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

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

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

Output:
paper_id = "arXiv:2020.86983"
title = "Reverse-engineered national Graphical User Interface"
abstract = "Sure finally site who truth. Close stop when low. Check news mother democratic."
keywords = [ "old", "indeed", "general", "claim", "every",]
citations = 221
[[authors]]
name = "Wesley Murphy"
affiliation = "Nunez, Meyer and Snow"
email = "nina74@example.net"

[[authors]]
name = "Richard Morgan"
affiliation = "Hall-Jones"
email = "justin85@example.org"

[[authors]]
name = "Anthony Johnson"
affiliation = "Kelley-Murphy"
email = "srichmond@example.com"

[publication]
venue = "Nature"
year = 2024
doi = "10.2539/QMDE"


[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": "Smith-Glover",
  "ticker": "JROI",
  "quarter": "Q3 2023",
  "revenue": 95238846,
  "expenses": 30652579,
  "net_income": 5856951,
  "eps": 7.31,
  "metrics": {
    "profit_margin": 9.94,
    "roe": 10.91
  }
}

[Assistant]
Approach:
1. Task: Convert financial report 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"?>
<financial_report>
<company>Smith-Glover</company>
<ticker>JROI</ticker>
<quarter>Q3 2023</quarter>
<revenue>95238846</revenue>
<expenses>30652579</expenses>
<net_income>5856951</net_income>
<eps>7.31</eps>
<metrics>
<profit_margin>9.94</profit_margin>
<roe>10.91</roe>
</metrics>
</financial_report>


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

[User] Output student assessment as XML.

[Assistant]
Approach:
1. Task: Create student assessment 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"?>
<student_assessment>
<assessment_id>ASMT-458464</assessment_id>
<student_id>STU-453066</student_id>
<course_id>CRS-7675</course_id>
<type>assignment</type>
<date>2026-01-06</date>
<scores>
<question>1</question>
<points_earned>0</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>4</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>4</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>0</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>3</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>7</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>9</question>
<points_earned>8</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>67</total_score>
<percentage>65.79</percentage>
<grade>B</grade>
</student_assessment>


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<student_assessment>
<assessment_id>ASMT-613322</assessment_id>
<student_id>STU-814570</student_id>
<course_id>CRS-3548</course_id>
<type>assignment</type>
<date>2026-01-01</date>
<scores>
<question>1</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>10</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>3</question>
<points_earned>8</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>6</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>7</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>7</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>64</total_score>
<percentage>69.35</percentage>
<grade>C</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-613322",
  "student_id": "STU-814570",
  "course_id": "CRS-3548",
  "type": "assignment",
  "date": "2026-01-01",
  "scores": [
    {
      "question": 1,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 10,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 6,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 1,
      "points_possible": 10
    }
  ],
  "total_score": 64,
  "percentage": 69.35,
  "grade": "C"
}


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

[User] Generate product listing data in JSON format.

[Assistant]
Approach:
1. Task: Create product listing 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:
{
  "product_id": "PROD-421885",
  "name": "Diverse 6thgeneration solution",
  "category": "books",
  "price": 48.12,
  "currency": "USD",
  "stock": 460,
  "is_available": true,
  "rating": 3.7,
  "reviews": 717,
  "specs": {
    "weight_kg": 20.82,
    "dimensions": "87x57x81cm"
  }
}


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

[User] Generate research paper data in TOML format.

[Assistant]
Approach:
1. Task: Create research paper in TOML
2. Complexity: 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:
paper_id = "arXiv:2022.73738"
title = "Switchable maximized Local Area Network"
abstract = "List son shake understand food. Up no police friend factor. Support company yes push argue."
keywords = [ "fact", "guess", "truth",]
citations = 36
funding_source = "Guerra, Richards and Schaefer"
[[authors]]
name = "Heather Lee"
affiliation = "Garcia, Ellison and Kim"
email = "kimberlysimpson@example.com"

[[authors]]
name = "Jeremy Gonzalez"
affiliation = "Wilson, Sanchez and Copeland"
email = "michelle83@example.com"

[[authors]]
name = "Brianna Hart"
affiliation = "Shannon, Tran and Taylor"
email = "penatyler@example.net"

[publication]
venue = "Cell"
year = 2024
doi = "10.7028/ttmb"


[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"?>
<sales_analytics>
<period>January 2024</period>
<total_revenue>3091656</total_revenue>
<units_sold>63856</units_sold>
<channels>
<name>wholesale</name>
<revenue>2739604</revenue>
<growth>-0.52</growth>
</channels>
<channels>
<name>online</name>
<revenue>247982</revenue>
<growth>14.46</growth>
</channels>
<top_products>
<sku>SKU-7268</sku>
<sales>409348</sales>
</top_products>
<top_products>
<sku>SKU-4030</sku>
<sales>70087</sales>
</top_products>
<top_products>
<sku>SKU-4380</sku>
<sales>298376</sales>
</top_products>
</sales_analytics>

[Assistant]
Approach:
1. Task: Convert sales analytics 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:
{
  "period": "January 2024",
  "total_revenue": 3091656,
  "units_sold": 63856,
  "channels": [
    {
      "name": "wholesale",
      "revenue": 2739604,
      "growth": -0.52
    },
    {
      "name": "online",
      "revenue": 247982,
      "growth": 14.46
    }
  ],
  "top_products": [
    {
      "sku": "SKU-7268",
      "sales": 409348
    },
    {
      "sku": "SKU-4030",
      "sales": 70087
    },
    {
      "sku": "SKU-4380",
      "sales": 298376
    }
  ]
}


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

[User]
Transform this TOML data into CSV format:
contract_id = "CTR-274282"
effective_date = "2026-01-01"
term_months = 28
value = 285721
status = "active"
[[parties]]
name = "Schroeder LLC"
role = "party_a"

[[parties]]
name = "Kemp-Jones"
role = "party_b"

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

Output:
contract_id,effective_date,parties,status,term_months,value
CTR-274282,2026-01-01,"[{""name"": ""Schroeder LLC"", ""role"": ""party_a""}, {""name"": ""Kemp-Jones"", ""role"": ""party_b""}]",active,28,285721
CTR-393552,2026-01-04,"[{""name"": ""Payne Group"", ""role"": ""party_a""}, {""name"": ""Larson and Sons"", ""role"": ""party_b""}]",executed,16,236218
CTR-899450,2026-01-06,"[{""name"": ""Price Ltd"", ""role"": ""party_a""}, {""name"": ""Oconnell Group"", ""role"": ""party_b""}]",executed,54,772487
CTR-220704,2026-01-02,"[{""name"": ""Perez-Floyd"", ""role"": ""party_a""}, {""name"": ""Holmes, Singh and Schmitt"", ""role"": ""party_b""",pending,28,556896
CTR-628948,2026-01-03,"[{""name"": ""Joseph LLC"", ""role"": ""party_a""}, {""name"": ""Perkins, Bowen and Smith"", ""role"": ""party_b""}]",executed,24,108661


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

[User] Output research paper as TOML.

[Assistant]
Approach:
1. Task: Create research paper 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:
paper_id = "arXiv:2020.93852"
title = "Reactive solution-oriented circuit"
abstract = "Law fund huge better or. Federal forward north law. Work available call never.\nCarry cultural day front resource write. Southern white pattern fear."
keywords = [ "wind", "wife", "report", "financial",]
citations = 45
[[authors]]
name = "Jennifer Gray"
affiliation = "Bryant, Lewis and Wells"
email = "spalmer@example.com"

[[authors]]
name = "David Brown"
affiliation = "Cortez, Cook and Ross"
email = "melvin21@example.com"

[publication]
venue = "Cell"
year = 2023
doi = "10.1277/DPuH"


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

[User] Generate prescription data in XML format.

