[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"?>
<student_assessment>
<assessment_id>ASMT-475777</assessment_id>
<student_id>STU-613124</student_id>
<course_id>CRS-2241</course_id>
<type>assignment</type>
<date>2026-01-06</date>
<scores>
<question>1</question>
<points_earned>8</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>6</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>3</question>
<points_earned>3</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>7</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>0</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>9</question>
<points_earned>3</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>75</total_score>
<percentage>81.54</percentage>
<grade>B</grade>
</student_assessment>

[Assistant]
Approach:
1. Task: Convert student assessment 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:
{
  "assessment_id": "ASMT-475777",
  "student_id": "STU-613124",
  "course_id": "CRS-2241",
  "type": "assignment",
  "date": "2026-01-06",
  "scores": [
    {
      "question": 1,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 6,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 3,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 0,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 9,
      "points_earned": 3,
      "points_possible": 10
    }
  ],
  "total_score": 75,
  "percentage": 81.54,
  "grade": "B"
}


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

[User] Produce a JSON document for a social media post.

[Assistant]
Approach:
1. Task: Create social media post 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:
{
  "post_id": "POST-15490463",
  "platform": "instagram",
  "user_id": "dcf0c28f-6ad6-4153-873b-0cd39fa73a46",
  "username": "allenjames",
  "content": "Eight television free focus window leave. Education Democrat past music mother able. Fund season represent when analysis movement.\nEverything over rich serious forget. Fire particular western.",
  "timestamp": "2026-01-07T13:51:27.338072",
  "hashtags": [
    "#left",
    "#long",
    "#instead",
    "#budget"
  ],
  "engagement": {
    "likes": 85,
    "shares": 112,
    "comments": 292
  }
}


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

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

[Assistant]
Approach:
1. Task: Create customer review 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:
category,content,currency,date,helpful_votes,is_available,name,price,product_id,rating,review_id,reviews,specs_dimensions,specs_weight_kg,stock,title,user_id,verified_purchase
,"Recent cause family writer. Old less control he woman. Coach quickly will.
Relationship same against",,2026-01-06,37,,,,PROD-300785,5,REV-1274071,,,,,Follow large high gas clear drug pretty else.,c183a72e-4d6f-40ac-92b0-2d1073039571,True
electronics,,USD,,,True,Extended analyzing approach,503.58,PROD-420019,2.78,,526,15x70x77cm,3.76,348,,,
clothing,,USD,,,True,Profit-focused discrete hub,410.14,PROD-373450,2.47,,739,47x90x88cm,9.42,750,,,


[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"?>
<course_syllabus>
<instructor>Tamara Stark</instructor>
<term>Spring 2022</term>
VMA483
<grading>
<homework>30</homework>
<midterm>30</midterm>
<final>40</final>
</grading>
</course_syllabus>

[Assistant]
Approach:
1. Task: Convert course syllabus 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:
{
  "instructor": "Tamara Stark",
  "term": "Spring 2022",
  "code": "VMA483",
  "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] Output news article as JSON.

[Assistant]
Approach:
1. Task: Create news article 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:
{
  "views": 92789,
  "content": "Couple and teacher radio compare consumer. Pass thing much rather light.\nFoot four country subject first interview. Defense TV artist to of. Fund miss window scene.\nWish successful movement city door politics measure. Police media TV out word remain as. Report option appear station example role.",
  "shares": 213,
  "headline": "Re-engineered composite Local Area Network",
  "tags": [
    "couple",
    "this",
    "themselves",
    "whom"
  ]
}


[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"?>
<contract>
<contract_id>CTR-143990</contract_id>
<parties>
<name>Brady Inc</name>
<role>party_a</role>
</parties>
<parties>
<name>Gonzalez, Coleman and Sanchez</name>
<role>party_b</role>
</parties>
<effective_date>2026-01-02</effective_date>
<term_months>32</term_months>
<value>452000</value>
<status>active</status>
</contract>

[Assistant]
Approach:
1. Task: Convert contract 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:
{
  "contract_id": "CTR-143990",
  "parties": [
    {
      "name": "Brady Inc",
      "role": "party_a"
    },
    {
      "name": "Gonzalez, Coleman and Sanchez",
      "role": "party_b"
    }
  ],
  "effective_date": "2026-01-02",
  "term_months": 32,
  "value": 452000,
  "status": "active"
}


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

[User] Generate experiment result data in JSON format.

[Assistant]
Approach:
1. Task: Create experiment 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:
{
  "experiment_id": "EXP-942720",
  "title": "Effect of edge on when",
  "methodology": {
    "design": "cohort",
    "sample_size": 645,
    "duration_days": 54
  },
  "results": [
    {
      "metric": "safety",
      "baseline": 79.64,
      "endpoint": 26.86,
      "p_value": 0.2863
    },
    {
      "metric": "safety",
      "baseline": 55.57,
      "endpoint": 59.78,
      "p_value": 0.1705
    },
    {
      "metric": "efficacy",
      "baseline": 30.69,
      "endpoint": 27.4,
      "p_value": 0.1116
    },
    {
      "metric": "efficacy",
      "baseline": 32.07,
      "endpoint": 35.79,
      "p_value": 0.1946
    }
  ],
  "conclusion": "non-significant"
}


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

[User] Produce a YAML document for a social media post.

[Assistant]
Approach:
1. Task: Create social media post in YAML
2. Complexity: medium - 5-8 fields, 2-3 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:
post_id: POST-69367106
platform: twitter
user_id: 7643b70d-1c60-436f-974e-7bc6cee5e032
username: gordonalexander
content: 'See personal couple road president most next. Laugh teach lawyer character
  work present.

  Page give education middle. Couple save view media instead police guy. Enough test
  notice capital size.'
timestamp: '2026-01-07T13:51:25.991400'
hashtags:
- '#PM'
- '#stage'
- '#government'
engagement:
  likes: 1911
  shares: 761
  comments: 62


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

[User]
Convert the following CSV to XML:
code,course_id,credits,grading_final,grading_homework,grading_midterm,instructor,schedule,term,title
FAH301,CRS-2063,4,40,30,30,Aaron Bailey,"[{""week"": 1, ""topic"": ""health""}, {""week"": 2, ""topic"": ""buy""}, {""week"": 3, ""topic"": ""conference""}, {""",Fall 2023,Ameliorated zero administration productivity 101
WGM196,CRS-9159,3,40,30,30,Kim Kelley,"[{""week"": 1, ""topic"": ""so""}, {""week"": 2, ""topic"": ""claim""}, {""week"": 3, ""topic"": ""happen""}, {""week"":",Fall 2024,Configurable coherent strategy 101
SKE322,CRS-7814,4,40,30,30,James Bell,"[{""week"": 1, ""topic"": ""base""}, {""week"": 2, ""topic"": ""usually""}, {""week"": 3, ""topic"": ""money""}, {""wee",Spring 2023,Streamlined multi-tasking function 101
DCJ343,CRS-1918,4,40,30,30,Katherine Pugh,"[{""week"": 1, ""topic"": ""garden""}, {""week"": 2, ""topic"": ""debate""}, {""week"": 3, ""topic"": ""pressure""}, {",Spring 2021,Open-architected national flexibility 101
EUN261,CRS-4802,4,40,30,30,Shane Chandler,"[{""week"": 1, ""topic"": ""job""}, {""week"": 2, ""topic"": ""community""}, {""week"": 3, ""topic"": ""necessary""}, ",Fall 2024,Future-proofed discrete monitoring 101

[Assistant]
Approach:
1. Task: Convert course syllabus from CSV 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"?>
<course_syllabus>
<course_id>CRS-2063</course_id>
FAH301
<title>Ameliorated zero administration productivity 101</title>
<instructor>Aaron Bailey</instructor>
<credits>4</credits>
<term>Fall 2023</term>
<schedule>
<week>1</week>
<topic>health</topic>
</schedule>
<schedule>
<week>2</week>
<topic>buy</topic>
</schedule>
<schedule>
<week>3</week>
<topic>conference</topic>
</schedule>
<schedule>
<week>4</week>
<topic>late</topic>
</schedule>
<schedule>
<week>5</week>
<topic>fear</topic>
</schedule>
<schedule>
<week>6</week>
<topic>ability</topic>
</schedule>
<schedule>
<week>7</week>
<topic>control</topic>
</schedule>
<schedule>
<week>8</week>
<topic>choose</topic>
</schedule>
<schedule>
<week>9</week>
<topic>measure</topic>
</schedule>
<schedule>
<week>10</week>
<topic>social</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]
Transform this JSON data into TOML format:
{
  "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"
}

[Assistant]
Approach:
1. Task: Convert student assessment from JSON to 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. Transform values to match the target format specifications.

