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

[User]
Transform this JSON data into CSV format:
{
  "assessment_id": "ASMT-482875",
  "student_id": "STU-646713",
  "course_id": "CRS-2679",
  "type": "assignment",
  "date": "2026-01-01",
  "scores": [
    {
      "question": 1,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 3,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 9,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 10,
      "points_earned": 8,
      "points_possible": 10
    }
  ],
  "total_score": 62,
  "percentage": 98.87,
  "grade": "C"
}

[Assistant]
Approach:
1. Task: Convert student assessment from JSON 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:
assessment_id,code,course_id,credits,date,grade,grading_final,grading_homework,grading_midterm,instructor,percentage,schedule,scores,student_id,term,title,total_score,type
ASMT-482875,,CRS-2679,,2026-01-01,C,,,,,98.87,,"[{""question"": 1, ""points_earned"": 1, ""points_possible"": 10}, {""question"": 2, ""points_earned"": 9, ""po",STU-646713,,,62,assignment
,RJP305,CRS-7530,3,,,40,30,30,Russell Salazar,,"[{""week"": 1, ""topic"": ""prepare""}, {""week"": 2, ""topic"": ""single""}, {""week"": 3, ""topic"": ""expert""}, {""",,,Spring 2024,Phased heuristic flexibility 101,,
,HYW296,CRS-6158,4,,,40,30,30,Robert Morris,,"[{""week"": 1, ""topic"": ""magazine""}, {""week"": 2, ""topic"": ""something""}, {""week"": 3, ""topic"": ""ever""}, ",,,Spring 2021,Object-based directional product 101,,
,MXU363,CRS-7693,3,,,40,30,30,Stephanie Fox,,"[{""week"": 1, ""topic"": ""thank""}, {""week"": 2, ""topic"": ""too""}, {""week"": 3, ""topic"": ""cell""}, {""week"": ",,,Fall 2022,Synergized full-range standardization 101,,
,CNB499,CRS-9415,3,,,40,30,30,Michelle Jimenez,,"[{""week"": 1, ""topic"": ""deal""}, {""week"": 2, ""topic"": ""should""}, {""week"": 3, ""topic"": ""along""}, {""week",,,Spring 2023,Robust actuating collaboration 101,,


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

[User]
Reformat the data below from YAML to CSV:
result_id: LAB-3793814
patient_mrn: MRN-247204
order_date: '2026-01-03'
panel: CBC
results:
- test: Hemoglobin
  value: 188.2
  unit: g/dL
  flag: low
- test: WBC
  value: 197.7
  unit: mg/dL
  flag: high
- test: Glucose
  value: 196.4
  unit: mg/dL
  flag: high
- test: Glucose
  value: 193.9
  unit: g/dL
  flag: high
- test: Glucose
  value: 197.2
  unit: g/dL
  flag: low
- test: Hemoglobin
  value: 109.5
  unit: mg/dL
  flag: normal

[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
2026-01-03,CBC,MRN-247204,LAB-3793814,"[{""test"": ""Hemoglobin"", ""value"": 188.2, ""unit"": ""g/dL"", ""flag"": ""low""}, {""test"": ""WBC"", ""value"": 197"
2026-01-04,CBC,MRN-825014,LAB-9525524,"[{""test"": ""Hemoglobin"", ""value"": 133.3, ""unit"": ""g/dL"", ""flag"": ""high""}, {""test"": ""Hemoglobin"", ""val"
2026-01-02,CMP,MRN-214742,LAB-3768472,"[{""test"": ""Glucose"", ""value"": 148.2, ""unit"": ""g/dL"", ""flag"": ""low""}, {""test"": ""Glucose"", ""value"": 16"
2026-01-03,Lipid,MRN-610171,LAB-7001483,"[{""test"": ""WBC"", ""value"": 69.1, ""unit"": ""mg/dL"", ""flag"": ""low""}, {""test"": ""WBC"", ""value"": 181.6, ""un"
2026-01-02,Lipid,MRN-414898,LAB-3038427,"[{""test"": ""WBC"", ""value"": 81.0, ""unit"": ""g/dL"", ""flag"": ""high""}, {""test"": ""Glucose"", ""value"": 56.2, "


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<api_specification>
<openapi>3.0.0</openapi>
<paths>
</sense>
<get>
<summary>Pay yes agree executive year ahead program.</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>
<//sense>
</paths>
<info>
<title>Customer-focused zero-defect array API</title>
<version>1.0.0</version>
</info>
</api_specification>

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

Output:
{
  "openapi": "3.0.0",
  "paths": {
    "/sense": {
      "get": {
        "summary": "Pay yes agree executive year ahead program.",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  },
  "info": {
    "title": "Customer-focused zero-defect array API",
    "version": "1.0.0"
  }
}


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

[User] Generate financial report data in YAML format.

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

Output:
net_income: 4233102
metrics:
  profit_margin: 14.29
  roe: 18.28
company: Blackwell, Simpson and Pace
eps: 0.79
expenses: 41343491


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

[User] Produce a JSON document for a prescription.

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

Output:
{
  "rx_id": "RX-5305677",
  "patient_mrn": "MRN-215469",
  "prescriber": "Jeremy Hatfield",
  "date": "2026-01-03",
  "medications": [
    {
      "name": "Metformin",
      "dosage": "10mg",
      "frequency": "daily",
      "quantity": 90
    },
    {
      "name": "Metformin",
      "dosage": "5mg",
      "frequency": "daily",
      "quantity": 30
    },
    {
      "name": "Atorvastatin",
      "dosage": "10mg",
      "frequency": "BID",
      "quantity": 90
    }
  ]
}


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

[User]
Convert the following TOML to XML:
review_id = "REV-9982202"
product_id = "PROD-452864"
user_id = "015289de-7f3e-45e2-b1d0-7fe22aff92a9"
rating = 3
title = "Example center fill free."
content = "North describe old attention usually third. Important wish security ago somebody remain everyone modern. Significant chair place throughout study administration American."
date = "2026-01-04"
verified_purchase = false
helpful_votes = 34

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


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

[User] Create a YAML representation of clinical note.

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

Output:
note_id: CN-6952117
patient:
  mrn: MRN-227055
  age: 50
  gender: F
encounter_date: '2026-01-03'
chief_complaint: headache
vitals:
  bp: 146/78
  hr: 63
  temp_f: 97.9
assessment:
- problem: hypertension
  icd10: J35
- problem: hypertension
  icd10: K44
- problem: hypertension
  icd10: I58


[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:
date: '2026-01-05'
title: Teach why painting per short.
rating: 4


[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: complex - 8-10 fields, 3-4 levels
3. Format rules: consistent indentation, colon-space syntax, hyphen lists
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

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


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

[User] Generate research paper data in JSON format.

[Assistant]
Approach:
1. Task: Create research paper 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:
{
  "title": "Polarized methodical algorithm",
  "authors": [
    {
      "name": "Caroline Barnes",
      "affiliation": "Parker Ltd",
      "email": "angelajackson@example.net"
    },
    {
      "name": "Mario Boyd",
      "affiliation": "Johnson, Barber and Higgins",
      "email": "lfuller@example.com"
    }
  ],
  "funding_source": null
}


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

[User] Produce a JSON document for a 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-9701957",
  "product_id": "PROD-683988",
  "user_id": "4d7f9754-e296-4a29-967f-5c8de166a17c",
  "rating": 5,
  "title": "Teach look history according want manager perform.",
  "content": "Admit large politics decide might Mr their. Hundred play I deal but player leader old. Then similar drug coach.",
  "date": "2026-01-03",
  "verified_purchase": false,
  "helpful_votes": 36
}


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

[User] Output prescription as TOML.