[Assistant]
Approach:
1. Task: Create prescription 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"?>
<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>


[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:
{
  "order_date": "2026-01-01",
  "panel": "Lipid",
  "patient_mrn": "MRN-952425",
  "result_id": "LAB-8958063",
  "results": [
    {
      "test": "Glucose",
      "value": 142.4,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 196.3,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 74.4,
      "unit": "mg/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 119.9,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "WBC",
      "value": 99.2,
      "unit": "mg/dL",
      "flag": "normal"
    },
    {
      "test": "Glucose",
      "value": 51.3,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "Glucose",
      "value": 186.5,
      "unit": "mg/dL",
      "flag": "low"
    }
  ]
}

[Assistant]
Approach:
1. Task: Convert lab result 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:
order_date = "2026-01-01"
panel = "Lipid"
patient_mrn = "MRN-952425"
result_id = "LAB-8958063"
[[results]]
test = "Glucose"
value = 142.4
unit = "g/dL"
flag = "normal"

[[results]]
test = "Hemoglobin"
value = 196.3
unit = "g/dL"
flag = "normal"

[[results]]
test = "Hemoglobin"
value = 74.4
unit = "mg/dL"
flag = "normal"

[[results]]
test = "Hemoglobin"
value = 119.9
unit = "mg/dL"
flag = "high"

[[results]]
test = "WBC"
value = 99.2
unit = "mg/dL"
flag = "normal"

[[results]]
test = "Glucose"
value = 51.3
unit = "g/dL"
flag = "normal"

[[results]]
test = "Glucose"
value = 186.5
unit = "mg/dL"
flag = "low"


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

[User] Create a JSON representation of financial report.

[Assistant]
Approach:
1. Task: Create financial report 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:
{
  "quarter": "Q3 2022",
  "company": "Dunn-Byrd",
  "expenses": 58548919,
  "eps": 9.56,
  "ticker": "ATGQ"
}


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

[User]
Convert the following JSON to XML:
{
  "net_income": 4233102,
  "metrics": {
    "profit_margin": 14.29,
    "roe": 18.28
  },
  "company": "Blackwell, Simpson and Pace",
  "eps": 0.79,
  "expenses": 41343491
}

[Assistant]
Approach:
1. Task: Convert financial report 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"?>
<financial_report>
<net_income>4233102</net_income>
<metrics>
<profit_margin>14.29</profit_margin>
<roe>18.28</roe>
</metrics>
<company>Blackwell, Simpson and Pace</company>
<eps>0.79</eps>
<expenses>41343491</expenses>
</financial_report>


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

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

[Assistant]
Approach:
1. Task: Create student assessment 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:
assessment_id = "ASMT-613322"
student_id = "STU-814570"
course_id = "CRS-3548"
type = "assignment"
date = "2026-01-01"
total_score = 64
percentage = 69.35
grade = "C"
[[scores]]
question = 1
points_earned = 1
points_possible = 10

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

[[scores]]
question = 3
points_earned = 8
points_possible = 10

[[scores]]
question = 4
points_earned = 6
points_possible = 10

[[scores]]
question = 5
points_earned = 7
points_possible = 10

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

[[scores]]
question = 7
points_earned = 1
points_possible = 10


[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:
{
  "total_score": 97,
  "scores": [
    {
      "question": 1,
      "points_earned": 0,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 10,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 5,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 5,
      "points_possible": 10
    },
    {
      "question": 9,
      "points_earned": 3,
      "points_possible": 10
    },
    {
      "question": 10,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 11,
      "points_earned": 5,
      "points_possible": 10
    }
  ],
  "percentage": 78.32,
  "course_id": "CRS-4089"
}

[Assistant]
Approach:
1. Task: Convert student assessment 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"?>
<student_assessment>
<total_score>97</total_score>
<scores>
<question>1</question>
<points_earned>0</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>10</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>5</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>4</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>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>5</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>9</question>
<points_earned>3</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>10</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>11</question>
<points_earned>5</points_earned>
<points_possible>10</points_possible>
</scores>
<percentage>78.32</percentage>
<course_id>CRS-4089</course_id>
</student_assessment>


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

[User] Generate course syllabus data in JSON format.

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

Output:
{
  "course_id": "CRS-8422",
  "code": "OMY437",
  "title": "Optimized upward-trending conglomeration 101",
  "instructor": "Rodney Anderson",
  "credits": 3,
  "term": "Spring 2023",
  "schedule": [
    {
      "week": 1,
      "topic": "answer"
    },
    {
      "week": 2,
      "topic": "best"
    },
    {
      "week": 3,
      "topic": "meet"
    },
    {
      "week": 4,
      "topic": "simple"
    },
    {
      "week": 5,
      "topic": "peace"
    },
    {
      "week": 6,
      "topic": "upon"
    },
    {
      "week": 7,
      "topic": "power"
    }
  ],
  "grading": {
    "homework": 30,
    "midterm": 30,
    "final": 40
  }
}


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<verified_purchase>True</verified_purchase>
<date>2026-01-05</date>
<rating>1</rating>
</customer_review>

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

Output:
{
  "verified_purchase": true,
  "date": "2026-01-05",
  "rating": 1
}


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

[User]
Convert the following JSON to XML:
{
  "period": "September 2022",
  "total_revenue": 4880286,
  "units_sold": 74173,
  "channels": [
    {
      "name": "retail",
      "revenue": 2000312,
      "growth": 0.96
    },
    {
      "name": "wholesale",
      "revenue": 3751658,
      "growth": -3.19
    }
  ],
  "top_products": [
    {
      "sku": "SKU-6977",
      "sales": 264067
    },
    {
      "sku": "SKU-7032",
      "sales": 443161
    },
    {
      "sku": "SKU-1793",
      "sales": 209512
    }
  ]
}

[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>September 2022</period>
<total_revenue>4880286</total_revenue>
<units_sold>74173</units_sold>
<channels>
<name>retail</name>
<revenue>2000312</revenue>
<growth>0.96</growth>
</channels>
<channels>
<name>wholesale</name>
<revenue>3751658</revenue>
<growth>-3.19</growth>
</channels>
<top_products>
<sku>SKU-6977</sku>
<sales>264067</sales>
</top_products>
<top_products>
<sku>SKU-7032</sku>
<sales>443161</sales>
</top_products>
<top_products>
<sku>SKU-1793</sku>
<sales>209512</sales>
</top_products>
</sales_analytics>


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

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

[Assistant]
Approach:
1. Task: Convert sales analytics 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"?>
<sales_analytics>
<period>November 2022</period>
<total_revenue>9138741</total_revenue>
<units_sold>89798</units_sold>
<channels>
<name>wholesale</name>
<revenue>1234153</revenue>
<growth>40.64</growth>
</channels>
<channels>
<name>online</name>
<revenue>991509</revenue>
<growth>-4.15</growth>
</channels>
<top_products>
<sku>SKU-9585</sku>
<sales>30234</sales>
</top_products>
<top_products>
<sku>SKU-8072</sku>
<sales>57362</sales>
</top_products>
<top_products>
<sku>SKU-4011</sku>
<sales>249730</sales>
</top_products>
</sales_analytics>


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

[User] Generate transaction record data in YAML format.

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

Output:
txn_id: TXN-28879814
customer_id: b13e97b5-e84b-41ec-9dea-05b4809cdd35
timestamp: '2026-01-07T13:51:25.895711'
items:
- sku: SKU-36351
  qty: 1
  price: 310.41
- sku: SKU-26629
  qty: 2
  price: 119.44
- sku: SKU-75447
  qty: 3
  price: 127.79
- sku: SKU-81003
  qty: 3
  price: 336.59
subtotal: 994.66
tax: 143.59
total: 1762.36
payment_method: apple_pay


[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: 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"?>
<error_log>
<error_id>2a52fc1b-775b-4f0d-9bad-8f4f44e2d81f</error_id>
<timestamp>2026-01-07T13:51:25.611338</timestamp>
<level>ERROR</level>
<service>typeService</service>
<message>Suggest involve part skill write left participant.</message>
<stack_trace>at risk.py:441</stack_trace>
<stack_trace>at strategy.py:390</stack_trace>
<stack_trace>at performance.py:267</stack_trace>
<stack_trace>at kind.py:265</stack_trace>
<context>
<user_id>3651fff2-dc6a-4fe5-a964-ed26913f3e4b</user_id>
<request_id>f4fc48f0-6374-4e80-b666-89c2abac0904</request_id>
</context>
</error_log>


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

[User] Generate prescription data in TOML format.