Output:
grade = "C"
date = "2026-01-01"
[[scores]]
question = 1
points_earned = 8
points_possible = 10

[[scores]]
question = 2
points_earned = 4
points_possible = 10

[[scores]]
question = 3
points_earned = 1
points_possible = 10

[[scores]]
question = 4
points_earned = 4
points_possible = 10

[[scores]]
question = 5
points_earned = 8
points_possible = 10

[[scores]]
question = 6
points_earned = 10
points_possible = 10

[[scores]]
question = 7
points_earned = 4
points_possible = 10

[[scores]]
question = 8
points_earned = 0
points_possible = 10


[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"?>
<news_article>
<article_id>ART-1748125</article_id>
<headline>Customizable leadingedge structure</headline>
<author>Sandra Bennett</author>
<published>2026-01-03T22:52:42.741679</published>

Sports

<content>Majority meeting sound have week public pass. Major food relate spend seven.
Indeed run fund.
Federal right stuff difficult alone miss. Stuff rest model job deep knowledge pull force. Too follow face husband every. Hit important agreement rather card west want.</content>
<tags>subject</tags>
<tags>attention</tags>
<tags>class</tags>
<tags>campaign</tags>
<tags>second</tags>
<views>63827</views>
<shares>2505</shares>
</news_article>

[Assistant]
Approach:
1. Task: Convert news article 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:
{
  "article_id": "ART-1748125",
  "headline": "Customizable leadingedge structure",
  "author": "Sandra Bennett",
  "published": "2026-01-03T22:52:42.741679",
  "section": "Sports",
  "content": "Majority meeting sound have week public pass. Major food relate spend seven.\nIndeed run fund.\nFederal right stuff difficult alone miss. Stuff rest model job deep knowledge pull force. Too follow face husband every. Hit important agreement rather card west want.",
  "tags": [
    "subject",
    "attention",
    "class",
    "campaign",
    "second"
  ],
  "views": 63827,
  "shares": 2505
}


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

[User] Output sales analytics as CSV.

[Assistant]
Approach:
1. Task: Create sales analytics 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,channels,citations,funding_source,keywords,paper_id,period,publication_doi,publication_venue,publication_year,title,top_products,total_revenue,units_sold
,,"[{""name"": ""retail"", ""revenue"": 2051641, ""growth"": 15.93}, {""name"": ""wholesale"", ""revenue"": 4340607, ",,,,,September 2024,,,,,"[{""sku"": ""SKU-7798"", ""sales"": 367269}, {""sku"": ""SKU-2105"", ""sales"": 291023}, {""sku"": ""SKU-5730"", ""sa",6726526,45392
Bag pull with paper quickly able. Where fill institution property able official.,"[{""name"": ""Jennifer Cunningham"", ""affiliation"": ""Ray Inc"", ""email"": ""woodsmichael@example.com""}, {""n",,107,None,"[""conference"", ""Mrs"", ""accept"", ""apply"", ""close""]",arXiv:2024.86027,,10.7937/DCTR,Nature,2021,Stand-alone next generation moratorium,,,
Reflect attention magazine plan attention performance. Interest pretty dark assume.,"[{""name"": ""Michelle Odom"", ""affiliation"": ""Deleon Group"", ""email"": ""sgreene@example.net""}, {""name"": ",,218,"Hamilton, Christian and Bartlett","[""sign"", ""war"", ""stage""]",arXiv:2021.34111,,10.2475/bBYg,Nature,2022,Open-architected incremental circuit,,,
"Center away water left technology all. Find foreign strong table. Big rise cultural before.
Its crea","[{""name"": ""Luis Flores"", ""affiliation"": ""Faulkner LLC"", ""email"": ""crystalwashington@example.org""}, {",,174,Ponce Group,"[""summer"", ""room"", ""stop""]",arXiv:2023.11664,,10.7325/vSim,Science,2021,De-engineered solution-oriented Graphic Interface,,,


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

[User]
Convert the following JSON to XML:
{
  "post_id": "POST-58883169",
  "user_id": "9fc1586a-703b-4459-a18b-2f5e0582ab64",
  "username": "alexandra57"
}

[Assistant]
Approach:
1. Task: Convert social media post from JSON to 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. Transform values to match the target format specifications.

Output:
<?xml version="1.0" encoding="UTF-8"?>
<social_media_post>
<post_id>POST-58883169</post_id>
<user_id>9fc1586a-703b-4459-a18b-2f5e0582ab64</user_id>
<username>alexandra57</username>
</social_media_post>


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

[User] Output social media post as TOML.

[Assistant]
Approach:
1. Task: Create social media post 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:
post_id = "POST-86945311"
platform = "facebook"
user_id = "b9da037c-f6cd-4ced-8c95-ca7562cf6118"
username = "martinsteven"
content = "Forget late prevent year cold able arrive. Few possible himself sing community. Activity campaign sure south. Chance on none line best magazine education."
timestamp = "2026-01-07T13:51:26.810240"
hashtags = [ "#drop", "#consider", "#nature", "#all",]

[engagement]
likes = 3344
shares = 900
comments = 482


[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"?>
<error_log>
<message>Baby inside high our should character study quickly.</message>
<stack_trace>at standard.py:486</stack_trace>
<stack_trace>at memory.py:53</stack_trace>
<stack_trace>at team.py:342</stack_trace>
<context>
<user_id>b89e754b-fd03-47c7-9600-09a7cb6d3517</user_id>
<request_id>0aea7b7e-f431-4209-a4db-008320d27043</request_id>
</context>
<timestamp>2026-01-07T13:51:25.507604</timestamp>
</error_log>

[Assistant]
Approach:
1. Task: Convert error log 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:
{
  "message": "Baby inside high our should character study quickly.",
  "stack_trace": [
    "at standard.py:486",
    "at memory.py:53",
    "at team.py:342"
  ],
  "context": {
    "user_id": "b89e754b-fd03-47c7-9600-09a7cb6d3517",
    "request_id": "0aea7b7e-f431-4209-a4db-008320d27043"
  },
  "timestamp": "2026-01-07T13:51:25.507604"
}


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

[User]
Reformat the data below from TOML to JSON:
subtotal = 1655.93
tax = 19.12
total = 1424.63
[[items]]
sku = "SKU-62708"
qty = 3
price = 121.39

[Assistant]
Approach:
1. Task: Convert transaction record from TOML 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:
{
  "subtotal": 1655.93,
  "items": [
    {
      "sku": "SKU-62708",
      "qty": 3,
      "price": 121.39
    }
  ],
  "tax": 19.12,
  "total": 1424.63
}


[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: 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-143990</contract_id>
<parties>
<name>Brady Inc</name>
<role>party_a</role>
</parties>
<parties>
<name>Gonzalez, Coleman and Sanchez</name>
<role>party_b</role>
</parties>
<effective_date>2026-01-02</effective_date>
<term_months>32</term_months>
<value>452000</value>
<status>active</status>
</contract>


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

[User] Produce a CSV document for a sales analytics.

[Assistant]
Approach:
1. Task: Create sales analytics 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:
abstract,authors,channels,citations,funding_source,keywords,paper_id,period,publication_doi,publication_venue,publication_year,title,top_products,total_revenue,units_sold
,,"[{""name"": ""wholesale"", ""revenue"": 2739604, ""growth"": -0.52}, {""name"": ""online"", ""revenue"": 247982, """,,,,,January 2024,,,,,"[{""sku"": ""SKU-7268"", ""sales"": 409348}, {""sku"": ""SKU-4030"", ""sales"": 70087}, {""sku"": ""SKU-4380"", ""sal",3091656,63856
Financial stage again some every store reach current. Know see important current exist. Continue per,"[{""name"": ""Tracy Wright"", ""affiliation"": ""Massey PLC"", ""email"": ""rthomas@example.org""}, {""name"": ""Ja",,39,Johnson-Lane,"[""lawyer"", ""nation"", ""strategy"", ""station""]",arXiv:2021.66961,,10.5482/CTzk,Nature,2023,Ameliorated fault-tolerant archive,,,
Enjoy too door born short region. Enter treatment minute fish pattern sense. Natural role front kind,"[{""name"": ""Jerry Griffin"", ""affiliation"": ""Johnston and Sons"", ""email"": ""vparks@example.net""}, {""nam",,250,"Hartman, Hill and Castillo","[""cover"", ""catch"", ""article"", ""the"", ""read""]",arXiv:2020.54486,,10.1743/bHmc,Cell,2021,Vision-oriented optimizing intranet,,,
Large American majority seek necessary. Would hundred cultural recently leader hand control. Any dre,"[{""name"": ""Samantha Robinson"", ""affiliation"": ""Roach-Mcdonald"", ""email"": ""idecker@example.com""}, {""n",,112,None,"[""room"", ""break"", ""what""]",arXiv:2023.36369,,10.4817/kALF,Cell,2021,Diverse homogeneous standardization,,,


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

[User] Output financial report as YAML.

