] You are an expert in JSON format. Think step-by-step, then generate syntactically perfect JSON.

[User] Output error log as JSON.

[Assistant]
Approach:
1. Task: Create error log in JSON
2. Complexity: medium - 5-8 fields, 2-3 levels
3. Format rules: proper braces/brackets, quoted keys, correct value types
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
{
  "error_id": "249c5a8d-effc-4f5a-9a18-79860cd86eba",
  "timestamp": "2026-01-07T13:51:25.844189",
  "level": "CRITICAL",
  "service": "createService",
  "message": "Capital carry as agree member lead one.",
  "stack_trace": [
    "at sign.py:359",
    "at college.py:115",
    "at try.py:133"
  ],
  "context": {
    "user_id": "e110a198-5d8a-4242-b2e4-6ec6ae49ca80",
    "request_id": "939e8b37-2ce6-4ba0-bde6-ca285c8d396c"
  }
}


[System] You are an expert in XML format. Think step-by-step, then generate syntactically perfect XML.

[User]
Reformat the data below from JSON to XML:
{
  "review_id": "REV-3982215",
  "product_id": "PROD-143836",
  "user_id": "0dd51960-e54b-4127-90d4-b32b17839969",
  "rating": 2,
  "title": "Fight and building toward office.",
  "content": "Hear media safe I visit language. Difference part thousand. Society inside describe decision.",
  "date": "2026-01-06",
  "verified_purchase": true,
  "helpful_votes": 16
}

[Assistant]
Approach:
1. Task: Convert customer review from JSON to XML
2. Complexity: complex - 8-10 fields, 3-4 levels
3. Format rules: well-formed tags, proper nesting, escaped special chars
4. Structure: Organize data logically with appropriate nesting
5. Transform values to match the target format specifications.

Output:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<review_id>REV-3982215</review_id>
<product_id>PROD-143836</product_id>
<user_id>0dd51960-e54b-4127-90d4-b32b17839969</user_id>
<rating>2</rating>
<title>Fight and building toward office.</title>
<content>Hear media safe I visit language. Difference part thousand. Society inside describe decision.</content>
<date>2026-01-06</date>
<verified_purchase>True</verified_purchase>
<helpful_votes>16</helpful_votes>
</customer_review>


[System] You are an expert in TOML format. Think step-by-step, then generate syntactically perfect TOML.

[User]
Transform this YAML data into TOML format:
rx_id: RX-1565761
patient_mrn: MRN-226686
prescriber: Regina Martin
date: '2026-01-03'
medications:
- name: Metformin
  dosage: 20mg
  frequency: TID
  quantity: 60
- name: Atorvastatin
  dosage: 20mg
  frequency: BID
  quantity: 90

[Assistant]
Approach:
1. Task: Convert prescription from YAML to TOML
2. Complexity: medium - 5-8 fields, 2-3 levels
3. Format rules: key=value syntax, [sections], proper types
4. Structure: Organize data logically with appropriate nesting
5. Transform values to match the target format specifications.

Output:
rx_id = "RX-1565761"
patient_mrn = "MRN-226686"
prescriber = "Regina Martin"
date = "2026-01-03"
[[medications]]
name = "Metformin"
dosage = "20mg"
frequency = "TID"
quantity = 60

[[medications]]
name = "Atorvastatin"
dosage = "20mg"
frequency = "BID"
quantity = 90


[System] You are an expert in XML format. Think step-by-step, then generate syntactically perfect XML.

[User] Generate contract data in XML format.

[Assistant]
Approach:
1. Task: Create contract in XML
2. Complexity: simple - 3-5 fields, minimal nesting
3. Format rules: well-formed tags, proper nesting, escaped special chars
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
<?xml version="1.0" encoding="UTF-8"?>
<contract>
<value>911148</value>
<contract_id>CTR-919818</contract_id>
<parties>
<name>Riggs, Carey and Rojas</name>
<role>party_a</role>
</parties>
<parties>
<name>Mcdowell-Koch</name>
<role>party_b</role>
</parties>
<status>active</status>
<term_months>18</term_months>
</contract>


[System] You are an expert in TOML format. Think step-by-step, then generate syntactically perfect TOML.

[User] Generate customer review data in TOML format.

[Assistant]
Approach:
1. Task: Create customer review in TOML
2. Complexity: simple - 3-5 fields, minimal nesting
3. Format rules: key=value syntax, [sections], proper types
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
helpful_votes = 39
date = "2026-01-04"
rating = 5
review_id = "REV-1864702"
title = "State standard bad message use."


[System] You are an expert in YAML format. Think step-by-step, then generate syntactically perfect YAML.

[User] Create a YAML representation of financial report.

[Assistant]
Approach:
1. Task: Create financial report in YAML
2. Complexity: simple - 3-5 fields, minimal nesting
3. Format rules: consistent indentation, colon-space syntax, hyphen lists
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
expenses: 65628233
eps: 5.75
quarter: Q2 2023
revenue: 73745517
net_income: 6367407


[System] You are an expert in JSON format. Think step-by-step, then generate syntactically perfect JSON.

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<prescription>
<rx_id>RX-9036427</rx_id>
<patient_mrn>MRN-461250</patient_mrn>
<prescriber>Zachary Berry</prescriber>
<date>2026-01-01</date>
<medications>
<name>Atorvastatin</name>
<dosage>5mg</dosage>
<frequency>daily</frequency>
<quantity>30</quantity>
</medications>
</prescription>

[Assistant]
Approach:
1. Task: Convert prescription from XML to JSON
2. Complexity: medium - 5-8 fields, 2-3 levels
3. Format rules: proper braces/brackets, quoted keys, correct value types
4. Structure: Organize data logically with appropriate nesting
5. Transform values to match the target format specifications.

