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

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

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

Output:
{
  "assessment_id": "ASMT-225883",
  "student_id": "STU-314827",
  "course_id": "CRS-2408",
  "type": "quiz",
  "date": "2026-01-01",
  "scores": [
    {
      "question": 1,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 3,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 3,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 9,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 10,
      "points_earned": 10,
      "points_possible": 10
    },
    {
      "question": 11,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 12,
      "points_earned": 10,
      "points_possible": 10
    },
    {
      "question": 13,
      "points_earned": 8,
      "points_possible": 10
    }
  ],
  "total_score": 99,
  "percentage": 82.0,
  "grade": "B"
}


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

[User]
Transform this JSON data into XML format:
{
  "result_id": "LAB-1812594",
  "patient_mrn": "MRN-755137",
  "order_date": "2026-01-06",
  "panel": "CMP",
  "results": [
    {
      "test": "Glucose",
      "value": 131.9,
      "unit": "mg/dL",
      "flag": "normal"
    },
    {
      "test": "Glucose",
      "value": 183.7,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "WBC",
      "value": 130.1,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "Hemoglobin",
      "value": 178.3,
      "unit": "g/dL",
      "flag": "low"
    }
  ]
}

[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-1812594</result_id>
<patient_mrn>MRN-755137</patient_mrn>
<order_date>2026-01-06</order_date>
<panel>CMP</panel>
<results>
<test>Glucose</test>
<value>131.9</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Glucose</test>
<value>183.7</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>WBC</test>
<value>130.1</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>178.3</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
</lab_result>


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

[User]
Transform this TOML data into JSON format:
period = "July 2021"
total_revenue = 5979422
units_sold = 82076
[[channels]]
name = "retail"
revenue = 3460112
growth = 36.85

[[channels]]
name = "online"
revenue = 3983364
growth = 5.55

[[top_products]]
sku = "SKU-1065"
sales = 105510

[[top_products]]
sku = "SKU-4043"
sales = 281142

[[top_products]]
sku = "SKU-1338"
sales = 43006

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

Output:
{
  "period": "July 2021",
  "total_revenue": 5979422,
  "units_sold": 82076,
  "channels": [
    {
      "name": "retail",
      "revenue": 3460112,
      "growth": 36.85
    },
    {
      "name": "online",
      "revenue": 3983364,
      "growth": 5.55
    }
  ],
  "top_products": [
    {
      "sku": "SKU-1065",
      "sales": 105510
    },
    {
      "sku": "SKU-4043",
      "sales": 281142
    },
    {
      "sku": "SKU-1338",
      "sales": 43006
    }
  ]
}


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

[User] Generate clinical note data in TOML format.

[Assistant]
Approach:
1. Task: Create clinical note 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:
note_id = "CN-5751204"
encounter_date = "2026-01-05"
chief_complaint = "headache"
[[assessment]]
problem = "diabetes"
icd10 = "I93"

[patient]
mrn = "MRN-566004"
age = 47
gender = "M"

[vitals]
bp = "160/96"
hr = 75
temp_f = 102.4


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

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

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

Output:
course_id: CRS-8328
code: QKE428
title: Decentralized content-based leverage 101
instructor: Sarah Simon
credits: 3
term: Fall 2022
schedule:
- week: 1
  topic: whole
- week: 2
  topic: table
- week: 3
  topic: determine
- week: 4
  topic: evening
- week: 5
  topic: once
- week: 6
  topic: some
- week: 7
  topic: themselves
- week: 8
  topic: table
grading:
  homework: 30
  midterm: 30
  final: 40


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

[User] Output api specification as CSV.

[Assistant]
Approach:
1. Task: Create api specification 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,funding_source,info_title,info_version,keywords,openapi,paper_id,paths_/improve_get_parameters,paths_/improve_get_responses_200_description,paths_/improve_get_responses_400_description,paths_/improve_get_summary,publication_doi,publication_venue,publication_year,title
,,,,Centralized web-enabled hardware API,1.0.0,,3.0.0,,"[{""name"": ""param0"", ""in"": ""query"", ""type"": ""string""}, {""name"": ""param1"", ""in"": ""query"", ""type"": ""str",Success,Bad Request,Act attention yes herself significant recent.,,,,
Left order purpose modern good. Part bit either work magazine draw.,"[{""name"": ""Courtney Stone"", ""affiliation"": ""Rojas-Hoffman"", ""email"": ""pcunningham@example.com""}, {""n",29,None,,,"[""hour"", ""issue"", ""environment"", ""drug"", ""relate""]",,arXiv:2023.70277,,,,,10.8906/jrxw,Science,2024,Enterprise-wide systematic product
Though official tree term space. Development almost feeling.,"[{""name"": ""David Weaver"", ""affiliation"": ""Dunlap-Gordon"", ""email"": ""williamsonkarina@example.com""}, ",341,None,,,"[""example"", ""everyone"", ""local""]",,arXiv:2024.59034,,,,,10.3725/mRXU,Nature,2023,Focused scalable encoding
Try check body structure begin bit traditional executive. East beautiful bit able. Pass wind if into,"[{""name"": ""Robert Stanley"", ""affiliation"": ""Wagner-Powell"", ""email"": ""strongmadison@example.net""}, {",274,Jacobs PLC,,,"[""six"", ""great"", ""new""]",,arXiv:2024.11837,,,,,10.8256/lPXo,Cell,2021,Exclusive radical orchestration


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

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

[Assistant]
Approach:
1. Task: Create customer review in TOML
2. Complexity: 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:
verified_purchase = true
title = "Country especially hand."
review_id = "REV-4835597"
product_id = "PROD-713270"


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

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

[Assistant]
Approach:
1. Task: Create course syllabus 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"?>
<course_syllabus>
<course_id>CRS-8422</course_id>
OMY437
<title>Optimized upward-trending conglomeration 101</title>
<instructor>Rodney Anderson</instructor>
<credits>3</credits>
<term>Spring 2023</term>
<schedule>
<week>1</week>
<topic>answer</topic>
</schedule>
<schedule>
<week>2</week>
<topic>best</topic>
</schedule>
<schedule>
<week>3</week>
<topic>meet</topic>
</schedule>
<schedule>
<week>4</week>
<topic>simple</topic>
</schedule>
<schedule>
<week>5</week>
<topic>peace</topic>
</schedule>
<schedule>
<week>6</week>
<topic>upon</topic>
</schedule>
<schedule>
<week>7</week>
<topic>power</topic>
</schedule>
<grading>
<homework>30</homework>
<midterm>30</midterm>
<final>40</final>
</grading>
</course_syllabus>


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

[User]
Reformat the data below from JSON to XML:
{
  "product_id": "PROD-738287",
  "name": "Function-based dedicated installation",
  "category": "electronics",
  "price": 364.53,
  "currency": "USD",
  "stock": 956,
  "is_available": true,
  "rating": 1.64,
  "reviews": 854,
  "specs": {
    "weight_kg": 19.72,
    "dimensions": "48x33x88cm"
  }
}

[Assistant]
Approach:
1. Task: Convert product listing 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"?>
<product_listing>
<product_id>PROD-738287</product_id>
<name>Function-based dedicated installation</name>
<category>electronics</category>
<price>364.53</price>
<currency>USD</currency>
<stock>956</stock>
<is_available>True</is_available>
<rating>1.64</rating>
<reviews>854</reviews>
<specs>
<weight_kg>19.72</weight_kg>
<dimensions>48x33x88cm</dimensions>
</specs>
</product_listing>


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

[User] Generate financial report data in JSON format.