[Assistant]
Approach:
1. Task: Create financial report 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:
company: Ortega-Owens
ticker: YLLB
quarter: Q3 2022
revenue: 37598920
expenses: 44591506
net_income: 3197580
eps: 1.51
metrics:
  profit_margin: 5.54
  roe: 6.32


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

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

[Assistant]
Approach:
1. Task: Create course syllabus 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:
course_id = "CRS-3741"
code = "XMJ312"
title = "Managed incremental focus group 101"
instructor = "Rachel Diaz"
credits = 4
term = "Fall 2021"
[[schedule]]
week = 1
topic = "body"

[[schedule]]
week = 2
topic = "rather"

[[schedule]]
week = 3
topic = "song"

[[schedule]]
week = 4
topic = "child"

[[schedule]]
week = 5
topic = "born"

[[schedule]]
week = 6
topic = "beyond"

[[schedule]]
week = 7
topic = "there"

[grading]
homework = 30
midterm = 30
final = 40


[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-299234",
  "parties": [
    {
      "name": "Murphy, Hawkins and Mckenzie",
      "role": "party_a"
    },
    {
      "name": "Collins-Miller",
      "role": "party_b"
    }
  ],
  "effective_date": "2026-01-06",
  "term_months": 46,
  "value": 506357,
  "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-299234</contract_id>
<parties>
<name>Murphy, Hawkins and Mckenzie</name>
<role>party_a</role>
</parties>
<parties>
<name>Collins-Miller</name>
<role>party_b</role>
</parties>
<effective_date>2026-01-06</effective_date>
<term_months>46</term_months>
<value>506357</value>
<status>pending</status>
</contract>


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

[User] Create a CSV representation of sales analytics.

[Assistant]
Approach:
1. Task: Create sales analytics 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,channels,citations,funding_source,keywords,paper_id,period,publication_doi,publication_venue,publication_year,title,top_products,total_revenue,units_sold
,,"[{""name"": ""wholesale"", ""revenue"": 3617590, ""growth"": 20.48}, {""name"": ""online"", ""revenue"": 654207, """,,,,,April 2020,,,,,"[{""sku"": ""SKU-4328"", ""sales"": 466200}, {""sku"": ""SKU-2589"", ""sales"": 244105}, {""sku"": ""SKU-7725"", ""sa",1914989,47758
Memory card policy each cell song anyone. When thousand service step require wonder.,"[{""name"": ""Krystal Dunn"", ""affiliation"": ""Howard-Hall"", ""email"": ""hooversarah@example.net""}, {""name""",,52,None,"[""rock"", ""movement"", ""health"", ""language""]",arXiv:2021.96547,,10.8169/sVCB,Cell,2023,Devolved incremental initiative,,,
"Item process seven politics rate. Ever sign many.
Painting let own reduce. Least call or city. Rule ","[{""name"": ""Richard Moss"", ""affiliation"": ""Martin-Smith"", ""email"": ""amberthomas@example.org""}, {""name",,283,None,"[""her"", ""edge"", ""away""]",arXiv:2020.78162,,10.4210/Zwmx,Cell,2022,Inverse background encoding,,,


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

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

[Assistant]
Approach:
1. Task: Create student assessment 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"?>
<student_assessment>
<assessment_id>ASMT-948175</assessment_id>
<student_id>STU-160858</student_id>
<course_id>CRS-5368</course_id>
<type>assignment</type>
<date>2026-01-03</date>
<scores>
<question>1</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>3</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>5</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>3</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>9</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>89</total_score>
<percentage>96.29</percentage>
<grade>B</grade>
</student_assessment>


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

[User] Output error log as XML.

[Assistant]
Approach:
1. Task: Create error log 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"?>
<error_log>
<error_id>fd278ff8-fdfc-4b1d-81ec-31cf5ce70502</error_id>
<timestamp>2026-01-07T13:51:26.554266</timestamp>
<level>ERROR</level>
<service>heartService</service>
<message>Attack candidate in give wish tree.</message>
<stack_trace>at thousand.py:354</stack_trace>
<stack_trace>at forget.py:20</stack_trace>
<stack_trace>at consider.py:392</stack_trace>
<context>
<user_id>d753ac0c-8931-4c37-8bd5-01413aaaba41</user_id>
<request_id>b35b2bd7-dc59-4d80-ba5d-dc21fa7f0bf7</request_id>
</context>
</error_log>


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

[User] Output clinical note as YAML.

[Assistant]
Approach:
1. Task: Create clinical note in YAML
2. Complexity: medium - 5-8 fields, 2-3 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-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


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

[User]
Reformat the data below from TOML to XML:
author = "Jenna Bryant"
tags = [ "most", "off", "shoulder",]
headline = "Secured composite leverage"
published = "2026-01-04T22:19:16.750289"

[Assistant]
Approach:
1. Task: Convert news article from TOML to 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. Transform values to match the target format specifications.

Output:
<?xml version="1.0" encoding="UTF-8"?>
<news_article>
<author>Jenna Bryant</author>
<tags>most</tags>
<tags>off</tags>
<tags>shoulder</tags>
<headline>Secured composite leverage</headline>
<published>2026-01-04T22:19:16.750289</published>
</news_article>


[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"?>
<prescription>
<date>2026-01-04</date>
<medications>
<name>Atorvastatin</name>
<dosage>20mg</dosage>
<frequency>TID</frequency>
<quantity>60</quantity>
</medications>
<medications>
<name>Metformin</name>
<dosage>20mg</dosage>
<frequency>daily</frequency>
<quantity>60</quantity>
</medications>
<medications>
<name>Atorvastatin</name>
<dosage>5mg</dosage>
<frequency>TID</frequency>
<quantity>60</quantity>
</medications>
<patient_mrn>MRN-588828</patient_mrn>
</prescription>

[Assistant]
Approach:
1. Task: Convert prescription 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:
{
  "date": "2026-01-04",
  "medications": [
    {
      "name": "Atorvastatin",
      "dosage": "20mg",
      "frequency": "TID",
      "quantity": 60
    },
    {
      "name": "Metformin",
      "dosage": "20mg",
      "frequency": "daily",
      "quantity": 60
    },
    {
      "name": "Atorvastatin",
      "dosage": "5mg",
      "frequency": "TID",
      "quantity": 60
    }
  ],
  "patient_mrn": "MRN-588828"
}


[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"?>
<customer_review>
<review_id>REV-9982202</review_id>
<product_id>PROD-452864</product_id>
<user_id>015289de-7f3e-45e2-b1d0-7fe22aff92a9</user_id>
<rating>3</rating>
<title>Example center fill free.</title>
<content>North describe old attention usually third. Important wish security ago somebody remain everyone modern. Significant chair place throughout study administration American.</content>
<date>2026-01-04</date>
<verified_purchase>False</verified_purchase>
<helpful_votes>34</helpful_votes>
</customer_review>

[Assistant]
Approach:
1. Task: Convert customer review 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:
{
  "review_id": "REV-9982202",
  "product_id": "PROD-452864",
  "user_id": "015289de-7f3e-45e2-b1d0-7fe22aff92a9",
  "rating": 3,
  "title": "Example center fill free.",
  "content": "North describe old attention usually third. Important wish security ago somebody remain everyone modern. Significant chair place throughout study administration American.",
  "date": "2026-01-04",
  "verified_purchase": false,
  "helpful_votes": 34
}


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

[User] Create a TOML representation of course syllabus.

[Assistant]
Approach:
1. Task: Create course syllabus 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:
course_id = "CRS-1689"
code = "NZW166"
title = "Operative modular system engine 101"
instructor = "David Chen"
credits = 4
term = "Fall 2021"
[[schedule]]
week = 1
topic = "in"

[[schedule]]
week = 2
topic = "summer"

[[schedule]]
week = 3
topic = "unit"

[[schedule]]
week = 4
topic = "wind"

[[schedule]]
week = 5
topic = "act"

[[schedule]]
week = 6
topic = "itself"

[[schedule]]
week = 7
topic = "would"

[[schedule]]
week = 8
topic = "itself"

[[schedule]]
week = 9
topic = "tell"

[[schedule]]
week = 10
topic = "money"

[[schedule]]
week = 11
topic = "long"

[grading]
homework = 30
midterm = 30
final = 40


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

[User]
Convert the following JSON to XML:
{
  "experiment_id": "EXP-506156",
  "title": "Effect of window on soldier",
  "methodology": {
    "design": "observational",
    "sample_size": 884,
    "duration_days": 87
  },
  "results": [
    {
      "metric": "safety",
      "baseline": 32.86,
      "endpoint": 81.82,
      "p_value": 0.3265
    },
    {
      "metric": "efficacy",
      "baseline": 88.84,
      "endpoint": 10.2,
      "p_value": 0.448
    },
    {
      "metric": "safety",
      "baseline": 27.68,
      "endpoint": 60.55,
      "p_value": 0.1062
    },
    {
      "metric": "safety",
      "baseline": 51.8,
      "endpoint": 89.23,
      "p_value": 0.4543
    }
  ],
  "conclusion": "significant"
}

[Assistant]
Approach:
1. Task: Convert experiment result 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"?>
<experiment_result>
<experiment_id>EXP-506156</experiment_id>
<title>Effect of window on soldier</title>
<methodology>
<design>observational</design>
<sample_size>884</sample_size>
<duration_days>87</duration_days>
</methodology>
<results>
<metric>safety</metric>
<baseline>32.86</baseline>
<endpoint>81.82</endpoint>
<p_value>0.3265</p_value>
</results>
<results>
<metric>efficacy</metric>
<baseline>88.84</baseline>
<endpoint>10.2</endpoint>
<p_value>0.448</p_value>
</results>
<results>
<metric>safety</metric>
<baseline>27.68</baseline>
<endpoint>60.55</endpoint>
<p_value>0.1062</p_value>
</results>
<results>
<metric>safety</metric>
<baseline>51.8</baseline>
<endpoint>89.23</endpoint>
<p_value>0.4543</p_value>
</results>
<conclusion>significant</conclusion>
</experiment_result>


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

[User] Produce a XML document for a transaction record.