Output:
{
  "rx_id": "RX-9036427",
  "patient_mrn": "MRN-461250",
  "prescriber": "Zachary Berry",
  "date": "2026-01-01",
  "medications": [
    {
      "name": "Atorvastatin",
      "dosage": "5mg",
      "frequency": "daily",
      "quantity": 30
    }
  ]
}


[System] You are an expert in CSV format. Think step-by-step, then generate syntactically perfect CSV.

[User] Create a CSV representation of social media post.

[Assistant]
Approach:
1. Task: Create social media post in CSV
2. Complexity: medium - 5-8 fields, 2-3 levels
3. Format rules: header row, comma-separated, quoted fields with commas
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
content,engagement_comments,engagement_likes,engagement_shares,hashtags,platform,post_id,timestamp,user_id,username
City window data describe address street. Environmental wall shoulder happy artist forget hospital. ,108,2391,751,"[""#yet"", ""#listen""]",instagram,POST-39289028,2026-01-07T13:51:26.862472,a2301bd9-5c11-406a-b2a8-1c1f96bbd31c,rhodessharon
"Happy around usually cup information. Popular read describe whether soldier.
Ahead Democrat glass he",308,3155,573,"[""#impact"", ""#data"", ""#recent"", ""#discuss""]",twitter,POST-14540052,2026-01-07T13:51:26.863649,b4f05259-aafe-4686-b254-beb458e839e1,charles18
"Table wait interview stay here skill name environment.
Certain think at than physical notice finally",186,5059,638,"[""#last"", ""#because""]",instagram,POST-34972107,2026-01-07T13:51:26.864071,459bbf5f-63ef-4324-8282-88c8e53b015f,wattskelsey
"Nothing real behavior skill.
Off agreement allow season factor form worker. National care want compu",484,1834,934,"[""#every"", ""#I"", ""#show""]",instagram,POST-34420003,2026-01-07T13:51:26.864442,66fbbc07-f1da-42c5-bf46-b6048cde92dc,parkerronald
Event accept ever address. Maintain soldier adult debate. Student leave game professional affect ran,335,4511,703,"[""#water"", ""#within"", ""#goal"", ""#vote""]",twitter,POST-29427753,2026-01-07T13:51:26.864831,c724647f-0610-4413-b7f6-1e3fefff7f3d,hugheschristopher


[System] You are an expert in YAML format. Think step-by-step, then generate syntactically perfect YAML.

[User] Generate clinical note data in YAML format.

[Assistant]
Approach:
1. Task: Create clinical note in YAML
2. Complexity: complex - 8-10 fields, 3-4 levels
3. Format rules: consistent indentation, colon-space syntax, hyphen lists
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
note_id: CN-4466987
patient:
  mrn: MRN-766590
  age: 87
  gender: F
encounter_date: '2026-01-02'
chief_complaint: headache
vitals:
  bp: 147/66
  hr: 72
  temp_f: 101.1
assessment:
- problem: diabetes
  icd10: K25


[System] You are an expert in TOML format. Think step-by-step, then generate syntactically perfect TOML.

[User] Generate prescription data in TOML format.

[Assistant]
Approach:
1. Task: Create prescription in TOML
2. Complexity: medium - 5-8 fields, 2-3 levels
3. Format rules: key=value syntax, [sections], proper types
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
rx_id = "RX-9719971"
patient_mrn = "MRN-909141"
prescriber = "Heather Stephens"
date = "2026-01-05"
[[medications]]
name = "Atorvastatin"
dosage = "20mg"
frequency = "daily"
quantity = 30


[System] You are an expert in YAML format. Think step-by-step, then generate syntactically perfect YAML.

[User] Create a YAML representation of transaction record.

[Assistant]
Approach:
1. Task: Create transaction record in YAML
2. Complexity: complex - 8-10 fields, 3-4 levels
3. Format rules: consistent indentation, colon-space syntax, hyphen lists
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
txn_id: TXN-48552675
customer_id: 19d3d880-f410-4b85-a35d-9c5777705d1f
timestamp: '2026-01-07T13:51:26.837603'
items:
- sku: SKU-30306
  qty: 4
  price: 206.74
subtotal: 1354.26
tax: 33.08
total: 766.28
payment_method: paypal


[System] You are an expert in XML format. Think step-by-step, then generate syntactically perfect XML.

[User]
Reformat the data below from JSON to XML:
{
  "rx_id": "RX-1795504",
  "patient_mrn": "MRN-355763",
  "prescriber": "Henry Padilla",
  "date": "2026-01-01",
  "medications": [
    {
      "name": "Metformin",
      "dosage": "20mg",
      "frequency": "daily",
      "quantity": 90
    }
  ]
}

[Assistant]
Approach:
1. Task: Convert prescription from JSON to XML
2. Complexity: complex - 8-10 fields, 3-4 levels
3. Format rules: well-formed tags, proper nesting, escaped special chars
4. Structure: Organize data logically with appropriate nesting
5. Transform values to match the target format specifications.

Output:
<?xml version="1.0" encoding="UTF-8"?>
<prescription>
<rx_id>RX-1795504</rx_id>
<patient_mrn>MRN-355763</patient_mrn>
<prescriber>Henry Padilla</prescriber>
<date>2026-01-01</date>
<medications>
<name>Metformin</name>
<dosage>20mg</dosage>
<frequency>daily</frequency>
<quantity>90</quantity>
</medications>
</prescription>


[System] You are an expert in YAML format. Think step-by-step, then generate syntactically perfect YAML.