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

Output:
{
  "company": "Woods and Sons",
  "ticker": "ZCNM",
  "quarter": "Q1 2020",
  "revenue": 42196406,
  "expenses": 48284794,
  "net_income": 2937548,
  "eps": 8.84,
  "metrics": {
    "profit_margin": 12.42,
    "roe": 23.86
  }
}


[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: 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:
{
  "product_id": "PROD-524008",
  "name": "Implemented multimedia focus group",
  "category": "electronics",
  "price": 524.9,
  "currency": "USD",
  "stock": 714,
  "is_available": true,
  "rating": 2.56,
  "reviews": 633,
  "specs": {
    "weight_kg": 40.1,
    "dimensions": "80x44x77cm"
  }
}


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

[User] Create a YAML representation of course syllabus.

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

Output:
course_id: CRS-9456
code: KDS432
title: Multi-channeled local complexity 101
instructor: Kenneth Rogers
credits: 3
term: Fall 2020
schedule:
- week: 1
  topic: activity
- week: 2
  topic: foot
- week: 3
  topic: reason
- week: 4
  topic: rule
- week: 5
  topic: paper
- week: 6
  topic: current
- week: 7
  topic: scene
- week: 8
  topic: later
- week: 9
  topic: choice
- week: 10
  topic: box
grading:
  homework: 30
  midterm: 30
  final: 40


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

[User]
Reformat the data below from YAML to JSON:
review_id: REV-9723622
product_id: PROD-853148
user_id: 44919496-69de-498e-922c-5ea4230c00fa
rating: 3
title: Risk tell team series house.
content: Official police serve past already. Number down similar senior head amount.
  Focus reality really hold lose.
date: '2026-01-03'
verified_purchase: false
helpful_votes: 99

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


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

[User]
Reformat the data below from YAML to JSON:
company: Tucker and Sons
ticker: BPQE
quarter: Q4 2024
revenue: 70279854
expenses: 61737533
net_income: 12235621
eps: 3.52
metrics:
  profit_margin: 24.27
  roe: 16.15

[Assistant]
Approach:
1. Task: Convert financial report from YAML 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:
{
  "company": "Tucker and Sons",
  "ticker": "BPQE",
  "quarter": "Q4 2024",
  "revenue": 70279854,
  "expenses": 61737533,
  "net_income": 12235621,
  "eps": 3.52,
  "metrics": {
    "profit_margin": 24.27,
    "roe": 16.15
  }
}


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

[User] Output transaction record as XML.

[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-23430167</txn_id>
<customer_id>7fb2e914-3f0f-4c3f-abb9-ef22ed2c1064</customer_id>
<timestamp>2026-01-07T13:51:26.046328</timestamp>
<items>
<sku>SKU-63492</sku>
<qty>1</qty>
<price>90.17</price>
</items>
<items>
<sku>SKU-56350</sku>
<qty>5</qty>
<price>336.79</price>
</items>
<subtotal>152.9</subtotal>
<tax>14.6</tax>
<total>796.85</total>
<payment_method>apple_pay</payment_method>
</transaction_record>


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<social_media_post>
<post_id>POST-29576154</post_id>
<platform>instagram</platform>
<user_id>b3774d2a-dced-4164-bd7b-7d043d7ec920</user_id>
<username>boydkaren</username>
<content>Responsibility this statement area thing imagine free. Under quickly treatment ever end social military. Majority before treatment decide.</content>
<timestamp>2026-01-07T13:51:27.160344</timestamp>
<hashtags>#involve</hashtags>
<hashtags>#fact</hashtags>
<hashtags>#rest</hashtags>
<engagement>
<likes>923</likes>
<shares>56</shares>
<comments>396</comments>
</engagement>
</social_media_post>


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

[User] Create a XML representation of 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>Upgradable 4thgeneration middleware API</title>
<version>1.0.0</version>
</info>
<paths>
</pass>
<get>
<summary>Story amount nor bed night get message.</summary>
<parameters>
<name>param0</name>
<in>query</in>
<type>string</type>
</parameters>
<responses>
<200>
<description>Success</description>
</200>
<400>
<description>Bad Request</description>
</400>
</responses>
</get>
<//pass>
</paths>
</api_specification>


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

[User]
Convert the following JSON to XML:
{
  "assessment_id": "ASMT-852879",
  "student_id": "STU-517758",
  "course_id": "CRS-9070",
  "type": "exam",
  "date": "2026-01-04",
  "scores": [
    {
      "question": 1,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 10,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 3,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 10,
      "points_possible": 10
    },
    {
      "question": 9,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 10,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 11,
      "points_earned": 6,
      "points_possible": 10
    },
    {
      "question": 12,
      "points_earned": 8,
      "points_possible": 10
    }
  ],
  "total_score": 58,
  "percentage": 53.23,
  "grade": "C"
}

[Assistant]
Approach:
1. Task: Convert student assessment 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"?>
<student_assessment>
<assessment_id>ASMT-852879</assessment_id>
<student_id>STU-517758</student_id>
<course_id>CRS-9070</course_id>
<type>exam</type>
<date>2026-01-04</date>
<scores>
<question>1</question>
<points_earned>4</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>10</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>3</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>7</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>4</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>3</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>10</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>9</question>
<points_earned>7</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>10</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>11</question>
<points_earned>6</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>12</question>
<points_earned>8</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>58</total_score>
<percentage>53.23</percentage>
<grade>C</grade>
</student_assessment>


[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:
review_id: REV-7122533
content: Expert difficult hot radio mission. Throw southern he book way media particular.
rating: 1
date: '2026-01-06'
verified_purchase: false


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

[User] Output error log as TOML.

[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 = "e01a43f8-d4eb-4ec7-a325-ad2b31726d0f"
timestamp = "2026-01-07T13:51:25.462522"
level = "ERROR"
service = "winService"
message = "Western energy project push building."
stack_trace = [ "at could.py:42", "at seem.py:198",]

[context]
user_id = "7197800d-0acd-4eee-b9ab-24b5158dfa0a"
request_id = "00c4c00d-dc22-4013-8495-1ed2381fc937"


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<social_media_post>
<engagement>
<likes>6676</likes>
<shares>196</shares>
<comments>84</comments>
</engagement>
<username>nicholasalvarez</username>
<post_id>POST-61351209</post_id>
<hashtags>#pretty</hashtags>
<hashtags>#admit</hashtags>
<hashtags>#available</hashtags>
<user_id>5e546096-8461-4a3f-84e6-813e9e89a39c</user_id>
</social_media_post>


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

[User] Generate clinical note data in JSON format.

[Assistant]
Approach:
1. Task: Create clinical note in JSON
2. Complexity: 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:
{
  "note_id": "CN-8348908",
  "patient": {
    "mrn": "MRN-109351",
    "age": 84,
    "gender": "F"
  },
  "encounter_date": "2026-01-06",
  "chief_complaint": "fever",
  "vitals": {
    "bp": "157/81",
    "hr": 101,
    "temp_f": 97.1
  },
  "assessment": [
    {
      "problem": "diabetes",
      "icd10": "J60"
    },
    {
      "problem": "diabetes",
      "icd10": "K69"
    },
    {
      "problem": "hypertension",
      "icd10": "J80"
    }
  ]
}


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

[User]
Convert the following YAML to CSV:
result_id: LAB-8093004
patient_mrn: MRN-777027
order_date: '2026-01-05'
panel: CMP
results:
- test: Glucose
  value: 140.2
  unit: mg/dL
  flag: low
- test: Hemoglobin
  value: 96.3
  unit: g/dL
  flag: normal
- test: Glucose
  value: 185.0
  unit: g/dL
  flag: high
- test: Glucose
  value: 139.7
  unit: g/dL
  flag: low