[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>
<subtotal>205.31</subtotal>
<payment_method>apple_pay</payment_method>
<total>1732.06</total>
</transaction_record>


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

[User] Generate student assessment data in TOML format.

[Assistant]
Approach:
1. Task: Create student assessment 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:
assessment_id = "ASMT-879460"
student_id = "STU-948921"
course_id = "CRS-8763"
type = "quiz"
date = "2026-01-03"
total_score = 83
percentage = 96.07
grade = "B"
[[scores]]
question = 1
points_earned = 1
points_possible = 10

[[scores]]
question = 2
points_earned = 4
points_possible = 10

[[scores]]
question = 3
points_earned = 7
points_possible = 10

[[scores]]
question = 4
points_earned = 3
points_possible = 10

[[scores]]
question = 5
points_earned = 5
points_possible = 10

[[scores]]
question = 6
points_earned = 2
points_possible = 10

[[scores]]
question = 7
points_earned = 6
points_possible = 10

[[scores]]
question = 8
points_earned = 9
points_possible = 10


[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:
{
  "course_id": "CRS-7514",
  "code": "NOO384",
  "title": "Fundamental encompassing database 101",
  "instructor": "Lori Martinez",
  "credits": 4,
  "term": "Fall 2024",
  "schedule": [
    {
      "week": 1,
      "topic": "bar"
    },
    {
      "week": 2,
      "topic": "population"
    },
    {
      "week": 3,
      "topic": "thus"
    },
    {
      "week": 4,
      "topic": "manage"
    },
    {
      "week": 5,
      "topic": "purpose"
    },
    {
      "week": 6,
      "topic": "look"
    },
    {
      "week": 7,
      "topic": "nothing"
    },
    {
      "week": 8,
      "topic": "remember"
    },
    {
      "week": 9,
      "topic": "song"
    },
    {
      "week": 10,
      "topic": "ahead"
    },
    {
      "week": 11,
      "topic": "pass"
    }
  ],
  "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-7514</course_id>
NOO384
<title>Fundamental encompassing database 101</title>
<instructor>Lori Martinez</instructor>
<credits>4</credits>
<term>Fall 2024</term>
<schedule>
<week>1</week>
<topic>bar</topic>
</schedule>
<schedule>
<week>2</week>
<topic>population</topic>
</schedule>
<schedule>
<week>3</week>
<topic>thus</topic>
</schedule>
<schedule>
<week>4</week>
<topic>manage</topic>
</schedule>
<schedule>
<week>5</week>
<topic>purpose</topic>
</schedule>
<schedule>
<week>6</week>
<topic>look</topic>
</schedule>
<schedule>
<week>7</week>
<topic>nothing</topic>
</schedule>
<schedule>
<week>8</week>
<topic>remember</topic>
</schedule>
<schedule>
<week>9</week>
<topic>song</topic>
</schedule>
<schedule>
<week>10</week>
<topic>ahead</topic>
</schedule>
<schedule>
<week>11</week>
<topic>pass</topic>
</schedule>
<grading>
<homework>30</homework>
<midterm>30</midterm>
<final>40</final>
</grading>
</course_syllabus>


[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:
{
  "note_id": "CN-4441974",
  "patient": {
    "mrn": "MRN-925906",
    "age": 60,
    "gender": "F"
  },
  "encounter_date": "2026-01-02",
  "chief_complaint": "headache",
  "vitals": {
    "bp": "154/95",
    "hr": 108,
    "temp_f": 97.8
  },
  "assessment": [
    {
      "problem": "diabetes",
      "icd10": "J60"
    },
    {
      "problem": "hypertension",
      "icd10": "I21"
    },
    {
      "problem": "diabetes",
      "icd10": "K16"
    }
  ]
}

[Assistant]
Approach:
1. Task: Convert clinical note 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"?>
<clinical_note>
<note_id>CN-4441974</note_id>
<patient>
<mrn>MRN-925906</mrn>
<age>60</age>
<gender>F</gender>
</patient>
<encounter_date>2026-01-02</encounter_date>
<chief_complaint>headache</chief_complaint>
<vitals>
<bp>154/95</bp>

108

<temp_f>97.8</temp_f>
</vitals>
<assessment>
<problem>diabetes</problem>
<icd10>J60</icd10>
</assessment>
<assessment>
<problem>hypertension</problem>
<icd10>I21</icd10>
</assessment>
<assessment>
<problem>diabetes</problem>
<icd10>K16</icd10>
</assessment>
</clinical_note>


[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"?>
<student_assessment>
<assessment_id>ASMT-879460</assessment_id>
<student_id>STU-948921</student_id>
<course_id>CRS-8763</course_id>
<type>quiz</type>
<date>2026-01-03</date>
<scores>
<question>1</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>4</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>3</question>
<points_earned>7</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>3</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>5</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>6</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>83</total_score>
<percentage>96.07</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-879460",
  "student_id": "STU-948921",
  "course_id": "CRS-8763",
  "type": "quiz",
  "date": "2026-01-03",
  "scores": [
    {
      "question": 1,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 3,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 5,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 6,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 9,
      "points_possible": 10
    }
  ],
  "total_score": 83,
  "percentage": 96.07,
  "grade": "B"
}


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

[User] Output product listing as CSV.

[Assistant]
Approach:
1. Task: Create product listing 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:
category,currency,is_available,name,price,product_id,rating,reviews,specs_dimensions,specs_weight_kg,stock
electronics,USD,True,Cross-platform client-server attitude,875.12,PROD-308726,1.18,705,78x81x41cm,37.34,161
electronics,USD,True,Optional 6thgeneration database,49.59,PROD-560709,2.49,504,80x90x48cm,28.59,652
books,USD,True,Quality-focused static flexibility,839.79,PROD-850153,2.25,163,47x46x71cm,9.98,547
clothing,USD,True,Distributed clear-thinking Graphical User Interface,178.27,PROD-529951,4.22,331,78x75x35cm,17.79,58


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

[User] Generate news article data in CSV format.

[Assistant]
Approach:
1. Task: Create news article 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:
article_id,author,content,headline,published,section,shares,tags,views
ART-9801838,Jeffrey Gordon,"Partner energy whose simply half because long. Pattern include thousand care four against.
Scene cen",Multi-lateral didactic encryption,2026-01-04T05:36:27.140251,Business,4423,"[""word"", ""public"", ""near""]",26731
ART-3928807,Dustin Lynch,"Shoulder not report see edge social. Teach yes rest easy decade.
Reach threat feel reflect table dif",Balanced composite circuit,2026-01-01T03:14:17.265249,Business,2180,"[""air"", ""risk"", ""cause""]",42066
ART-4834512,Susan Anderson,"East opportunity way field some. Hard well box nor. Organization spend test night Republican.
Fine D",Robust fresh-thinking capability,2026-01-02T21:15:55.002860,Business,4671,"[""indeed"", ""pattern"", ""least"", ""particular""]",73576
ART-1189164,Beth Nguyen,"Safe family seek door. Place realize mean.
Face every girl turn particular benefit. Through most tow",Progressive neutral artificial intelligence,2026-01-05T16:13:36.304830,Sports,3498,"[""indeed"", ""test"", ""forget"", ""each"", ""apply""]",38510
ART-3890269,Destiny Maxwell,Since human go drop blood prove thousand. Book serve green force half manager. Young respond availab,Down-sized modular collaboration,2026-01-05T13:46:37.070553,Tech,2432,"[""rise"", ""tonight"", ""focus"", ""its""]",88843


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

[User]
Reformat the data below from YAML to JSON:
product_id: PROD-469887
is_available: true
reviews: 612
name: Networked executive capability
currency: USD

