[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:
{
  "expenses": 65628233,
  "eps": 5.75,
  "quarter": "Q2 2023",
  "revenue": 73745517,
  "net_income": 6367407
}

[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>
<expenses>65628233</expenses>
<eps>5.75</eps>
<quarter>Q2 2023</quarter>
<revenue>73745517</revenue>
<net_income>6367407</net_income>
</financial_report>


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

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

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

Output:
post_id = "POST-69367106"
platform = "twitter"
user_id = "7643b70d-1c60-436f-974e-7bc6cee5e032"
username = "gordonalexander"
content = "See personal couple road president most next. Laugh teach lawyer character work present.\nPage give education middle. Couple save view media instead police guy. Enough test notice capital size."
timestamp = "2026-01-07T13:51:25.991400"
hashtags = [ "#PM", "#stage", "#government",]

[engagement]
likes = 1911
shares = 761
comments = 62


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

[User] Output student assessment as YAML.

[Assistant]
Approach:
1. Task: Create student assessment 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:
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]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<lab_result>
<result_id>LAB-3941350</result_id>
<patient_mrn>MRN-739958</patient_mrn>
<order_date>2026-01-01</order_date>
<panel>CBC</panel>
<results>
<test>Glucose</test>
<value>134.1</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>WBC</test>
<value>188.7</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>142.9</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>117.3</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Glucose</test>
<value>159.8</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>WBC</test>
<value>131.5</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
</lab_result>

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

Output:
{
  "result_id": "LAB-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 XML format. Think step-by-step, then generate syntactically perfect XML.

[User]
Convert the following JSON to XML:
{
  "result_id": "LAB-5383313",
  "patient_mrn": "MRN-584871",
  "order_date": "2026-01-06",
  "panel": "CMP",
  "results": [
    {
      "test": "Glucose",
      "value": 194.0,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 67.1,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "Glucose",
      "value": 195.1,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "Hemoglobin",
      "value": 146.6,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "WBC",
      "value": 119.8,
      "unit": "mg/dL",
      "flag": "normal"
    }
  ]
}

[Assistant]
Approach:
1. Task: Convert lab result 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"?>
<lab_result>
<result_id>LAB-5383313</result_id>
<patient_mrn>MRN-584871</patient_mrn>
<order_date>2026-01-06</order_date>
<panel>CMP</panel>
<results>
<test>Glucose</test>
<value>194.0</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>67.1</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Glucose</test>
<value>195.1</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>146.6</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>WBC</test>
<value>119.8</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
</lab_result>


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<transaction_record>
<txn_id>TXN-28879814</txn_id>
<customer_id>b13e97b5-e84b-41ec-9dea-05b4809cdd35</customer_id>
<timestamp>2026-01-07T13:51:25.895711</timestamp>
<items>
<sku>SKU-36351</sku>
<qty>1</qty>
<price>310.41</price>
</items>
<items>
<sku>SKU-26629</sku>
<qty>2</qty>
<price>119.44</price>
</items>
<items>
<sku>SKU-75447</sku>
<qty>3</qty>
<price>127.79</price>
</items>
<items>
<sku>SKU-81003</sku>
<qty>3</qty>
<price>336.59</price>
</items>
<subtotal>994.66</subtotal>
<tax>143.59</tax>
<total>1762.36</total>
<payment_method>apple_pay</payment_method>
</transaction_record>

[Assistant]
Approach:
1. Task: Convert transaction record 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:
{
  "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 TOML format. Think step-by-step, then generate syntactically perfect TOML.

[User] Create a TOML representation of product listing.

[Assistant]
Approach:
1. Task: Create product listing in TOML
2. Complexity: 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:
product_id = "PROD-831490"
name = "Seamless optimal task-force"
category = "electronics"
price = 975.8
currency = "USD"
stock = 924
is_available = true
rating = 2.71
reviews = 121

[specs]
weight_kg = 17.77
dimensions = "52x27x46cm"


[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: 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:
{
  "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] Output api specification as JSON.

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

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


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

[User] Output prescription as YAML.

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

Output:
date: '2026-01-06'
patient_mrn: MRN-259808
rx_id: RX-8539167
prescriber: Joseph Griffin
medications:
- name: Atorvastatin
  dosage: 10mg
  frequency: daily
  quantity: 90
- name: Lisinopril
  dosage: 10mg
  frequency: TID
  quantity: 30
- name: Metformin
  dosage: 5mg
  frequency: BID
  quantity: 30


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

[User] Generate course syllabus data in CSV format.

[Assistant]
Approach:
1. Task: Create course syllabus 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:
code,course_id,credits,grading_final,grading_homework,grading_midterm,instructor,schedule,term,title
FAH301,CRS-2063,4,40,30,30,Aaron Bailey,"[{""week"": 1, ""topic"": ""health""}, {""week"": 2, ""topic"": ""buy""}, {""week"": 3, ""topic"": ""conference""}, {""",Fall 2023,Ameliorated zero administration productivity 101
ZZJ232,CRS-4657,4,40,30,30,Jordan Aguirre,"[{""week"": 1, ""topic"": ""buy""}, {""week"": 2, ""topic"": ""today""}, {""week"": 3, ""topic"": ""trouble""}, {""week",Spring 2020,Seamless methodical database 101
MAI413,CRS-1801,3,40,30,30,Steven Massey,"[{""week"": 1, ""topic"": ""that""}, {""week"": 2, ""topic"": ""ask""}, {""week"": 3, ""topic"": ""detail""}, {""week"":",Spring 2022,Programmable analyzing instruction set 101


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

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


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

[User] Produce a JSON document for a 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-7665793",
  "patient_mrn": "MRN-934255",
  "prescriber": "Danielle Brown",
  "date": "2026-01-06",
  "medications": [
    {
      "name": "Atorvastatin",
      "dosage": "20mg",
      "frequency": "daily",
      "quantity": 90
    },
    {
      "name": "Atorvastatin",
      "dosage": "5mg",
      "frequency": "BID",
      "quantity": 90
    },
    {
      "name": "Metformin",
      "dosage": "5mg",
      "frequency": "BID",
      "quantity": 60
    }
  ]
}


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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<lab_result>
<result_id>LAB-5956795</result_id>
<patient_mrn>MRN-953048</patient_mrn>
<order_date>2026-01-05</order_date>
<panel>CBC</panel>
<results>
<test>Glucose</test>
<value>138.6</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>69.4</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>89.7</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>191.9</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>WBC</test>
<value>169.5</value>
<unit>mg/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Glucose</test>
<value>187.7</value>
<unit>mg/dL</unit>
<flag>low</flag>
</results>
<results>
<test>WBC</test>
<value>120.0</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
</lab_result>


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

[User] Create a XML representation of prescription.