[User] Create a YAML representation of news article.

[Assistant]
Approach:
1. Task: Create news article in YAML
2. Complexity: complex - 8-10 fields, 3-4 levels
3. Format rules: consistent indentation, colon-space syntax, hyphen lists
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
article_id: ART-8136358
headline: Realigned multimedia paradigm
author: Brian White
published: '2026-01-02T14:21:25.908532'
section: Sports
content: 'Give model worry sense. Including reflect teacher near image.

  Culture kitchen run first would. Agency media particularly past office every.

  Bag water address admit. Skin tend Mr significant dark pretty. Painting water campaign.'
tags:
- involve
- service
- along
- stand
views: 7987
shares: 4175


[System] You are an expert in JSON format. Think step-by-step, then generate syntactically perfect JSON.

[User] Generate contract data in JSON format.

[Assistant]
Approach:
1. Task: Create contract in JSON
2. Complexity: complex - 8-10 fields, 3-4 levels
3. Format rules: proper braces/brackets, quoted keys, correct value types
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
{
  "contract_id": "CTR-760727",
  "parties": [
    {
      "name": "King, Moore and Vazquez",
      "role": "party_a"
    },
    {
      "name": "Brown, Henry and Craig",
      "role": "party_b"
    }
  ],
  "effective_date": "2026-01-04",
  "term_months": 15,
  "value": 170545,
  "status": "active"
}


[System] You are an expert in XML format. Think step-by-step, then generate syntactically perfect XML.

[User]
Reformat the data below from JSON to XML:
{
  "contract_id": "CTR-760727",
  "parties": [
    {
      "name": "King, Moore and Vazquez",
      "role": "party_a"
    },
    {
      "name": "Brown, Henry and Craig",
      "role": "party_b"
    }
  ],
  "effective_date": "2026-01-04",
  "term_months": 15,
  "value": 170545,
  "status": "active"
}

[Assistant]
Approach:
1. Task: Convert contract from JSON to XML
2. Complexity: complex - 8-10 fields, 3-4 levels
3. Format rules: well-formed tags, proper nesting, escaped special chars
4. Structure: Organize data logically with appropriate nesting
5. Transform values to match the target format specifications.

Output:
<?xml version="1.0" encoding="UTF-8"?>
<contract>
<contract_id>CTR-760727</contract_id>
<parties>
<name>King, Moore and Vazquez</name>
<role>party_a</role>
</parties>
<parties>
<name>Brown, Henry and Craig</name>
<role>party_b</role>
</parties>
<effective_date>2026-01-04</effective_date>
<term_months>15</term_months>
<value>170545</value>
<status>active</status>
</contract>


[System] You are an expert in XML format. Think step-by-step, then generate syntactically perfect XML.

[User]
Transform this TOML data into XML format:
openapi = "3.0.0"

[info]
title = "Business-focused zero administration encryption API"
version = "1.0.0"

[paths."/teach".get]
summary = "Government trade direction personal reason hundred"
[[paths."/teach".get.parameters]]
name = "param0"
in = "query"
type = "string"

[[paths."/teach".get.parameters]]
name = "param1"
in = "query"
type = "string"

[paths."/teach".get.responses.200]
description = "Success"

[paths."/teach".get.responses.400]
description = "Bad Request"

[Assistant]
Approach:
1. Task: Convert api specification from TOML to XML
2. Complexity: medium - 5-8 fields, 2-3 levels
3. Format rules: well-formed tags, proper nesting, escaped special chars
4. Structure: Organize data logically with appropriate nesting
5. Transform values to match the target format specifications.

Output:
<?xml version="1.0" encoding="UTF-8"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Business-focused zero administration encryption API</title>
<version>1.0.0</version>
</info>
<paths>
</teach>
<get>
<summary>Government trade direction personal reason hundred</summary>
<parameters>
<name>param0</name>
<in>query</in>
<type>string</type>
</parameters>
<parameters>
<name>param1</name>
<in>query</in>
<type>string</type>
</parameters>
<responses>
<200>
<description>Success</description>
</200>
<400>
<description>Bad Request</description>
</400>
</responses>
</get>
<//teach>
</paths>
</api_specification>


[System] You are an expert in XML format. Think step-by-step, then generate syntactically perfect XML.

[User]
Transform this JSON data into XML format:
{
  "openapi": "3.0.0",
  "info": {
    "title": "Streamlined logistical help-desk API",
    "version": "1.0.0"
  },
  "paths": {
    "/grow": {
      "get": {
        "summary": "Will entire deep source history.",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          },
          {
            "name": "param1",
            "in": "query",
            "type": "string"
          },
          {
            "name": "param2",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  }
}

[Assistant]
Approach:
1. Task: Convert api specification from JSON to XML
2. Complexity: complex - 8-10 fields, 3-4 levels
3. Format rules: well-formed tags, proper nesting, escaped special chars
4. Structure: Organize data logically with appropriate nesting
5. Transform values to match the target format specifications.

Output:
<?xml version="1.0" encoding="UTF-8"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Streamlined logistical help-desk API</title>
<version>1.0.0</version>
</info>
<paths>
</grow>
<get>
<summary>Will entire deep source history.</summary>
<parameters>
<name>param0</name>
<in>query</in>
<type>string</type>
</parameters>
<parameters>
<name>param1</name>
<in>query</in>
<type>string</type>
</parameters>
<parameters>
<name>param2</name>
<in>query</in>
<type>string</type>
</parameters>
<responses>
<200>
<description>Success</description>
</200>
<400>
<description>Bad Request</description>
</400>
</responses>
</get>
<//grow>
</paths>
</api_specification>


[System] You are an expert in TOML format. Think step-by-step, then generate syntactically perfect TOML.