[Assistant]
Approach:
1. Task: Convert lab result from YAML 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:
order_date,panel,patient_mrn,result_id,results
2026-01-05,CMP,MRN-777027,LAB-8093004,"[{""test"": ""Glucose"", ""value"": 140.2, ""unit"": ""mg/dL"", ""flag"": ""low""}, {""test"": ""Hemoglobin"", ""value"""
2026-01-04,CMP,MRN-636298,LAB-4135521,"[{""test"": ""Hemoglobin"", ""value"": 57.8, ""unit"": ""mg/dL"", ""flag"": ""low""}, {""test"": ""Hemoglobin"", ""valu"
2026-01-01,CMP,MRN-536906,LAB-7594088,"[{""test"": ""Glucose"", ""value"": 114.3, ""unit"": ""g/dL"", ""flag"": ""low""}, {""test"": ""WBC"", ""value"": 126.6,"
2026-01-01,CBC,MRN-570632,LAB-8841115,"[{""test"": ""Hemoglobin"", ""value"": 182.5, ""unit"": ""g/dL"", ""flag"": ""normal""}, {""test"": ""Glucose"", ""valu"


[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-1681251</review_id>
<product_id>PROD-380005</product_id>
<user_id>6ee75bbe-7aec-42b2-b8ce-db908c5fbc3a</user_id>
<rating>3</rating>
<title>Floor measure may hear dark at.</title>
<content>Us board wonder trouble. Up as inside party growth seat. College late direction amount best team.
Fish gas end appear mother assume. Anyone major game miss similar argue. Moment describe require.</content>
<date>2026-01-05</date>
<verified_purchase>True</verified_purchase>
<helpful_votes>21</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-1681251",
  "product_id": "PROD-380005",
  "user_id": "6ee75bbe-7aec-42b2-b8ce-db908c5fbc3a",
  "rating": 3,
  "title": "Floor measure may hear dark at.",
  "content": "Us board wonder trouble. Up as inside party growth seat. College late direction amount best team.\nFish gas end appear mother assume. Anyone major game miss similar argue. Moment describe require.",
  "date": "2026-01-05",
  "verified_purchase": true,
  "helpful_votes": 21
}


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

[User] Generate lab result data in JSON format.

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

Output:
{
  "result_id": "LAB-3990665",
  "patient_mrn": "MRN-508219",
  "order_date": "2026-01-04",
  "panel": "Lipid",
  "results": [
    {
      "test": "Hemoglobin",
      "value": 80.7,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "Glucose",
      "value": 90.9,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 138.0,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "WBC",
      "value": 131.3,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "Glucose",
      "value": 172.4,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "WBC",
      "value": 151.6,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "Hemoglobin",
      "value": 188.6,
      "unit": "g/dL",
      "flag": "high"
    }
  ]
}


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

[User] Create a YAML representation of experiment result.

[Assistant]
Approach:
1. Task: Create experiment result 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:
experiment_id: EXP-160417
title: Effect of agree on both
methodology:
  design: cohort
  sample_size: 663
  duration_days: 354
results:
- metric: safety
  baseline: 13.92
  endpoint: 49.07
  p_value: 0.4102
- metric: safety
  baseline: 15.99
  endpoint: 65.81
  p_value: 0.3043
- metric: efficacy
  baseline: 46.51
  endpoint: 82.23
  p_value: 0.4775
conclusion: non-significant


[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:
{
  "assessment_id": "ASMT-744456",
  "student_id": "STU-954920",
  "course_id": "CRS-3021",
  "type": "exam",
  "date": "2026-01-03",
  "scores": [
    {
      "question": 1,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 5,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 10,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 5,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 9,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 10,
      "points_earned": 3,
      "points_possible": 10
    },
    {
      "question": 11,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 12,
      "points_earned": 9,
      "points_possible": 10
    }
  ],
  "total_score": 97,
  "percentage": 89.67,
  "grade": "C"
}

[Assistant]
Approach:
1. Task: Convert student assessment 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"?>
<student_assessment>
<assessment_id>ASMT-744456</assessment_id>
<student_id>STU-954920</student_id>
<course_id>CRS-3021</course_id>
<type>exam</type>
<date>2026-01-03</date>
<scores>
<question>1</question>
<points_earned>7</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>3</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>5</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>10</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>5</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>9</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>10</question>
<points_earned>3</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>11</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>12</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>97</total_score>
<percentage>89.67</percentage>
<grade>C</grade>
</student_assessment>


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

[User] Generate experiment result data in CSV format.

[Assistant]
Approach:
1. Task: Create experiment result in CSV
2. Complexity: 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
significant,EXP-725280,observational,166,907,"[{""metric"": ""safety"", ""baseline"": 43.19, ""endpoint"": 64.81, ""p_value"": 0.4813}, {""metric"": ""safety"",",Effect of city on expert
significant,EXP-303305,RCT,140,832,"[{""metric"": ""efficacy"", ""baseline"": 97.45, ""endpoint"": 96.0, ""p_value"": 0.1993}, {""metric"": ""safety""",Effect of own on find
non-significant,EXP-177606,observational,235,737,"[{""metric"": ""efficacy"", ""baseline"": 58.91, ""endpoint"": 44.12, ""p_value"": 0.1897}, {""metric"": ""effica",Effect of whole on note


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

[User]
Convert the following JSON to XML:
{
  "period": "January 2024",
  "total_revenue": 3091656,
  "units_sold": 63856,
  "channels": [
    {
      "name": "wholesale",
      "revenue": 2739604,
      "growth": -0.52
    },
    {
      "name": "online",
      "revenue": 247982,
      "growth": 14.46
    }
  ],
  "top_products": [
    {
      "sku": "SKU-7268",
      "sales": 409348
    },
    {
      "sku": "SKU-4030",
      "sales": 70087
    },
    {
      "sku": "SKU-4380",
      "sales": 298376
    }
  ]
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<sales_analytics>
<period>January 2024</period>
<total_revenue>3091656</total_revenue>
<units_sold>63856</units_sold>
<channels>
<name>wholesale</name>
<revenue>2739604</revenue>
<growth>-0.52</growth>
</channels>
<channels>
<name>online</name>
<revenue>247982</revenue>
<growth>14.46</growth>
</channels>
<top_products>
<sku>SKU-7268</sku>
<sales>409348</sales>
</top_products>
<top_products>
<sku>SKU-4030</sku>
<sales>70087</sales>
</top_products>
<top_products>
<sku>SKU-4380</sku>
<sales>298376</sales>
</top_products>
</sales_analytics>


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

[User]
Convert the following JSON to CSV:
{
  "article_id": "ART-6180455",
  "headline": "Grass-roots multi-tasking hub",
  "author": "David Espinoza",
  "published": "2026-01-07T13:20:10.771283",
  "section": "Politics",
  "content": "Either large lot east. Show everybody away city election happy my. Believe left sure mother.\nWhom game determine road little. Sing this character. Agent fill kitchen themselves agreement.\nWoman draw budget stage. Star cultural old president where national success.",
  "tags": [
    "size",
    "commercial",
    "president",
    "city",
    "expect"
  ],
  "views": 43396,
  "shares": 2564
}

[Assistant]
Approach:
1. Task: Convert news article from JSON to CSV
2. Complexity: medium - 5-8 fields, 2-3 levels
3. Format rules: header row, comma-separated, quoted fields with commas
4. Structure: Organize data logically with appropriate nesting
5. Transform values to match the target format specifications.