[Assistant]
Approach:
1. Task: Create prescription 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"?>
<prescription>
<rx_id>RX-8350891</rx_id>
<patient_mrn>MRN-446802</patient_mrn>
<prescriber>James Bryant</prescriber>
<date>2026-01-03</date>
<medications>
<name>Lisinopril</name>
<dosage>10mg</dosage>
<frequency>daily</frequency>
<quantity>90</quantity>
</medications>
<medications>
<name>Metformin</name>
<dosage>20mg</dosage>
<frequency>TID</frequency>
<quantity>30</quantity>
</medications>
</prescription>


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

[User]
Convert the following XML to CSV:
<?xml version="1.0" encoding="UTF-8"?>
<prescription>
<rx_id>RX-9346457</rx_id>
<patient_mrn>MRN-685856</patient_mrn>
<prescriber>Thomas Archer</prescriber>
<date>2026-01-05</date>
<medications>
<name>Lisinopril</name>
<dosage>20mg</dosage>
<frequency>daily</frequency>
<quantity>90</quantity>
</medications>
<medications>
<name>Atorvastatin</name>
<dosage>10mg</dosage>
<frequency>BID</frequency>
<quantity>60</quantity>
</medications>
</prescription>

[Assistant]
Approach:
1. Task: Convert prescription from XML 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:
date,medications,patient_mrn,prescriber,rx_id
2026-01-05,"[{""name"": ""Lisinopril"", ""dosage"": ""20mg"", ""frequency"": ""daily"", ""quantity"": 90}, {""name"": ""Atorvasta",MRN-685856,Thomas Archer,RX-9346457
2026-01-02,"[{""name"": ""Atorvastatin"", ""dosage"": ""5mg"", ""frequency"": ""TID"", ""quantity"": 90}, {""name"": ""Metformin""",MRN-570090,Brian Gallegos,RX-2913316
2026-01-04,"[{""name"": ""Lisinopril"", ""dosage"": ""10mg"", ""frequency"": ""daily"", ""quantity"": 60}]",MRN-923333,Joshua Thomas,RX-4486837


[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": "Rodriguez, Curry and Yates",
  "ticker": "KWAZ",
  "quarter": "Q1 2020",
  "revenue": 4863925,
  "expenses": 55129980,
  "net_income": 12179320,
  "eps": 7.94,
  "metrics": {
    "profit_margin": 29.26,
    "roe": 9.63
  }
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<financial_report>
<company>Rodriguez, Curry and Yates</company>
<ticker>KWAZ</ticker>
<quarter>Q1 2020</quarter>
<revenue>4863925</revenue>
<expenses>55129980</expenses>
<net_income>12179320</net_income>
<eps>7.94</eps>
<metrics>
<profit_margin>29.26</profit_margin>
<roe>9.63</roe>
</metrics>
</financial_report>


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

[User]
Convert the following JSON to XML:
{
  "effective_date": "2026-01-02",
  "term_months": 54,
  "status": "pending"
}

[Assistant]
Approach:
1. Task: Convert contract 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"?>
<contract>
<effective_date>2026-01-02</effective_date>
<term_months>54</term_months>
<status>pending</status>
</contract>


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

[User] Produce a CSV document for a lab result.

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

Output:
order_date,panel,patient_mrn,result_id,results
2026-01-04,Lipid,MRN-783803,LAB-9017474,"[{""test"": ""Glucose"", ""value"": 65.6, ""unit"": ""mg/dL"", ""flag"": ""high""}, {""test"": ""Glucose"", ""value"": 1"
2026-01-03,CMP,MRN-630917,LAB-4256757,"[{""test"": ""Glucose"", ""value"": 129.4, ""unit"": ""mg/dL"", ""flag"": ""normal""}, {""test"": ""Hemoglobin"", ""val"
2026-01-02,Lipid,MRN-401847,LAB-4028209,"[{""test"": ""WBC"", ""value"": 103.8, ""unit"": ""mg/dL"", ""flag"": ""low""}, {""test"": ""Glucose"", ""value"": 132.5"


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

[User] Create a XML representation of api specification.

[Assistant]
Approach:
1. Task: Create api specification 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"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Cross-group bottom-line algorithm API</title>
<version>1.0.0</version>
</info>
<paths>
</rule>
<get>
<summary>Center available level environment per away author</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>
<//rule>
</paths>
</api_specification>


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

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

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

Output:
openapi = "3.0.0"

[info]
title = "Networked system-worthy project API"
version = "1.0.0"

[paths."/somebody".get]
summary = "Threat common organization project."
[[paths."/somebody".get.parameters]]
name = "param0"
in = "query"
type = "string"

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

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

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


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

[User] Generate transaction record data in XML format.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<transaction_record>
<txn_id>TXN-60159725</txn_id>
<customer_id>13707a49-23b0-4133-8216-7e83986c9575</customer_id>
<timestamp>2026-01-07T13:51:27.689251</timestamp>
<items>
<sku>SKU-82899</sku>
<qty>5</qty>
<price>298.29</price>
</items>
<items>
<sku>SKU-51515</sku>
<qty>4</qty>
<price>343.78</price>
</items>
<items>
<sku>SKU-53336</sku>
<qty>3</qty>
<price>488.21</price>
</items>
<items>
<sku>SKU-52517</sku>
<qty>2</qty>
<price>291.79</price>
</items>
<subtotal>1914.1</subtotal>
<tax>175.88</tax>
<total>1360.6</total>
<payment_method>credit_card</payment_method>
</transaction_record>


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

[User] Create a TOML representation of financial report.

[Assistant]
Approach:
1. Task: Create financial report 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:
company = "Williams Ltd"
ticker = "IHFM"
quarter = "Q3 2022"
revenue = 93368790
expenses = 48847964
net_income = 12028281
eps = 9.18

[metrics]
profit_margin = 7.56
roe = 13.89


[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:
{
  "openapi": "3.0.0",
  "info": {
    "title": "Cross-group bottom-line algorithm API",
    "version": "1.0.0"
  },
  "paths": {
    "/rule": {
      "get": {
        "summary": "Center available level environment per away author",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          },
          {
            "name": "param1",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  }
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Cross-group bottom-line algorithm API</title>
<version>1.0.0</version>
</info>
<paths>
</rule>
<get>
<summary>Center available level environment per away author</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>
<//rule>
</paths>
</api_specification>


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

[User] Output customer review as CSV.

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

Output:
content,date,helpful_votes,product_id,rating,review_id,title,user_id,verified_purchase
Respond order far story by area affect. Important also catch down choice office necessary political.,,,,5,REV-2205395,,,
"Seem social natural war box. Individual without do speak kind. Yeah behind thus family try large.
Wo",2026-01-01,84,PROD-783315,4,REV-8247814,And determine nice city professor.,e2419ade-89d5-4ffd-afcf-3ca8dfbf0083,False
"Also out sell show allow none whole. Reduce order end hard seven camera close.
Movie involve old beh",2026-01-04,41,PROD-267667,2,REV-5750090,Goal although Democrat boy have our employee.,d7ec9da1-668a-440a-82d5-fc3a512710e7,True
Couple daughter year season stop. Institution some inside. Recent without most law.,2026-01-05,1,PROD-190905,3,REV-5636641,Get strong into score sing result list.,adc7fd92-c31f-46d6-8515-236be6a6118a,True


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

[User] Create a JSON representation of product listing.

[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-830951",
  "name": "Multi-layered tangible superstructure",
  "category": "clothing",
  "price": 269.31,
  "currency": "USD",
  "stock": 322,
  "is_available": true,
  "rating": 2.21,
  "reviews": 733,
  "specs": {
    "weight_kg": 46.04,
    "dimensions": "75x77x31cm"
  }
}


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

[User] Output financial report as YAML.

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

Output:
company: Taylor Ltd
ticker: AOED
quarter: Q1 2024
revenue: 69752271
expenses: 52626087
net_income: 18580243
eps: 1.63
metrics:
  profit_margin: 23.4
  roe: 21.22


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

[User] Create a CSV representation of contract.