[Assistant]
Approach:
1. Task: Create prescription 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:
rx_id = "RX-5855932"
patient_mrn = "MRN-921122"
prescriber = "Spencer Smith"
date = "2026-01-05"
[[medications]]
name = "Metformin"
dosage = "20mg"
frequency = "daily"
quantity = 30


[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: medium - 5-8 fields, 2-3 levels
3. Format rules: header row, comma-separated, quoted fields with commas
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
order_date,panel,patient_mrn,result_id,results
2026-01-06,CMP,MRN-478989,LAB-9047593,"[{""test"": ""Hemoglobin"", ""value"": 171.8, ""unit"": ""mg/dL"", ""flag"": ""normal""}, {""test"": ""WBC"", ""value"":"
2026-01-06,CMP,MRN-240690,LAB-3892435,"[{""test"": ""Glucose"", ""value"": 142.9, ""unit"": ""g/dL"", ""flag"": ""high""}, {""test"": ""Hemoglobin"", ""value"""
2026-01-04,CBC,MRN-701199,LAB-7161198,"[{""test"": ""Glucose"", ""value"": 58.6, ""unit"": ""mg/dL"", ""flag"": ""high""}, {""test"": ""WBC"", ""value"": 50.4,"
2026-01-01,Lipid,MRN-684071,LAB-8865790,"[{""test"": ""Hemoglobin"", ""value"": 64.3, ""unit"": ""g/dL"", ""flag"": ""low""}, {""test"": ""Hemoglobin"", ""value"
2026-01-04,CMP,MRN-247887,LAB-7550762,"[{""test"": ""Glucose"", ""value"": 99.2, ""unit"": ""mg/dL"", ""flag"": ""low""}, {""test"": ""Hemoglobin"", ""value"":"


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

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

[Assistant]
Approach:
1. Task: Create product listing 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:
product_id: PROD-942707
name: Organic demand-driven installation
category: books
price: 698.66
currency: USD
stock: 819
is_available: true
rating: 4.45
reviews: 103
specs:
  weight_kg: 32.63
  dimensions: 66x30x83cm


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

[User] Generate sales analytics data in TOML format.

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

Output:
period = "March 2024"
total_revenue = 2433324
units_sold = 8686
[[channels]]
name = "online"
revenue = 3952303
growth = 2.75

[[channels]]
name = "retail"
revenue = 3970412
growth = 12.57

[[top_products]]
sku = "SKU-2514"
sales = 485558

[[top_products]]
sku = "SKU-5241"
sales = 142515

[[top_products]]
sku = "SKU-4600"
sales = 420300


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

[User] Generate course syllabus data in XML format.

[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-4164</course_id>
RVR286
<title>Team-oriented incremental info-mediaries 101</title>
<instructor>Shannon Miller</instructor>
<credits>3</credits>
<term>Fall 2023</term>
<schedule>
<week>1</week>
<topic>stuff</topic>
</schedule>
<schedule>
<week>2</week>
<topic>professional</topic>
</schedule>
<schedule>
<week>3</week>
<topic>hard</topic>
</schedule>
<schedule>
<week>4</week>
<topic>rather</topic>
</schedule>
<schedule>
<week>5</week>
<topic>lawyer</topic>
</schedule>
<schedule>
<week>6</week>
<topic>camera</topic>
</schedule>
<schedule>
<week>7</week>
<topic>focus</topic>
</schedule>
<schedule>
<week>8</week>
<topic>spend</topic>
</schedule>
<schedule>
<week>9</week>
<topic>couple</topic>
</schedule>
<schedule>
<week>10</week>
<topic>quickly</topic>
</schedule>
<grading>
<homework>30</homework>
<midterm>30</midterm>
<final>40</final>
</grading>
</course_syllabus>


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

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

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

Output:
company,eps,expenses,metrics_profit_margin,metrics_roe,net_income,quarter,revenue,ticker
"Nichols, Ferguson and Butler",3.2,26562838,27.93,5.96,16784469,Q1 2022,39470251,NDVN
Smith-Butler,6.38,5773848,12.47,7.16,5911317,Q2 2024,58381133,NZVM
"Lewis, Schneider and Vasquez",2.13,47941753,18.93,17.23,235510,Q4 2020,14343287,OWPK


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

[User]
Convert the following JSON to XML:
{
  "product_id": "PROD-428311",
  "name": "Object-based value-added workforce",
  "category": "books",
  "price": 802.3,
  "currency": "USD",
  "stock": 719,
  "is_available": true,
  "rating": 1.5,
  "reviews": 81,
  "specs": {
    "weight_kg": 27.85,
    "dimensions": "99x87x32cm"
  }
}

[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-428311</product_id>
<name>Object-based value-added workforce</name>
<category>books</category>
<price>802.3</price>
<currency>USD</currency>
<stock>719</stock>
<is_available>True</is_available>
<rating>1.5</rating>
<reviews>81</reviews>
<specs>
<weight_kg>27.85</weight_kg>
<dimensions>99x87x32cm</dimensions>
</specs>
</product_listing>


[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:
{
  "author": "Jenna Bryant",
  "tags": [
    "most",
    "off",
    "shoulder"
  ],
  "headline": "Secured composite leverage",
  "published": "2026-01-04T22:19:16.750289"
}

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

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


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

[User]
Reformat the data below from TOML to XML:
total_revenue = 6798538
[[channels]]
name = "online"
revenue = 2139770
growth = -9.99

[[channels]]
name = "retail"
revenue = 1809716
growth = 7.01

[[top_products]]
sku = "SKU-3049"
sales = 22854

[[top_products]]
sku = "SKU-5505"
sales = 203281

[[top_products]]
sku = "SKU-9853"
sales = 260538

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<sales_analytics>
<total_revenue>6798538</total_revenue>
<channels>
<name>online</name>
<revenue>2139770</revenue>
<growth>-9.99</growth>
</channels>
<channels>
<name>retail</name>
<revenue>1809716</revenue>
<growth>7.01</growth>
</channels>
<top_products>
<sku>SKU-3049</sku>
<sales>22854</sales>
</top_products>
<top_products>
<sku>SKU-5505</sku>
<sales>203281</sales>
</top_products>
<top_products>
<sku>SKU-9853</sku>
<sales>260538</sales>
</top_products>
</sales_analytics>


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

[User]
Convert the following YAML to JSON:
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.

  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.'
tags:
- movie
- it
- chance
views: 12438
shares: 1329

[Assistant]
Approach:
1. Task: Convert news article 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:
{
  "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
}


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

[User] Create a YAML representation of financial report.

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

Output:
net_income: 16280737
revenue: 93235840
metrics:
  profit_margin: 9.67
  roe: 5.79
expenses: 6835352


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

[User]
Transform this CSV data into JSON format:
abstract,authors,citations,funding_source,info_title,info_version,keywords,openapi,paper_id,paths_/air_get_parameters,paths_/air_get_responses_200_description,paths_/air_get_responses_400_description,paths_/air_get_summary,publication_doi,publication_venue,publication_year,title
,,,,Pre-emptive interactive encryption API,1.0.0,,3.0.0,,"[{""name"": ""param0"", ""in"": ""query"", ""type"": ""string""}]",Success,Bad Request,Final democratic whatever event director guy.,,,,
Nearly many care lead police field seat. Customer store personal be best everything family.,"[{""name"": ""Angel Schroeder"", ""affiliation"": ""Davis Ltd"", ""email"": ""michaeldean@example.net""}, {""name",205,None,,,"[""wonder"", ""feel"", ""plan"", ""federal""]",,arXiv:2023.17978,,,,,10.6326/cwoW,Science,2022,Expanded bi-directional firmware
How process natural relationship still friend court. Have herself both cover page. Music full of you,"[{""name"": ""Juan Nguyen"", ""affiliation"": ""Gonzalez-Gonzalez"", ""email"": ""tamara52@example.net""}, {""nam",468,Clark Group,,,"[""deal"", ""concern"", ""challenge""]",,arXiv:2024.29034,,,,,10.1598/cNqA,Nature,2020,Robust non-volatile emulation

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

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


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

[User] Output transaction record as TOML.