Output:
article_id,author,content,headline,published,section,shares,tags,views
ART-6180455,David Espinoza,"Either large lot east. Show everybody away city election happy my. Believe left sure mother.
Whom ga",Grass-roots multi-tasking hub,2026-01-07T13:20:10.771283,Politics,2564,"[""size"", ""commercial"", ""president"", ""city"", ""expect""]",43396
ART-9783952,John Hendricks,Send truth approach learn few success. Within sound such know keep court responsibility. Approach ho,Optimized stable flexibility,2026-01-05T15:20:15.286883,Politics,4957,"[""key"", ""thing"", ""enough""]",77371
ART-1887395,Michelle Hood,"Figure example character. Somebody rock college focus book despite.
Full east if half state school p",Diverse needs-based parallelism,2026-01-04T13:14:28.038369,Sports,1344,"[""may"", ""history"", ""significant"", ""car"", ""area""]",19249
ART-7943494,Terri Trujillo,Eye picture talk media foot. Do within energy degree ask before. Mention kid third civil seat throug,Multi-tiered intermediate superstructure,2026-01-02T20:21:36.265337,Business,3519,"[""dream"", ""like"", ""to"", ""rise"", ""turn""]",13467


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

[User] Output clinical note as YAML.

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

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


[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"?>
<clinical_note>
<note_id>CN-6224145</note_id>
<patient>
<mrn>MRN-560569</mrn>
<age>88</age>
<gender>F</gender>
</patient>
<encounter_date>2026-01-04</encounter_date>
<chief_complaint>headache</chief_complaint>
<vitals>
<bp>119/73</bp>

63

<temp_f>100.0</temp_f>
</vitals>
<assessment>
<problem>hypertension</problem>
<icd10>I32</icd10>
</assessment>
</clinical_note>

[Assistant]
Approach:
1. Task: Convert clinical note 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:
{
  "note_id": "CN-6224145",
  "patient": {
    "mrn": "MRN-560569",
    "age": 88,
    "gender": "F"
  },
  "encounter_date": "2026-01-04",
  "chief_complaint": "headache",
  "vitals": {
    "bp": "119/73",
    "hr": 63,
    "temp_f": 100.0
  },
  "assessment": [
    {
      "problem": "hypertension",
      "icd10": "I32"
    }
  ]
}


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

[User] Create a JSON representation of financial report.

[Assistant]
Approach:
1. Task: Create financial report in JSON
2. Complexity: 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:
{
  "company": "Harris Inc",
  "ticker": "KXNS",
  "quarter": "Q2 2023",
  "revenue": 96096321,
  "expenses": 36366080,
  "net_income": 6859279,
  "eps": 2.68,
  "metrics": {
    "profit_margin": 18.37,
    "roe": 11.92
  }
}


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

[User] Generate news article data in XML format.

[Assistant]
Approach:
1. Task: Create news article 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"?>
<news_article>
<article_id>ART-8846154</article_id>
<headline>Phased bifurcated instruction set</headline>
<author>Melanie Kennedy</author>
<published>2026-01-02T14:27:49.190328</published>

Sports

<content>Edge wear coach whether dog sell respond. Claim feeling meeting somebody four real.
Indeed use send represent leader require. Cup attack instead discuss. Plan with character rule.
Information mind company even serve. Experience pattern but certain she design speech.</content>
<tags>memory</tags>
<tags>score</tags>
<tags>game</tags>
<tags>join</tags>
<views>47684</views>
<shares>4081</shares>
</news_article>


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

[User]
Reformat the data below from TOML to XML:
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

[Assistant]
Approach:
1. Task: Convert student assessment from TOML 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"?>
<student_assessment>
<assessment_id>ASMT-503362</assessment_id>
<student_id>STU-235214</student_id>
<course_id>CRS-9952</course_id>
<type>assignment</type>
<date>2026-01-01</date>
<scores>
<question>1</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>0</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>3</question>
<points_earned>0</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>4</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>6</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>8</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>5</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>9</question>
<points_earned>4</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>10</question>
<points_earned>0</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>11</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>12</question>
<points_earned>8</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>52</total_score>
<percentage>94.35</percentage>
<grade>C</grade>
</student_assessment>


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

[User] Output social media post as XML.

[Assistant]
Approach:
1. Task: Create social media post in XML
2. Complexity: 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"?>
<social_media_post>
<post_id>POST-19357850</post_id>
<platform>twitter</platform>
<user_id>664b960b-1331-492f-addd-e9b37d21656f</user_id>
<username>mbaldwin</username>
<content>Forward front agreement cover hour we remember ask. Read glass few word mother deep TV.</content>
<timestamp>2026-01-07T13:51:27.605837</timestamp>
<hashtags>#cost</hashtags>
<hashtags>#he</hashtags>
<hashtags>#relationship</hashtags>
<engagement>
<likes>304</likes>
<shares>796</shares>
<comments>124</comments>
</engagement>
</social_media_post>


[System] You are an expert in 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-3684509</rx_id>
<patient_mrn>MRN-644382</patient_mrn>
<prescriber>Chelsea Henson</prescriber>
<date>2026-01-04</date>
<medications>
<name>Atorvastatin</name>
<dosage>10mg</dosage>
<frequency>BID</frequency>
<quantity>60</quantity>
</medications>
<medications>
<name>Metformin</name>
<dosage>20mg</dosage>
<frequency>daily</frequency>
<quantity>60</quantity>
</medications>
<medications>
<name>Metformin</name>
<dosage>10mg</dosage>
<frequency>TID</frequency>
<quantity>60</quantity>
</medications>
</prescription>


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

[User]
Convert the following YAML to XML:
views: 92789
content: 'Couple and teacher radio compare consumer. Pass thing much rather light.

  Foot four country subject first interview. Defense TV artist to of. Fund miss window
  scene.

  Wish successful movement city door politics measure. Police media TV out word remain
  as. Report option appear station example role.'
shares: 213
headline: Re-engineered composite Local Area Network
tags:
- couple
- this
- themselves
- whom

[Assistant]
Approach:
1. Task: Convert news article from YAML to XML
2. Complexity: simple - 3-5 fields, minimal nesting
3. Format rules: well-formed tags, proper nesting, escaped special chars
4. Structure: Organize data logically with appropriate nesting
5. Transform values to match the target format specifications.

Output:
<?xml version="1.0" encoding="UTF-8"?>
<news_article>
<views>92789</views>
<content>Couple and teacher radio compare consumer. Pass thing much rather light.
Foot four country subject first interview. Defense TV artist to of. Fund miss window scene.
Wish successful movement city door politics measure. Police media TV out word remain as. Report option appear station example role.</content>
<shares>213</shares>
<headline>Re-engineered composite Local Area Network</headline>
<tags>couple</tags>
<tags>this</tags>
<tags>themselves</tags>
<tags>whom</tags>
</news_article>


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

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

[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-61935008"
platform = "instagram"
user_id = "ecd9585e-2adb-45f4-adda-e91c5f4f7ebe"
username = "halezachary"
content = "Treat second sing development scientist particularly their. Like question recently line top. Resource movie enter involve order stop region."
timestamp = "2026-01-07T13:51:25.597395"
hashtags = [ "#box", "#speak", "#reason",]

[engagement]
likes = 4027
shares = 604
comments = 194


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

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

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

Output:
timestamp: '2026-01-07T13:51:25.400660'
items:
- sku: SKU-41387
  qty: 1
  price: 386.75
txn_id: TXN-44773795
customer_id: acd22e98-51a5-48fa-ad66-a69b8fba3f2b
tax: 171.02


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

[User]
Reformat the data below from JSON to XML:
{
  "period": "October 2022",
  "total_revenue": 4790876,
  "units_sold": 72609,
  "channels": [
    {
      "name": "retail",
      "revenue": 1112533,
      "growth": 2.85
    },
    {
      "name": "wholesale",
      "revenue": 3150615,
      "growth": -3.34
    }
  ],
  "top_products": [
    {
      "sku": "SKU-7795",
      "sales": 492045
    },
    {
      "sku": "SKU-5231",
      "sales": 195976
    },
    {
      "sku": "SKU-5539",
      "sales": 335045
    }
  ]
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<sales_analytics>
<period>October 2022</period>
<total_revenue>4790876</total_revenue>
<units_sold>72609</units_sold>
<channels>
<name>retail</name>
<revenue>1112533</revenue>
<growth>2.85</growth>
</channels>
<channels>
<name>wholesale</name>
<revenue>3150615</revenue>
<growth>-3.34</growth>
</channels>
<top_products>
<sku>SKU-7795</sku>
<sales>492045</sales>
</top_products>
<top_products>
<sku>SKU-5231</sku>
<sales>195976</sales>
</top_products>
<top_products>
<sku>SKU-5539</sku>
<sales>335045</sales>
</top_products>
</sales_analytics>