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

Output:
rx_id = "RX-9458448"
patient_mrn = "MRN-362998"
prescriber = "Courtney Hansen"
date = "2026-01-02"
[[medications]]
name = "Lisinopril"
dosage = "10mg"
frequency = "BID"
quantity = 30


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

[User] Create a YAML representation of 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-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


[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"?>
<research_paper>
<paper_id>arXiv:2024.66116</paper_id>
<title>Quality-focused grid-enabled service-desk</title>
<authors>
<name>David Cohen</name>
<affiliation>Lopez and Sons</affiliation>
<email>mark98@example.com</email>
</authors>
<authors>
<name>Ashley Spencer</name>
<affiliation>Hood Ltd</affiliation>
<email>pbailey@example.org</email>
</authors>
<authors>
<name>Robin Lynch</name>
<affiliation>Camacho, Nelson and Perez</affiliation>
<email>samantha44@example.net</email>
</authors>
<abstract>Body exactly last operation trouble. Financial whole check management chance eat us. Likely wrong explain by would born only.</abstract>
<keywords>rather</keywords>
<keywords>hair</keywords>
<keywords>attorney</keywords>
<keywords>chance</keywords>
<keywords>bring</keywords>
<publication>
<venue>Cell</venue>
<year>2020</year>
<doi>10.7468/EeJM</doi>
</publication>
<citations>174</citations>
<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:2024.66116",
  "title": "Quality-focused grid-enabled service-desk",
  "authors": [
    {
      "name": "David Cohen",
      "affiliation": "Lopez and Sons",
      "email": "mark98@example.com"
    },
    {
      "name": "Ashley Spencer",
      "affiliation": "Hood Ltd",
      "email": "pbailey@example.org"
    },
    {
      "name": "Robin Lynch",
      "affiliation": "Camacho, Nelson and Perez",
      "email": "samantha44@example.net"
    }
  ],
  "abstract": "Body exactly last operation trouble. Financial whole check management chance eat us. Likely wrong explain by would born only.",
  "keywords": [
    "rather",
    "hair",
    "attorney",
    "chance",
    "bring"
  ],
  "publication": {
    "venue": "Cell",
    "year": 2020,
    "doi": "10.7468/EeJM"
  },
  "citations": 174,
  "funding_source": null
}


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

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

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

Output:
title: Polarized methodical algorithm
authors:
- name: Caroline Barnes
  affiliation: Parker Ltd
  email: angelajackson@example.net
- name: Mario Boyd
  affiliation: Johnson, Barber and Higgins
  email: lfuller@example.com
funding_source: null


[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:
{
  "payment_method": "paypal",
  "customer_id": "fe237049-a4a1-4a5c-af14-940bbb31d0e7",
  "total": 1227.54
}

[Assistant]
Approach:
1. Task: Convert transaction record 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"?>
<transaction_record>
<payment_method>paypal</payment_method>
<customer_id>fe237049-a4a1-4a5c-af14-940bbb31d0e7</customer_id>
<total>1227.54</total>
</transaction_record>


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

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

[Assistant]
Approach:
1. Task: Create research paper 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:
paper_id: arXiv:2023.99214
title: Integrated mobile database
authors:
- name: Clayton Martinez
  affiliation: Flores, Levy and Farmer
  email: kathy80@example.org
- name: Susan Bennett
  affiliation: Collins, Daniel and Lyons
  email: shawnjefferson@example.org
abstract: Full with spend role first drive. Want man instead today bed hand character.
keywords:
- bed
- very
- population
publication:
  venue: Nature
  year: 2023
  doi: 10.4640/CkqB
citations: 395
funding_source: null


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

[User] Produce a TOML document for a news article.

[Assistant]
Approach:
1. Task: Create news article 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:
article_id = "ART-2188860"
headline = "Advanced well-modulated service-desk"
author = "Michael Logan"
published = "2026-01-03T08:09:52.608144"
section = "Politics"
content = "Include start build no effort continue. Mention sister mention threat.\nChoose herself case writer question over. Hand quickly house send shoulder expert hour.\nAll probably suffer law consider kitchen relationship. Data population personal past security but across."
tags = [ "hear", "civil", "might", "way", "win",]
views = 35184
shares = 1092


[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:
{
  "section": "Politics",
  "tags": [
    "machine",
    "fund",
    "station",
    "our"
  ],
  "published": "2026-01-05T17:58:55.100855",
  "views": 86295
}

[Assistant]
Approach:
1. Task: Convert news article 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"?>
<news_article>

Politics

<tags>machine</tags>
<tags>fund</tags>
<tags>station</tags>
<tags>our</tags>
<published>2026-01-05T17:58:55.100855</published>
<views>86295</views>
</news_article>


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<product_listing>
<product_id>PROD-361703</product_id>
<name>Grass-roots methodical neural-net</name>
<category>books</category>
<price>156.58</price>
<currency>USD</currency>
<stock>3</stock>
<is_available>True</is_available>
<rating>3.73</rating>
<reviews>915</reviews>
<specs>
<weight_kg>25.41</weight_kg>
<dimensions>90x40x81cm</dimensions>
</specs>
</product_listing>

[Assistant]
Approach:
1. Task: Convert product listing 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:
{
  "product_id": "PROD-361703",
  "name": "Grass-roots methodical neural-net",
  "category": "books",
  "price": 156.58,
  "currency": "USD",
  "stock": 3,
  "is_available": true,
  "rating": 3.73,
  "reviews": 915,
  "specs": {
    "weight_kg": 25.41,
    "dimensions": "90x40x81cm"
  }
}


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

[User] Output financial report as CSV.

[Assistant]
Approach:
1. Task: Create financial report 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:
company,eps,expenses,metrics_profit_margin,metrics_roe,net_income,quarter,revenue,ticker
Richard Ltd,4.63,54916122,14.39,19.33,1190834,Q4 2020,71255223,XHCL
Hayes-Saunders,9.88,61967267,12.94,18.69,17077718,Q3 2021,60264470,CZNY
"Montes, Cook and Morrison",1.12,61025572,17.08,16.56,665787,Q2 2024,1475042,WCTY
"Pitts, Barnes and Adams",2.04,2865401,10.62,13.19,16591840,Q1 2022,65764775,QATD
"Ellis, Brown and Lee",2.55,29896802,28.99,11.73,8444401,Q2 2024,58955391,LPHN


[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-3637179</review_id>
<product_id>PROD-905516</product_id>
<user_id>cbc145e7-7f32-438c-ba90-61711bf65a15</user_id>
<rating>1</rating>
<title>Hand ok join you population.</title>
<content>Develop particularly receive thing process sister source. Ago short fact start meeting note need. However music factor my million scene use.</content>
<date>2026-01-03</date>
<verified_purchase>False</verified_purchase>
<helpful_votes>42</helpful_votes>
</customer_review>

[Assistant]
Approach:
1. Task: Convert customer review 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:
{
  "review_id": "REV-3637179",
  "product_id": "PROD-905516",
  "user_id": "cbc145e7-7f32-438c-ba90-61711bf65a15",
  "rating": 1,
  "title": "Hand ok join you population.",
  "content": "Develop particularly receive thing process sister source. Ago short fact start meeting note need. However music factor my million scene use.",
  "date": "2026-01-03",
  "verified_purchase": false,
  "helpful_votes": 42
}


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

[User]
Reformat the data below from XML to TOML:
<?xml version="1.0" encoding="UTF-8"?>
<experiment_result>
<experiment_id>EXP-818679</experiment_id>
<title>Effect of begin on task</title>
<methodology>
<design>RCT</design>
<sample_size>180</sample_size>
<duration_days>157</duration_days>
</methodology>
<results>
<metric>safety</metric>
<baseline>17.77</baseline>
<endpoint>32.37</endpoint>
<p_value>0.477</p_value>
</results>
<results>
<metric>safety</metric>
<baseline>20.98</baseline>
<endpoint>13.84</endpoint>
<p_value>0.2984</p_value>
</results>
<conclusion>non-significant</conclusion>
</experiment_result>

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

Output:
experiment_id = "EXP-818679"
title = "Effect of begin on task"
conclusion = "non-significant"
[[results]]
metric = "safety"
baseline = 17.77
endpoint = 32.37
p_value = 0.477

[[results]]
metric = "safety"
baseline = 20.98
endpoint = 13.84
p_value = 0.2984

[methodology]
design = "RCT"
sample_size = 180
duration_days = 157


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

[User] Generate social media post data in JSON format.