[User] Create a TOML representation of product listing.

[Assistant]
Approach:
1. Task: Create product listing in TOML
2. Complexity: simple - 3-5 fields, minimal nesting
3. Format rules: key=value syntax, [sections], proper types
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
reviews = 730
category = "books"
stock = 824
is_available = true

[specs]
weight_kg = 7.36
dimensions = "46x21x76cm"


[System] You are an expert in XML format. Think step-by-step, then generate syntactically perfect XML.

[User] Output customer review as XML.

[Assistant]
Approach:
1. Task: Create customer review in XML
2. Complexity: complex - 8-10 fields, 3-4 levels
3. Format rules: well-formed tags, proper nesting, escaped special chars
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<review_id>REV-9529513</review_id>
<product_id>PROD-542599</product_id>
<user_id>67bb80c4-7c72-4c1b-886f-8186f18f45e3</user_id>
<rating>3</rating>
<title>Money face statement talk day.</title>
<content>Candidate stuff mission end nature hundred. Recently game stage agreement. Seem central blood add environment several.
Set less job reveal protect. Similar second staff owner international major.</content>
<date>2026-01-01</date>
<verified_purchase>True</verified_purchase>
<helpful_votes>8</helpful_votes>
</customer_review>


[System] You are an expert in TOML format. Think step-by-step, then generate syntactically perfect TOML.

[User] Output financial report as TOML.

[Assistant]
Approach:
1. Task: Create financial report in TOML
2. Complexity: medium - 5-8 fields, 2-3 levels
3. Format rules: key=value syntax, [sections], proper types
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
company = "Thompson, Yang and Roberts"
ticker = "ATOM"
quarter = "Q1 2022"
revenue = 59725729
expenses = 36274579
net_income = 7802792
eps = 8.84

[metrics]
profit_margin = 17.46
roe = 22.69


[System] You are an expert in XML format. Think step-by-step, then generate syntactically perfect XML.

[User]
Transform this JSON data into XML format:
{
  "post_id": "POST-58559815",
  "platform": "instagram",
  "user_id": "0fae79ab-dabb-47f5-823b-f22743181c7c",
  "username": "ortizkristina",
  "content": "Speech can sea play. Season near story animal remain.\nOff present vote wall. Society know family build. Certain thing live rise.",
  "timestamp": "2026-01-07T13:51:26.463560",
  "hashtags": [
    "#once",
    "#it",
    "#rich",
    "#keep"
  ],
  "engagement": {
    "likes": 248,
    "shares": 32,
    "comments": 161
  }
}

[Assistant]
Approach:
1. Task: Convert social media post from JSON to XML
2. Complexity: medium - 5-8 fields, 2-3 levels
3. Format rules: well-formed tags, proper nesting, escaped special chars
4. Structure: Organize data logically with appropriate nesting
5. Transform values to match the target format specifications.

Output:
<?xml version="1.0" encoding="UTF-8"?>
<social_media_post>
<post_id>POST-58559815</post_id>
<platform>instagram</platform>
<user_id>0fae79ab-dabb-47f5-823b-f22743181c7c</user_id>
<username>ortizkristina</username>
<content>Speech can sea play. Season near story animal remain.
Off present vote wall. Society know family build. Certain thing live rise.</content>
<timestamp>2026-01-07T13:51:26.463560</timestamp>
<hashtags>#once</hashtags>
<hashtags>#it</hashtags>
<hashtags>#rich</hashtags>
<hashtags>#keep</hashtags>
<engagement>
<likes>248</likes>
<shares>32</shares>
<comments>161</comments>
</engagement>
</social_media_post>


[System] You are an expert in TOML format. Think step-by-step, then generate syntactically perfect TOML.

[User] Create a TOML representation of lab result.

[Assistant]
Approach:
1. Task: Create lab result in TOML
2. Complexity: medium - 5-8 fields, 2-3 levels
3. Format rules: key=value syntax, [sections], proper types
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
result_id = "LAB-9047593"
patient_mrn = "MRN-478989"
order_date = "2026-01-06"
panel = "CMP"
[[results]]
test = "Hemoglobin"
value = 171.8
unit = "mg/dL"
flag = "normal"

[[results]]
test = "WBC"
value = 58.0
unit = "g/dL"
flag = "normal"

[[results]]
test = "WBC"
value = 78.7
unit = "mg/dL"
flag = "normal"

[[results]]
test = "Glucose"
value = 138.7
unit = "mg/dL"
flag = "low"

[[results]]
test = "Hemoglobin"
value = 51.5
unit = "g/dL"
flag = "high"

[[results]]
test = "Hemoglobin"
value = 141.9
unit = "mg/dL"
flag = "low"

[[results]]
test = "Hemoglobin"
value = 191.7
unit = "mg/dL"
flag = "high"


[System] You are an expert in JSON format. Think step-by-step, then generate syntactically perfect JSON.

[User] Create a JSON representation of sales analytics.

[Assistant]
Approach:
1. Task: Create sales analytics in JSON
2. Complexity: complex - 8-10 fields, 3-4 levels
3. Format rules: proper braces/brackets, quoted keys, correct value types
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
{
  "period": "November 2022",
  "total_revenue": 9138741,
  "units_sold": 89798,
  "channels": [
    {
      "name": "wholesale",
      "revenue": 1234153,
      "growth": 40.64
    },
    {
      "name": "online",
      "revenue": 991509,
      "growth": -4.15
    }
  ],
  "top_products": [
    {
      "sku": "SKU-9585",
      "sales": 30234
    },
    {
      "sku": "SKU-8072",
      "sales": 57362
    },
    {
      "sku": "SKU-4011",
      "sales": 249730
    }
  ]
}


[System] You are an expert in CSV format. Think step-by-step, then generate syntactically perfect CSV.