[Assistant]
Approach:
1. Task: Convert product listing from YAML 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:
{
  "product_id": "PROD-469887",
  "is_available": true,
  "reviews": 612,
  "name": "Networked executive capability",
  "currency": "USD"
}


[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"?>
<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>

[Assistant]
Approach:
1. Task: Convert transaction record 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:
{
  "items": [
    {
      "sku": "SKU-89816",
      "qty": 1,
      "price": 437.44
    },
    {
      "sku": "SKU-65650",
      "qty": 1,
      "price": 455.72
    },
    {
      "sku": "SKU-98183",
      "qty": 3,
      "price": 337.62
    }
  ],
  "total": 1900.4,
  "payment_method": "apple_pay"
}


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

[User]
Reformat the data below from JSON to YAML:
{
  "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 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:
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


[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-33796851",
  "platform": "instagram",
  "user_id": "aa32cdd3-72c6-4e38-bd5e-ff3918321d73",
  "username": "qtownsend",
  "content": "List floor whatever fly. Play represent five my. Stuff area push other begin team. Wind leg require represent.",
  "timestamp": "2026-01-07T13:51:26.038556",
  "hashtags": [
    "#study",
    "#able",
    "#week"
  ],
  "engagement": {
    "likes": 3006,
    "shares": 53,
    "comments": 61
  }
}

[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-33796851</post_id>
<platform>instagram</platform>
<user_id>aa32cdd3-72c6-4e38-bd5e-ff3918321d73</user_id>
<username>qtownsend</username>
<content>List floor whatever fly. Play represent five my. Stuff area push other begin team. Wind leg require represent.</content>
<timestamp>2026-01-07T13:51:26.038556</timestamp>
<hashtags>#study</hashtags>
<hashtags>#able</hashtags>
<hashtags>#week</hashtags>
<engagement>
<likes>3006</likes>
<shares>53</shares>
<comments>61</comments>
</engagement>
</social_media_post>


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

[User] Create a XML representation of transaction record.

[Assistant]
Approach:
1. Task: Create transaction record 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"?>
<transaction_record>
<txn_id>TXN-30876983</txn_id>
<customer_id>b5aca191-66fe-49e0-85ce-2d363d5ef454</customer_id>
<timestamp>2026-01-07T13:51:26.163076</timestamp>
<items>
<sku>SKU-56664</sku>
<qty>2</qty>
<price>285.83</price>
</items>
<items>
<sku>SKU-25305</sku>
<qty>1</qty>
<price>45.15</price>
</items>
<items>
<sku>SKU-78820</sku>
<qty>4</qty>
<price>47.49</price>
</items>
<subtotal>199.93</subtotal>
<tax>118.13</tax>
<total>913.78</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]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<experiment_result>
<experiment_id>EXP-574681</experiment_id>
<title>Effect of anyone on society</title>
<methodology>
<design>cohort</design>
<sample_size>560</sample_size>
<duration_days>320</duration_days>
</methodology>
<results>
<metric>efficacy</metric>
<baseline>50.77</baseline>
<endpoint>70.83</endpoint>
<p_value>0.3046</p_value>
</results>
<results>
<metric>efficacy</metric>
<baseline>96.52</baseline>
<endpoint>82.25</endpoint>
<p_value>0.0326</p_value>
</results>
<results>
<metric>safety</metric>
<baseline>43.38</baseline>
<endpoint>72.88</endpoint>
<p_value>0.2787</p_value>
</results>
<results>
<metric>safety</metric>
<baseline>17.71</baseline>
<endpoint>95.37</endpoint>
<p_value>0.4542</p_value>
</results>
<conclusion>non-significant</conclusion>
</experiment_result>

[Assistant]
Approach:
1. Task: Convert experiment result 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:
{
  "experiment_id": "EXP-574681",
  "title": "Effect of anyone on society",
  "methodology": {
    "design": "cohort",
    "sample_size": 560,
    "duration_days": 320
  },
  "results": [
    {
      "metric": "efficacy",
      "baseline": 50.77,
      "endpoint": 70.83,
      "p_value": 0.3046
    },
    {
      "metric": "efficacy",
      "baseline": 96.52,
      "endpoint": 82.25,
      "p_value": 0.0326
    },
    {
      "metric": "safety",
      "baseline": 43.38,
      "endpoint": 72.88,
      "p_value": 0.2787
    },
    {
      "metric": "safety",
      "baseline": 17.71,
      "endpoint": 95.37,
      "p_value": 0.4542
    }
  ],
  "conclusion": "non-significant"
}


[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: 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:
{
  "error_id": "ff91c212-6cce-4ac2-978d-0740381882de",
  "timestamp": "2026-01-07T13:51:27.679071",
  "level": "WARNING",
  "service": "drawService",
  "message": "Support red list product forget cut speak.",
  "stack_trace": [
    "at girl.py:186",
    "at hold.py:186"
  ],
  "context": {
    "user_id": "473e683b-291e-461f-b848-d224b7dcbd8b",
    "request_id": "454a35ad-23ee-42a8-9d57-dbf5cedbef74"
  }
}


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

[User]
Convert the following JSON to XML:
{
  "company": "Hardy-Nguyen",
  "ticker": "ZAMS",
  "quarter": "Q3 2024",
  "revenue": 23201336,
  "expenses": 30350118,
  "net_income": 14673850,
  "eps": 3.22,
  "metrics": {
    "profit_margin": 18.82,
    "roe": 21.21
  }
}

[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>Hardy-Nguyen</company>
<ticker>ZAMS</ticker>
<quarter>Q3 2024</quarter>
<revenue>23201336</revenue>
<expenses>30350118</expenses>
<net_income>14673850</net_income>
<eps>3.22</eps>
<metrics>
<profit_margin>18.82</profit_margin>
<roe>21.21</roe>
</metrics>
</financial_report>


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

[User] Generate clinical note data in XML format.

[Assistant]
Approach:
1. Task: Create clinical note 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"?>
<clinical_note>
<note_id>CN-5751204</note_id>
<patient>
<mrn>MRN-566004</mrn>
<age>47</age>
<gender>M</gender>
</patient>
<encounter_date>2026-01-05</encounter_date>
<chief_complaint>headache</chief_complaint>
<vitals>
<bp>160/96</bp>

75

<temp_f>102.4</temp_f>
</vitals>
<assessment>
<problem>diabetes</problem>
<icd10>I93</icd10>
</assessment>
</clinical_note>


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

[User] Generate course syllabus data in YAML format.

[Assistant]
Approach:
1. Task: Create course syllabus in YAML
2. Complexity: medium - 5-8 fields, 2-3 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:
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 XML format. Think step-by-step, then generate syntactically perfect XML.

[User]
Convert the following JSON to XML:
{
  "course_id": "CRS-5570",
  "code": "ZMD258",
  "title": "Mandatory leadingedge superstructure 101",
  "instructor": "Gregory Dunn",
  "credits": 3,
  "term": "Spring 2021",
  "schedule": [
    {
      "week": 1,
      "topic": "guess"
    },
    {
      "week": 2,
      "topic": "forget"
    },
    {
      "week": 3,
      "topic": "technology"
    },
    {
      "week": 4,
      "topic": "nothing"
    },
    {
      "week": 5,
      "topic": "sea"
    },
    {
      "week": 6,
      "topic": "other"
    },
    {
      "week": 7,
      "topic": "new"
    },
    {
      "week": 8,
      "topic": "report"
    },
    {
      "week": 9,
      "topic": "guy"
    },
    {
      "week": 10,
      "topic": "can"
    },
    {
      "week": 11,
      "topic": "inside"
    }
  ],
  "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-5570</course_id>
ZMD258
<title>Mandatory leadingedge superstructure 101</title>
<instructor>Gregory Dunn</instructor>
<credits>3</credits>
<term>Spring 2021</term>
<schedule>
<week>1</week>
<topic>guess</topic>
</schedule>
<schedule>
<week>2</week>
<topic>forget</topic>
</schedule>
<schedule>
<week>3</week>
<topic>technology</topic>
</schedule>
<schedule>
<week>4</week>
<topic>nothing</topic>
</schedule>
<schedule>
<week>5</week>
<topic>sea</topic>
</schedule>
<schedule>
<week>6</week>
<topic>other</topic>
</schedule>
<schedule>
<week>7</week>
<topic>new</topic>
</schedule>
<schedule>
<week>8</week>
<topic>report</topic>
</schedule>
<schedule>
<week>9</week>
<topic>guy</topic>
</schedule>
<schedule>
<week>10</week>
<topic>can</topic>
</schedule>
<schedule>
<week>11</week>
<topic>inside</topic>
</schedule>
<grading>
<homework>30</homework>
<midterm>30</midterm>
<final>40</final>
</grading>
</course_syllabus>


[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"?>
<news_article>
<article_id>ART-8172649</article_id>
<headline>Triple-buffered responsive model</headline>
<author>Rachel Clark</author>
<published>2026-01-03T00:35:22.551008</published>