[Assistant]
Approach:
1. Task: Create social media post 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:
{
  "post_id": "POST-59844758",
  "timestamp": "2026-01-07T13:51:27.358144",
  "hashtags": [
    "#population",
    "#during",
    "#executive",
    "#house"
  ]
}


[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-19357850",
  "platform": "twitter",
  "user_id": "664b960b-1331-492f-addd-e9b37d21656f",
  "username": "mbaldwin",
  "content": "Forward front agreement cover hour we remember ask. Read glass few word mother deep TV.",
  "timestamp": "2026-01-07T13:51:27.605837",
  "hashtags": [
    "#cost",
    "#he",
    "#relationship"
  ],
  "engagement": {
    "likes": 304,
    "shares": 796,
    "comments": 124
  }
}

[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-19357850</post_id>
<platform>twitter</platform>
<user_id>664b960b-1331-492f-addd-e9b37d21656f</user_id>
<username>mbaldwin</username>
<content>Forward front agreement cover hour we remember ask. Read glass few word mother deep TV.</content>
<timestamp>2026-01-07T13:51:27.605837</timestamp>
<hashtags>#cost</hashtags>
<hashtags>#he</hashtags>
<hashtags>#relationship</hashtags>
<engagement>
<likes>304</likes>
<shares>796</shares>
<comments>124</comments>
</engagement>
</social_media_post>


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

[User]
Transform this XML data into TOML format:
<?xml version="1.0" encoding="UTF-8"?>
<social_media_post>
<post_id>POST-39289028</post_id>
<platform>instagram</platform>
<user_id>a2301bd9-5c11-406a-b2a8-1c1f96bbd31c</user_id>
<username>rhodessharon</username>
<content>City window data describe address street. Environmental wall shoulder happy artist forget hospital. Chair their before reach picture serve.</content>
<timestamp>2026-01-07T13:51:26.862472</timestamp>
<hashtags>#yet</hashtags>
<hashtags>#listen</hashtags>
<engagement>
<likes>2391</likes>
<shares>751</shares>
<comments>108</comments>
</engagement>
</social_media_post>

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

Output:
post_id = "POST-39289028"
platform = "instagram"
user_id = "a2301bd9-5c11-406a-b2a8-1c1f96bbd31c"
username = "rhodessharon"
content = "City window data describe address street. Environmental wall shoulder happy artist forget hospital. Chair their before reach picture serve."
timestamp = "2026-01-07T13:51:26.862472"
hashtags = [ "#yet", "#listen",]

[engagement]
likes = 2391
shares = 751
comments = 108


[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"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Horizontal interactive project API</title>
<version>1.0.0</version>
</info>
<paths>
</base>
<get>
<summary>Management send father actually special image.</summary>
<parameters>
<name>param0</name>
<in>query</in>
<type>string</type>
</parameters>
<responses>
<200>
<description>Success</description>
</200>
<400>
<description>Bad Request</description>
</400>
</responses>
</get>
<//base>
</paths>
</api_specification>

[Assistant]
Approach:
1. Task: Convert api specification 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:
{
  "openapi": "3.0.0",
  "info": {
    "title": "Horizontal interactive project API",
    "version": "1.0.0"
  },
  "paths": {
    "/base": {
      "get": {
        "summary": "Management send father actually special image.",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  }
}


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

[User]
Convert the following JSON to XML:
{
  "period": "March 2022",
  "total_revenue": 7500818,
  "units_sold": 73950,
  "channels": [
    {
      "name": "retail",
      "revenue": 528123,
      "growth": 12.05
    },
    {
      "name": "online",
      "revenue": 1160273,
      "growth": 23.93
    }
  ],
  "top_products": [
    {
      "sku": "SKU-6153",
      "sales": 328911
    },
    {
      "sku": "SKU-4483",
      "sales": 21251
    },
    {
      "sku": "SKU-5114",
      "sales": 21486
    }
  ]
}

[Assistant]
Approach:
1. Task: Convert sales analytics 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"?>
<sales_analytics>
<period>March 2022</period>
<total_revenue>7500818</total_revenue>
<units_sold>73950</units_sold>
<channels>
<name>retail</name>
<revenue>528123</revenue>
<growth>12.05</growth>
</channels>
<channels>
<name>online</name>
<revenue>1160273</revenue>
<growth>23.93</growth>
</channels>
<top_products>
<sku>SKU-6153</sku>
<sales>328911</sales>
</top_products>
<top_products>
<sku>SKU-4483</sku>
<sales>21251</sales>
</top_products>
<top_products>
<sku>SKU-5114</sku>
<sales>21486</sales>
</top_products>
</sales_analytics>


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

[User] Output financial report as TOML.

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

Output:
company = "Mcintyre, French and Sherman"
ticker = "GRIC"
quarter = "Q4 2021"
revenue = 78125638
expenses = 13448897
net_income = 14876002
eps = 9.04

[metrics]
profit_margin = 9.81
roe = 23.34


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

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

[Assistant]
Approach:
1. Task: Create student assessment 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:
{
  "assessment_id": "ASMT-577861",
  "student_id": "STU-664280",
  "course_id": "CRS-8099",
  "type": "exam",
  "date": "2026-01-06",
  "scores": [
    {
      "question": 1,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 0,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 5,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 6,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 3,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 0,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 1,
      "points_possible": 10
    }
  ],
  "total_score": 52,
  "percentage": 81.98,
  "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 financial report.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<financial_report>
<company>Smith-Glover</company>
<ticker>JROI</ticker>
<quarter>Q3 2023</quarter>
<revenue>95238846</revenue>
<expenses>30652579</expenses>
<net_income>5856951</net_income>
<eps>7.31</eps>
<metrics>
<profit_margin>9.94</profit_margin>
<roe>10.91</roe>
</metrics>
</financial_report>


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

[User] Generate product listing data in CSV format.

[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,Universal bottom-line system engine,225.75,PROD-325945,3.31,802,77x29x32cm,22.25,955
clothing,USD,True,Realigned neutral ability,312.76,PROD-600685,3.88,688,46x55x87cm,4.41,872
books,USD,True,Cross-platform solution-oriented framework,674.2,PROD-743990,4.76,455,59x58x21cm,38.77,368


[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-2063",
  "code": "FAH301",
  "title": "Ameliorated zero administration productivity 101",
  "instructor": "Aaron Bailey",
  "credits": 4,
  "term": "Fall 2023",
  "schedule": [
    {
      "week": 1,
      "topic": "health"
    },
    {
      "week": 2,
      "topic": "buy"
    },
    {
      "week": 3,
      "topic": "conference"
    },
    {
      "week": 4,
      "topic": "late"
    },
    {
      "week": 5,
      "topic": "fear"
    },
    {
      "week": 6,
      "topic": "ability"
    },
    {
      "week": 7,
      "topic": "control"
    },
    {
      "week": 8,
      "topic": "choose"
    },
    {
      "week": 9,
      "topic": "measure"
    },
    {
      "week": 10,
      "topic": "social"
    }
  ],
  "grading": {
    "homework": 30,
    "midterm": 30,
    "final": 40
  }
}

[Assistant]
Approach:
1. Task: Convert course syllabus 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"?>
<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 XML format. Think step-by-step, then generate syntactically perfect XML.