[User] Create a CSV representation of error log.

[Assistant]
Approach:
1. Task: Create error log in CSV
2. Complexity: medium - 5-8 fields, 2-3 levels
3. Format rules: header row, comma-separated, quoted fields with commas
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
abstract,authors,citations,context_request_id,context_user_id,error_id,funding_source,keywords,level,message,paper_id,publication_doi,publication_venue,publication_year,service,stack_trace,timestamp,title
,,,f4cb6737-30c9-41ef-814b-34c3ec971deb,c92bcb8f-c109-47f8-aa13-b43737a1fc38,92d36993-19b1-4c19-9b64-8b4669c6636f,,,WARNING,Analysis beautiful attack blue eye.,,,,,voiceService,"[""at well.py:163"", ""at will.py:421"", ""at run.py:384"", ""at TV.py:103""]",2026-01-07T13:51:27.222487,
Pretty lot mission that could model almost. Note material admit which. Citizen able tonight water.,"[{""name"": ""Kathleen Carter"", ""affiliation"": ""Stevens, Thomas and Frost"", ""email"": ""xgomez@example.or",251,,,,None,"[""forward"", ""each"", ""attack"", ""stage""]",,,arXiv:2023.12601,10.6819/NFFB,Cell,2022,,,,Stand-alone bi-directional challenge
"Yes oil effect meeting cup.
Become would increase morning off field. Start station since benefit dow","[{""name"": ""Jennifer Hall"", ""affiliation"": ""Faulkner PLC"", ""email"": ""jfisher@example.org""}, {""name"": ",475,,,,None,"[""good"", ""section"", ""pick""]",,,arXiv:2020.73807,10.2239/WxRd,Cell,2022,,,,Profound scalable methodology
Personal none foot worry tough modern toward. Free find wall official top sure history.,"[{""name"": ""Sandra Martin"", ""affiliation"": ""Bailey, Rice and Hanson"", ""email"": ""hernandeztammy@exampl",434,,,,Williamson and Sons,"[""senior"", ""character"", ""listen"", ""argue"", ""full""]",,,arXiv:2022.64046,10.5789/vzEC,Nature,2021,,,,Digitized local emulation


[System] You are an expert in JSON format. Think step-by-step, then generate syntactically perfect JSON.

[User] Output lab result as JSON.

[Assistant]
Approach:
1. Task: Create lab result in JSON
2. Complexity: complex - 8-10 fields, 3-4 levels
3. Format rules: proper braces/brackets, quoted keys, correct value types
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
{
  "result_id": "LAB-5956795",
  "patient_mrn": "MRN-953048",
  "order_date": "2026-01-05",
  "panel": "CBC",
  "results": [
    {
      "test": "Glucose",
      "value": 138.6,
      "unit": "g/dL",
      "flag": "high"
    },
    {
      "test": "Hemoglobin",
      "value": 69.4,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 89.7,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 191.9,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "WBC",
      "value": 169.5,
      "unit": "mg/dL",
      "flag": "low"
    },
    {
      "test": "Glucose",
      "value": 187.7,
      "unit": "mg/dL",
      "flag": "low"
    },
    {
      "test": "WBC",
      "value": 120.0,
      "unit": "mg/dL",
      "flag": "high"
    }
  ]
}


[System] You are an expert in XML format. Think step-by-step, then generate syntactically perfect XML.

[User]
Transform this JSON data into XML format:
{
  "error_id": "69ef512f-ddd4-415a-b99a-51e8f50d151c",
  "timestamp": "2026-01-07T13:51:25.644182",
  "level": "WARNING",
  "service": "fillService",
  "message": "Minute heart focus arrive.",
  "stack_trace": [
    "at administration.py:211",
    "at lawyer.py:276",
    "at discussion.py:115"
  ],
  "context": {
    "user_id": "29c6c678-1224-4e33-8bc1-e94776cd4eb2",
    "request_id": "42e054d1-48f9-4a1c-ad7b-82ed505d6250"
  }
}

[Assistant]
Approach:
1. Task: Convert error log from JSON to XML
2. Complexity: complex - 8-10 fields, 3-4 levels
3. Format rules: well-formed tags, proper nesting, escaped special chars
4. Structure: Organize data logically with appropriate nesting
5. Transform values to match the target format specifications.

Output:
<?xml version="1.0" encoding="UTF-8"?>
<error_log>
<error_id>69ef512f-ddd4-415a-b99a-51e8f50d151c</error_id>
<timestamp>2026-01-07T13:51:25.644182</timestamp>
<level>WARNING</level>
<service>fillService</service>
<message>Minute heart focus arrive.</message>
<stack_trace>at administration.py:211</stack_trace>
<stack_trace>at lawyer.py:276</stack_trace>
<stack_trace>at discussion.py:115</stack_trace>
<context>
<user_id>29c6c678-1224-4e33-8bc1-e94776cd4eb2</user_id>
<request_id>42e054d1-48f9-4a1c-ad7b-82ed505d6250</request_id>
</context>
</error_log>


[System] You are an expert in XML format. Think step-by-step, then generate syntactically perfect XML.

[User] Create a XML representation of financial report.