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

[User] Generate research paper data in XML format.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<research_paper>
<paper_id>arXiv:2021.53732</paper_id>
<title>De-engineered exuding monitoring</title>
<authors>
<name>Joseph Johnson</name>
<affiliation>Mccann, Romero and Ortiz</affiliation>
<email>wcook@example.org</email>
</authors>
<authors>
<name>Mr. Henry Thomas</name>
<affiliation>Clarke-Williams</affiliation>
<email>mlittle@example.com</email>
</authors>
<abstract>Cut happen you after talk trial accept she. Country church development card. Learn support son service.</abstract>
<keywords>positive</keywords>
<keywords>American</keywords>
<keywords>hand</keywords>
<keywords>sure</keywords>
<publication>
<venue>Science</venue>
<year>2024</year>
<doi>10.3815/gTFt</doi>
</publication>
<citations>88</citations>
<funding_source>Kim LLC</funding_source>
</research_paper>


[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: 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:
units_sold: 11543
period: June 2021
channels:
- name: online
  revenue: 1417680
  growth: 41.94
- name: wholesale
  revenue: 3176166
  growth: 26.78
total_revenue: 8223229
top_products:
- sku: SKU-9002
  sales: 412560
- sku: SKU-3918
  sales: 426996
- sku: SKU-1618
  sales: 496165


[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:
{
  "patient": {
    "mrn": "MRN-802088",
    "age": 30,
    "gender": "M"
  },
  "note_id": "CN-3759937",
  "vitals": {
    "bp": "119/74",
    "hr": 67,
    "temp_f": 100.9
  }
}

[Assistant]
Approach:
1. Task: Convert clinical note 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"?>
<clinical_note>
<patient>
<mrn>MRN-802088</mrn>
<age>30</age>
<gender>M</gender>
</patient>
<note_id>CN-3759937</note_id>
<vitals>
<bp>119/74</bp>

67

<temp_f>100.9</temp_f>
</vitals>
</clinical_note>


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

[User]
Reformat the data below from CSV to XML:
code,course_id,credits,grading_final,grading_homework,grading_midterm,instructor,schedule,term,title
KDS432,CRS-9456,3,40,30,30,Kenneth Rogers,"[{""week"": 1, ""topic"": ""activity""}, {""week"": 2, ""topic"": ""foot""}, {""week"": 3, ""topic"": ""reason""}, {""w",Fall 2020,Multi-channeled local complexity 101
KXW117,CRS-6421,3,40,30,30,Shelley Scott,"[{""week"": 1, ""topic"": ""specific""}, {""week"": 2, ""topic"": ""well""}, {""week"": 3, ""topic"": ""wrong""}, {""we",Fall 2020,Enterprise-wide 5thgeneration strategy 101
NFV230,CRS-2609,3,40,30,30,Ashley Mccullough,"[{""week"": 1, ""topic"": ""such""}, {""week"": 2, ""topic"": ""bar""}, {""week"": 3, ""topic"": ""task""}, {""week"": 4",Fall 2022,Cross-group non-volatile conglomeration 101
SEY107,CRS-7967,3,40,30,30,Shane Smith,"[{""week"": 1, ""topic"": ""eight""}, {""week"": 2, ""topic"": ""material""}, {""week"": 3, ""topic"": ""site""}, {""we",Fall 2023,Managed executive project 101

[Assistant]
Approach:
1. Task: Convert course syllabus 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"?>
<course_syllabus>
<course_id>CRS-9456</course_id>
KDS432
<title>Multi-channeled local complexity 101</title>
<instructor>Kenneth Rogers</instructor>
<credits>3</credits>
<term>Fall 2020</term>
<schedule>
<week>1</week>
<topic>activity</topic>
</schedule>
<schedule>
<week>2</week>
<topic>foot</topic>
</schedule>
<schedule>
<week>3</week>
<topic>reason</topic>
</schedule>
<schedule>
<week>4</week>
<topic>rule</topic>
</schedule>
<schedule>
<week>5</week>
<topic>paper</topic>
</schedule>
<schedule>
<week>6</week>
<topic>current</topic>
</schedule>
<schedule>
<week>7</week>
<topic>scene</topic>
</schedule>
<schedule>
<week>8</week>
<topic>later</topic>
</schedule>
<schedule>
<week>9</week>
<topic>choice</topic>
</schedule>
<schedule>
<week>10</week>
<topic>box</topic>
</schedule>
<grading>
<homework>30</homework>
<midterm>30</midterm>
<final>40</final>
</grading>
</course_syllabus>


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

[User]
Transform this JSON data into XML format:
{
  "article_id": "ART-3682408",
  "headline": "Decentralized stable neural-net",
  "author": "Thomas Acevedo",
  "published": "2026-01-01T11:30:40.673887",
  "section": "Business",
  "content": "Cold trial recognize improve nice between these. Happy herself suggest impact tell easy.\nStart movie up social real effort. Onto federal prepare class direction rest.\nNews party school five bit. Trouble box year how.\nPressure respond nature. Prepare ball put happen.",
  "tags": [
    "movie",
    "it",
    "chance"
  ],
  "views": 12438,
  "shares": 1329
}

[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-3682408</article_id>
<headline>Decentralized stable neural-net</headline>
<author>Thomas Acevedo</author>
<published>2026-01-01T11:30:40.673887</published>

Business

<content>Cold trial recognize improve nice between these. Happy herself suggest impact tell easy.
Start movie up social real effort. Onto federal prepare class direction rest.
News party school five bit. Trouble box year how.
Pressure respond nature. Prepare ball put happen.</content>
<tags>movie</tags>
<tags>it</tags>
<tags>chance</tags>
<views>12438</views>
<shares>1329</shares>
</news_article>


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

[User] Create a YAML representation of course syllabus.

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

Output:
course_id: CRS-4513
code: NEE477
title: Exclusive bottom-line artificial intelligence 101
instructor: Jaime Roman
credits: 3
term: Spring 2022
schedule:
- week: 1
  topic: marriage
- week: 2
  topic: wonder
- week: 3
  topic: system
- week: 4
  topic: order
- week: 5
  topic: very
- week: 6
  topic: laugh
- week: 7
  topic: practice
- week: 8
  topic: sister
- week: 9
  topic: join
- week: 10
  topic: expect
grading:
  homework: 30
  midterm: 30
  final: 40


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

[User] Output social media post as YAML.

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

Output:
post_id: POST-23186111
platform: twitter
user_id: 85951ac5-a9b8-4154-8edc-693bcde245cf
username: srodriguez
content: 'Stand leave decade year collection. Republican point edge yet business.

  Suffer accept central against. Cup theory mouth side message.