[User]
Convert the following JSON to XML:
{
  "review_id": "REV-7122533",
  "content": "Expert difficult hot radio mission. Throw southern he book way media particular.",
  "rating": 1,
  "date": "2026-01-06",
  "verified_purchase": false
}

[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>
<review_id>REV-7122533</review_id>
<content>Expert difficult hot radio mission. Throw southern he book way media particular.</content>
<rating>1</rating>
<date>2026-01-06</date>
<verified_purchase>False</verified_purchase>
</customer_review>


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

[User]
Reformat the data below from JSON to XML:
{
  "course_id": "CRS-8328",
  "code": "QKE428",
  "title": "Decentralized content-based leverage 101",
  "instructor": "Sarah Simon",
  "credits": 3,
  "term": "Fall 2022",
  "schedule": [
    {
      "week": 1,
      "topic": "whole"
    },
    {
      "week": 2,
      "topic": "table"
    },
    {
      "week": 3,
      "topic": "determine"
    },
    {
      "week": 4,
      "topic": "evening"
    },
    {
      "week": 5,
      "topic": "once"
    },
    {
      "week": 6,
      "topic": "some"
    },
    {
      "week": 7,
      "topic": "themselves"
    },
    {
      "week": 8,
      "topic": "table"
    }
  ],
  "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-8328</course_id>
QKE428
<title>Decentralized content-based leverage 101</title>
<instructor>Sarah Simon</instructor>
<credits>3</credits>
<term>Fall 2022</term>
<schedule>
<week>1</week>
<topic>whole</topic>
</schedule>
<schedule>
<week>2</week>
<topic>table</topic>
</schedule>
<schedule>
<week>3</week>
<topic>determine</topic>
</schedule>
<schedule>
<week>4</week>
<topic>evening</topic>
</schedule>
<schedule>
<week>5</week>
<topic>once</topic>
</schedule>
<schedule>
<week>6</week>
<topic>some</topic>
</schedule>
<schedule>
<week>7</week>
<topic>themselves</topic>
</schedule>
<schedule>
<week>8</week>
<topic>table</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]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Pre-emptive interactive encryption API</title>
<version>1.0.0</version>
</info>
<paths>
</air>
<get>
<summary>Final democratic whatever event director guy.</summary>
<parameters>
<name>param0</name>
<in>query</in>
<type>string</type>
</parameters>
<responses>
<200>
<description>Success</description>
</200>
<400>
<description>Bad Request</description>
</400>
</responses>
</get>
<//air>
</paths>
</api_specification>

[Assistant]
Approach:
1. Task: Convert api specification 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:
{
  "openapi": "3.0.0",
  "info": {
    "title": "Pre-emptive interactive encryption API",
    "version": "1.0.0"
  },
  "paths": {
    "/air": {
      "get": {
        "summary": "Final democratic whatever event director guy.",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  }
}


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

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

[Assistant]
Approach:
1. Task: Convert api specification 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:
{
  "openapi": "3.0.0",
  "info": {
    "title": "Business-focused zero administration encryption API",
    "version": "1.0.0"
  },
  "paths": {
    "/teach": {
      "get": {
        "summary": "Government trade direction personal reason hundred",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          },
          {
            "name": "param1",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  }
}


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

[User] Output customer review as XML.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<review_id>REV-8549692</review_id>
<product_id>PROD-108019</product_id>
<user_id>a4c4fbe3-7a0e-49f5-b14b-2ab1ca2d6ed5</user_id>
<rating>4</rating>
<title>Development know write believe teacher ability.</title>
<content>Guy generation provide economy test bit. Page cost and.
Arm test ok green. Likely card reality school stop something those.
Your spend discuss yeah hear. Same language box us magazine simple.</content>
<date>2026-01-06</date>
<verified_purchase>True</verified_purchase>
<helpful_votes>22</helpful_votes>
</customer_review>


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

[User] Output api specification as YAML.

[Assistant]
Approach:
1. Task: Create api specification 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:
openapi: 3.0.0
info:
  title: Horizontal interactive project API
  version: 1.0.0
paths:
  /base:
    get:
      summary: Management send father actually special image.
      parameters:
      - name: param0
        in: query
        type: string
      responses:
        '200':
          description: Success
        '400':
          description: Bad Request


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

[User] Generate lab result data in YAML format.

[Assistant]
Approach:
1. Task: Create lab result 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:
result_id: LAB-3941350
patient_mrn: MRN-739958
order_date: '2026-01-01'
panel: CBC
results:
- test: Glucose
  value: 134.1
  unit: mg/dL
  flag: high
- test: WBC
  value: 188.7
  unit: g/dL
  flag: low
- test: Hemoglobin
  value: 142.9
  unit: mg/dL
  flag: high
- test: Hemoglobin
  value: 117.3
  unit: g/dL
  flag: normal
- test: Glucose
  value: 159.8
  unit: g/dL
  flag: normal
- test: WBC
  value: 131.5
  unit: g/dL
  flag: normal


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

[User] Produce a CSV document for a product listing.

[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,Implemented multimedia focus group,524.9,PROD-524008,2.56,633,80x44x77cm,40.1,714
electronics,USD,True,Team-oriented multi-state throughput,635.65,PROD-270227,4.75,372,27x73x85cm,0.69,932
electronics,USD,True,Robust coherent functionalities,471.03,PROD-496343,1.49,761,14x34x27cm,8.37,2
electronics,USD,True,Diverse didactic data-warehouse,628.69,PROD-513692,4.88,552,42x62x20cm,4.11,733
electronics,USD,True,Up-sized motivating infrastructure,350.07,PROD-474691,4.54,1,43x42x97cm,26.52,742


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

[User] Output sales analytics as XML.

[Assistant]
Approach:
1. Task: Create sales analytics 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"?>
<sales_analytics>
<period>December 2023</period>
<total_revenue>5338205</total_revenue>
<units_sold>90572</units_sold>
<channels>
<name>wholesale</name>
<revenue>2316482</revenue>
<growth>-1.07</growth>
</channels>
<channels>
<name>online</name>
<revenue>3744469</revenue>
<growth>-0.81</growth>
</channels>
<top_products>
<sku>SKU-4601</sku>
<sales>454934</sales>
</top_products>
<top_products>
<sku>SKU-9892</sku>
<sales>55264</sales>
</top_products>
<top_products>
<sku>SKU-8319</sku>
<sales>254442</sales>
</top_products>
</sales_analytics>


[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:
{
  "article_id": "ART-8136358",
  "headline": "Realigned multimedia paradigm",
  "author": "Brian White",
  "published": "2026-01-02T14:21:25.908532",
  "section": "Sports",
  "content": "Give model worry sense. Including reflect teacher near image.\nCulture kitchen run first would. Agency media particularly past office every.\nBag water address admit. Skin tend Mr significant dark pretty. Painting water campaign.",
  "tags": [
    "involve",
    "service",
    "along",
    "stand"
  ],
  "views": 7987,
  "shares": 4175
}

[Assistant]
Approach:
1. Task: Convert news article 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"?>
<news_article>
<article_id>ART-8136358</article_id>
<headline>Realigned multimedia paradigm</headline>
<author>Brian White</author>
<published>2026-01-02T14:21:25.908532</published>

Sports

<content>Give model worry sense. Including reflect teacher near image.
Culture kitchen run first would. Agency media particularly past office every.
Bag water address admit. Skin tend Mr significant dark pretty. Painting water campaign.</content>
<tags>involve</tags>
<tags>service</tags>
<tags>along</tags>
<tags>stand</tags>
<views>7987</views>
<shares>4175</shares>
</news_article>


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

[User] Create a TOML representation of transaction record.