[Assistant]
Approach:
1. Task: Create financial report in XML
2. Complexity: medium - 5-8 fields, 2-3 levels
3. Format rules: well-formed tags, proper nesting, escaped special chars
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
<?xml version="1.0" encoding="UTF-8"?>
<financial_report>
<company>Rodriguez, Sanchez and French</company>
<ticker>TOPI</ticker>
<quarter>Q3 2022</quarter>
<revenue>30596216</revenue>
<expenses>79425858</expenses>
<net_income>10739155</net_income>
<eps>9.27</eps>
<metrics>
<profit_margin>21.79</profit_margin>
<roe>22.32</roe>
</metrics>
</financial_report>


[System] You are an expert in JSON format. Think step-by-step, then generate syntactically perfect JSON.

[User] Generate clinical note data in JSON format.

[Assistant]
Approach:
1. Task: Create clinical note in JSON
2. Complexity: complex - 8-10 fields, 3-4 levels
3. Format rules: proper braces/brackets, quoted keys, correct value types
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
{
  "note_id": "CN-9595817",
  "patient": {
    "mrn": "MRN-972408",
    "age": 32,
    "gender": "F"
  },
  "encounter_date": "2026-01-02",
  "chief_complaint": "chest pain",
  "vitals": {
    "bp": "102/103",
    "hr": 113,
    "temp_f": 102.5
  },
  "assessment": [
    {
      "problem": "hypertension",
      "icd10": "K99"
    }
  ]
}


[System] You are an expert in JSON format. Think step-by-step, then generate syntactically perfect JSON.

[User] Generate financial report data in JSON format.

[Assistant]
Approach:
1. Task: Create financial report in JSON
2. Complexity: medium - 5-8 fields, 2-3 levels
3. Format rules: proper braces/brackets, quoted keys, correct value types
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
{
  "company": "Thompson, Yang and Roberts",
  "ticker": "ATOM",
  "quarter": "Q1 2022",
  "revenue": 59725729,
  "expenses": 36274579,
  "net_income": 7802792,
  "eps": 8.84,
  "metrics": {
    "profit_margin": 17.46,
    "roe": 22.69
  }
}


[System] You are an expert in XML format. Think step-by-step, then generate syntactically perfect XML.

[User]
Convert the following JSON to XML:
{
  "error_id": "e01a43f8-d4eb-4ec7-a325-ad2b31726d0f",
  "timestamp": "2026-01-07T13:51:25.462522",
  "level": "ERROR",
  "service": "winService",
  "message": "Western energy project push building.",
  "stack_trace": [
    "at could.py:42",
    "at seem.py:198"
  ],
  "context": {
    "user_id": "7197800d-0acd-4eee-b9ab-24b5158dfa0a",
    "request_id": "00c4c00d-dc22-4013-8495-1ed2381fc937"
  }
}

[Assistant]
Approach:
1. Task: Convert error log from JSON to XML
2. Complexity: complex - 8-10 fields, 3-4 levels
3. Format rules: well-formed tags, proper nesting, escaped special chars
4. Structure: Organize data logically with appropriate nesting
5. Transform values to match the target format specifications.

Output:
<?xml version="1.0" encoding="UTF-8"?>
<error_log>
<error_id>e01a43f8-d4eb-4ec7-a325-ad2b31726d0f</error_id>
<timestamp>2026-01-07T13:51:25.462522</timestamp>
<level>ERROR</level>
<service>winService</service>
<message>Western energy project push building.</message>
<stack_trace>at could.py:42</stack_trace>
<stack_trace>at seem.py:198</stack_trace>
<context>
<user_id>7197800d-0acd-4eee-b9ab-24b5158dfa0a</user_id>
<request_id>00c4c00d-dc22-4013-8495-1ed2381fc937</request_id>
</context>
</error_log>


[System] You are an expert in XML format. Think step-by-step, then generate syntactically perfect XML.

[User]
Convert the following JSON to XML:
{
  "contract_id": "CTR-464030",
  "parties": [
    {
      "name": "Morales, Williams and Williams",
      "role": "party_a"
    },
    {
      "name": "Ward-Miller",
      "role": "party_b"
    }
  ],
  "effective_date": "2026-01-06",
  "term_months": 35,
  "value": 994957,
  "status": "active"
}

[Assistant]
Approach:
1. Task: Convert contract from JSON to XML
2. Complexity: complex - 8-10 fields, 3-4 levels
3. Format rules: well-formed tags, proper nesting, escaped special chars
4. Structure: Organize data logically with appropriate nesting
5. Transform values to match the target format specifications.

Output:
<?xml version="1.0" encoding="UTF-8"?>
<contract>
<contract_id>CTR-464030</contract_id>
<parties>
<name>Morales, Williams and Williams</name>
<role>party_a</role>
</parties>
<parties>
<name>Ward-Miller</name>
<role>party_b</role>
</parties>
<effective_date>2026-01-06</effective_date>
<term_months>35</term_months>
<value>994957</value>
<status>active</status>
</contract>


[System] You are an expert in TOML format. Think step-by-step, then generate syntactically perfect TOML.

[User] Generate research paper data in TOML format.

[Assistant]
Approach:
1. Task: Create research paper in TOML
2. Complexity: complex - 8-10 fields, 3-4 levels
3. Format rules: key=value syntax, [sections], proper types
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
paper_id = "arXiv:2021.53732"
title = "De-engineered exuding monitoring"
abstract = "Cut happen you after talk trial accept she. Country church development card. Learn support son service."
keywords = [ "positive", "American", "hand", "sure",]
citations = 88
funding_source = "Kim LLC"
[[authors]]
name = "Joseph Johnson"
affiliation = "Mccann, Romero and Ortiz"
email = "wcook@example.org"

[[authors]]
name = "Mr. Henry Thomas"
affiliation = "Clarke-Williams"
email = "mlittle@example.com"

[publication]
venue = "Science"
year = 2024
doi = "10.3815/gTFt"


[System] You are an expert in JSON format. Think step-by-step, then generate syntactically perfect JSON.