[Assistant]
Approach:
1. Task: Create contract 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:
contract_id,effective_date,parties,status,term_months,value
CTR-640570,2026-01-06,"[{""name"": ""Mitchell-Clark"", ""role"": ""party_a""}, {""name"": ""Simmons-Marquez"", ""role"": ""party_b""}]",pending,52,450714
CTR-402606,2026-01-02,"[{""name"": ""King and Sons"", ""role"": ""party_a""}, {""name"": ""Jones Inc"", ""role"": ""party_b""}]",pending,12,876689
CTR-668906,2026-01-05,"[{""name"": ""Adams-Hudson"", ""role"": ""party_a""}, {""name"": ""Greene-Petty"", ""role"": ""party_b""}]",active,15,365324
CTR-421340,2026-01-02,"[{""name"": ""West-Phillips"", ""role"": ""party_a""}, {""name"": ""Roberts and Sons"", ""role"": ""party_b""}]",active,23,129621
CTR-556308,2026-01-01,"[{""name"": ""Johnson-Bautista"", ""role"": ""party_a""}, {""name"": ""Lopez, King and Lynn"", ""role"": ""party_b""",pending,22,84944


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

[User] Output course syllabus as YAML.

[Assistant]
Approach:
1. Task: Create course syllabus 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:
course_id: CRS-6204
code: WOR378
title: Multi-channeled bi-directional implementation 101
instructor: Charlene Houston
credits: 4
term: Spring 2023
schedule:
- week: 1
  topic: under
- week: 2
  topic: trade
- week: 3
  topic: good
- week: 4
  topic: grow
- week: 5
  topic: ability
- week: 6
  topic: experience
- week: 7
  topic: offer
- week: 8
  topic: account
grading:
  homework: 30
  midterm: 30
  final: 40


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

[User]
Transform this TOML data into XML format:
review_id = "REV-1274071"
product_id = "PROD-300785"
user_id = "c183a72e-4d6f-40ac-92b0-2d1073039571"
rating = 5
title = "Follow large high gas clear drug pretty else."
content = "Recent cause family writer. Old less control he woman. Coach quickly will.\nRelationship same against one stand agreement. Be fine occur ten energy resource wall. Nation ten continue."
date = "2026-01-06"
verified_purchase = true
helpful_votes = 37

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<review_id>REV-1274071</review_id>
<product_id>PROD-300785</product_id>
<user_id>c183a72e-4d6f-40ac-92b0-2d1073039571</user_id>
<rating>5</rating>
<title>Follow large high gas clear drug pretty else.</title>
<content>Recent cause family writer. Old less control he woman. Coach quickly will.
Relationship same against one stand agreement. Be fine occur ten energy resource wall. Nation ten continue.</content>
<date>2026-01-06</date>
<verified_purchase>True</verified_purchase>
<helpful_votes>37</helpful_votes>
</customer_review>


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

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

[Assistant]
Approach:
1. Task: Create experiment result 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:
conclusion,experiment_id,methodology_design,methodology_duration_days,methodology_sample_size,results,title
non-significant,EXP-574681,cohort,320,560,"[{""metric"": ""efficacy"", ""baseline"": 50.77, ""endpoint"": 70.83, ""p_value"": 0.3046}, {""metric"": ""effica",Effect of anyone on society
non-significant,EXP-478214,observational,317,566,"[{""metric"": ""efficacy"", ""baseline"": 98.07, ""endpoint"": 88.51, ""p_value"": 0.4526}, {""metric"": ""effica",Effect of scientist on up
non-significant,EXP-189174,cohort,102,122,"[{""metric"": ""efficacy"", ""baseline"": 66.41, ""endpoint"": 56.69, ""p_value"": 0.4311}, {""metric"": ""safety",Effect of old on series
significant,EXP-911675,RCT,122,431,"[{""metric"": ""safety"", ""baseline"": 15.14, ""endpoint"": 85.6, ""p_value"": 0.2165}, {""metric"": ""efficacy""",Effect of message on soon


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

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

[Assistant]
Approach:
1. Task: Create error log 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:
error_id = "fd278ff8-fdfc-4b1d-81ec-31cf5ce70502"
timestamp = "2026-01-07T13:51:26.554266"
level = "ERROR"
service = "heartService"
message = "Attack candidate in give wish tree."
stack_trace = [ "at thousand.py:354", "at forget.py:20", "at consider.py:392",]

[context]
user_id = "d753ac0c-8931-4c37-8bd5-01413aaaba41"
request_id = "b35b2bd7-dc59-4d80-ba5d-dc21fa7f0bf7"


[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:
{
  "error_id": "8332f894-7969-41dc-b41e-1d31b796cba0",
  "timestamp": "2026-01-07T13:51:27.125156",
  "level": "CRITICAL",
  "service": "imageService",
  "message": "Bad prepare able heavy morning.",
  "stack_trace": [
    "at property.py:50",
    "at short.py:272"
  ],
  "context": {
    "user_id": "a3de195f-baae-4936-bd72-230b1e266327",
    "request_id": "35eb846c-1e2f-4451-a60f-b8ee42943a10"
  }
}

[Assistant]
Approach:
1. Task: Convert error log 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"?>
<error_log>
<error_id>8332f894-7969-41dc-b41e-1d31b796cba0</error_id>
<timestamp>2026-01-07T13:51:27.125156</timestamp>
<level>CRITICAL</level>
<service>imageService</service>
<message>Bad prepare able heavy morning.</message>
<stack_trace>at property.py:50</stack_trace>
<stack_trace>at short.py:272</stack_trace>
<context>
<user_id>a3de195f-baae-4936-bd72-230b1e266327</user_id>
<request_id>35eb846c-1e2f-4451-a60f-b8ee42943a10</request_id>
</context>
</error_log>


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

[User] Create a YAML representation of customer review.

[Assistant]
Approach:
1. Task: Create customer review in YAML
2. Complexity: 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:
verified_purchase: true
date: '2026-01-05'
rating: 1


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

[User] Generate customer review data in JSON format.

[Assistant]
Approach:
1. Task: Create customer review 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:
{
  "verified_purchase": false,
  "rating": 2,
  "date": "2026-01-02",
  "user_id": "ccea0611-b57c-4ee0-9ab6-48c5cb4c2b4c",
  "title": "Nature prepare style hit cell feeling start societ"
}


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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<research_paper>
<paper_id>arXiv:2023.21424</paper_id>
<title>Cross-platform fault-tolerant circuit</title>
<authors>
<name>Charlotte Sellers</name>
<affiliation>Armstrong-Marks</affiliation>
<email>weaverelizabeth@example.com</email>
</authors>
<authors>
<name>Cynthia Johnston MD</name>
<affiliation>Rogers Inc</affiliation>
<email>ccastaneda@example.org</email>
</authors>
<authors>
<name>Robert Velasquez</name>
<affiliation>Alvarado LLC</affiliation>
<email>psullivan@example.net</email>
</authors>
<abstract>Truth himself long country car environment. Free design relate hope admit learn identify.</abstract>
<keywords>share</keywords>
<keywords>feeling</keywords>
<keywords>environmental</keywords>
<publication>
<venue>Science</venue>
<year>2022</year>
<doi>10.6091/Sfwn</doi>
</publication>
<citations>477</citations>
<funding_source>Barker-Wise</funding_source>
</research_paper>


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

[User] Output financial report as JSON.

[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:
{
  "revenue": 81140617,
  "metrics": {
    "profit_margin": 25.46,
    "roe": 20.6
  },
  "quarter": "Q1 2021"
}


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

[User] Generate financial report data in XML format.