[Assistant]
Approach:
1. Task: Create transaction record 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:
txn_id = "TXN-15638187"
customer_id = "242fd3fb-d1fb-4e06-b998-4ca6fd25c6b7"
timestamp = "2026-01-07T13:51:27.047573"
subtotal = 1338.06
tax = 172.92
total = 2048.81
payment_method = "apple_pay"
[[items]]
sku = "SKU-16950"
qty = 3
price = 120.22

[[items]]
sku = "SKU-76122"
qty = 1
price = 377.76

[[items]]
sku = "SKU-41194"
qty = 3
price = 254.19

[[items]]
sku = "SKU-75246"
qty = 2
price = 418.85


[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:
{
  "post_id": "POST-93814090",
  "platform": "facebook",
  "user_id": "6a4446e9-5537-4ba1-bf03-5db2d36e07b9",
  "username": "tonyaguzman",
  "content": "Subject watch side owner new. Quality million clear hand clearly environmental. Forget face machine little check.",
  "timestamp": "2026-01-07T13:51:26.454281",
  "hashtags": [
    "#plan",
    "#area",
    "#foreign"
  ],
  "engagement": {
    "likes": 5322,
    "shares": 327,
    "comments": 152
  }
}

[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-93814090</post_id>
<platform>facebook</platform>
<user_id>6a4446e9-5537-4ba1-bf03-5db2d36e07b9</user_id>
<username>tonyaguzman</username>
<content>Subject watch side owner new. Quality million clear hand clearly environmental. Forget face machine little check.</content>
<timestamp>2026-01-07T13:51:26.454281</timestamp>
<hashtags>#plan</hashtags>
<hashtags>#area</hashtags>
<hashtags>#foreign</hashtags>
<engagement>
<likes>5322</likes>
<shares>327</shares>
<comments>152</comments>
</engagement>
</social_media_post>


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

[User] Generate error log data in XML format.

[Assistant]
Approach:
1. Task: Create error log 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"?>
<error_log>
<level>ERROR</level>
<service>writeService</service>
<error_id>85223c4c-4b76-4351-95ee-55a2460043f3</error_id>
</error_log>


[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"?>
<course_syllabus>
<course_id>CRS-3741</course_id>
XMJ312
<title>Managed incremental focus group 101</title>
<instructor>Rachel Diaz</instructor>
<credits>4</credits>
<term>Fall 2021</term>
<schedule>
<week>1</week>
<topic>body</topic>
</schedule>
<schedule>
<week>2</week>
<topic>rather</topic>
</schedule>
<schedule>
<week>3</week>
<topic>song</topic>
</schedule>
<schedule>
<week>4</week>
<topic>child</topic>
</schedule>
<schedule>
<week>5</week>
<topic>born</topic>
</schedule>
<schedule>
<week>6</week>
<topic>beyond</topic>
</schedule>
<schedule>
<week>7</week>
<topic>there</topic>
</schedule>
<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: 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:
{
  "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"
    },
    {
      "week": 2,
      "topic": "rather"
    },
    {
      "week": 3,
      "topic": "song"
    },
    {
      "week": 4,
      "topic": "child"
    },
    {
      "week": 5,
      "topic": "born"
    },
    {
      "week": 6,
      "topic": "beyond"
    },
    {
      "week": 7,
      "topic": "there"
    }
  ],
  "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] Produce a CSV document for a financial report.

[Assistant]
Approach:
1. Task: Create financial report 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:
company,eps,expenses,metrics_profit_margin,metrics_roe,net_income,quarter,revenue,ticker
Brooks LLC,3.56,61265128,26.89,20.49,10426094,Q1 2020,30917299,HFOB
Moore-Fisher,9.25,79657155,8.07,8.55,1215082,Q4 2021,65147243,ABGJ
Parsons Ltd,2.79,36392887,12.87,12.45,16676177,Q2 2020,63436953,DCLS
Day PLC,1.43,27995430,23.59,13.33,1293190,Q1 2024,60094250,ORIH


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

[User]
Convert the following JSON to XML:
{
  "note_id": "CN-3508494",
  "patient": {
    "mrn": "MRN-721804",
    "age": 51,
    "gender": "F"
  },
  "encounter_date": "2026-01-06",
  "chief_complaint": "chest pain",
  "vitals": {
    "bp": "130/109",
    "hr": 78,
    "temp_f": 100.6
  },
  "assessment": [
    {
      "problem": "hypertension",
      "icd10": "K96"
    },
    {
      "problem": "diabetes",
      "icd10": "K86"
    }
  ]
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<clinical_note>
<note_id>CN-3508494</note_id>
<patient>
<mrn>MRN-721804</mrn>
<age>51</age>
<gender>F</gender>
</patient>
<encounter_date>2026-01-06</encounter_date>
<chief_complaint>chest pain</chief_complaint>
<vitals>
<bp>130/109</bp>

78

<temp_f>100.6</temp_f>
</vitals>
<assessment>
<problem>hypertension</problem>
<icd10>K96</icd10>
</assessment>
<assessment>
<problem>diabetes</problem>
<icd10>K86</icd10>
</assessment>
</clinical_note>


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

[User]
Reformat the data below from XML to YAML:
<?xml version="1.0" encoding="UTF-8"?>
<product_listing>
<product_id>PROD-428311</product_id>
<name>Object-based value-added workforce</name>
<category>books</category>
<price>802.3</price>
<currency>USD</currency>
<stock>719</stock>
<is_available>True</is_available>
<rating>1.5</rating>
<reviews>81</reviews>
<specs>
<weight_kg>27.85</weight_kg>
<dimensions>99x87x32cm</dimensions>
</specs>
</product_listing>

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

Output:
product_id: PROD-428311
name: Object-based value-added workforce
category: books
price: 802.3
currency: USD
stock: 719
is_available: true
rating: 1.5
reviews: 81
specs:
  weight_kg: 27.85
  dimensions: 99x87x32cm


[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: 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:
assessment_id = "ASMT-817642"
student_id = "STU-222420"
course_id = "CRS-8326"
type = "assignment"
date = "2026-01-03"
total_score = 60
percentage = 56.31
grade = "A"
[[scores]]
question = 1
points_earned = 9
points_possible = 10

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

[[scores]]
question = 3
points_earned = 0
points_possible = 10

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

[[scores]]
question = 5
points_earned = 7
points_possible = 10

[[scores]]
question = 6
points_earned = 4
points_possible = 10

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

[[scores]]
question = 8
points_earned = 7
points_possible = 10


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

[User]
Transform this YAML data into TOML format:
period: December 2023
total_revenue: 5338205
units_sold: 90572
channels:
- name: wholesale
  revenue: 2316482
  growth: -1.07
- name: online
  revenue: 3744469
  growth: -0.81
top_products:
- sku: SKU-4601
  sales: 454934
- sku: SKU-9892
  sales: 55264
- sku: SKU-8319
  sales: 254442

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

Output:
period = "December 2023"
total_revenue = 5338205
units_sold = 90572
[[channels]]
name = "wholesale"
revenue = 2316482
growth = -1.07

[[channels]]
name = "online"
revenue = 3744469
growth = -0.81

[[top_products]]
sku = "SKU-4601"
sales = 454934

[[top_products]]
sku = "SKU-9892"
sales = 55264

[[top_products]]
sku = "SKU-8319"
sales = 254442


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

[User]
Transform this TOML data into YAML format:
period = "February 2020"
total_revenue = 2337421
units_sold = 23839
[[channels]]
name = "retail"
revenue = 3840938
growth = 18.52

[[channels]]
name = "wholesale"
revenue = 1512471
growth = 13.02

[[top_products]]
sku = "SKU-1744"
sales = 276633

[[top_products]]
sku = "SKU-5145"
sales = 26445

[[top_products]]
sku = "SKU-9218"
sales = 412054

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

Output:
period: February 2020
total_revenue: 2337421
units_sold: 23839
channels:
- name: retail
  revenue: 3840938
  growth: 18.52
- name: wholesale
  revenue: 1512471
  growth: 13.02
top_products:
- sku: SKU-1744
  sales: 276633
- sku: SKU-5145
  sales: 26445
- sku: SKU-9218
  sales: 412054


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

[User]
Reformat the data below from JSON to XML:
{
  "rx_id": "RX-4278484",
  "patient_mrn": "MRN-990980",
  "prescriber": "Andrew Kelly",
  "date": "2026-01-06",
  "medications": [
    {
      "name": "Metformin",
      "dosage": "10mg",
      "frequency": "BID",
      "quantity": 30
    },
    {
      "name": "Atorvastatin",
      "dosage": "10mg",
      "frequency": "BID",
      "quantity": 90
    }
  ]
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<prescription>
<rx_id>RX-4278484</rx_id>
<patient_mrn>MRN-990980</patient_mrn>
<prescriber>Andrew Kelly</prescriber>
<date>2026-01-06</date>
<medications>
<name>Metformin</name>
<dosage>10mg</dosage>
<frequency>BID</frequency>
<quantity>30</quantity>
</medications>
<medications>
<name>Atorvastatin</name>
<dosage>10mg</dosage>
<frequency>BID</frequency>
<quantity>90</quantity>
</medications>
</prescription>


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

[User] Output research paper as TOML.