  Concern magazine exactly maybe oil difficult.'
timestamp: '2026-01-07T13:51:25.750515'
hashtags:
- '#community'
- '#whatever'
engagement:
  likes: 4745
  shares: 251
  comments: 51


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

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

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

Output:
{
  "period": "March 2022",
  "total_revenue": 2472943,
  "units_sold": 2053,
  "channels": [
    {
      "name": "wholesale",
      "revenue": 3703587,
      "growth": 38.49
    },
    {
      "name": "retail",
      "revenue": 3200920,
      "growth": -8.82
    }
  ],
  "top_products": [
    {
      "sku": "SKU-8959",
      "sales": 220308
    },
    {
      "sku": "SKU-7189",
      "sales": 206126
    },
    {
      "sku": "SKU-5359",
      "sales": 225947
    }
  ]
}


[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: 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,code,funding_source,grading_final,grading_homework,grading_midterm,instructor,keywords,paper_id,publication_doi,publication_venue,publication_year,term,title
,,,VMA483,,40,30,30,Tamara Stark,,,,,,Spring 2022,
Field where gun save. End discover price the nation positive. Bill military after something save. Be,"[{""name"": ""Steven Castaneda"", ""affiliation"": ""Cohen, Fernandez and Sanders"", ""email"": ""tamara15@exam",67,,Roy Inc,,,,,"[""focus"", ""without"", ""people"", ""write""]",arXiv:2021.22486,10.4738/jgld,Nature,2022,,Adaptive dynamic core
Wind third will send compare speak. Phone me chance record sense politics.,"[{""name"": ""Timothy Juarez"", ""affiliation"": ""West-Nunez"", ""email"": ""amandagallegos@example.net""}, {""n",416,,None,,,,,"[""that"", ""myself"", ""prove"", ""how""]",arXiv:2023.83300,10.7283/tRhP,Science,2024,,Programmable responsive methodology
Claim argue you must artist believe. Business including option difficult bank development. Race only,"[{""name"": ""Selena Bruce"", ""affiliation"": ""Garcia LLC"", ""email"": ""richardstewart@example.org""}, {""nam",191,,Stout Inc,,,,,"[""street"", ""notice"", ""fine"", ""like"", ""everyone""]",arXiv:2023.20004,10.2231/oVZY,Cell,2021,,Persistent 4thgeneration approach


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

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

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

Output:
article_id = "ART-5347545"
headline = "Triple-buffered zero administration algorithm"
author = "Martha Brown"
published = "2026-01-05T16:28:34.342789"
section = "Sports"
content = "Have fall sing then fast research break. Bar ready eye medical school might recognize. Nice sometimes impact point white.\nTake many this never ever trip. Specific call according. We argue person federal central each."
tags = [ "line", "true", "compare", "for",]
views = 96946
shares = 1479


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

[User]
Reformat the data below from YAML to CSV:
contract_id: CTR-504304
parties:
- name: Waters-Vega
  role: party_a
- name: Petty, Thompson and Dillon
  role: party_b
effective_date: '2026-01-01'
term_months: 50
value: 407863
status: executed

[Assistant]
Approach:
1. Task: Convert contract from YAML to CSV
2. Complexity: medium - 5-8 fields, 2-3 levels
3. Format rules: header row, comma-separated, quoted fields with commas
4. Structure: Organize data logically with appropriate nesting
5. Transform values to match the target format specifications.

Output:
contract_id,effective_date,parties,status,term_months,value
CTR-504304,2026-01-01,"[{""name"": ""Waters-Vega"", ""role"": ""party_a""}, {""name"": ""Petty, Thompson and Dillon"", ""role"": ""party_b",executed,50,407863
CTR-508948,2026-01-01,"[{""name"": ""Jones Ltd"", ""role"": ""party_a""}, {""name"": ""Stewart-Johnson"", ""role"": ""party_b""}]",pending,33,425897
CTR-627668,2026-01-04,"[{""name"": ""Hester, Flowers and Hubbard"", ""role"": ""party_a""}, {""name"": ""Holland-Cunningham"", ""role"": ",pending,27,601243


[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: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"
}

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


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

[User]
Reformat the data below from XML to CSV:
<?xml version="1.0" encoding="UTF-8"?>
<product_listing>
<product_id>PROD-210763</product_id>
<name>Team-oriented grid-enabled support</name>
<category>clothing</category>
<price>360.14</price>
<currency>USD</currency>
<stock>657</stock>
<is_available>True</is_available>
<rating>3.34</rating>
<reviews>923</reviews>
<specs>
<weight_kg>14.15</weight_kg>
<dimensions>28x80x26cm</dimensions>
</specs>
</product_listing>

[Assistant]
Approach:
1. Task: Convert product listing 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:
category,currency,is_available,name,price,product_id,rating,reviews,specs_dimensions,specs_weight_kg,stock
clothing,USD,True,Team-oriented grid-enabled support,360.14,PROD-210763,3.34,923,28x80x26cm,14.15,657
books,USD,True,Compatible 3rdgeneration Graphic Interface,785.98,PROD-162596,3.26,63,89x67x94cm,39.1,565
books,USD,True,Polarized global throughput,980.85,PROD-480978,3.49,10,73x71x39cm,46.4,341
electronics,USD,True,Ergonomic 3rdgeneration installation,258.59,PROD-613482,3.88,26,16x33x60cm,21.14,590
electronics,USD,True,Ameliorated modular benchmark,50.07,PROD-943559,2.84,10,28x85x80cm,18.98,993


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

[User] Create a JSON representation of customer review.

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

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


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

[User] Output error log as CSV.

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

Output:
abstract,authors,citations,context_request_id,context_user_id,error_id,funding_source,keywords,level,message,paper_id,publication_doi,publication_venue,publication_year,service,stack_trace,timestamp,title
,,,a05e806a-f592-4611-8d80-dbe2773bec40,162209b9-e3ae-4c7a-af39-f96af44cdcaa,8ef553f5-74fa-47eb-bfcb-571b6fa73c35,,,WARNING,Professional pull soon.,,,,,radioService,"[""at eye.py:220"", ""at short.py:148"", ""at the.py:448""]",2026-01-07T13:51:27.105544,
Sister anyone want family she present fund laugh. This its suddenly fear. Ready us argue body.,"[{""name"": ""Stacy Weaver"", ""affiliation"": ""Torres-Johnson"", ""email"": ""vnelson@example.com""}, {""name"":",305,,,,Williams Inc,"[""brother"", ""item"", ""record""]",,,arXiv:2021.81740,10.5245/MfqF,Science,2022,,,,Open-architected systematic Graphic Interface
Enter herself defense consider. Finish yes matter action management. Fish plant remain radio wear th,"[{""name"": ""Tammy Anthony"", ""affiliation"": ""Summers-Bright"", ""email"": ""amanda26@example.net""}, {""name",411,,,,None,"[""population"", ""report"", ""someone"", ""color"", ""value""]",,,arXiv:2022.23294,10.8940/PGcG,Cell,2022,,,,Realigned leadingedge knowledge user
Rather across leave owner.,"[{""name"": ""Jeanne Banks"", ""affiliation"": ""Scott-Padilla"", ""email"": ""nhanson@example.net""}, {""name"": ",328,,,,None,"[""president"", ""future"", ""cut""]",,,arXiv:2020.69254,10.5444/KjKz,Nature,2021,,,,Stand-alone 24/7 functionalities


[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"?>
<sales_analytics>
<period>February 2020</period>
<total_revenue>5010605</total_revenue>
<units_sold>4486</units_sold>
<channels>
<name>online</name>
<revenue>4865933</revenue>
<growth>41.22</growth>
</channels>
<channels>
<name>wholesale</name>
<revenue>4636446</revenue>
<growth>21.68</growth>
</channels>
<top_products>
<sku>SKU-3361</sku>
<sales>360256</sales>
</top_products>
<top_products>
<sku>SKU-1576</sku>
<sales>355717</sales>
</top_products>
<top_products>
<sku>SKU-8891</sku>
<sales>396344</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": "February 2020",
  "total_revenue": 5010605,
  "units_sold": 4486,
  "channels": [
    {
      "name": "online",
      "revenue": 4865933,
      "growth": 41.22
    },
    {
      "name": "wholesale",
      "revenue": 4636446,
      "growth": 21.68
    }
  ],
  "top_products": [
    {
      "sku": "SKU-3361",
      "sales": 360256
    },
    {
      "sku": "SKU-1576",
      "sales": 355717
    },
    {
      "sku": "SKU-8891",
      "sales": 396344
    }
  ]
}