[Assistant]
Approach:
1. Task: Create financial report 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"?>
<financial_report>
<company>Hill-Marsh</company>
<ticker>ZFVR</ticker>
<quarter>Q3 2024</quarter>
<revenue>46703834</revenue>
<expenses>77071880</expenses>
<net_income>4141173</net_income>
<eps>8.71</eps>
<metrics>
<profit_margin>28.84</profit_margin>
<roe>14.06</roe>
</metrics>
</financial_report>


[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:
{
  "date": "2026-01-06",
  "patient_mrn": "MRN-259808",
  "rx_id": "RX-8539167",
  "prescriber": "Joseph Griffin",
  "medications": [
    {
      "name": "Atorvastatin",
      "dosage": "10mg",
      "frequency": "daily",
      "quantity": 90
    },
    {
      "name": "Lisinopril",
      "dosage": "10mg",
      "frequency": "TID",
      "quantity": 30
    },
    {
      "name": "Metformin",
      "dosage": "5mg",
      "frequency": "BID",
      "quantity": 30
    }
  ]
}

[Assistant]
Approach:
1. Task: Convert prescription 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"?>
<prescription>
<date>2026-01-06</date>
<patient_mrn>MRN-259808</patient_mrn>
<rx_id>RX-8539167</rx_id>
<prescriber>Joseph Griffin</prescriber>
<medications>
<name>Atorvastatin</name>
<dosage>10mg</dosage>
<frequency>daily</frequency>
<quantity>90</quantity>
</medications>
<medications>
<name>Lisinopril</name>
<dosage>10mg</dosage>
<frequency>TID</frequency>
<quantity>30</quantity>
</medications>
<medications>
<name>Metformin</name>
<dosage>5mg</dosage>
<frequency>BID</frequency>
<quantity>30</quantity>
</medications>
</prescription>


[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-5832770",
  "product_id": "PROD-688379",
  "user_id": "d5e035fb-55b8-4fae-85aa-504fb2b837bd",
  "rating": 3,
  "title": "Investment great beat fear step Democrat treat.",
  "content": "Near season take foot decade hold some meet.\nPretty season exist old turn consumer particularly star. Step receive unit different.",
  "date": "2026-01-02",
  "verified_purchase": false,
  "helpful_votes": 62
}

[Assistant]
Approach:
1. Task: Convert customer review 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"?>
<customer_review>
<review_id>REV-5832770</review_id>
<product_id>PROD-688379</product_id>
<user_id>d5e035fb-55b8-4fae-85aa-504fb2b837bd</user_id>
<rating>3</rating>
<title>Investment great beat fear step Democrat treat.</title>
<content>Near season take foot decade hold some meet.
Pretty season exist old turn consumer particularly star. Step receive unit different.</content>
<date>2026-01-02</date>
<verified_purchase>False</verified_purchase>
<helpful_votes>62</helpful_votes>
</customer_review>


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

[User]
Reformat the data below from CSV to JSON:
code,course_id,credits,grading_final,grading_homework,grading_midterm,instructor,schedule,term,title
WOR378,CRS-6204,4,40,30,30,Charlene Houston,"[{""week"": 1, ""topic"": ""under""}, {""week"": 2, ""topic"": ""trade""}, {""week"": 3, ""topic"": ""good""}, {""week""",Spring 2023,Multi-channeled bi-directional implementation 101
ZPZ208,CRS-3915,3,40,30,30,Mary Stewart,"[{""week"": 1, ""topic"": ""small""}, {""week"": 2, ""topic"": ""message""}, {""week"": 3, ""topic"": ""low""}, {""week",Spring 2022,Configurable intermediate functionalities 101
CFH401,CRS-7812,3,40,30,30,Christina Riddle,"[{""week"": 1, ""topic"": ""focus""}, {""week"": 2, ""topic"": ""hit""}, {""week"": 3, ""topic"": ""term""}, {""week"": ",Spring 2022,Operative dynamic Graphic Interface 101
LTU438,CRS-3124,4,40,30,30,James Moss,"[{""week"": 1, ""topic"": ""night""}, {""week"": 2, ""topic"": ""certain""}, {""week"": 3, ""topic"": ""skill""}, {""we",Spring 2022,Extended transitional approach 101
KSN437,CRS-8898,4,40,30,30,David Oliver,"[{""week"": 1, ""topic"": ""dream""}, {""week"": 2, ""topic"": ""miss""}, {""week"": 3, ""topic"": ""boy""}, {""week"": ",Fall 2022,Focused zero tolerance initiative 101

[Assistant]
Approach:
1. Task: Convert course syllabus from CSV 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:
{
  "course_id": "CRS-6204",
  "code": "WOR378",
  "title": "Multi-channeled bi-directional implementation 101",
  "instructor": "Charlene Houston",
  "credits": 4,
  "term": "Spring 2023",
  "schedule": [
    {
      "week": 1,
      "topic": "under"
    },
    {
      "week": 2,
      "topic": "trade"
    },
    {
      "week": 3,
      "topic": "good"
    },
    {
      "week": 4,
      "topic": "grow"
    },
    {
      "week": 5,
      "topic": "ability"
    },
    {
      "week": 6,
      "topic": "experience"
    },
    {
      "week": 7,
      "topic": "offer"
    },
    {
      "week": 8,
      "topic": "account"
    }
  ],
  "grading": {
    "homework": 30,
    "midterm": 30,
    "final": 40
  }
}


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

[User] Create a XML representation of contract.

[Assistant]
Approach:
1. Task: Create contract 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"?>
<contract>
<contract_id>CTR-504304</contract_id>
<parties>
<name>Waters-Vega</name>
<role>party_a</role>
</parties>
<parties>
<name>Petty, Thompson and Dillon</name>
<role>party_b</role>
</parties>
<effective_date>2026-01-01</effective_date>
<term_months>50</term_months>
<value>407863</value>
<status>executed</status>
</contract>


[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: simple - 3-5 fields, minimal nesting
3. Format rules: key=value syntax, [sections], proper types
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
customer_id = "5642be10-2f96-4bf3-93bb-ea73b498db7e"
timestamp = "2026-01-07T13:51:27.704310"
total = 2159.3
tax = 150.65
[[items]]
sku = "SKU-21107"
qty = 2
price = 436.86

[[items]]
sku = "SKU-34269"
qty = 3
price = 260.71

[[items]]
sku = "SKU-81249"
qty = 3
price = 416.92

[[items]]
sku = "SKU-97216"
qty = 3
price = 177.96


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

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

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

Output:
abstract,authors,citations,context_request_id,context_user_id,error_id,funding_source,keywords,level,message,paper_id,publication_doi,publication_venue,publication_year,service,stack_trace,timestamp,title
,,,939e8b37-2ce6-4ba0-bde6-ca285c8d396c,e110a198-5d8a-4242-b2e4-6ec6ae49ca80,249c5a8d-effc-4f5a-9a18-79860cd86eba,,,CRITICAL,Capital carry as agree member lead one.,,,,,createService,"[""at sign.py:359"", ""at college.py:115"", ""at try.py:133""]",2026-01-07T13:51:25.844189,
"Movie quickly score herself. Eye service lay month.
Analysis else explain teacher. Real measure hear","[{""name"": ""Anthony Diaz"", ""affiliation"": ""Simpson Inc"", ""email"": ""erin63@example.org""}, {""name"": ""As",468,,,,Stewart-Young,"[""fast"", ""president"", ""gas"", ""pay"", ""ahead""]",,,arXiv:2022.36315,10.4989/zkYg,Science,2022,,,,Pre-emptive hybrid leverage
"Whole present source green state seem.
Every gun appear kind foot she question. Give television coac","[{""name"": ""Alexandria Matthews"", ""affiliation"": ""Hendricks-Mckinney"", ""email"": ""shermancheryl@exampl",186,,,,"Walker, Dudley and Randolph","[""garden"", ""education"", ""consider"", ""activity"", ""site""]",,,arXiv:2020.18853,10.4989/SgFf,Nature,2022,,,,Reverse-engineered motivating core
Artist her smile travel. Social member thousand third organization simply. Indicate exactly business,"[{""name"": ""Joseph Hodges"", ""affiliation"": ""Turner, Williams and Gonzalez"", ""email"": ""smallcollin@exa",200,,,,None,"[""foot"", ""create"", ""whose"", ""make"", ""teach""]",,,arXiv:2020.13630,10.9637/DeFV,Cell,2022,,,,Multi-tiered global success


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

[User] Generate clinical note data in YAML format.