Business

<content>Pattern capital time compare include night top. Large than important morning.
Card authority protect present return while middle. Development miss write five.</content>
<tags>consider</tags>
<tags>whatever</tags>
<tags>part</tags>
<tags>however</tags>
<tags>special</tags>
<views>49705</views>
<shares>392</shares>
</news_article>

[Assistant]
Approach:
1. Task: Convert news article 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:
{
  "article_id": "ART-8172649",
  "headline": "Triple-buffered responsive model",
  "author": "Rachel Clark",
  "published": "2026-01-03T00:35:22.551008",
  "section": "Business",
  "content": "Pattern capital time compare include night top. Large than important morning.\nCard authority protect present return while middle. Development miss write five.",
  "tags": [
    "consider",
    "whatever",
    "part",
    "however",
    "special"
  ],
  "views": 49705,
  "shares": 392
}


[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>
<review_id>REV-9723622</review_id>
<product_id>PROD-853148</product_id>
<user_id>44919496-69de-498e-922c-5ea4230c00fa</user_id>
<rating>3</rating>
<title>Risk tell team series house.</title>
<content>Official police serve past already. Number down similar senior head amount. Focus reality really hold lose.</content>
<date>2026-01-03</date>
<verified_purchase>False</verified_purchase>
<helpful_votes>99</helpful_votes>
</customer_review>

[Assistant]
Approach:
1. Task: Convert customer review 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:
{
  "review_id": "REV-9723622",
  "product_id": "PROD-853148",
  "user_id": "44919496-69de-498e-922c-5ea4230c00fa",
  "rating": 3,
  "title": "Risk tell team series house.",
  "content": "Official police serve past already. Number down similar senior head amount. Focus reality really hold lose.",
  "date": "2026-01-03",
  "verified_purchase": false,
  "helpful_votes": 99
}


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

[User] Output product listing as CSV.

[Assistant]
Approach:
1. Task: Create product listing 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:
abstract,authors,citations,currency,funding_source,keywords,paper_id,publication_doi,publication_venue,publication_year,rating,specs_dimensions,specs_weight_kg,stock,title
,,,USD,,,,,,,4.54,61x86x65cm,34.7,843,
Meeting popular something research officer. Officer prove dark pull sit significant. Suffer special ,"[{""name"": ""Laura Bennett"", ""affiliation"": ""Powell Ltd"", ""email"": ""dmurillo@example.net""}, {""name"": """,227,,None,"[""authority"", ""apply"", ""note""]",arXiv:2021.11729,10.7787/cniH,Science,2021,,,,,Organic contextually-based policy
"Soldier hot in play road economy democratic.
Give group off suddenly mission. Understand care attack","[{""name"": ""Willie Romero"", ""affiliation"": ""Smith, Mccann and Patel"", ""email"": ""bryantsamantha@exampl",257,,None,"[""determine"", ""enter"", ""have"", ""push"", ""oil""]",arXiv:2023.13528,10.3796/yQTO,Nature,2023,,,,,Synergistic clear-thinking strategy
Democratic couple lot responsibility tree.,"[{""name"": ""Alexis Lane"", ""affiliation"": ""Weeks-Schultz"", ""email"": ""wilsonmark@example.org""}, {""name""",403,,Knox-Diaz,"[""customer"", ""would"", ""high"", ""learn"", ""professional""]",arXiv:2021.34669,10.4085/adaM,Science,2023,,,,,Universal holistic core


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

[User] Create a TOML representation of course syllabus.

[Assistant]
Approach:
1. Task: Create course syllabus 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:
course_id = "CRS-6204"
code = "WOR378"
title = "Multi-channeled bi-directional implementation 101"
instructor = "Charlene Houston"
credits = 4
term = "Spring 2023"
[[schedule]]
week = 1
topic = "under"

[[schedule]]
week = 2
topic = "trade"

[[schedule]]
week = 3
topic = "good"

[[schedule]]
week = 4
topic = "grow"

[[schedule]]
week = 5
topic = "ability"

[[schedule]]
week = 6
topic = "experience"

[[schedule]]
week = 7
topic = "offer"

[[schedule]]
week = 8
topic = "account"

[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] Output experiment result as JSON.

[Assistant]
Approach:
1. Task: Create experiment 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:
{
  "experiment_id": "EXP-818679",
  "title": "Effect of begin on task",
  "methodology": {
    "design": "RCT",
    "sample_size": 180,
    "duration_days": 157
  },
  "results": [
    {
      "metric": "safety",
      "baseline": 17.77,
      "endpoint": 32.37,
      "p_value": 0.477
    },
    {
      "metric": "safety",
      "baseline": 20.98,
      "endpoint": 13.84,
      "p_value": 0.2984
    }
  ],
  "conclusion": "non-significant"
}


[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"?>
<research_paper>
<paper_id>arXiv:2023.21424</paper_id>
<title>Cross-platform fault-tolerant circuit</title>
<authors>
<name>Charlotte Sellers</name>
<affiliation>Armstrong-Marks</affiliation>
<email>weaverelizabeth@example.com</email>
</authors>
<authors>
<name>Cynthia Johnston MD</name>
<affiliation>Rogers Inc</affiliation>
<email>ccastaneda@example.org</email>
</authors>
<authors>
<name>Robert Velasquez</name>
<affiliation>Alvarado LLC</affiliation>
<email>psullivan@example.net</email>
</authors>
<abstract>Truth himself long country car environment. Free design relate hope admit learn identify.</abstract>
<keywords>share</keywords>
<keywords>feeling</keywords>
<keywords>environmental</keywords>
<publication>
<venue>Science</venue>
<year>2022</year>
<doi>10.6091/Sfwn</doi>
</publication>
<citations>477</citations>
<funding_source>Barker-Wise</funding_source>
</research_paper>

[Assistant]
Approach:
1. Task: Convert research paper 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:
{
  "paper_id": "arXiv:2023.21424",
  "title": "Cross-platform fault-tolerant circuit",
  "authors": [
    {
      "name": "Charlotte Sellers",
      "affiliation": "Armstrong-Marks",
      "email": "weaverelizabeth@example.com"
    },
    {
      "name": "Cynthia Johnston MD",
      "affiliation": "Rogers Inc",
      "email": "ccastaneda@example.org"
    },
    {
      "name": "Robert Velasquez",
      "affiliation": "Alvarado LLC",
      "email": "psullivan@example.net"
    }
  ],
  "abstract": "Truth himself long country car environment. Free design relate hope admit learn identify.",
  "keywords": [
    "share",
    "feeling",
    "environmental"
  ],
  "publication": {
    "venue": "Science",
    "year": 2022,
    "doi": "10.6091/Sfwn"
  },
  "citations": 477,
  "funding_source": "Barker-Wise"
}


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

[User] Generate research paper data in XML format.

[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:2024.40808</paper_id>
<title>Versatile systematic infrastructure</title>
<authors>
<name>Andres Compton</name>
<affiliation>Knight, Wyatt and Mccarty</affiliation>
<email>lawsontammy@example.org</email>
</authors>
<authors>
<name>Michael Mcgrath</name>
<affiliation>Garcia, Davis and Caldwell</affiliation>
<email>madison05@example.net</email>
</authors>
<abstract>Face direction whom party go follow. According meet pick hit environmental resource glass.</abstract>
<keywords>service</keywords>
<keywords>walk</keywords>
<keywords>although</keywords>
<keywords>several</keywords>
<keywords>against</keywords>
<publication>
<venue>Cell</venue>
<year>2021</year>
<doi>10.1740/TuDe</doi>
</publication>
<citations>172</citations>
<funding_source>Bautista, Saunders and Delgado</funding_source>
</research_paper>


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

[User]
Transform this TOML data into JSON format:
post_id = "POST-20150897"
platform = "instagram"
user_id = "ace3958f-4578-4576-9236-9cbfc1f62953"
username = "spatrick"
content = "About industry woman size. Available box return camera public time. Establish outside ability sport describe air who.\nCertain miss girl different both wife. Blood relationship if model."
timestamp = "2026-01-07T13:51:25.995017"
hashtags = [ "#share", "#prevent", "#entire", "#owner",]

[engagement]
likes = 3129
shares = 891
comments = 28

[Assistant]
Approach:
1. Task: Convert social media post from TOML 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:
{
  "post_id": "POST-20150897",
  "platform": "instagram",
  "user_id": "ace3958f-4578-4576-9236-9cbfc1f62953",
  "username": "spatrick",
  "content": "About industry woman size. Available box return camera public time. Establish outside ability sport describe air who.\nCertain miss girl different both wife. Blood relationship if model.",
  "timestamp": "2026-01-07T13:51:25.995017",
  "hashtags": [
    "#share",
    "#prevent",
    "#entire",
    "#owner"
  ],
  "engagement": {
    "likes": 3129,
    "shares": 891,
    "comments": 28
  }
}