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

Output:
txn_id = "TXN-23430167"
customer_id = "7fb2e914-3f0f-4c3f-abb9-ef22ed2c1064"
timestamp = "2026-01-07T13:51:26.046328"
subtotal = 152.9
tax = 14.6
total = 796.85
payment_method = "apple_pay"
[[items]]
sku = "SKU-63492"
qty = 1
price = 90.17

[[items]]
sku = "SKU-56350"
qty = 5
price = 336.79


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

[User]
Transform this CSV data into JSON format:
date,medications,patient_mrn,prescriber,rx_id
2026-01-04,"[{""name"": ""Metformin"", ""dosage"": ""20mg"", ""frequency"": ""TID"", ""quantity"": 30}, {""name"": ""Metformin"", ",MRN-277514,Timothy Goodman,RX-9442688
2026-01-05,"[{""name"": ""Atorvastatin"", ""dosage"": ""10mg"", ""frequency"": ""TID"", ""quantity"": 60}, {""name"": ""Atorvasta",MRN-666429,Sarah Rivera,RX-4605582
2026-01-01,"[{""name"": ""Atorvastatin"", ""dosage"": ""10mg"", ""frequency"": ""BID"", ""quantity"": 90}, {""name"": ""Lisinopri",MRN-199282,Barbara Rosales,RX-4998864
2026-01-03,"[{""name"": ""Atorvastatin"", ""dosage"": ""10mg"", ""frequency"": ""TID"", ""quantity"": 90}]",MRN-643231,Denise Mullen,RX-4860420

[Assistant]
Approach:
1. Task: Convert prescription 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:
{
  "rx_id": "RX-9442688",
  "patient_mrn": "MRN-277514",
  "prescriber": "Timothy Goodman",
  "date": "2026-01-04",
  "medications": [
    {
      "name": "Metformin",
      "dosage": "20mg",
      "frequency": "TID",
      "quantity": 30
    },
    {
      "name": "Metformin",
      "dosage": "5mg",
      "frequency": "BID",
      "quantity": 30
    },
    {
      "name": "Lisinopril",
      "dosage": "5mg",
      "frequency": "TID",
      "quantity": 30
    }
  ]
}


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

[User] Create a CSV representation of contract.

[Assistant]
Approach:
1. Task: Create contract 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,effective_date,funding_source,keywords,paper_id,publication_doi,publication_venue,publication_year,status,term_months,title,value
,,,2026-01-03,,,,,,,executed,24,,837359
Create author deep beat break them concern. Mother not hit road. Develop trade eight lay camera.,"[{""name"": ""Cameron Combs"", ""affiliation"": ""Roberts Group"", ""email"": ""stewartdavid@example.org""}, {""n",1,,None,"[""instead"", ""without"", ""pass"", ""work""]",arXiv:2024.54008,10.2217/fDwl,Nature,2022,,,Polarized didactic implementation,
Million position statement appear seem difference capital. Somebody network call movie office month.,"[{""name"": ""Brian Brown"", ""affiliation"": ""Wolfe-Ochoa"", ""email"": ""cpeters@example.net""}, {""name"": ""Sa",359,,Bishop-Barnes,"[""teacher"", ""fund"", ""oil"", ""fact"", ""include""]",arXiv:2024.35432,10.8620/aDnX,Science,2024,,,Decentralized intermediate challenge,
Budget improve huge character. We money bag executive name great. Actually record drug record.,"[{""name"": ""Hannah Brooks"", ""affiliation"": ""Brown, Nguyen and Martin"", ""email"": ""roger22@example.com""",221,,"Valencia, Myers and Miller","[""white"", ""by"", ""safe"", ""professional""]",arXiv:2021.56267,10.1547/YAIw,Nature,2020,,,Optional high-level extranet,


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

[User] Generate clinical note data in CSV format.

[Assistant]
Approach:
1. Task: Create clinical note 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:
assessment,chief_complaint,encounter_date,note_id,patient_age,patient_gender,patient_mrn,vitals_bp,vitals_hr,vitals_temp_f
,,,CN-3759937,30,M,MRN-802088,119/74,67,100.9
"[{""problem"": ""diabetes"", ""icd10"": ""J95""}, {""problem"": ""diabetes"", ""icd10"": ""I43""}, {""problem"": ""hype",fever,2026-01-03,CN-7361771,74,F,MRN-264539,129/66,86,103.0
"[{""problem"": ""diabetes"", ""icd10"": ""J10""}, {""problem"": ""hypertension"", ""icd10"": ""K99""}, {""problem"": """,fever,2026-01-02,CN-3812265,69,M,MRN-504012,109/82,60,97.1
"[{""problem"": ""diabetes"", ""icd10"": ""I74""}, {""problem"": ""diabetes"", ""icd10"": ""I56""}]",headache,2026-01-02,CN-7745905,60,M,MRN-317880,125/104,61,102.7


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

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

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

Output:
{
  "openapi": "3.0.0",
  "info": {
    "title": "Re-engineered mobile superstructure API",
    "version": "1.0.0"
  },
  "paths": {
    "/benefit": {
      "get": {
        "summary": "Chair media space recognize doctor would second me",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          },
          {
            "name": "param1",
            "in": "query",
            "type": "string"
          },
          {
            "name": "param2",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  }
}


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

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

[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-18209344
platform: facebook
user_id: 8880ae5d-22ce-466e-ac5d-224201417b5e
username: xmcbride
content: 'Determine live compare center as direction. Eye experience low wear. If
  south level.

  Worry expect style camera. Scene majority pay voice television professor.'
timestamp: '2026-01-07T13:51:27.602464'
hashtags:
- '#culture'
- '#whole'
- '#central'
engagement:
  likes: 2214
  shares: 878
  comments: 146


[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"?>
<product_listing>
<product_id>PROD-319304</product_id>
<name>Self-enabling clear-thinking help-desk</name>
<category>clothing</category>
<price>510.64</price>
<currency>USD</currency>
<stock>595</stock>
<is_available>True</is_available>
<rating>2.22</rating>
<reviews>791</reviews>
<specs>
<weight_kg>30.42</weight_kg>
<dimensions>12x58x39cm</dimensions>
</specs>
</product_listing>

[Assistant]
Approach:
1. Task: Convert product listing 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:
{
  "product_id": "PROD-319304",
  "name": "Self-enabling clear-thinking help-desk",
  "category": "clothing",
  "price": 510.64,
  "currency": "USD",
  "stock": 595,
  "is_available": true,
  "rating": 2.22,
  "reviews": 791,
  "specs": {
    "weight_kg": 30.42,
    "dimensions": "12x58x39cm"
  }
}


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

[User] Output error log as JSON.

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

Output:
{
  "error_id": "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 TOML format. Think step-by-step, then generate syntactically perfect TOML.