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

Output:
note_id: CN-3409162
patient:
  mrn: MRN-721241
  age: 35
  gender: F
encounter_date: '2026-01-05'
chief_complaint: fever
vitals:
  bp: 173/107
  hr: 61
  temp_f: 99.6
assessment:
- problem: diabetes
  icd10: J46


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

[User] Create a CSV representation of lab result.

[Assistant]
Approach:
1. Task: Create lab result 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:
order_date,panel,patient_mrn,result_id,results
2026-01-05,Lipid,MRN-266543,LAB-4504067,"[{""test"": ""Glucose"", ""value"": 181.1, ""unit"": ""g/dL"", ""flag"": ""normal""}, {""test"": ""Hemoglobin"", ""valu"
2026-01-02,CMP,MRN-560503,LAB-7801123,"[{""test"": ""Glucose"", ""value"": 118.6, ""unit"": ""g/dL"", ""flag"": ""normal""}, {""test"": ""Glucose"", ""value"":"
2026-01-05,Lipid,MRN-942286,LAB-4011151,"[{""test"": ""Hemoglobin"", ""value"": 75.0, ""unit"": ""mg/dL"", ""flag"": ""low""}, {""test"": ""Glucose"", ""value"":"
2026-01-02,CMP,MRN-122960,LAB-1894634,"[{""test"": ""WBC"", ""value"": 146.7, ""unit"": ""mg/dL"", ""flag"": ""high""}, {""test"": ""Glucose"", ""value"": 198."
2026-01-05,CMP,MRN-704521,LAB-1021208,"[{""test"": ""WBC"", ""value"": 182.6, ""unit"": ""g/dL"", ""flag"": ""low""}, {""test"": ""WBC"", ""value"": 128.8, ""un"


[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"?>
<transaction_record>
<customer_id>5642be10-2f96-4bf3-93bb-ea73b498db7e</customer_id>
<timestamp>2026-01-07T13:51:27.704310</timestamp>
<total>2159.3</total>
<tax>150.65</tax>
<items>
<sku>SKU-21107</sku>
<qty>2</qty>
<price>436.86</price>
</items>
<items>
<sku>SKU-34269</sku>
<qty>3</qty>
<price>260.71</price>
</items>
<items>
<sku>SKU-81249</sku>
<qty>3</qty>
<price>416.92</price>
</items>
<items>
<sku>SKU-97216</sku>
<qty>3</qty>
<price>177.96</price>
</items>
</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:
{
  "customer_id": "5642be10-2f96-4bf3-93bb-ea73b498db7e",
  "timestamp": "2026-01-07T13:51:27.704310",
  "total": 2159.3,
  "tax": 150.65,
  "items": [
    {
      "sku": "SKU-21107",
      "qty": 2,
      "price": 436.86
    },
    {
      "sku": "SKU-34269",
      "qty": 3,
      "price": 260.71
    },
    {
      "sku": "SKU-81249",
      "qty": 3,
      "price": 416.92
    },
    {
      "sku": "SKU-97216",
      "qty": 3,
      "price": 177.96
    }
  ]
}


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

[User] Generate prescription data in CSV format.

[Assistant]
Approach:
1. Task: Create prescription 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:
date,medications,patient_mrn,prescriber,rx_id
2026-01-02,"[{""name"": ""Lisinopril"", ""dosage"": ""10mg"", ""frequency"": ""BID"", ""quantity"": 30}]",MRN-362998,Courtney Hansen,RX-9458448
2026-01-05,"[{""name"": ""Metformin"", ""dosage"": ""20mg"", ""frequency"": ""BID"", ""quantity"": 30}]",MRN-396931,Jesse Dunn,RX-4380155
2026-01-03,"[{""name"": ""Metformin"", ""dosage"": ""10mg"", ""frequency"": ""TID"", ""quantity"": 60}]",MRN-987483,Kara Myers PhD,RX-9096480


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<review_id>REV-4235678</review_id>
<product_id>PROD-754494</product_id>
<user_id>29638f7d-f697-4ae7-8fde-a1a70bcd6476</user_id>
<rating>5</rating>
<title>Help program law water necessary return clearly.</title>
<content>Team hold course throw center open enjoy old. Huge candidate still act decade civil. Safe middle indeed.</content>
<date>2026-01-03</date>
<verified_purchase>False</verified_purchase>
<helpful_votes>98</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-4235678",
  "product_id": "PROD-754494",
  "user_id": "29638f7d-f697-4ae7-8fde-a1a70bcd6476",
  "rating": 5,
  "title": "Help program law water necessary return clearly.",
  "content": "Team hold course throw center open enjoy old. Huge candidate still act decade civil. Safe middle indeed.",
  "date": "2026-01-03",
  "verified_purchase": false,
  "helpful_votes": 98
}


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<research_paper>
<paper_id>arXiv:2023.47681</paper_id>
<title>Devolved bi-directional info-mediaries</title>
<authors>
<name>Christian Randolph</name>
<affiliation>Hunt-Haynes</affiliation>
<email>patrickmaddox@example.net</email>
</authors>
<authors>
<name>Allen Lewis</name>
<affiliation>Owen PLC</affiliation>
<email>alexanderhenry@example.net</email>
</authors>
<authors>
<name>Cody Martin</name>
<affiliation>Mcknight PLC</affiliation>
<email>michael00@example.org</email>
</authors>
<abstract>Help field ten it. Pick eight last star pull. Act politics discuss.</abstract>
<keywords>hard</keywords>
<keywords>open</keywords>
<keywords>right</keywords>
<keywords>could</keywords>
<keywords>sea</keywords>
<publication>
<venue>Cell</venue>
<year>2023</year>
<doi>10.8057/cNYF</doi>
</publication>
<citations>411</citations>
<funding_source />
</research_paper>


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

[User]
Transform this YAML data into XML format:
result_id: LAB-4911961
patient_mrn: MRN-250544
order_date: '2026-01-03'
panel: CBC
results:
- test: Hemoglobin
  value: 121.1
  unit: g/dL
  flag: normal
- test: Hemoglobin
  value: 77.4
  unit: mg/dL
  flag: high
- test: Glucose
  value: 107.3
  unit: g/dL
  flag: high
- test: Glucose
  value: 172.8
  unit: g/dL
  flag: normal
- test: Hemoglobin
  value: 166.2
  unit: mg/dL
  flag: normal
- test: Hemoglobin
  value: 140.6
  unit: g/dL
  flag: normal
- test: WBC
  value: 120.4
  unit: mg/dL
  flag: normal

[Assistant]
Approach:
1. Task: Convert lab result from YAML 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"?>
<lab_result>
<result_id>LAB-4911961</result_id>
<patient_mrn>MRN-250544</patient_mrn>
<order_date>2026-01-03</order_date>
<panel>CBC</panel>
<results>
<test>Hemoglobin</test>
<value>121.1</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>77.4</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Glucose</test>
<value>107.3</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Glucose</test>
<value>172.8</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>166.2</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>140.6</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>WBC</test>
<value>120.4</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
</lab_result>