[User] Create a JSON representation of course syllabus.

[Assistant]
Approach:
1. Task: Create course syllabus in JSON
2. Complexity: medium - 5-8 fields, 2-3 levels
3. Format rules: proper braces/brackets, quoted keys, correct value types
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
{
  "course_id": "CRS-4765",
  "code": "VMZ479",
  "title": "Exclusive grid-enabled software 101",
  "instructor": "Amy Baker",
  "credits": 4,
  "term": "Fall 2022",
  "schedule": [
    {
      "week": 1,
      "topic": "show"
    },
    {
      "week": 2,
      "topic": "cut"
    },
    {
      "week": 3,
      "topic": "next"
    },
    {
      "week": 4,
      "topic": "everything"
    },
    {
      "week": 5,
      "topic": "people"
    },
    {
      "week": 6,
      "topic": "international"
    },
    {
      "week": 7,
      "topic": "since"
    }
  ],
  "grading": {
    "homework": 30,
    "midterm": 30,
    "final": 40
  }
}


[System] You are an expert in JSON format. Think step-by-step, then generate syntactically perfect JSON.

[User]
Transform this CSV data into JSON format:
abstract,authors,citations,funding_source,info_title,info_version,keywords,openapi,paper_id,paths_/pass_get_parameters,paths_/pass_get_responses_200_description,paths_/pass_get_responses_400_description,paths_/pass_get_summary,publication_doi,publication_venue,publication_year,title
,,,,Upgradable 4thgeneration middleware API,1.0.0,,3.0.0,,"[{""name"": ""param0"", ""in"": ""query"", ""type"": ""string""}]",Success,Bad Request,Story amount nor bed night get message.,,,,
Just along even public. Relationship water seek government. Cup why deep year sell.,"[{""name"": ""Michael Leonard"", ""affiliation"": ""Bishop-Richard"", ""email"": ""ian00@example.net""}, {""name""",460,"Bruce, Daniels and Robertson",,,"[""war"", ""walk"", ""radio"", ""beat""]",,arXiv:2021.54096,,,,,10.2876/MCVm,Science,2020,Re-engineered bi-directional benchmark
Fear something somebody ability training. Continue physical win president wind action throw as. Incl,"[{""name"": ""Joshua Reyes"", ""affiliation"": ""Castro-Mcfarland"", ""email"": ""jennifer60@example.net""}, {""n",484,None,,,"[""mention"", ""none"", ""Mr"", ""range"", ""society""]",,arXiv:2022.30182,,,,,10.4032/Xaul,Nature,2021,Persistent mission-critical instruction set
"City wrong few study. Available figure as unit edge suffer.
Explain seat answer next national fine. ","[{""name"": ""Kendra Smith"", ""affiliation"": ""Berry-Stephenson"", ""email"": ""jay43@example.com""}, {""name"":",476,None,,,"[""everyone"", ""discussion"", ""answer"", ""environmental"", ""ability""]",,arXiv:2023.17961,,,,,10.6416/Zmpx,Nature,2020,Team-oriented bandwidth-monitored monitoring
Choice especially produce show often. Minute large treatment report watch.,"[{""name"": ""William Lopez"", ""affiliation"": ""Taylor, Richard and Norton"", ""email"": ""melanie79@example.",40,None,,,"[""forward"", ""college"", ""interesting""]",,arXiv:2023.28016,,,,,10.3441/bDPI,Science,2024,Virtual 6thgeneration leverage

[Assistant]
Approach:
1. Task: Convert api specification from CSV to JSON
2. Complexity: medium - 5-8 fields, 2-3 levels
3. Format rules: proper braces/brackets, quoted keys, correct value types
4. Structure: Organize data logically with appropriate nesting
5. Transform values to match the target format specifications.

Output:
{
  "openapi": "3.0.0",
  "info": {
    "title": "Upgradable 4thgeneration middleware API",
    "version": "1.0.0"
  },
  "paths": {
    "/pass": {
      "get": {
        "summary": "Story amount nor bed night get message.",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  }
}


[System] You are an expert in YAML format. Think step-by-step, then generate syntactically perfect YAML.

[User] Produce a YAML document for a prescription.

[Assistant]
Approach:
1. Task: Create prescription in YAML
2. Complexity: simple - 3-5 fields, minimal nesting
3. Format rules: consistent indentation, colon-space syntax, hyphen lists
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
medications:
- name: Atorvastatin
  dosage: 5mg
  frequency: BID
  quantity: 30
prescriber: Isaac Howard
date: '2026-01-03'


[System] You are an expert in XML format. Think step-by-step, then generate syntactically perfect XML.

[User] Output research paper as XML.

[Assistant]
Approach:
1. Task: Create research paper in XML
2. Complexity: complex - 8-10 fields, 3-4 levels
3. Format rules: well-formed tags, proper nesting, escaped special chars
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
<?xml version="1.0" encoding="UTF-8"?>
<research_paper>
<paper_id>arXiv:2020.86983</paper_id>
<title>Reverse-engineered national Graphical User Interface</title>
<authors>
<name>Wesley Murphy</name>
<affiliation>Nunez, Meyer and Snow</affiliation>
<email>nina74@example.net</email>
</authors>
<authors>
<name>Richard Morgan</name>
<affiliation>Hall-Jones</affiliation>
<email>justin85@example.org</email>
</authors>
<authors>
<name>Anthony Johnson</name>
<affiliation>Kelley-Murphy</affiliation>
<email>srichmond@example.com</email>
</authors>
<abstract>Sure finally site who truth. Close stop when low. Check news mother democratic.</abstract>
<keywords>old</keywords>
<keywords>indeed</keywords>
<keywords>general</keywords>
<keywords>claim</keywords>
<keywords>every</keywords>
<publication>
<venue>Nature</venue>
<year>2024</year>
<doi>10.2539/QMDE</doi>
</publication>
<citations>221</citations>
<funding_source />
</research_paper>


[System] You are an expert in JSON format. Think step-by-step, then generate syntactically perfect JSON.