[Assistant]
Approach:
1. Task: Create research paper 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:
paper_id = "arXiv:2020.57295"
title = "Persevering global groupware"
abstract = "Stand season mind indicate either. Buy gas keep skin."
keywords = [ "stock", "member", "laugh", "language", "right",]
citations = 204
[[authors]]
name = "Edwin Moore"
affiliation = "Smith-Jones"
email = "bowenzachary@example.net"

[[authors]]
name = "Anna Collins"
affiliation = "Thomas, Rogers and Baldwin"
email = "thill@example.com"

[[authors]]
name = "Mrs. Mary Delacruz MD"
affiliation = "French, Rodriguez and Johnson"
email = "amywest@example.org"

[publication]
venue = "Cell"
year = 2022
doi = "10.9461/HDZk"


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

[User] Create a TOML representation of sales analytics.

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

Output:
period = "March 2022"
total_revenue = 7500818
units_sold = 73950
[[channels]]
name = "retail"
revenue = 528123
growth = 12.05

[[channels]]
name = "online"
revenue = 1160273
growth = 23.93

[[top_products]]
sku = "SKU-6153"
sales = 328911

[[top_products]]
sku = "SKU-4483"
sales = 21251

[[top_products]]
sku = "SKU-5114"
sales = 21486


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

[User] Generate sales analytics data in XML format.

[Assistant]
Approach:
1. Task: Create sales analytics 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"?>
<sales_analytics>
<period>February 2022</period>
<total_revenue>6033804</total_revenue>
<units_sold>27183</units_sold>
<channels>
<name>wholesale</name>
<revenue>4147239</revenue>
<growth>40.37</growth>
</channels>
<channels>
<name>online</name>
<revenue>2663137</revenue>
<growth>9.96</growth>
</channels>
<top_products>
<sku>SKU-2538</sku>
<sales>420940</sales>
</top_products>
<top_products>
<sku>SKU-8680</sku>
<sales>364206</sales>
</top_products>
<top_products>
<sku>SKU-2062</sku>
<sales>350623</sales>
</top_products>
</sales_analytics>


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

[User] Output product listing as XML.

[Assistant]
Approach:
1. Task: Create product listing 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"?>
<product_listing>
<product_id>PROD-110536</product_id>
<name>Organized didactic parallelism</name>
<category>clothing</category>
<price>68.12</price>
<currency>USD</currency>
<stock>153</stock>
<is_available>True</is_available>
<rating>1.45</rating>
<reviews>277</reviews>
<specs>
<weight_kg>1.85</weight_kg>
<dimensions>33x70x14cm</dimensions>
</specs>
</product_listing>


[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: 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-2063"
code = "FAH301"
title = "Ameliorated zero administration productivity 101"
instructor = "Aaron Bailey"
credits = 4
term = "Fall 2023"
[[schedule]]
week = 1
topic = "health"

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

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

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

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

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

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

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

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

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

[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] Generate course syllabus data in JSON format.

[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-3741",
  "code": "XMJ312",
  "title": "Managed incremental focus group 101",
  "instructor": "Rachel Diaz",
  "credits": 4,
  "term": "Fall 2021",
  "schedule": [
    {
      "week": 1,
      "topic": "body"
    },
    {
      "week": 2,
      "topic": "rather"
    },
    {
      "week": 3,
      "topic": "song"
    },
    {
      "week": 4,
      "topic": "child"
    },
    {
      "week": 5,
      "topic": "born"
    },
    {
      "week": 6,
      "topic": "beyond"
    },
    {
      "week": 7,
      "topic": "there"
    }
  ],
  "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] Generate student assessment data in CSV format.

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

Output:
assessment_id,code,course_id,credits,date,grade,grading_final,grading_homework,grading_midterm,instructor,percentage,schedule,scores,student_id,term,title,total_score,type
ASMT-475777,,CRS-2241,,2026-01-06,B,,,,,81.54,,"[{""question"": 1, ""points_earned"": 8, ""points_possible"": 10}, {""question"": 2, ""points_earned"": 6, ""po",STU-613124,,,75,assignment
,TZG120,CRS-4715,4,,,40,30,30,Jesus White,,"[{""week"": 1, ""topic"": ""add""}, {""week"": 2, ""topic"": ""protect""}, {""week"": 3, ""topic"": ""low""}, {""week"":",,,Fall 2020,Total mission-critical architecture 101,,
,MVH294,CRS-6858,3,,,40,30,30,Joseph Stewart,,"[{""week"": 1, ""topic"": ""democratic""}, {""week"": 2, ""topic"": ""break""}, {""week"": 3, ""topic"": ""right""}, {",,,Spring 2023,De-engineered methodical time-frame 101,,
,QJL265,CRS-8275,3,,,40,30,30,Melissa Kline,,"[{""week"": 1, ""topic"": ""important""}, {""week"": 2, ""topic"": ""soldier""}, {""week"": 3, ""topic"": ""so""}, {""w",,,Spring 2024,Function-based optimal portal 101,,


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

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

[Assistant]
Approach:
1. Task: Create transaction record 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:
customer_id,items,payment_method,subtotal,tax,timestamp,total,txn_id
39de4165-2950-403a-b7cf-252ec7bafdcc,"[{""sku"": ""SKU-68017"", ""qty"": 5, ""price"": 287.63}, {""sku"": ""SKU-13598"", ""qty"": 1, ""price"": 397.9}, {""",credit_card,964.6,142.48,2026-01-07T13:51:25.757679,1270.74,TXN-38439045
8e15dc93-19b0-4a46-a65b-a0f2975f0da5,"[{""sku"": ""SKU-26136"", ""qty"": 1, ""price"": 479.13}]",apple_pay,158.49,145.25,2026-01-07T13:51:25.758879,1793.23,TXN-44154413
f3c8b8ca-c61b-44cb-87be-d8bf22380d1b,"[{""sku"": ""SKU-65105"", ""qty"": 3, ""price"": 368.07}, {""sku"": ""SKU-23963"", ""qty"": 4, ""price"": 14.41}]",apple_pay,1566.7,178.05,2026-01-07T13:51:25.758927,1347.17,TXN-20568264


[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: simple - 3-5 fields, minimal nesting
3. Format rules: consistent indentation, colon-space syntax, hyphen lists
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
total_score: 65
percentage: 51.02
assessment_id: ASMT-810488


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

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

[Assistant]
Approach:
1. Task: Create api specification 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"?>
<api_specification>
<paths>
</population>
<get>
<summary>Lead room develop man according street century.</summary>
<parameters>
<name>param0</name>
<in>query</in>
<type>string</type>
</parameters>
<parameters>
<name>param1</name>
<in>query</in>
<type>string</type>
</parameters>
<parameters>
<name>param2</name>
<in>query</in>
<type>string</type>
</parameters>
<responses>
<200>
<description>Success</description>
</200>
<400>
<description>Bad Request</description>
</400>
</responses>
</get>
<//population>
</paths>
<info>
<title>Ameliorated radical initiative API</title>
<version>1.0.0</version>
</info>
<openapi>3.0.0</openapi>
</api_specification>


[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"?>
<transaction_record>
<subtotal>1655.93</subtotal>
<items>
<sku>SKU-62708</sku>
<qty>3</qty>
<price>121.39</price>
</items>
<tax>19.12</tax>
<total>1424.63</total>
</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:
{
  "subtotal": 1655.93,
  "items": [
    {
      "sku": "SKU-62708",
      "qty": 3,
      "price": 121.39
    }
  ],
  "tax": 19.12,
  "total": 1424.63
}


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

[User] Create a TOML representation of customer review.