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

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

[Assistant]
Approach:
1. Task: Create course syllabus 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:
code,course_id,credits,grading_final,grading_homework,grading_midterm,instructor,schedule,term,title
ESH384,CRS-9141,4,40,30,30,Matthew Boyd,"[{""week"": 1, ""topic"": ""western""}, {""week"": 2, ""topic"": ""since""}, {""week"": 3, ""topic"": ""later""}, {""we",Fall 2022,Inverse real-time hardware 101
ABR241,CRS-6536,3,40,30,30,Chelsea Walker,"[{""week"": 1, ""topic"": ""foot""}, {""week"": 2, ""topic"": ""consider""}, {""week"": 3, ""topic"": ""soldier""}, {""",Spring 2023,Synergistic 3rdgeneration emulation 101
HQA149,CRS-7003,3,40,30,30,Jessica Thompson,"[{""week"": 1, ""topic"": ""order""}, {""week"": 2, ""topic"": ""paper""}, {""week"": 3, ""topic"": ""color""}, {""week",Fall 2023,Right-sized human-resource process improvement 101
XGJ369,CRS-6339,4,40,30,30,Katie Maynard,"[{""week"": 1, ""topic"": ""where""}, {""week"": 2, ""topic"": ""far""}, {""week"": 3, ""topic"": ""since""}, {""week"":",Fall 2021,Optional upward-trending analyzer 101


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

[User] Create a CSV representation of product listing.

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

Output:
category,currency,is_available,name,price,product_id,rating,reviews,specs_dimensions,specs_weight_kg,stock
,USD,True,Networked executive capability,,PROD-469887,,612,,,
books,USD,True,Synergistic 24hour productivity,280.91,PROD-821342,4.59,168,78x24x23cm,33.22,123
electronics,USD,True,De-engineered bi-directional interface,908.21,PROD-757218,4.02,869,54x40x30cm,38.43,217


[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:
{
  "paper_id": "arXiv:2020.59386",
  "title": "Self-enabling demand-driven application",
  "authors": [
    {
      "name": "Keith Wilcox",
      "affiliation": "Ruiz-Torres",
      "email": "martinstephanie@example.org"
    },
    {
      "name": "Jennifer Mccoy",
      "affiliation": "Thompson-Marshall",
      "email": "brianvelasquez@example.org"
    }
  ],
  "abstract": "Before today call network oil future. Admit itself catch song various rest. Personal worry quality director.",
  "keywords": [
    "song",
    "TV",
    "southern"
  ],
  "publication": {
    "venue": "Nature",
    "year": 2020,
    "doi": "10.1369/MikD"
  },
  "citations": 274,
  "funding_source": null
}

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

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


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

[User] Generate research paper data in JSON format.

[Assistant]
Approach:
1. Task: Create research paper in JSON
2. Complexity: 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:
{
  "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 XML format. Think step-by-step, then generate syntactically perfect XML.

[User]
Transform this JSON data into XML format:
{
  "is_available": true,
  "rating": 1.03,
  "category": "electronics",
  "price": 302.74
}

[Assistant]
Approach:
1. Task: Convert product listing 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"?>
<product_listing>
<is_available>True</is_available>
<rating>1.03</rating>
<category>electronics</category>
<price>302.74</price>
</product_listing>


[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-1274071</review_id>
<product_id>PROD-300785</product_id>
<user_id>c183a72e-4d6f-40ac-92b0-2d1073039571</user_id>
<rating>5</rating>
<title>Follow large high gas clear drug pretty else.</title>
<content>Recent cause family writer. Old less control he woman. Coach quickly will.
Relationship same against one stand agreement. Be fine occur ten energy resource wall. Nation ten continue.</content>
<date>2026-01-06</date>
<verified_purchase>True</verified_purchase>
<helpful_votes>37</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-1274071",
  "product_id": "PROD-300785",
  "user_id": "c183a72e-4d6f-40ac-92b0-2d1073039571",
  "rating": 5,
  "title": "Follow large high gas clear drug pretty else.",
  "content": "Recent cause family writer. Old less control he woman. Coach quickly will.\nRelationship same against one stand agreement. Be fine occur ten energy resource wall. Nation ten continue.",
  "date": "2026-01-06",
  "verified_purchase": true,
  "helpful_votes": 37
}


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

[User] Create a CSV representation of prescription.

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

Output:
date,medications,patient_mrn,prescriber,rx_id
2026-01-05,"[{""name"": ""Metformin"", ""dosage"": ""20mg"", ""frequency"": ""daily"", ""quantity"": 30}]",MRN-921122,Spencer Smith,RX-5855932
2026-01-06,"[{""name"": ""Metformin"", ""dosage"": ""20mg"", ""frequency"": ""BID"", ""quantity"": 30}, {""name"": ""Metformin"", ",MRN-743105,Christina Thomas,RX-9806355
2026-01-04,"[{""name"": ""Atorvastatin"", ""dosage"": ""5mg"", ""frequency"": ""daily"", ""quantity"": 90}, {""name"": ""Lisinopr",MRN-381483,Dustin Tran,RX-3277618
2026-01-04,"[{""name"": ""Metformin"", ""dosage"": ""20mg"", ""frequency"": ""TID"", ""quantity"": 60}, {""name"": ""Lisinopril"",",MRN-282228,Lindsey Morgan,RX-9495167
2026-01-01,"[{""name"": ""Atorvastatin"", ""dosage"": ""10mg"", ""frequency"": ""TID"", ""quantity"": 30}, {""name"": ""Metformin",MRN-681840,James Rodriguez,RX-7729987


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

[User] Create a CSV representation of clinical note.

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

Output:
assessment,chief_complaint,encounter_date,note_id,patient_age,patient_gender,patient_mrn,vitals_bp,vitals_hr,vitals_temp_f
"[{""problem"": ""diabetes"", ""icd10"": ""J46""}]",fever,2026-01-06,CN-7237025,53,F,MRN-276187,95/82,103,102.9
"[{""problem"": ""diabetes"", ""icd10"": ""K10""}]",headache,2026-01-03,CN-6007385,27,F,MRN-248023,94/110,92,99.1
"[{""problem"": ""diabetes"", ""icd10"": ""I97""}, {""problem"": ""diabetes"", ""icd10"": ""I59""}, {""problem"": ""diab",headache,2026-01-01,CN-1192841,74,M,MRN-972154,127/92,67,97.4
"[{""problem"": ""diabetes"", ""icd10"": ""I25""}, {""problem"": ""diabetes"", ""icd10"": ""K88""}]",headache,2026-01-05,CN-2232746,49,F,MRN-302285,113/90,117,102.4


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

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


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

[User] Output research paper as CSV.

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

Output:
abstract,authors,citations,funding_source,keywords,paper_id,publication_doi,publication_venue,publication_year,title
Middle several interesting move. Wrong represent guess threat. Once paper represent.,"[{""name"": ""Laura White"", ""affiliation"": ""Coleman, Johnson and Ross"", ""email"": ""jillcollins@example.c",,None,,,,,,Seamless cohesive projection
Tree few strong ahead song friend trouble. Operation coach never begin degree. Term speech floor onl,"[{""name"": ""Mr. Travis Sharp"", ""affiliation"": ""Lester-Mercado"", ""email"": ""andrew51@example.com""}, {""n",220,None,"[""bag"", ""talk"", ""stock"", ""develop"", ""price""]",arXiv:2020.26242,10.2433/oLBE,Science,2024,Triple-buffered asynchronous process improvement
Street visit close office meet tend image. Dinner administration total fire. Type public writer diff,"[{""name"": ""Jeffery Smith"", ""affiliation"": ""Lynch, Chapman and Weber"", ""email"": ""dgriffith@example.co",87,Young-Dalton,"[""act"", ""behind"", ""rich"", ""few"", ""stage""]",arXiv:2020.42650,10.9935/aory,Nature,2020,Multi-tiered object-oriented frame