[User] Generate transaction record data in TOML format.

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

Output:
txn_id = "TXN-98000345"
customer_id = "681a59bc-1151-4d49-8e75-1af0878315cb"
timestamp = "2026-01-07T13:51:26.087659"
subtotal = 948.16
tax = 93.65
total = 1389.7
payment_method = "credit_card"
[[items]]
sku = "SKU-50616"
qty = 3
price = 180.94

[[items]]
sku = "SKU-82812"
qty = 5
price = 490.31


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

[User]
Convert the following YAML to XML:
items:
- sku: SKU-89816
  qty: 1
  price: 437.44
- sku: SKU-65650
  qty: 1
  price: 455.72
- sku: SKU-98183
  qty: 3
  price: 337.62
total: 1900.4
payment_method: apple_pay

[Assistant]
Approach:
1. Task: Convert transaction record 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"?>
<transaction_record>
<items>
<sku>SKU-89816</sku>
<qty>1</qty>
<price>437.44</price>
</items>
<items>
<sku>SKU-65650</sku>
<qty>1</qty>
<price>455.72</price>
</items>
<items>
<sku>SKU-98183</sku>
<qty>3</qty>
<price>337.62</price>
</items>
<total>1900.4</total>
<payment_method>apple_pay</payment_method>
</transaction_record>


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

[User]
Transform this XML data into TOML format:
<?xml version="1.0" encoding="UTF-8"?>
<clinical_note>
<vitals>
<bp>97/107</bp>

107

<temp_f>99.6</temp_f>
</vitals>
<patient>
<mrn>MRN-705297</mrn>
<age>67</age>
<gender>F</gender>
</patient>
<chief_complaint>chest pain</chief_complaint>
<assessment>
<problem>hypertension</problem>
<icd10>K41</icd10>
</assessment>
<assessment>
<problem>hypertension</problem>
<icd10>J91</icd10>
</assessment>
<assessment>
<problem>hypertension</problem>
<icd10>J64</icd10>
</assessment>
<note_id>CN-6154695</note_id>
</clinical_note>

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

Output:
chief_complaint = "chest pain"
note_id = "CN-6154695"
[[assessment]]
problem = "hypertension"
icd10 = "K41"

[[assessment]]
problem = "hypertension"
icd10 = "J91"

[[assessment]]
problem = "hypertension"
icd10 = "J64"

[vitals]
bp = "97/107"
hr = 107
temp_f = 99.6

[patient]
mrn = "MRN-705297"
age = 67
gender = "F"


[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: 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:
review_id: REV-8549692
product_id: PROD-108019
user_id: a4c4fbe3-7a0e-49f5-b14b-2ab1ca2d6ed5
rating: 4
title: Development know write believe teacher ability.
content: 'Guy generation provide economy test bit. Page cost and.

  Arm test ok green. Likely card reality school stop something those.

  Your spend discuss yeah hear. Same language box us magazine simple.'
date: '2026-01-06'
verified_purchase: true
helpful_votes: 22


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

[User] Produce a CSV document for a contract.

[Assistant]
Approach:
1. Task: Create contract 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:
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-293527,2026-01-06,"[{""name"": ""Pearson, Hayes and Miller"", ""role"": ""party_a""}, {""name"": ""Johnson LLC"", ""role"": ""party_b""",pending,26,761782
CTR-879663,2026-01-04,"[{""name"": ""Fuller, Williams and Glass"", ""role"": ""party_a""}, {""name"": ""Fry Ltd"", ""role"": ""party_b""}]",pending,59,716297
CTR-777920,2026-01-01,"[{""name"": ""Stanley-Miller"", ""role"": ""party_a""}, {""name"": ""Gibson, Wall and Mcconnell"", ""role"": ""part",pending,13,757097


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

[User] Generate transaction record data in JSON format.

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

[User] Generate sales analytics data in JSON format.

[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 2024",
  "total_revenue": 2433324,
  "units_sold": 8686,
  "channels": [
    {
      "name": "online",
      "revenue": 3952303,
      "growth": 2.75
    },
    {
      "name": "retail",
      "revenue": 3970412,
      "growth": 12.57
    }
  ],
  "top_products": [
    {
      "sku": "SKU-2514",
      "sales": 485558
    },
    {
      "sku": "SKU-5241",
      "sales": 142515
    },
    {
      "sku": "SKU-4600",
      "sales": 420300
    }
  ]
}


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

[User] Create a TOML representation of customer review.

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

Output:
review_id = "REV-9701957"
product_id = "PROD-683988"
user_id = "4d7f9754-e296-4a29-967f-5c8de166a17c"
rating = 5
title = "Teach look history according want manager perform."
content = "Admit large politics decide might Mr their. Hundred play I deal but player leader old. Then similar drug coach."
date = "2026-01-03"
verified_purchase = false
helpful_votes = 36


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

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

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

Output:
review_id = "REV-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 TOML format. Think step-by-step, then generate syntactically perfect TOML.

[User] Create a TOML representation of api specification.

[Assistant]
Approach:
1. Task: Create api specification 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:
openapi = "3.0.0"

[info]
title = "Optional bottom-line complexity API"
version = "1.0.0"

[paths."/traditional".get]
summary = "Discussion then kind hair."
[[paths."/traditional".get.parameters]]
name = "param0"
in = "query"
type = "string"

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

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

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


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

[User]
Transform this JSON data into XML format:
{
  "post_id": "POST-32645861",
  "platform": "facebook",
  "user_id": "b5521d05-1410-43ee-b828-2c240f95461c",
  "username": "yanderson",
  "content": "Example suggest around pattern small everybody. Rate watch blue walk test camera. Partner decide leave really.",
  "timestamp": "2026-01-07T13:51:27.526455",
  "hashtags": [
    "#door",
    "#relate"
  ],
  "engagement": {
    "likes": 5828,
    "shares": 957,
    "comments": 117
  }
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<social_media_post>
<post_id>POST-32645861</post_id>
<platform>facebook</platform>
<user_id>b5521d05-1410-43ee-b828-2c240f95461c</user_id>
<username>yanderson</username>
<content>Example suggest around pattern small everybody. Rate watch blue walk test camera. Partner decide leave really.</content>
<timestamp>2026-01-07T13:51:27.526455</timestamp>
<hashtags>#door</hashtags>
<hashtags>#relate</hashtags>
<engagement>
<likes>5828</likes>
<shares>957</shares>
<comments>117</comments>
</engagement>
</social_media_post>


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

[User]
Transform this YAML data into TOML format:
level: ERROR
service: writeService
error_id: 85223c4c-4b76-4351-95ee-55a2460043f3

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

Output:
level = "ERROR"
service = "writeService"
error_id = "85223c4c-4b76-4351-95ee-55a2460043f3"


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

[User]
Reformat the data below from JSON to XML:
{
  "rx_id": "RX-9001624",
  "patient_mrn": "MRN-695608",
  "prescriber": "Stephen Davis",
  "date": "2026-01-05",
  "medications": [
    {
      "name": "Lisinopril",
      "dosage": "20mg",
      "frequency": "daily",
      "quantity": 90
    }
  ]
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<prescription>
<rx_id>RX-9001624</rx_id>
<patient_mrn>MRN-695608</patient_mrn>
<prescriber>Stephen Davis</prescriber>
<date>2026-01-05</date>
<medications>
<name>Lisinopril</name>
<dosage>20mg</dosage>
<frequency>daily</frequency>
<quantity>90</quantity>
</medications>
</prescription>


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

[User]
Reformat the data below from JSON to XML:
{
  "post_id": "POST-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.\nGovernment 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
  }
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<social_media_post>
<post_id>POST-19844803</post_id>
<platform>instagram</platform>
<user_id>eee48898-e428-4685-b6ea-d0074f4ffb8a</user_id>
<username>pinedaryan</username>
<content>Between past agree writer forget big. Simple glass protect job answer thank.
Government prepare rather agency hard. Fear director room future hospital.</content>
<timestamp>2026-01-07T13:51:25.753060</timestamp>
<hashtags>#fast</hashtags>
<hashtags>#imagine</hashtags>
<hashtags>#carry</hashtags>
<engagement>
<likes>1299</likes>
<shares>900</shares>
<comments>90</comments>
</engagement>
</social_media_post>


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

[User] Generate product listing data in JSON format.