[Assistant]
Approach:
1. Task: Create customer review 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:
review_id = "REV-5911912"
product_id = "PROD-652506"
user_id = "e81c58cf-1a13-4302-a93a-5e1fbbfd28db"
rating = 3
title = "Their husband whole president threat argue."
content = "Happen member step can deal animal fine. Like among study from book.\nDemocratic significant every sport next want. List religious computer rise wrong."
date = "2026-01-02"
verified_purchase = true
helpful_votes = 61


[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"?>
<sales_analytics>
<period>June 2021</period>
<total_revenue>4317671</total_revenue>
<units_sold>11582</units_sold>
<channels>
<name>wholesale</name>
<revenue>2780960</revenue>
<growth>22.76</growth>
</channels>
<channels>
<name>retail</name>
<revenue>4140341</revenue>
<growth>-9.84</growth>
</channels>
<top_products>
<sku>SKU-8636</sku>
<sales>261407</sales>
</top_products>
<top_products>
<sku>SKU-9950</sku>
<sales>107242</sales>
</top_products>
<top_products>
<sku>SKU-8311</sku>
<sales>494004</sales>
</top_products>
</sales_analytics>

[Assistant]
Approach:
1. Task: Convert sales analytics 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:
{
  "period": "June 2021",
  "total_revenue": 4317671,
  "units_sold": 11582,
  "channels": [
    {
      "name": "wholesale",
      "revenue": 2780960,
      "growth": 22.76
    },
    {
      "name": "retail",
      "revenue": 4140341,
      "growth": -9.84
    }
  ],
  "top_products": [
    {
      "sku": "SKU-8636",
      "sales": 261407
    },
    {
      "sku": "SKU-9950",
      "sales": 107242
    },
    {
      "sku": "SKU-8311",
      "sales": 494004
    }
  ]
}


[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: 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:
post_id = "POST-90196326"
platform = "facebook"
user_id = "146c178d-e548-4357-8cd4-e8464cea2f9b"
username = "kevincunningham"
content = "Three would identify method across operation opportunity.\nWhat realize number. Country perform simple team player. Improve order east mother news magazine trade.\nCentral thus simple thousand morning."
timestamp = "2026-01-07T13:51:26.698310"
hashtags = [ "#pay", "#keep",]

[engagement]
likes = 458
shares = 383
comments = 63


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

[User] Create a JSON representation of prescription.

[Assistant]
Approach:
1. Task: Create prescription 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:
{
  "rx_id": "RX-9719971",
  "patient_mrn": "MRN-909141",
  "prescriber": "Heather Stephens",
  "date": "2026-01-05",
  "medications": [
    {
      "name": "Atorvastatin",
      "dosage": "20mg",
      "frequency": "daily",
      "quantity": 30
    }
  ]
}


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

[User]
Reformat the data below from YAML to CSV:
result_id: LAB-9548003
patient_mrn: MRN-322322
order_date: '2026-01-03'
panel: CMP
results:
- test: Glucose
  value: 67.0
  unit: g/dL
  flag: high
- test: Hemoglobin
  value: 66.7
  unit: mg/dL
  flag: low
- test: Glucose
  value: 118.1
  unit: mg/dL
  flag: normal
- test: Hemoglobin
  value: 198.6
  unit: mg/dL
  flag: normal
- test: Glucose
  value: 167.9
  unit: mg/dL
  flag: low
- test: Hemoglobin
  value: 143.5
  unit: mg/dL
  flag: normal
- test: Glucose
  value: 150.3
  unit: g/dL
  flag: low

[Assistant]
Approach:
1. Task: Convert lab result from YAML 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
2026-01-03,CMP,MRN-322322,LAB-9548003,"[{""test"": ""Glucose"", ""value"": 67.0, ""unit"": ""g/dL"", ""flag"": ""high""}, {""test"": ""Hemoglobin"", ""value"":"
2026-01-02,CBC,MRN-470224,LAB-4309449,"[{""test"": ""WBC"", ""value"": 84.5, ""unit"": ""mg/dL"", ""flag"": ""low""}, {""test"": ""Glucose"", ""value"": 184.9,"
2026-01-04,CMP,MRN-210418,LAB-6311661,"[{""test"": ""WBC"", ""value"": 78.7, ""unit"": ""g/dL"", ""flag"": ""high""}, {""test"": ""WBC"", ""value"": 59.9, ""uni"
2026-01-02,Lipid,MRN-949225,LAB-5947677,"[{""test"": ""WBC"", ""value"": 155.2, ""unit"": ""mg/dL"", ""flag"": ""normal""}, {""test"": ""WBC"", ""value"": 85.7, "
2026-01-03,CMP,MRN-314491,LAB-7337985,"[{""test"": ""Glucose"", ""value"": 96.6, ""unit"": ""g/dL"", ""flag"": ""normal""}, {""test"": ""Glucose"", ""value"": "


[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:
{
  "rx_id": "RX-2317847",
  "patient_mrn": "MRN-412331",
  "prescriber": "Tammy Adams",
  "date": "2026-01-01",
  "medications": [
    {
      "name": "Lisinopril",
      "dosage": "10mg",
      "frequency": "BID",
      "quantity": 60
    },
    {
      "name": "Lisinopril",
      "dosage": "10mg",
      "frequency": "BID",
      "quantity": 90
    },
    {
      "name": "Atorvastatin",
      "dosage": "5mg",
      "frequency": "BID",
      "quantity": 30
    }
  ]
}

[Assistant]
Approach:
1. Task: Convert prescription 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"?>
<prescription>
<rx_id>RX-2317847</rx_id>
<patient_mrn>MRN-412331</patient_mrn>
<prescriber>Tammy Adams</prescriber>
<date>2026-01-01</date>
<medications>
<name>Lisinopril</name>
<dosage>10mg</dosage>
<frequency>BID</frequency>
<quantity>60</quantity>
</medications>
<medications>
<name>Lisinopril</name>
<dosage>10mg</dosage>
<frequency>BID</frequency>
<quantity>90</quantity>
</medications>
<medications>
<name>Atorvastatin</name>
<dosage>5mg</dosage>
<frequency>BID</frequency>
<quantity>30</quantity>
</medications>
</prescription>


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

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

[Assistant]
Approach:
1. Task: Create student assessment 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:
assessment_id = "ASMT-946690"
student_id = "STU-268675"
course_id = "CRS-1216"
type = "assignment"
date = "2026-01-01"
total_score = 81
percentage = 50.49
grade = "B"
[[scores]]
question = 1
points_earned = 10
points_possible = 10

[[scores]]
question = 2
points_earned = 1
points_possible = 10

[[scores]]
question = 3
points_earned = 2
points_possible = 10

[[scores]]
question = 4
points_earned = 8
points_possible = 10

[[scores]]
question = 5
points_earned = 2
points_possible = 10

[[scores]]
question = 6
points_earned = 5
points_possible = 10

[[scores]]
question = 7
points_earned = 8
points_possible = 10

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

[[scores]]
question = 9
points_earned = 0
points_possible = 10

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

[[scores]]
question = 11
points_earned = 2
points_possible = 10

[[scores]]
question = 12
points_earned = 2
points_possible = 10