[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: 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-1689",
  "code": "NZW166",
  "title": "Operative modular system engine 101",
  "instructor": "David Chen",
  "credits": 4,
  "term": "Fall 2021",
  "schedule": [
    {
      "week": 1,
      "topic": "in"
    },
    {
      "week": 2,
      "topic": "summer"
    },
    {
      "week": 3,
      "topic": "unit"
    },
    {
      "week": 4,
      "topic": "wind"
    },
    {
      "week": 5,
      "topic": "act"
    },
    {
      "week": 6,
      "topic": "itself"
    },
    {
      "week": 7,
      "topic": "would"
    },
    {
      "week": 8,
      "topic": "itself"
    },
    {
      "week": 9,
      "topic": "tell"
    },
    {
      "week": 10,
      "topic": "money"
    },
    {
      "week": 11,
      "topic": "long"
    }
  ],
  "grading": {
    "homework": 30,
    "midterm": 30,
    "final": 40
  }
}


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

[User]
Reformat the data below from XML to CSV:
<?xml version="1.0" encoding="UTF-8"?>
<lab_result>
<result_id>LAB-4303735</result_id>
<patient_mrn>MRN-230243</patient_mrn>
<order_date>2026-01-02</order_date>
<panel>Lipid</panel>
<results>
<test>WBC</test>
<value>142.8</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>100.6</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>WBC</test>
<value>148.7</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>95.1</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
</lab_result>

[Assistant]
Approach:
1. Task: Convert lab result from XML to 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. Transform values to match the target format specifications.

Output:
order_date,panel,patient_mrn,result_id,results
2026-01-02,Lipid,MRN-230243,LAB-4303735,"[{""test"": ""WBC"", ""value"": 142.8, ""unit"": ""g/dL"", ""flag"": ""high""}, {""test"": ""Hemoglobin"", ""value"": 10"
2026-01-02,CBC,MRN-734729,LAB-3869434,"[{""test"": ""Hemoglobin"", ""value"": 159.1, ""unit"": ""mg/dL"", ""flag"": ""high""}, {""test"": ""WBC"", ""value"": 7"
2026-01-01,CMP,MRN-886182,LAB-4165206,"[{""test"": ""Glucose"", ""value"": 145.3, ""unit"": ""mg/dL"", ""flag"": ""normal""}, {""test"": ""Hemoglobin"", ""val"


[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: 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-5383313"
patient_mrn = "MRN-584871"
order_date = "2026-01-06"
panel = "CMP"
[[results]]
test = "Glucose"
value = 194.0
unit = "g/dL"
flag = "normal"

[[results]]
test = "Hemoglobin"
value = 67.1
unit = "g/dL"
flag = "low"

[[results]]
test = "Glucose"
value = 195.1
unit = "g/dL"
flag = "low"

[[results]]
test = "Hemoglobin"
value = 146.6
unit = "mg/dL"
flag = "high"

[[results]]
test = "WBC"
value = 119.8
unit = "mg/dL"
flag = "normal"


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

[User]
Convert the following JSON to XML:
{
  "post_id": "POST-86898750",
  "platform": "instagram",
  "user_id": "a47ec401-ca4e-44b5-afc7-6c2b372f589e",
  "username": "dylan00",
  "content": "Might north politics.\nMoment bad without change physical store call. Enjoy question state student political boy tonight.\nSoon ten last small develop left enter. Health lead bank and air capital save.",
  "timestamp": "2026-01-07T13:51:25.591017",
  "hashtags": [
    "#kid",
    "#off",
    "#school",
    "#fund"
  ],
  "engagement": {
    "likes": 9146,
    "shares": 205,
    "comments": 18
  }
}

[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-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 YAML format. Think step-by-step, then generate syntactically perfect YAML.

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

[Assistant]
Approach:
1. Task: Create student assessment 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:
assessment_id: ASMT-225883
student_id: STU-314827
course_id: CRS-2408
type: quiz
date: '2026-01-01'
scores:
- question: 1
  points_earned: 8
  points_possible: 10
- question: 2
  points_earned: 2
  points_possible: 10
- question: 3
  points_earned: 9
  points_possible: 10
- question: 4
  points_earned: 7
  points_possible: 10
- question: 5
  points_earned: 2
  points_possible: 10
- question: 6
  points_earned: 3
  points_possible: 10
- question: 7
  points_earned: 3
  points_possible: 10
- question: 8
  points_earned: 4
  points_possible: 10
- question: 9
  points_earned: 2
  points_possible: 10
- question: 10
  points_earned: 10
  points_possible: 10
- question: 11
  points_earned: 4
  points_possible: 10
- question: 12
  points_earned: 10
  points_possible: 10
- question: 13
  points_earned: 8
  points_possible: 10
total_score: 99
percentage: 82.0
grade: B


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

[User] Produce a XML document for a research paper.

[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:2020.69453</paper_id>
<title>Assimilated needs-based portal</title>
<authors>
<name>Evan Reed</name>
<affiliation>Orr, Wheeler and Johnson</affiliation>
<email>cheryl05@example.net</email>
</authors>
<authors>
<name>Amanda Mcmahon</name>
<affiliation>Maxwell-Price</affiliation>
<email>mbowen@example.org</email>
</authors>
<authors>
<name>Angel Vasquez</name>
<affiliation>Melendez, Osborne and Harris</affiliation>
<email>timothysutton@example.com</email>
</authors>
<abstract>Economy instead thank kitchen. For pattern he purpose strong goal challenge.</abstract>
<keywords>power</keywords>
<keywords>main</keywords>
<keywords>light</keywords>
<keywords>form</keywords>
<keywords>system</keywords>
<publication>
<venue>Cell</venue>
<year>2024</year>
<doi>10.9550/gbOm</doi>
</publication>
<citations>115</citations>
<funding_source />
</research_paper>


[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-2971879"
product_id = "PROD-601177"
user_id = "49ec79ac-cc63-409f-8812-a70c492b6835"
rating = 3
title = "Safe everything country understand subject."
content = "Explain among above role speech. Hear law enjoy. Lose building fall everything million.\nEast choose however class dark test good contain. Indicate worker mean hot."
date = "2026-01-06"
verified_purchase = true
helpful_votes = 67


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

[User] Produce a YAML document for a contract.

[Assistant]
Approach:
1. Task: Create contract 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:
contract_id: CTR-896633
parties:
- name: Smith-Cross
  role: party_a
- name: Carrillo and Sons
  role: party_b
effective_date: '2026-01-03'
term_months: 21
value: 926875
status: pending


[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: 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:
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
,,,4ccfb0b5-8185-4d26-902a-0379b3534400,6765bd92-f82e-426f-a383-fa0a088a0752,234c0781-6e40-4e46-8b0d-ad1b39309eb0,,,WARNING,Section material entire top community.,,,,,beyondService,"[""at reason.py:320"", ""at always.py:365"", ""at red.py:27""]",2026-01-07T13:51:25.659911,
He spring these realize fund watch pattern five. House job concern green involve staff live.,"[{""name"": ""Ashley Castro"", ""affiliation"": ""Murray-Pineda"", ""email"": ""austin77@example.com""}, {""name""",178,,,,Golden-Young,"[""thousand"", ""training"", ""paper"", ""me""]",,,arXiv:2021.11274,10.6489/QMWy,Nature,2021,,,,Versatile tertiary forecast
"Professor simple choice discussion though trade. Base energy hear chance.
Player mean radio he contr","[{""name"": ""Mr. Charles Cole"", ""affiliation"": ""Bullock Inc"", ""email"": ""john05@example.com""}, {""name"":",138,,,,None,"[""pass"", ""teach"", ""entire"", ""civil""]",,,arXiv:2021.97664,10.5548/vtXG,Science,2024,,,,Polarized global collaboration


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

[User] Produce a TOML document for a experiment result.

[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-160417"
title = "Effect of agree on both"
conclusion = "non-significant"
[[results]]
metric = "safety"
baseline = 13.92
endpoint = 49.07
p_value = 0.4102

[[results]]
metric = "safety"
baseline = 15.99
endpoint = 65.81
p_value = 0.3043

[[results]]
metric = "efficacy"
baseline = 46.51
endpoint = 82.23
p_value = 0.4775

[methodology]
design = "cohort"
sample_size = 663
duration_days = 354


[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: 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-485879,,CRS-1053,,2026-01-03,A,,,,,64.04,,"[{""question"": 1, ""points_earned"": 0, ""points_possible"": 10}, {""question"": 2, ""points_earned"": 6, ""po",STU-284737,,,89,exam
,IWN240,CRS-4017,3,,,40,30,30,Beth Hoffman,,"[{""week"": 1, ""topic"": ""happy""}, {""week"": 2, ""topic"": ""bit""}, {""week"": 3, ""topic"": ""camera""}, {""week""",,,Fall 2023,Pre-emptive client-driven groupware 101,,
,VER341,CRS-8686,3,,,40,30,30,Lauren Avila,,"[{""week"": 1, ""topic"": ""bag""}, {""week"": 2, ""topic"": ""society""}, {""week"": 3, ""topic"": ""partner""}, {""we",,,Fall 2023,Distributed 4thgeneration strategy 101,,
,JLD206,CRS-7575,4,,,40,30,30,Michael Rodriguez,,"[{""week"": 1, ""topic"": ""during""}, {""week"": 2, ""topic"": ""traditional""}, {""week"": 3, ""topic"": ""example""",,,Fall 2022,Inverse radical collaboration 101,,


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

[User] Generate research paper data in JSON format.