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

Output:
{
  "product_id": "PROD-831490",
  "name": "Seamless optimal task-force",
  "category": "electronics",
  "price": 975.8,
  "currency": "USD",
  "stock": 924,
  "is_available": true,
  "rating": 2.71,
  "reviews": 121,
  "specs": {
    "weight_kg": 17.77,
    "dimensions": "52x27x46cm"
  }
}


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

[User] Generate clinical note data in YAML format.

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

Output:
note_id: CN-4493327
patient:
  mrn: MRN-934301
  age: 62
  gender: F
encounter_date: '2026-01-06'
chief_complaint: fever
vitals:
  bp: 141/91
  hr: 100
  temp_f: 98.5
assessment:
- problem: diabetes
  icd10: I32


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

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

[Assistant]
Approach:
1. Task: Create product listing 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"?>
<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 YAML format. Think step-by-step, then generate syntactically perfect YAML.

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

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

Output:
experiment_id: EXP-137327
title: Effect of class on read
methodology:
  design: RCT
  sample_size: 679
  duration_days: 111
results:
- metric: safety
  baseline: 73.26
  endpoint: 72.84
  p_value: 0.0533
- metric: efficacy
  baseline: 49.24
  endpoint: 28.3
  p_value: 0.0809
conclusion: significant


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

[User] Output customer review as XML.

[Assistant]
Approach:
1. Task: Create customer review in XML
2. Complexity: 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"?>
<customer_review>
<date>2026-01-04</date>
<user_id>d6e6e646-61a4-4af9-a9a1-d03d234244eb</user_id>
<content>It herself scene five side support onto. Shake fear western believe. Say fact shoulder investment television pretty suffer.
Ground listen official hand at indeed. Effort thus wife control.</content>
</customer_review>


[System] You are an expert in 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: 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-948175",
  "student_id": "STU-160858",
  "course_id": "CRS-5368",
  "type": "assignment",
  "date": "2026-01-03",
  "scores": [
    {
      "question": 1,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 9,
      "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": 9,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 3,
      "points_possible": 10
    },
    {
      "question": 9,
      "points_earned": 9,
      "points_possible": 10
    }
  ],
  "total_score": 89,
  "percentage": 96.29,
  "grade": "B"
}


[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: 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-718533",
  "student_id": "STU-781568",
  "course_id": "CRS-7994",
  "type": "assignment",
  "date": "2026-01-03",
  "scores": [
    {
      "question": 1,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 5,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 0,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 5,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 9,
      "points_earned": 6,
      "points_possible": 10
    },
    {
      "question": 10,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 11,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 12,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 13,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 14,
      "points_earned": 3,
      "points_possible": 10
    }
  ],
  "total_score": 62,
  "percentage": 88.34,
  "grade": "B"
}


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

[User]
Convert the following JSON to XML:
{
  "result_id": "LAB-5387789",
  "patient_mrn": "MRN-887521",
  "order_date": "2026-01-05",
  "panel": "CBC",
  "results": [
    {
      "test": "WBC",
      "value": 66.6,
      "unit": "mg/dL",
      "flag": "normal"
    },
    {
      "test": "Glucose",
      "value": 111.4,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "Hemoglobin",
      "value": 168.1,
      "unit": "g/dL",
      "flag": "high"
    },
    {
      "test": "Hemoglobin",
      "value": 136.7,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "WBC",
      "value": 148.7,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "Glucose",
      "value": 86.9,
      "unit": "mg/dL",
      "flag": "normal"
    }
  ]
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<lab_result>
<result_id>LAB-5387789</result_id>
<patient_mrn>MRN-887521</patient_mrn>
<order_date>2026-01-05</order_date>
<panel>CBC</panel>
<results>
<test>WBC</test>
<value>66.6</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Glucose</test>
<value>111.4</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>168.1</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>136.7</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>WBC</test>
<value>148.7</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Glucose</test>
<value>86.9</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
</lab_result>


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

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

[Assistant]
Approach:
1. Task: Create financial report 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:
company,eps,expenses,metrics_profit_margin,metrics_roe,net_income,quarter,revenue,ticker
Thompson LLC,0.69,967762,22.56,23.58,16633381,Q2 2020,63838743,QQLN
"Alvarado, Jefferson and Fowler",7.31,62078740,25.79,14.61,18352362,Q4 2023,55620742,GGGW
"Miller, Anderson and Brooks",9.82,49609947,12.67,6.82,2637276,Q4 2022,50641904,UDAE
Chapman-Vasquez,4.3,32240329,14.21,5.42,2773314,Q4 2024,44604389,STOB
"Gibson, Oconnor and Gutierrez",9.64,21945315,14.0,13.41,15970306,Q2 2020,46676417,ZWYS


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

[User] Output api specification as YAML.

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

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


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

[User] Generate research paper data in XML format.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<research_paper>
<paper_id>arXiv:2022.79764</paper_id>
<title>Progressive exuding adapter</title>
<authors>
<name>Gary Johnson</name>
<affiliation>Wolf Group</affiliation>
<email>jamie40@example.org</email>
</authors>
<authors>
<name>Lisa Ortega</name>
<affiliation>Wells, Flores and Cooper</affiliation>
<email>nicholas25@example.com</email>
</authors>
<authors>
<name>Kimberly Alvarez</name>
<affiliation>Lewis-Hunt</affiliation>
<email>bookersteven@example.com</email>
</authors>
<abstract>Win both purpose hour professor table.</abstract>
<keywords>office</keywords>
<keywords>during</keywords>
<keywords>more</keywords>
<keywords>apply</keywords>
<keywords>program</keywords>
<publication>
<venue>Nature</venue>
<year>2023</year>
<doi>10.1780/NyHo</doi>
</publication>
<citations>258</citations>
<funding_source>Espinoza, Khan and Lowe</funding_source>
</research_paper>


[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-619223
parties:
- name: Mcdaniel LLC
  role: party_a
- name: Hunt-Bowman
  role: party_b
effective_date: '2026-01-03'
term_months: 21
value: 87478
status: pending


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

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

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

Output:
post_id = "POST-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]
Convert the following JSON to XML:
{
  "period": "June 2020",
  "total_revenue": 2603625,
  "units_sold": 51574,
  "channels": [
    {
      "name": "retail",
      "revenue": 1926384,
      "growth": 34.29
    },
    {
      "name": "online",
      "revenue": 1062444,
      "growth": -1.99
    }
  ],
  "top_products": [
    {
      "sku": "SKU-3818",
      "sales": 48786
    },
    {
      "sku": "SKU-7605",
      "sales": 408187
    },
    {
      "sku": "SKU-6728",
      "sales": 223732
    }
  ]
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<sales_analytics>
<period>June 2020</period>
<total_revenue>2603625</total_revenue>
<units_sold>51574</units_sold>
<channels>
<name>retail</name>
<revenue>1926384</revenue>
<growth>34.29</growth>
</channels>
<channels>
<name>online</name>
<revenue>1062444</revenue>
<growth>-1.99</growth>
</channels>
<top_products>
<sku>SKU-3818</sku>
<sales>48786</sales>
</top_products>
<top_products>
<sku>SKU-7605</sku>
<sales>408187</sales>
</top_products>
<top_products>
<sku>SKU-6728</sku>
<sales>223732</sales>
</top_products>
</sales_analytics>


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

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

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

Output:
course_id = "CRS-4164"
code = "RVR286"
title = "Team-oriented incremental info-mediaries 101"
instructor = "Shannon Miller"
credits = 3
term = "Fall 2023"
[[schedule]]
week = 1
topic = "stuff"

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

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

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

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

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

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

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

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

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

[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] Produce a JSON document for a transaction record.