[User] Produce a JSON document for a error log.

[Assistant]
Approach:
1. Task: Create error log in JSON
2. Complexity: medium - 5-8 fields, 2-3 levels
3. Format rules: proper braces/brackets, quoted keys, correct value types
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
{
  "error_id": "92d36993-19b1-4c19-9b64-8b4669c6636f",
  "timestamp": "2026-01-07T13:51:27.222487",
  "level": "WARNING",
  "service": "voiceService",
  "message": "Analysis beautiful attack blue eye.",
  "stack_trace": [
    "at well.py:163",
    "at will.py:421",
    "at run.py:384",
    "at TV.py:103"
  ],
  "context": {
    "user_id": "c92bcb8f-c109-47f8-aa13-b43737a1fc38",
    "request_id": "f4cb6737-30c9-41ef-814b-34c3ec971deb"
  }
}


[System] You are an expert in XML format. Think step-by-step, then generate syntactically perfect XML.

[User] Produce a XML document for a contract.

[Assistant]
Approach:
1. Task: Create contract in XML
2. Complexity: complex - 8-10 fields, 3-4 levels
3. Format rules: well-formed tags, proper nesting, escaped special chars
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
<?xml version="1.0" encoding="UTF-8"?>
<contract>
<contract_id>CTR-896633</contract_id>
<parties>
<name>Smith-Cross</name>
<role>party_a</role>
</parties>
<parties>
<name>Carrillo and Sons</name>
<role>party_b</role>
</parties>
<effective_date>2026-01-03</effective_date>
<term_months>21</term_months>
<value>926875</value>
<status>pending</status>
</contract>


[System] You are an expert in YAML format. Think step-by-step, then generate syntactically perfect YAML.

[User] Output product listing as YAML.

[Assistant]
Approach:
1. Task: Create product listing in YAML
2. Complexity: complex - 8-10 fields, 3-4 levels
3. Format rules: consistent indentation, colon-space syntax, hyphen lists
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
product_id: PROD-110536
name: Organized didactic parallelism
category: clothing
price: 68.12
currency: USD
stock: 153
is_available: true
rating: 1.45
reviews: 277
specs:
  weight_kg: 1.85
  dimensions: 33x70x14cm


[System] You are an expert in JSON format. Think step-by-step, then generate syntactically perfect JSON.

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<news_article>
<article_id>ART-2388619</article_id>
<headline>Switchable tertiary collaboration</headline>
<author>Paula Martinez</author>
<published>2026-01-07T02:15:35.006278</published>

Politics

<content>Choice list strong let reason. Education class ok front impact successful. Huge professor happen data image stop. Notice movie reduce everyone among ask already company.
Door president he always capital.
Black democratic heart read name. Professional billion prepare executive meeting sport.</content>
<tags>hair</tags>
<tags>democratic</tags>
<tags>financial</tags>
<tags>huge</tags>
<tags>available</tags>
<views>74003</views>
<shares>1794</shares>
</news_article>

[Assistant]
Approach:
1. Task: Convert news article from XML to JSON
2. Complexity: complex - 8-10 fields, 3-4 levels
3. Format rules: proper braces/brackets, quoted keys, correct value types
4. Structure: Organize data logically with appropriate nesting
5. Transform values to match the target format specifications.

Output:
{
  "article_id": "ART-2388619",
  "headline": "Switchable tertiary collaboration",
  "author": "Paula Martinez",
  "published": "2026-01-07T02:15:35.006278",
  "section": "Politics",
  "content": "Choice list strong let reason. Education class ok front impact successful. Huge professor happen data image stop. Notice movie reduce everyone among ask already company.\nDoor president he always capital.\nBlack democratic heart read name. Professional billion prepare executive meeting sport.",
  "tags": [
    "hair",
    "democratic",
    "financial",
    "huge",
    "available"
  ],
  "views": 74003,
  "shares": 1794
}


[System] You are an expert in CSV format. Think step-by-step, then generate syntactically perfect CSV.

[User] Produce a CSV document for a prescription.

[Assistant]
Approach:
1. Task: Create prescription in CSV
2. Complexity: complex - 8-10 fields, 3-4 levels
3. Format rules: header row, comma-separated, quoted fields with commas
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
date,medications,patient_mrn,prescriber,rx_id
2026-01-05,"[{""name"": ""Metformin"", ""dosage"": ""20mg"", ""frequency"": ""TID"", ""quantity"": 90}]",MRN-440463,Lisa Mathews,RX-6036951
2026-01-06,"[{""name"": ""Metformin"", ""dosage"": ""10mg"", ""frequency"": ""TID"", ""quantity"": 90}]",MRN-374219,Kyle Arnold,RX-9467282
2026-01-03,"[{""name"": ""Lisinopril"", ""dosage"": ""20mg"", ""frequency"": ""BID"", ""quantity"": 90}]",MRN-404153,Tyler Day,RX-6466107
2026-01-02,"[{""name"": ""Atorvastatin"", ""dosage"": ""5mg"", ""frequency"": ""BID"", ""quantity"": 60}]",MRN-983646,Joshua Jennings,RX-9128747