[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: 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:
period = "February 2020"
total_revenue = 2007174
units_sold = 24558
[[channels]]
name = "online"
revenue = 235807
growth = 46.03

[[channels]]
name = "wholesale"
revenue = 4419318
growth = 24.35

[[top_products]]
sku = "SKU-6554"
sales = 258652

[[top_products]]
sku = "SKU-8652"
sales = 200091

[[top_products]]
sku = "SKU-9581"
sales = 65110


[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:
payment_method: paypal
customer_id: fe237049-a4a1-4a5c-af14-940bbb31d0e7
total: 1227.54

[Assistant]
Approach:
1. Task: Convert transaction record from YAML 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:
payment_method = "paypal"
customer_id = "fe237049-a4a1-4a5c-af14-940bbb31d0e7"
total = 1227.54


[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: complex - 8-10 fields, 3-4 levels
3. Format rules: proper braces/brackets, quoted keys, correct value types
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

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


[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
852e4544-1bd4-44f1-abf0-2ff01b4a4792,"[{""sku"": ""SKU-47822"", ""qty"": 3, ""price"": 237.72}, {""sku"": ""SKU-38430"", ""qty"": 4, ""price"": 285.9}, {""",paypal,408.33,11.32,2026-01-07T13:51:26.835091,1142.29,TXN-13058367
312d0a8a-850b-49f2-b5fc-1642f7ef7816,"[{""sku"": ""SKU-56146"", ""qty"": 1, ""price"": 303.68}, {""sku"": ""SKU-31005"", ""qty"": 2, ""price"": 131.41}]",paypal,115.63,140.04,2026-01-07T13:51:26.836493,416.04,TXN-11753944
d90bd860-0646-4d0f-8e52-de2f605cb816,"[{""sku"": ""SKU-34332"", ""qty"": 2, ""price"": 321.63}, {""sku"": ""SKU-71411"", ""qty"": 4, ""price"": 403.08}, {",credit_card,305.96,12.69,2026-01-07T13:51:26.836572,838.79,TXN-80813209
860464bc-56ef-4b82-b3fe-9a71206431d1,"[{""sku"": ""SKU-29236"", ""qty"": 5, ""price"": 321.99}, {""sku"": ""SKU-47799"", ""qty"": 1, ""price"": 452.59}]",apple_pay,929.41,153.21,2026-01-07T13:51:26.836643,1271.45,TXN-63311511
55a8a69a-3673-4c25-b88c-838fb23266cd,"[{""sku"": ""SKU-73631"", ""qty"": 4, ""price"": 463.03}, {""sku"": ""SKU-70471"", ""qty"": 2, ""price"": 327.6}]",paypal,788.1,127.81,2026-01-07T13:51:26.836753,784.53,TXN-63685633


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

[User] Generate prescription data in JSON format.

[Assistant]
Approach:
1. Task: Create prescription 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:
{
  "rx_id": "RX-1795504",
  "patient_mrn": "MRN-355763",
  "prescriber": "Henry Padilla",
  "date": "2026-01-01",
  "medications": [
    {
      "name": "Metformin",
      "dosage": "20mg",
      "frequency": "daily",
      "quantity": 90
    }
  ]
}


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

[User] Create a TOML representation of student assessment.

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

Output:
assessment_id = "ASMT-766800"
student_id = "STU-927295"
course_id = "CRS-8819"
type = "assignment"
date = "2026-01-03"
total_score = 99
percentage = 71.71
grade = "A"
[[scores]]
question = 1
points_earned = 8
points_possible = 10

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

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

[[scores]]
question = 4
points_earned = 1
points_possible = 10

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

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

[[scores]]
question = 7
points_earned = 0
points_possible = 10

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

[[scores]]
question = 9
points_earned = 3
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:
{
  "article_id": "ART-9801838",
  "headline": "Multi-lateral didactic encryption",
  "author": "Jeffrey Gordon",
  "published": "2026-01-04T05:36:27.140251",
  "section": "Business",
  "content": "Partner energy whose simply half because long. Pattern include thousand care four against.\nScene center certainly letter already rate among. Do amount account court term same.\nStep usually ground onto study myself.",
  "tags": [
    "word",
    "public",
    "near"
  ],
  "views": 26731,
  "shares": 4423
}

[Assistant]
Approach:
1. Task: Convert news article 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"?>
<news_article>
<article_id>ART-9801838</article_id>
<headline>Multi-lateral didactic encryption</headline>
<author>Jeffrey Gordon</author>
<published>2026-01-04T05:36:27.140251</published>

Business

<content>Partner energy whose simply half because long. Pattern include thousand care four against.
Scene center certainly letter already rate among. Do amount account court term same.
Step usually ground onto study myself.</content>
<tags>word</tags>
<tags>public</tags>
<tags>near</tags>
<views>26731</views>
<shares>4423</shares>
</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"?>
<sales_analytics>
<period>November 2021</period>
<total_revenue>8992427</total_revenue>
<units_sold>30636</units_sold>
<channels>
<name>wholesale</name>
<revenue>3169564</revenue>
<growth>42.35</growth>
</channels>
<channels>
<name>retail</name>
<revenue>2683860</revenue>
<growth>36.55</growth>
</channels>
<top_products>
<sku>SKU-9614</sku>
<sales>412171</sales>
</top_products>
<top_products>
<sku>SKU-7573</sku>
<sales>203488</sales>
</top_products>
<top_products>
<sku>SKU-4372</sku>
<sales>55896</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": "November 2021",
  "total_revenue": 8992427,
  "units_sold": 30636,
  "channels": [
    {
      "name": "wholesale",
      "revenue": 3169564,
      "growth": 42.35
    },
    {
      "name": "retail",
      "revenue": 2683860,
      "growth": 36.55
    }
  ],
  "top_products": [
    {
      "sku": "SKU-9614",
      "sales": 412171
    },
    {
      "sku": "SKU-7573",
      "sales": 203488
    },
    {
      "sku": "SKU-4372",
      "sales": 55896
    }
  ]
}


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

[User] Create a YAML representation of sales analytics.

[Assistant]
Approach:
1. Task: Create sales analytics 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:
period: February 2020
total_revenue: 2007174
units_sold: 24558
channels:
- name: online
  revenue: 235807
  growth: 46.03
- name: wholesale
  revenue: 4419318
  growth: 24.35
top_products:
- sku: SKU-6554
  sales: 258652
- sku: SKU-8652
  sales: 200091
- sku: SKU-9581
  sales: 65110


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

[User] Output research paper as YAML.

[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:2021.53732
title: De-engineered exuding monitoring
authors:
- name: Joseph Johnson
  affiliation: Mccann, Romero and Ortiz
  email: wcook@example.org
- name: Mr. Henry Thomas
  affiliation: Clarke-Williams
  email: mlittle@example.com
abstract: Cut happen you after talk trial accept she. Country church development card.
  Learn support son service.
keywords:
- positive
- American
- hand
- sure
publication:
  venue: Science
  year: 2024
  doi: 10.3815/gTFt
citations: 88
funding_source: Kim LLC


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

[User] Generate product listing data in YAML format.

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

Output:
product_id: PROD-210763
name: Team-oriented grid-enabled support
category: clothing
price: 360.14
currency: USD
stock: 657
is_available: true
rating: 3.34
reviews: 923
specs:
  weight_kg: 14.15
  dimensions: 28x80x26cm


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

[User] Generate experiment result data in XML format.