[Assistant]
Approach:
1. Task: Create transaction record 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:
{
  "txn_id": "TXN-30876983",
  "customer_id": "b5aca191-66fe-49e0-85ce-2d363d5ef454",
  "timestamp": "2026-01-07T13:51:26.163076",
  "items": [
    {
      "sku": "SKU-56664",
      "qty": 2,
      "price": 285.83
    },
    {
      "sku": "SKU-25305",
      "qty": 1,
      "price": 45.15
    },
    {
      "sku": "SKU-78820",
      "qty": 4,
      "price": 47.49
    }
  ],
  "subtotal": 199.93,
  "tax": 118.13,
  "total": 913.78,
  "payment_method": "apple_pay"
}


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

[User] Output transaction record as CSV.

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

Output:
abstract,authors,citations,funding_source,keywords,paper_id,payment_method,publication_doi,publication_venue,publication_year,subtotal,title,total
,,,,,,apple_pay,,,,205.31,,1732.06
Ability budget west experience. Article thing their statement guy. Very life skill fear executive tr,"[{""name"": ""Karen Olson"", ""affiliation"": ""Bryant, Harris and Baker"", ""email"": ""tinagraves@example.com",246,None,"[""give"", ""brother"", ""federal"", ""some"", ""senior""]",arXiv:2021.85268,,10.2921/PETm,Nature,2020,,Integrated analyzing knowledgebase,
Only drive happen size stay run many. Generation down national check strategy.,"[{""name"": ""Olivia Clark"", ""affiliation"": ""Hawkins-Kelley"", ""email"": ""vgarcia@example.net""}, {""name"":",206,"Boone, Bell and Keller","[""campaign"", ""nothing"", ""often""]",arXiv:2022.65815,,10.7165/uJjY,Nature,2023,,Quality-focused full-range definition,


[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:
{
  "product_id": "PROD-325945",
  "name": "Universal bottom-line system engine",
  "category": "electronics",
  "price": 225.75,
  "currency": "USD",
  "stock": 955,
  "is_available": true,
  "rating": 3.31,
  "reviews": 802,
  "specs": {
    "weight_kg": 22.25,
    "dimensions": "77x29x32cm"
  }
}

[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-325945</product_id>
<name>Universal bottom-line system engine</name>
<category>electronics</category>
<price>225.75</price>
<currency>USD</currency>
<stock>955</stock>
<is_available>True</is_available>
<rating>3.31</rating>
<reviews>802</reviews>
<specs>
<weight_kg>22.25</weight_kg>
<dimensions>77x29x32cm</dimensions>
</specs>
</product_listing>


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

[User] Generate contract data in XML format.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<contract>
<term_months>33</term_months>
<parties>
<name>Hart-Villanueva</name>
<role>party_a</role>
</parties>
<parties>
<name>Roberts Ltd</name>
<role>party_b</role>
</parties>
<effective_date>2026-01-05</effective_date>
<value>95653</value>
</contract>


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

[User] Generate experiment result data in XML format.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<experiment_result>
<experiment_id>EXP-942720</experiment_id>
<title>Effect of edge on when</title>
<methodology>
<design>cohort</design>
<sample_size>645</sample_size>
<duration_days>54</duration_days>
</methodology>
<results>
<metric>safety</metric>
<baseline>79.64</baseline>
<endpoint>26.86</endpoint>
<p_value>0.2863</p_value>
</results>
<results>
<metric>safety</metric>
<baseline>55.57</baseline>
<endpoint>59.78</endpoint>
<p_value>0.1705</p_value>
</results>
<results>
<metric>efficacy</metric>
<baseline>30.69</baseline>
<endpoint>27.4</endpoint>
<p_value>0.1116</p_value>
</results>
<results>
<metric>efficacy</metric>
<baseline>32.07</baseline>
<endpoint>35.79</endpoint>
<p_value>0.1946</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] Output clinical note as JSON.

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


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

[User] Generate experiment result data in TOML format.

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

Output:
experiment_id = "EXP-318732"
title = "Effect of produce on stock"
conclusion = "non-significant"
[[results]]
metric = "safety"
baseline = 20.77
endpoint = 67.03
p_value = 0.1826

[[results]]
metric = "safety"
baseline = 69.69
endpoint = 32.04
p_value = 0.1176

[methodology]
design = "observational"
sample_size = 303
duration_days = 155


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

[User] Create a CSV representation of lab result.

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

Output:
order_date,panel,patient_mrn,result_id,results
2026-01-06,Lipid,MRN-496025,LAB-5796495,"[{""test"": ""Hemoglobin"", ""value"": 74.9, ""unit"": ""g/dL"", ""flag"": ""low""}, {""test"": ""Hemoglobin"", ""value"
2026-01-03,CBC,MRN-797266,LAB-9032696,"[{""test"": ""Hemoglobin"", ""value"": 85.1, ""unit"": ""g/dL"", ""flag"": ""low""}, {""test"": ""Glucose"", ""value"": "
2026-01-04,CMP,MRN-148220,LAB-1764345,"[{""test"": ""WBC"", ""value"": 53.8, ""unit"": ""g/dL"", ""flag"": ""high""}, {""test"": ""Hemoglobin"", ""value"": 199"
2026-01-06,CBC,MRN-914718,LAB-6311343,"[{""test"": ""Hemoglobin"", ""value"": 166.5, ""unit"": ""mg/dL"", ""flag"": ""high""}, {""test"": ""Glucose"", ""value"


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

[User] Generate api specification data in YAML format.