[Assistant]
Approach:
1. Task: Create research paper 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:
{
  "paper_id": "arXiv:2023.67497",
  "title": "Open-architected logistical paradigm",
  "authors": [
    {
      "name": "William Martin",
      "affiliation": "George, Nichols and Johnston",
      "email": "crystal73@example.org"
    },
    {
      "name": "Thomas Boyer",
      "affiliation": "Powers, Miller and Johnston",
      "email": "xhardin@example.com"
    },
    {
      "name": "Tanner Coffey",
      "affiliation": "Perez, Marks and Thomas",
      "email": "tracywilliams@example.com"
    }
  ],
  "abstract": "Yes eat up himself consumer. Technology just debate bill live oil.",
  "keywords": [
    "each",
    "on",
    "perhaps"
  ],
  "publication": {
    "venue": "Nature",
    "year": 2022,
    "doi": "10.2923/Xnio"
  },
  "citations": 265,
  "funding_source": "Smith Ltd"
}


[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: 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-948175,,CRS-5368,,2026-01-03,B,,,,,96.29,,"[{""question"": 1, ""points_earned"": 1, ""points_possible"": 10}, {""question"": 2, ""points_earned"": 9, ""po",STU-160858,,,89,assignment
,FBS379,CRS-6392,4,,,40,30,30,Richard White,,"[{""week"": 1, ""topic"": ""evening""}, {""week"": 2, ""topic"": ""face""}, {""week"": 3, ""topic"": ""nice""}, {""week",,,Fall 2021,Advanced optimizing encoding 101,,
,UZK284,CRS-4795,4,,,40,30,30,Russell Shields,,"[{""week"": 1, ""topic"": ""heart""}, {""week"": 2, ""topic"": ""agree""}, {""week"": 3, ""topic"": ""may""}, {""week"":",,,Fall 2022,Object-based intangible initiative 101,,
,CUH168,CRS-2705,4,,,40,30,30,Michael Morton,,"[{""week"": 1, ""topic"": ""senior""}, {""week"": 2, ""topic"": ""relate""}, {""week"": 3, ""topic"": ""coach""}, {""we",,,Spring 2023,Expanded web-enabled definition 101,,


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

[User] Create a JSON representation of experiment result.

[Assistant]
Approach:
1. Task: Create experiment 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:
{
  "experiment_id": "EXP-330074",
  "title": "Effect of politics on stop",
  "methodology": {
    "design": "RCT",
    "sample_size": 328,
    "duration_days": 247
  },
  "results": [
    {
      "metric": "efficacy",
      "baseline": 34.54,
      "endpoint": 53.32,
      "p_value": 0.0487
    },
    {
      "metric": "safety",
      "baseline": 10.4,
      "endpoint": 13.84,
      "p_value": 0.1164
    },
    {
      "metric": "efficacy",
      "baseline": 78.27,
      "endpoint": 47.78,
      "p_value": 0.0781
    }
  ],
  "conclusion": "non-significant"
}


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

[User]
Convert the following JSON to XML:
{
  "date": "2026-01-04",
  "user_id": "d6e6e646-61a4-4af9-a9a1-d03d234244eb",
  "content": "It herself scene five side support onto. Shake fear western believe. Say fact shoulder investment television pretty suffer.\nGround listen official hand at indeed. Effort thus wife control."
}

[Assistant]
Approach:
1. Task: Convert customer review from JSON to 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. Transform values to match the target format specifications.

Output:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<date>2026-01-04</date>
<user_id>d6e6e646-61a4-4af9-a9a1-d03d234244eb</user_id>
<content>It herself scene five side support onto. Shake fear western believe. Say fact shoulder investment television pretty suffer.
Ground listen official hand at indeed. Effort thus wife control.</content>
</customer_review>


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

[User] Create a YAML representation of customer review.

[Assistant]
Approach:
1. Task: Create customer review in YAML
2. Complexity: medium - 5-8 fields, 2-3 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:
review_id: REV-7169946
product_id: PROD-908355
user_id: 109a43ce-0a9d-47ca-b5cc-5940dcb3a5c0
rating: 3
title: Suffer kid daughter race still baby.
content: 'Young lot card leave book. Thank agency tree shake. Manage organization
  reduce from sort soldier.

  Run rich marriage parent discover kitchen. Positive person baby list positive really
  range.'
date: '2026-01-05'
verified_purchase: true
helpful_votes: 3


[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
non-significant,EXP-942720,cohort,54,645,"[{""metric"": ""safety"", ""baseline"": 79.64, ""endpoint"": 26.86, ""p_value"": 0.2863}, {""metric"": ""safety"",",Effect of edge on when
non-significant,EXP-275450,observational,222,577,"[{""metric"": ""safety"", ""baseline"": 47.39, ""endpoint"": 55.82, ""p_value"": 0.2351}, {""metric"": ""efficacy",Effect of market on computer
significant,EXP-602547,observational,241,244,"[{""metric"": ""efficacy"", ""baseline"": 16.77, ""endpoint"": 86.1, ""p_value"": 0.0756}, {""metric"": ""safety""",Effect of culture on food


[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:
{
  "period": "June 2021",
  "total_revenue": 1467254,
  "units_sold": 63744,
  "channels": [
    {
      "name": "wholesale",
      "revenue": 2975287,
      "growth": -1.88
    },
    {
      "name": "online",
      "revenue": 2665464,
      "growth": 14.77
    }
  ],
  "top_products": [
    {
      "sku": "SKU-1172",
      "sales": 348860
    },
    {
      "sku": "SKU-4431",
      "sales": 479568
    },
    {
      "sku": "SKU-6244",
      "sales": 245719
    }
  ]
}

[Assistant]
Approach:
1. Task: Convert sales analytics 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"?>
<sales_analytics>
<period>June 2021</period>
<total_revenue>1467254</total_revenue>
<units_sold>63744</units_sold>
<channels>
<name>wholesale</name>
<revenue>2975287</revenue>
<growth>-1.88</growth>
</channels>
<channels>
<name>online</name>
<revenue>2665464</revenue>
<growth>14.77</growth>
</channels>
<top_products>
<sku>SKU-1172</sku>
<sales>348860</sales>
</top_products>
<top_products>
<sku>SKU-4431</sku>
<sales>479568</sales>
</top_products>
<top_products>
<sku>SKU-6244</sku>
<sales>245719</sales>
</top_products>
</sales_analytics>


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

[User] Output error log as CSV.

[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
,,,4ed63374-fc09-4101-b987-4a8ee575fee3,432ef3ee-7f2b-4bc8-a8a7-159d64a89fd5,a016c8d2-6aba-435a-ab46-60ac8aacf0a5,,,CRITICAL,Well nation stay number now but.,,,,,currentService,"[""at daughter.py:364"", ""at same.py:66""]",2026-01-07T13:51:26.006823,
Election news mission against. Heavy tree number fund.,"[{""name"": ""Jennifer White"", ""affiliation"": ""Hull, Ward and Dodson"", ""email"": ""qtorres@example.com""},",424,,,,Schneider-Williams,"[""past"", ""consumer"", ""argue"", ""today"", ""bag""]",,,arXiv:2022.85316,10.2316/bVwS,Cell,2021,,,,Stand-alone encompassing success
Lot front fact thought benefit. Drop every age team then. Leader man window wonder. Computer remain ,"[{""name"": ""Cheryl Good"", ""affiliation"": ""Garcia Group"", ""email"": ""rwhite@example.org""}, {""name"": ""Dy",68,,,,Johnson Inc,"[""send"", ""movie"", ""next"", ""school"", ""test""]",,,arXiv:2022.78053,10.5989/PcwP,Cell,2022,,,,Future-proofed multimedia protocol
"Notice community road. Outside already scientist benefit.
Wife factor physical although head. Black ","[{""name"": ""Melissa Alvarez"", ""affiliation"": ""Jackson-Mason"", ""email"": ""dcross@example.net""}, {""name""",131,,,,Grant-Wilcox,"[""since"", ""a"", ""I""]",,,arXiv:2021.75079,10.8936/lZYL,Nature,2021,,,,User-centric interactive portal