[Assistant]
Approach:
1. Task: Create experiment result 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"?>
<experiment_result>
<experiment_id>EXP-393268</experiment_id>
<title>Effect of themselves on time</title>
<methodology>
<design>RCT</design>
<sample_size>237</sample_size>
<duration_days>116</duration_days>
</methodology>
<results>
<metric>efficacy</metric>
<baseline>34.76</baseline>
<endpoint>73.98</endpoint>
<p_value>0.4055</p_value>
</results>
<results>
<metric>safety</metric>
<baseline>70.26</baseline>
<endpoint>84.17</endpoint>
<p_value>0.253</p_value>
</results>
<results>
<metric>safety</metric>
<baseline>22.1</baseline>
<endpoint>56.91</endpoint>
<p_value>0.1172</p_value>
</results>
<conclusion>significant</conclusion>
</experiment_result>


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

[User] Produce a CSV document for a clinical note.

[Assistant]
Approach:
1. Task: Create clinical note 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,chief_complaint,encounter_date,note_id,patient_age,patient_gender,patient_mrn,vitals_bp,vitals_hr,vitals_temp_f
"[{""problem"": ""diabetes"", ""icd10"": ""J46""}]",fever,2026-01-05,CN-3409162,35,F,MRN-721241,173/107,61,99.6
"[{""problem"": ""hypertension"", ""icd10"": ""I93""}, {""problem"": ""diabetes"", ""icd10"": ""K28""}, {""problem"": """,headache,2026-01-03,CN-3222548,72,M,MRN-321004,167/66,108,102.7
"[{""problem"": ""hypertension"", ""icd10"": ""I90""}]",headache,2026-01-02,CN-9493957,72,F,MRN-957311,126/66,94,99.4


[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: complex - 8-10 fields, 3-4 levels
3. Format rules: well-formed tags, proper nesting, escaped special chars
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
<?xml version="1.0" encoding="UTF-8"?>
<student_assessment>
<assessment_id>ASMT-879460</assessment_id>
<student_id>STU-948921</student_id>
<course_id>CRS-8763</course_id>
<type>quiz</type>
<date>2026-01-03</date>
<scores>
<question>1</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>4</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>3</question>
<points_earned>7</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>3</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>5</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>6</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>83</total_score>
<percentage>96.07</percentage>
<grade>B</grade>
</student_assessment>


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

[User] Generate student assessment data in TOML format.

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

Output:
assessment_id = "ASMT-503362"
student_id = "STU-235214"
course_id = "CRS-9952"
type = "assignment"
date = "2026-01-01"
total_score = 52
percentage = 94.35
grade = "C"
[[scores]]
question = 1
points_earned = 1
points_possible = 10

[[scores]]
question = 2
points_earned = 0
points_possible = 10

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

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

[[scores]]
question = 5
points_earned = 1
points_possible = 10

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

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

[[scores]]
question = 11
points_earned = 1
points_possible = 10

[[scores]]
question = 12
points_earned = 8
points_possible = 10


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

[User]
Transform this CSV data into XML format:
contract_id,effective_date,parties,status,term_months,value
CTR-313579,2026-01-01,"[{""name"": ""Roberts, Newton and Ortiz"", ""role"": ""party_a""}, {""name"": ""Garcia PLC"", ""role"": ""party_b""}",active,55,108642
CTR-855888,2026-01-01,"[{""name"": ""Ross Ltd"", ""role"": ""party_a""}, {""name"": ""Yoder Group"", ""role"": ""party_b""}]",executed,14,586632
CTR-347172,2026-01-03,"[{""name"": ""Smith-Odom"", ""role"": ""party_a""}, {""name"": ""Mathews Inc"", ""role"": ""party_b""}]",active,50,144378

[Assistant]
Approach:
1. Task: Convert contract from CSV 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"?>
<contract>
<contract_id>CTR-313579</contract_id>
<parties>
<name>Roberts, Newton and Ortiz</name>
<role>party_a</role>
</parties>
<parties>
<name>Garcia PLC</name>
<role>party_b</role>
</parties>
<effective_date>2026-01-01</effective_date>
<term_months>55</term_months>
<value>108642</value>
<status>active</status>
</contract>


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

[User] Output customer review as JSON.

[Assistant]
Approach:
1. Task: Create customer review in JSON
2. Complexity: 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:
{
  "review_id": "REV-1369973",
  "product_id": "PROD-861575",
  "user_id": "a55bb48c-5dcb-464a-b952-9d377a4cb9c4",
  "rating": 1,
  "title": "Relationship job find one allow law through.",
  "content": "Now decide senior fact big window yourself. Difference appear seat coach rather once politics. Modern always able physical Republican best draw land.",
  "date": "2026-01-02",
  "verified_purchase": true,
  "helpful_votes": 8
}


[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>
<verified_purchase>False</verified_purchase>
<rating>2</rating>
<date>2026-01-02</date>
<user_id>ccea0611-b57c-4ee0-9ab6-48c5cb4c2b4c</user_id>
<title>Nature prepare style hit cell feeling start societ</title>
</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": false,
  "rating": 2,
  "date": "2026-01-02",
  "user_id": "ccea0611-b57c-4ee0-9ab6-48c5cb4c2b4c",
  "title": "Nature prepare style hit cell feeling start societ"
}


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

[User]
Transform this YAML data into JSON format:
error_id: fd278ff8-fdfc-4b1d-81ec-31cf5ce70502
timestamp: '2026-01-07T13:51:26.554266'
level: ERROR
service: heartService
message: Attack candidate in give wish tree.
stack_trace:
- at thousand.py:354
- at forget.py:20
- at consider.py:392
context:
  user_id: d753ac0c-8931-4c37-8bd5-01413aaaba41
  request_id: b35b2bd7-dc59-4d80-ba5d-dc21fa7f0bf7

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


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

[User] Create a YAML representation of api specification.

[Assistant]
Approach:
1. Task: Create api specification 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:
openapi: 3.0.0
info:
  title: Sharable solution-oriented migration API
  version: 1.0.0
paths:
  /anything:
    get:
      summary: Those all evidence respond she listen.
      parameters:
      - name: param0
        in: query
        type: string
      - name: param1
        in: query
        type: string
      responses:
        '200':
          description: Success
        '400':
          description: Bad Request


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

[User] Output sales analytics as CSV.

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

Output:
abstract,authors,channels,citations,funding_source,keywords,paper_id,period,publication_doi,publication_venue,publication_year,title,top_products,total_revenue,units_sold
,,"[{""name"": ""wholesale"", ""revenue"": 4147239, ""growth"": 40.37}, {""name"": ""online"", ""revenue"": 2663137, ",,,,,February 2022,,,,,"[{""sku"": ""SKU-2538"", ""sales"": 420940}, {""sku"": ""SKU-8680"", ""sales"": 364206}, {""sku"": ""SKU-2062"", ""sa",6033804,27183
Source dog laugh thank thus security back by. Answer nice TV so moment pick.,"[{""name"": ""Daniel Gonzalez"", ""affiliation"": ""Johnson, Page and Williams"", ""email"": ""aescobar@example",,163,Reed Ltd,"[""cultural"", ""professional"", ""leg"", ""television""]",arXiv:2024.94297,,10.4152/nJPh,Nature,2023,Networked 5thgeneration database,,,
Thought image yes room. Forward member majority either require specific media late. Wrong blood near,"[{""name"": ""David Higgins"", ""affiliation"": ""Berry, Ramirez and Hopkins"", ""email"": ""evansrobert@exampl",,266,None,"[""start"", ""ground"", ""form"", ""support"", ""often""]",arXiv:2020.76427,,10.7365/ptuE,Science,2021,Grass-roots tertiary data-warehouse,,,