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

Output:
openapi: 3.0.0
info:
  title: Optional bottom-line complexity API
  version: 1.0.0
paths:
  /traditional:
    get:
      summary: Discussion then kind hair.
      parameters:
      - name: param0
        in: query
        type: string
      - name: param1
        in: query
        type: string
      responses:
        '200':
          description: Success
        '400':
          description: Bad Request


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

[User] Produce a XML document for a 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-20150897</post_id>
<platform>instagram</platform>
<user_id>ace3958f-4578-4576-9236-9cbfc1f62953</user_id>
<username>spatrick</username>
<content>About industry woman size. Available box return camera public time. Establish outside ability sport describe air who.
Certain miss girl different both wife. Blood relationship if model.</content>
<timestamp>2026-01-07T13:51:25.995017</timestamp>
<hashtags>#share</hashtags>
<hashtags>#prevent</hashtags>
<hashtags>#entire</hashtags>
<hashtags>#owner</hashtags>
<engagement>
<likes>3129</likes>
<shares>891</shares>
<comments>28</comments>
</engagement>
</social_media_post>


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

[User]
Convert the following XML to CSV:
<?xml version="1.0" encoding="UTF-8"?>
<transaction_record>
<txn_id>TXN-59995807</txn_id>
<customer_id>0d66cadd-c42f-4e9b-ae40-46d71f47623d</customer_id>
<timestamp>2026-01-07T13:51:27.084892</timestamp>
<items>
<sku>SKU-83766</sku>
<qty>4</qty>
<price>55.35</price>
</items>
<items>
<sku>SKU-77209</sku>
<qty>2</qty>
<price>217.97</price>
</items>
<items>
<sku>SKU-11210</sku>
<qty>5</qty>
<price>436.04</price>
</items>
<subtotal>1600.85</subtotal>
<tax>34.84</tax>
<total>602.79</total>
<payment_method>apple_pay</payment_method>
</transaction_record>

[Assistant]
Approach:
1. Task: Convert transaction record 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:
customer_id,items,payment_method,subtotal,tax,timestamp,total,txn_id
0d66cadd-c42f-4e9b-ae40-46d71f47623d,"[{""sku"": ""SKU-83766"", ""qty"": 4, ""price"": 55.35}, {""sku"": ""SKU-77209"", ""qty"": 2, ""price"": 217.97}, {""",apple_pay,1600.85,34.84,2026-01-07T13:51:27.084892,602.79,TXN-59995807
fc5bc0fc-5610-443e-84f4-98f2aabfa36a,"[{""sku"": ""SKU-94211"", ""qty"": 3, ""price"": 342.97}, {""sku"": ""SKU-43833"", ""qty"": 1, ""price"": 327.6}, {""",apple_pay,343.36,177.95,2026-01-07T13:51:27.086217,233.76,TXN-94960112
bfea1dd4-3e4d-4152-9e72-15765b683f24,"[{""sku"": ""SKU-45015"", ""qty"": 5, ""price"": 392.83}, {""sku"": ""SKU-69017"", ""qty"": 1, ""price"": 443.02}]",paypal,1892.9,158.99,2026-01-07T13:51:27.086262,616.38,TXN-82250594
0eab4114-9644-4e3f-96b9-71785d9e6ba6,"[{""sku"": ""SKU-26390"", ""qty"": 4, ""price"": 492.46}, {""sku"": ""SKU-59120"", ""qty"": 5, ""price"": 455.89}, {",paypal,156.2,48.74,2026-01-07T13:51:27.086297,553.54,TXN-18355431
4c051ca3-66e6-48f3-a91d-e229b3cfd16a,"[{""sku"": ""SKU-99804"", ""qty"": 5, ""price"": 54.06}]",paypal,1668.56,11.2,2026-01-07T13:51:27.086339,2191.56,TXN-18363692


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

[User] Produce a TOML document for a contract.

[Assistant]
Approach:
1. Task: Create contract 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:
contract_id = "CTR-143990"
effective_date = "2026-01-02"
term_months = 32
value = 452000
status = "active"
[[parties]]
name = "Brady Inc"
role = "party_a"

[[parties]]
name = "Gonzalez, Coleman and Sanchez"
role = "party_b"


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<experiment_result>
<experiment_id>EXP-137327</experiment_id>
<title>Effect of class on read</title>
<methodology>
<design>RCT</design>
<sample_size>679</sample_size>
<duration_days>111</duration_days>
</methodology>
<results>
<metric>safety</metric>
<baseline>73.26</baseline>
<endpoint>72.84</endpoint>
<p_value>0.0533</p_value>
</results>
<results>
<metric>efficacy</metric>
<baseline>49.24</baseline>
<endpoint>28.3</endpoint>
<p_value>0.0809</p_value>
</results>
<conclusion>significant</conclusion>
</experiment_result>

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

Output:
{
  "experiment_id": "EXP-137327",
  "title": "Effect of class on read",
  "methodology": {
    "design": "RCT",
    "sample_size": 679,
    "duration_days": 111
  },
  "results": [
    {
      "metric": "safety",
      "baseline": 73.26,
      "endpoint": 72.84,
      "p_value": 0.0533
    },
    {
      "metric": "efficacy",
      "baseline": 49.24,
      "endpoint": 28.3,
      "p_value": 0.0809
    }
  ],
  "conclusion": "significant"
}


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

[User] Create a XML representation of lab result.

[Assistant]
Approach:
1. Task: Create lab result 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"?>
<lab_result>
<patient_mrn>MRN-119365</patient_mrn>
<order_date>2026-01-05</order_date>
<results>
<test>Glucose</test>
<value>134.6</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>69.4</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Glucose</test>
<value>85.6</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>WBC</test>
<value>69.6</value>
<unit>mg/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>79.1</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
</lab_result>


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

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

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

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


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

[User]
Reformat the data below from CSV to YAML:
abstract,authors,citations,eps,expenses,funding_source,keywords,net_income,paper_id,publication_doi,publication_venue,publication_year,quarter,revenue,title
,,,5.75,65628233,,,6367407,,,,,Q2 2023,73745517,
But development pressure hope about. Street city hospital six his woman series.,"[{""name"": ""Christina Hernandez"", ""affiliation"": ""Cardenas-Lyons"", ""email"": ""hrichardson@example.net""",152,,,Lam-Thompson,"[""trade"", ""consider"", ""stuff""]",,arXiv:2022.23624,10.3200/kISO,Science,2021,,,Optional context-sensitive firmware
"To administration by site less. Lot compare better choose might.
Probably space detail tend.","[{""name"": ""Catherine Baker"", ""affiliation"": ""Robbins Group"", ""email"": ""melissamcguire@example.net""},",288,,,"Valencia, Jackson and Boyd","[""community"", ""foot"", ""special"", ""million""]",,arXiv:2020.47472,10.9274/wmpG,Science,2020,,,Multi-layered 24hour interface

[Assistant]
Approach:
1. Task: Convert financial report from CSV to 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. Transform values to match the target format specifications.

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


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

[User] Generate contract data in TOML format.

[Assistant]
Approach:
1. Task: Create contract 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:
contract_id = "CTR-640570"
effective_date = "2026-01-06"
term_months = 52
value = 450714
status = "pending"
[[parties]]
name = "Mitchell-Clark"
role = "party_a"

[[parties]]
name = "Simmons-Marquez"
role = "party_b"


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<transaction_record>
<txn_id>TXN-98000345</txn_id>
<customer_id>681a59bc-1151-4d49-8e75-1af0878315cb</customer_id>
<timestamp>2026-01-07T13:51:26.087659</timestamp>
<items>
<sku>SKU-50616</sku>
<qty>3</qty>
<price>180.94</price>
</items>
<items>
<sku>SKU-82812</sku>
<qty>5</qty>
<price>490.31</price>
</items>
<subtotal>948.16</subtotal>
<tax>93.65</tax>
<total>1389.7</total>
<payment_method>credit_card</payment_method>
</transaction_record>


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

[User]
Convert the following JSON to XML:
{
  "publication": {
    "venue": "Cell",
    "year": 2021,
    "doi": "10.3653/hXNF"
  },
  "funding_source": "Kramer Ltd",
  "title": "Configurable bandwidth-monitored strategy",
  "authors": [
    {
      "name": "James Brown",
      "affiliation": "Ward-Davidson",
      "email": "wilsonkristin@example.org"
    },
    {
      "name": "Luke Liu",
      "affiliation": "Obrien-Huynh",
      "email": "jason08@example.org"
    },
    {
      "name": "Paula Gonzalez",
      "affiliation": "Jones-Howell",
      "email": "brent41@example.org"
    }
  ]
}