[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:
result_id: LAB-5790382
patient_mrn: MRN-357903
order_date: '2026-01-02'
panel: CBC
results:
- test: Glucose
  value: 56.1
  unit: mg/dL
  flag: high
- test: Glucose
  value: 114.1
  unit: mg/dL
  flag: normal
- test: WBC
  value: 154.7
  unit: mg/dL
  flag: low
- test: Glucose
  value: 196.1
  unit: g/dL
  flag: normal

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

Output:
result_id = "LAB-5790382"
patient_mrn = "MRN-357903"
order_date = "2026-01-02"
panel = "CBC"
[[results]]
test = "Glucose"
value = 56.1
unit = "mg/dL"
flag = "high"

[[results]]
test = "Glucose"
value = 114.1
unit = "mg/dL"
flag = "normal"

[[results]]
test = "WBC"
value = 154.7
unit = "mg/dL"
flag = "low"

[[results]]
test = "Glucose"
value = 196.1
unit = "g/dL"
flag = "normal"


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

[User] Output lab result as TOML.

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

Output:
result_id = "LAB-8547948"
patient_mrn = "MRN-375584"
order_date = "2026-01-05"
panel = "Lipid"
[[results]]
test = "WBC"
value = 136.4
unit = "mg/dL"
flag = "low"

[[results]]
test = "Glucose"
value = 110.1
unit = "mg/dL"
flag = "normal"

[[results]]
test = "Glucose"
value = 77.6
unit = "mg/dL"
flag = "high"

[[results]]
test = "Glucose"
value = 164.2
unit = "g/dL"
flag = "normal"

[[results]]
test = "Hemoglobin"
value = 53.3
unit = "g/dL"
flag = "high"


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

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

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

Output:
{
  "paper_id": "arXiv: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 YAML format. Think step-by-step, then generate syntactically perfect YAML.

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

[Assistant]
Approach:
1. Task: Create social media post 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:
post_id: POST-19844803
platform: instagram
user_id: eee48898-e428-4685-b6ea-d0074f4ffb8a
username: pinedaryan
content: 'Between past agree writer forget big. Simple glass protect job answer thank.

  Government prepare rather agency hard. Fear director room future hospital.'
timestamp: '2026-01-07T13:51:25.753060'
hashtags:
- '#fast'
- '#imagine'
- '#carry'
engagement:
  likes: 1299
  shares: 900
  comments: 90


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

[User] Create a YAML representation of student assessment.

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

Output:
assessment_id: ASMT-744456
student_id: STU-954920
course_id: CRS-3021
type: exam
date: '2026-01-03'
scores:
- question: 1
  points_earned: 7
  points_possible: 10
- question: 2
  points_earned: 2
  points_possible: 10
- question: 3
  points_earned: 2
  points_possible: 10
- question: 4
  points_earned: 9
  points_possible: 10
- question: 5
  points_earned: 5
  points_possible: 10
- question: 6
  points_earned: 10
  points_possible: 10
- question: 7
  points_earned: 5
  points_possible: 10
- question: 8
  points_earned: 1
  points_possible: 10
- question: 9
  points_earned: 9
  points_possible: 10
- question: 10
  points_earned: 3
  points_possible: 10
- question: 11
  points_earned: 9
  points_possible: 10
- question: 12
  points_earned: 9
  points_possible: 10
total_score: 97
percentage: 89.67
grade: C


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

[User] Create a XML representation of sales analytics.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<sales_analytics>
<units_sold>11543</units_sold>
<period>June 2021</period>
<channels>
<name>online</name>
<revenue>1417680</revenue>
<growth>41.94</growth>
</channels>
<channels>
<name>wholesale</name>
<revenue>3176166</revenue>
<growth>26.78</growth>
</channels>
<total_revenue>8223229</total_revenue>
<top_products>
<sku>SKU-9002</sku>
<sales>412560</sales>
</top_products>
<top_products>
<sku>SKU-3918</sku>
<sales>426996</sales>
</top_products>
<top_products>
<sku>SKU-1618</sku>
<sales>496165</sales>
</top_products>
</sales_analytics>


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

[User] Create a JSON representation of customer review.

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

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


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

[User]
Transform this JSON data into XML format:
{
  "course_id": "CRS-9141",
  "code": "ESH384",
  "title": "Inverse real-time hardware 101",
  "instructor": "Matthew Boyd",
  "credits": 4,
  "term": "Fall 2022",
  "schedule": [
    {
      "week": 1,
      "topic": "western"
    },
    {
      "week": 2,
      "topic": "since"
    },
    {
      "week": 3,
      "topic": "later"
    },
    {
      "week": 4,
      "topic": "next"
    },
    {
      "week": 5,
      "topic": "tree"
    },
    {
      "week": 6,
      "topic": "until"
    },
    {
      "week": 7,
      "topic": "everything"
    },
    {
      "week": 8,
      "topic": "until"
    },
    {
      "week": 9,
      "topic": "how"
    },
    {
      "week": 10,
      "topic": "test"
    },
    {
      "week": 11,
      "topic": "half"
    }
  ],
  "grading": {
    "homework": 30,
    "midterm": 30,
    "final": 40
  }
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<course_syllabus>
<course_id>CRS-9141</course_id>
ESH384
<title>Inverse real-time hardware 101</title>
<instructor>Matthew Boyd</instructor>
<credits>4</credits>
<term>Fall 2022</term>
<schedule>
<week>1</week>
<topic>western</topic>
</schedule>
<schedule>
<week>2</week>
<topic>since</topic>
</schedule>
<schedule>
<week>3</week>
<topic>later</topic>
</schedule>
<schedule>
<week>4</week>
<topic>next</topic>
</schedule>
<schedule>
<week>5</week>
<topic>tree</topic>
</schedule>
<schedule>
<week>6</week>
<topic>until</topic>
</schedule>
<schedule>
<week>7</week>
<topic>everything</topic>
</schedule>
<schedule>
<week>8</week>
<topic>until</topic>
</schedule>
<schedule>
<week>9</week>
<topic>how</topic>
</schedule>
<schedule>
<week>10</week>
<topic>test</topic>
</schedule>
<schedule>
<week>11</week>
<topic>half</topic>
</schedule>
<grading>
<homework>30</homework>
<midterm>30</midterm>
<final>40</final>
</grading>
</course_syllabus>


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

[User]
Transform this JSON data into TOML format:
{
  "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 TOML
2. Complexity: medium - 5-8 fields, 2-3 levels
3. Format rules: key=value syntax, [sections], proper types
4. Structure: Organize data logically with appropriate nesting
5. Transform values to match the target format specifications.

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

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

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

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

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


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

[User] Create a JSON representation of error log.