[Assistant]
Approach:
1. Task: Convert research paper 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"?>
<research_paper>
<publication>
<venue>Cell</venue>
<year>2021</year>
<doi>10.3653/hXNF</doi>
</publication>
<funding_source>Kramer Ltd</funding_source>
<title>Configurable bandwidth-monitored strategy</title>
<authors>
<name>James Brown</name>
<affiliation>Ward-Davidson</affiliation>
<email>wilsonkristin@example.org</email>
</authors>
<authors>
<name>Luke Liu</name>
<affiliation>Obrien-Huynh</affiliation>
<email>jason08@example.org</email>
</authors>
<authors>
<name>Paula Gonzalez</name>
<affiliation>Jones-Howell</affiliation>
<email>brent41@example.org</email>
</authors>
</research_paper>


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

Output:
{
  "error_id": "bcec7cd1-70fc-42ba-97dd-2c6e2159fc7d",
  "timestamp": "2026-01-07T13:51:27.288021",
  "level": "CRITICAL",
  "service": "reasonService",
  "message": "Recent security meet three Congress find seat.",
  "stack_trace": [
    "at current.py:236",
    "at your.py:146",
    "at without.py:194"
  ],
  "context": {
    "user_id": "fc408ea4-9df4-4d81-87da-9d63d4bc8744",
    "request_id": "d8c95012-b6bb-42d7-8cb4-e57e77353a5b"
  }
}


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

[User] Generate financial report data in YAML format.

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

Output:
company: Hardy-Nguyen
ticker: ZAMS
quarter: Q3 2024
revenue: 23201336
expenses: 30350118
net_income: 14673850
eps: 3.22
metrics:
  profit_margin: 18.82
  roe: 21.21


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

[User] Output sales analytics as YAML.

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

Output:
period: June 2020
total_revenue: 2603625
units_sold: 51574
channels:
- name: retail
  revenue: 1926384
  growth: 34.29
- name: online
  revenue: 1062444
  growth: -1.99
top_products:
- sku: SKU-3818
  sales: 48786
- sku: SKU-7605
  sales: 408187
- sku: SKU-6728
  sales: 223732


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

[User] Output transaction record as JSON.

[Assistant]
Approach:
1. Task: Create transaction record 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:
{
  "txn_id": "TXN-23430167",
  "customer_id": "7fb2e914-3f0f-4c3f-abb9-ef22ed2c1064",
  "timestamp": "2026-01-07T13:51:26.046328",
  "items": [
    {
      "sku": "SKU-63492",
      "qty": 1,
      "price": 90.17
    },
    {
      "sku": "SKU-56350",
      "qty": 5,
      "price": 336.79
    }
  ],
  "subtotal": 152.9,
  "tax": 14.6,
  "total": 796.85,
  "payment_method": "apple_pay"
}


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<news_article>
<article_id>ART-8136358</article_id>
<headline>Realigned multimedia paradigm</headline>
<author>Brian White</author>
<published>2026-01-02T14:21:25.908532</published>

Sports

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

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

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


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

[User] Generate error log data in JSON format.

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

Output:
{
  "error_id": "7af25ba6-3e63-43d5-89e6-c5a6b377b923",
  "timestamp": "2026-01-07T13:51:26.975438",
  "level": "CRITICAL",
  "service": "downService",
  "message": "Prevent true movie stop.",
  "stack_trace": [
    "at hand.py:436",
    "at whose.py:275",
    "at information.py:57",
    "at central.py:306"
  ],
  "context": {
    "user_id": "dc348ded-7e54-44aa-bfc8-75caf977ffdf",
    "request_id": "cc597ab0-ad26-419a-8cbb-1facc38a2f79"
  }
}


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

[User] Create a TOML representation of error log.

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

Output:
error_id = "69ef512f-ddd4-415a-b99a-51e8f50d151c"
timestamp = "2026-01-07T13:51:25.644182"
level = "WARNING"
service = "fillService"
message = "Minute heart focus arrive."
stack_trace = [ "at administration.py:211", "at lawyer.py:276", "at discussion.py:115",]

[context]
user_id = "29c6c678-1224-4e33-8bc1-e94776cd4eb2"
request_id = "42e054d1-48f9-4a1c-ad7b-82ed505d6250"


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

[User]
Reformat the data below from JSON to TOML:
{
  "company": "Scott-Campbell",
  "ticker": "SZQB",
  "quarter": "Q2 2021",
  "revenue": 15063505,
  "expenses": 40738667,
  "net_income": 16626814,
  "eps": 6.47,
  "metrics": {
    "profit_margin": 15.92,
    "roe": 8.35
  }
}

[Assistant]
Approach:
1. Task: Convert financial report 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:
company = "Scott-Campbell"
ticker = "SZQB"
quarter = "Q2 2021"
revenue = 15063505
expenses = 40738667
net_income = 16626814
eps = 6.47

[metrics]
profit_margin = 15.92
roe = 8.35


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

[User] Create a YAML representation of clinical note.

[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-6709459
patient:
  mrn: MRN-104418
  age: 50
  gender: M
encounter_date: '2026-01-03'
chief_complaint: fever
vitals:
  bp: 143/96
  hr: 69
  temp_f: 101.3
assessment:
- problem: diabetes
  icd10: J90
- problem: hypertension
  icd10: I22
- problem: hypertension
  icd10: K97


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

[User]
Reformat the data below from JSON to XML:
{
  "paper_id": "arXiv:2023.67735",
  "title": "Optimized even-keeled conglomeration",
  "authors": [
    {
      "name": "Garrett Contreras",
      "affiliation": "Drake-Dunn",
      "email": "sandrapineda@example.net"
    },
    {
      "name": "Ryan Bell",
      "affiliation": "Ramos, Gates and Reed",
      "email": "kdavis@example.net"
    },
    {
      "name": "Cindy Silva",
      "affiliation": "Bryant, Pratt and Henderson",
      "email": "fmiller@example.net"
    }
  ],
  "abstract": "Sort suffer stand purpose six resource. Forward hard officer film the word human first.",
  "keywords": [
    "attack",
    "not",
    "describe"
  ],
  "publication": {
    "venue": "Nature",
    "year": 2024,
    "doi": "10.7544/lKSL"
  },
  "citations": 172,
  "funding_source": "Wood, Baldwin and Cain"
}

[Assistant]
Approach:
1. Task: Convert research paper 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"?>
<research_paper>
<paper_id>arXiv:2023.67735</paper_id>
<title>Optimized even-keeled conglomeration</title>
<authors>
<name>Garrett Contreras</name>
<affiliation>Drake-Dunn</affiliation>
<email>sandrapineda@example.net</email>
</authors>
<authors>
<name>Ryan Bell</name>
<affiliation>Ramos, Gates and Reed</affiliation>
<email>kdavis@example.net</email>
</authors>
<authors>
<name>Cindy Silva</name>
<affiliation>Bryant, Pratt and Henderson</affiliation>
<email>fmiller@example.net</email>
</authors>
<abstract>Sort suffer stand purpose six resource. Forward hard officer film the word human first.</abstract>
<keywords>attack</keywords>
<keywords>not</keywords>
<keywords>describe</keywords>
<publication>
<venue>Nature</venue>
<year>2024</year>
<doi>10.7544/lKSL</doi>
</publication>
<citations>172</citations>
<funding_source>Wood, Baldwin and Cain</funding_source>
</research_paper>