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


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

[User]
Reformat the data below from CSV to JSON:
abstract,authors,citations,funding_source,keywords,paper_id,publication_doi,publication_venue,publication_year,title
"Read deal buy final thus. Sure home game rest lose.
Those any reality if teach.
Main never still lit","[{""name"": ""Scott Dunlap"", ""affiliation"": ""Daniels PLC"", ""email"": ""williamssheri@example.com""}, {""nam",388,Reese-Perez,"[""measure"", ""stage"", ""scene"", ""reason""]",arXiv:2023.54834,10.8776/UhOT,Science,2020,Profit-focused radical throughput
Successful laugh price range read budget teach or. Think generation sell force. Cup also mission wou,"[{""name"": ""Russell Woods"", ""affiliation"": ""Ward-Diaz"", ""email"": ""mccarthychristopher@example.org""}, ",260,None,"[""clear"", ""war"", ""now"", ""old"", ""light""]",arXiv:2023.17967,10.6121/bfko,Science,2021,Monitored 24/7 moderator
What pick culture relationship deep. Former she because course on head finally behavior. Only floor ,"[{""name"": ""Daniel Martinez"", ""affiliation"": ""Lowe, Chan and Moreno"", ""email"": ""stevenbell@example.co",56,Thomas-Lopez,"[""sea"", ""mission"", ""success"", ""machine"", ""television""]",arXiv:2022.73303,10.8325/DalW,Nature,2022,Grass-roots actuating framework
Door product western someone plan make speak which. Home note color like.,"[{""name"": ""Patrick Allen"", ""affiliation"": ""Palmer-Ball"", ""email"": ""amay@example.org""}, {""name"": ""Jes",126,None,"[""not"", ""he"", ""wrong""]",arXiv:2024.83375,10.3690/MgLP,Cell,2023,Upgradable reciprocal circuit

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

Output:
{
  "paper_id": "arXiv:2023.54834",
  "title": "Profit-focused radical throughput",
  "authors": [
    {
      "name": "Scott Dunlap",
      "affiliation": "Daniels PLC",
      "email": "williamssheri@example.com"
    },
    {
      "name": "Shawn Payne",
      "affiliation": "Dorsey, Price and Burns",
      "email": "smoyer@example.net"
    },
    {
      "name": "Chase Lee",
      "affiliation": "Garcia Inc",
      "email": "burgesssarah@example.org"
    }
  ],
  "abstract": "Read deal buy final thus. Sure home game rest lose.\nThose any reality if teach.\nMain never still little study clearly today.",
  "keywords": [
    "measure",
    "stage",
    "scene",
    "reason"
  ],
  "publication": {
    "venue": "Science",
    "year": 2020,
    "doi": "10.8776/UhOT"
  },
  "citations": 388,
  "funding_source": "Reese-Perez"
}


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

[User] Output contract as YAML.

[Assistant]
Approach:
1. Task: Create contract 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:
contract_id: CTR-123472
parties:
- name: Palmer-White
  role: party_a
- name: Rodriguez-Moore
  role: party_b
effective_date: '2026-01-06'
term_months: 59
value: 388976
status: pending


[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"?>
<error_log>
<error_id>042db0a1-c9b1-49a9-9d69-5247a8c47159</error_id>
<timestamp>2026-01-07T13:51:27.377057</timestamp>
<level>ERROR</level>
<service>whomService</service>
<message>Each reality trip red enough tough common.</message>
<stack_trace>at note.py:398</stack_trace>
<stack_trace>at purpose.py:452</stack_trace>
<stack_trace>at onto.py:106</stack_trace>
<stack_trace>at member.py:439</stack_trace>
<context>
<user_id>70c0c786-0e43-42b2-8ec7-e975f39a71f7</user_id>
<request_id>95ca942a-a33a-413f-b1a1-a21e12fa0f30</request_id>
</context>
</error_log>

[Assistant]
Approach:
1. Task: Convert error log 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:
{
  "error_id": "042db0a1-c9b1-49a9-9d69-5247a8c47159",
  "timestamp": "2026-01-07T13:51:27.377057",
  "level": "ERROR",
  "service": "whomService",
  "message": "Each reality trip red enough tough common.",
  "stack_trace": [
    "at note.py:398",
    "at purpose.py:452",
    "at onto.py:106",
    "at member.py:439"
  ],
  "context": {
    "user_id": "70c0c786-0e43-42b2-8ec7-e975f39a71f7",
    "request_id": "95ca942a-a33a-413f-b1a1-a21e12fa0f30"
  }
}


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

[User] Output lab result as CSV.

[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
2026-01-06,Lipid,MRN-871984,LAB-4827299,"[{""test"": ""WBC"", ""value"": 156.4, ""unit"": ""g/dL"", ""flag"": ""high""}, {""test"": ""WBC"", ""value"": 186.0, ""u"
2026-01-04,CBC,MRN-322233,LAB-4110221,"[{""test"": ""WBC"", ""value"": 130.9, ""unit"": ""g/dL"", ""flag"": ""low""}, {""test"": ""WBC"", ""value"": 139.4, ""un"
2026-01-03,CBC,MRN-633637,LAB-9180719,"[{""test"": ""WBC"", ""value"": 147.9, ""unit"": ""g/dL"", ""flag"": ""normal""}, {""test"": ""Hemoglobin"", ""value"": "
2026-01-04,Lipid,MRN-329788,LAB-4253485,"[{""test"": ""WBC"", ""value"": 85.8, ""unit"": ""mg/dL"", ""flag"": ""high""}, {""test"": ""Hemoglobin"", ""value"": 15"


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

[User] Create a XML representation of experiment result.

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


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<social_media_post>
<post_id>POST-78526123</post_id>
<platform>twitter</platform>
<user_id>17596017-ad50-41af-8dc2-8746d15af00d</user_id>
<username>qsharp</username>
<content>Seven behavior less water pretty.
Rock key include. Kind than game agreement.
Paper position reduce purpose I affect wait threat. Third effect newspaper before include decision recently million.</content>
<timestamp>2026-01-07T13:51:27.460227</timestamp>
<hashtags>#draw</hashtags>
<hashtags>#five</hashtags>
<hashtags>#culture</hashtags>
<hashtags>#sport</hashtags>
<engagement>
<likes>1826</likes>
<shares>489</shares>
<comments>393</comments>
</engagement>
</social_media_post>

[Assistant]
Approach:
1. Task: Convert social media post 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:
{
  "post_id": "POST-78526123",
  "platform": "twitter",
  "user_id": "17596017-ad50-41af-8dc2-8746d15af00d",
  "username": "qsharp",
  "content": "Seven behavior less water pretty.\nRock key include. Kind than game agreement.\nPaper position reduce purpose I affect wait threat. Third effect newspaper before include decision recently million.",
  "timestamp": "2026-01-07T13:51:27.460227",
  "hashtags": [
    "#draw",
    "#five",
    "#culture",
    "#sport"
  ],
  "engagement": {
    "likes": 1826,
    "shares": 489,
    "comments": 393
  }
}


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

[User] Generate error log data in XML format.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<error_log>
<error_id>424897c8-d97d-4bfb-9c1a-7b6e63fd6096</error_id>
<timestamp>2026-01-07T13:51:27.529237</timestamp>
<level>ERROR</level>
<service>heartService</service>
<message>How these anyone stop indeed.</message>
<stack_trace>at manage.py:289</stack_trace>
<stack_trace>at thing.py:107</stack_trace>
<stack_trace>at guy.py:172</stack_trace>
<stack_trace>at seat.py:479</stack_trace>
<context>
<user_id>082cc3eb-3997-4d99-990c-f696ca4ee534</user_id>
<request_id>0f3326d0-3afd-48c1-9c4d-32cc8b0c5920</request_id>
</context>
</error_log>


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

[User] Create a JSON representation of student assessment.

[Assistant]
Approach:
1. Task: Create student assessment 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:
{
  "assessment_id": "ASMT-353280",
  "student_id": "STU-259399",
  "course_id": "CRS-9241",
  "type": "quiz",
  "date": "2026-01-05",
  "scores": [
    {
      "question": 1,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 6,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 0,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 9,
      "points_earned": 3,
      "points_possible": 10
    },
    {
      "question": 10,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 11,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 12,
      "points_earned": 0,
      "points_possible": 10
    },
    {
      "question": 13,
      "points_earned": 2,
      "points_possible": 10
    }
  ],
  "total_score": 68,
  "percentage": 88.23,
  "grade": "C"
}