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

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

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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<review_id>REV-9529513</review_id>
<product_id>PROD-542599</product_id>
<user_id>67bb80c4-7c72-4c1b-886f-8186f18f45e3</user_id>
<rating>3</rating>
<title>Money face statement talk day.</title>
<content>Candidate stuff mission end nature hundred. Recently game stage agreement. Seem central blood add environment several.
Set less job reveal protect. Similar second staff owner international major.</content>
<date>2026-01-01</date>
<verified_purchase>True</verified_purchase>
<helpful_votes>8</helpful_votes>
</customer_review>

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

Output:
{
  "review_id": "REV-9529513",
  "product_id": "PROD-542599",
  "user_id": "67bb80c4-7c72-4c1b-886f-8186f18f45e3",
  "rating": 3,
  "title": "Money face statement talk day.",
  "content": "Candidate stuff mission end nature hundred. Recently game stage agreement. Seem central blood add environment several.\nSet less job reveal protect. Similar second staff owner international major.",
  "date": "2026-01-01",
  "verified_purchase": true,
  "helpful_votes": 8
}


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

[User]
Reformat the data below from JSON to XML:
{
  "period": "February 2024",
  "total_revenue": 3108970,
  "units_sold": 70292,
  "channels": [
    {
      "name": "online",
      "revenue": 1867975,
      "growth": -2.95
    },
    {
      "name": "retail",
      "revenue": 1947932,
      "growth": 22.54
    }
  ],
  "top_products": [
    {
      "sku": "SKU-5409",
      "sales": 492017
    },
    {
      "sku": "SKU-4816",
      "sales": 486050
    },
    {
      "sku": "SKU-9957",
      "sales": 44038
    }
  ]
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<sales_analytics>
<period>February 2024</period>
<total_revenue>3108970</total_revenue>
<units_sold>70292</units_sold>
<channels>
<name>online</name>
<revenue>1867975</revenue>
<growth>-2.95</growth>
</channels>
<channels>
<name>retail</name>
<revenue>1947932</revenue>
<growth>22.54</growth>
</channels>
<top_products>
<sku>SKU-5409</sku>
<sales>492017</sales>
</top_products>
<top_products>
<sku>SKU-4816</sku>
<sales>486050</sales>
</top_products>
<top_products>
<sku>SKU-9957</sku>
<sales>44038</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 XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<contract>
<contract_id>CTR-299234</contract_id>
<parties>
<name>Murphy, Hawkins and Mckenzie</name>
<role>party_a</role>
</parties>
<parties>
<name>Collins-Miller</name>
<role>party_b</role>
</parties>
<effective_date>2026-01-06</effective_date>
<term_months>46</term_months>
<value>506357</value>
<status>pending</status>
</contract>

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

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


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

[User]
Reformat the data below from TOML to CSV:
rx_id = "RX-5160762"
patient_mrn = "MRN-568012"
prescriber = "Linda Gonzalez"
date = "2026-01-06"
[[medications]]
name = "Lisinopril"
dosage = "20mg"
frequency = "TID"
quantity = 30

[[medications]]
name = "Atorvastatin"
dosage = "5mg"
frequency = "daily"
quantity = 60

[Assistant]
Approach:
1. Task: Convert prescription from TOML to CSV
2. Complexity: complex - 8-10 fields, 3-4 levels
3. Format rules: header row, comma-separated, quoted fields with commas
4. Structure: Organize data logically with appropriate nesting
5. Transform values to match the target format specifications.

Output:
date,medications,patient_mrn,prescriber,rx_id
2026-01-06,"[{""name"": ""Lisinopril"", ""dosage"": ""20mg"", ""frequency"": ""TID"", ""quantity"": 30}, {""name"": ""Atorvastati",MRN-568012,Linda Gonzalez,RX-5160762
2026-01-01,"[{""name"": ""Lisinopril"", ""dosage"": ""20mg"", ""frequency"": ""daily"", ""quantity"": 60}, {""name"": ""Metformin",MRN-924347,Claudia Hernandez,RX-3797976
2026-01-01,"[{""name"": ""Atorvastatin"", ""dosage"": ""20mg"", ""frequency"": ""BID"", ""quantity"": 90}]",MRN-672489,Tammy Young,RX-6676978
2026-01-03,"[{""name"": ""Metformin"", ""dosage"": ""10mg"", ""frequency"": ""TID"", ""quantity"": 60}, {""name"": ""Metformin"", ",MRN-741092,Leslie Young,RX-7163544
2026-01-03,"[{""name"": ""Lisinopril"", ""dosage"": ""5mg"", ""frequency"": ""BID"", ""quantity"": 60}, {""name"": ""Lisinopril"",",MRN-784812,Martha Douglas,RX-2230263


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

[User] Output customer review as JSON.

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

Output:
{
  "review_id": "REV-1384784",
  "product_id": "PROD-499626",
  "user_id": "4c396b1f-b1b7-4ef7-9587-0fda03a6f7f9",
  "rating": 1,
  "title": "Respond out five.",
  "content": "I stay little Democrat money where stop. Than development activity.\nAlong ahead their standard early nor reason. Fight with minute learn soldier understand.",
  "date": "2026-01-05",
  "verified_purchase": false,
  "helpful_votes": 94
}


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

[User] Create a CSV representation of student assessment.

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

Output:
assessment_id,code,course_id,credits,date,grade,grading_final,grading_homework,grading_midterm,instructor,percentage,schedule,scores,student_id,term,title,total_score,type
ASMT-422317,,CRS-7308,,2026-01-01,B,,,,,83.59,,"[{""question"": 1, ""points_earned"": 2, ""points_possible"": 10}, {""question"": 2, ""points_earned"": 3, ""po",STU-280699,,,75,exam
,MKW494,CRS-3575,3,,,40,30,30,Michael Young,,"[{""week"": 1, ""topic"": ""head""}, {""week"": 2, ""topic"": ""quickly""}, {""week"": 3, ""topic"": ""see""}, {""week""",,,Fall 2020,Extended next generation neural-net 101,,
,OXF127,CRS-9131,3,,,40,30,30,Dr. Gina Nash,,"[{""week"": 1, ""topic"": ""prepare""}, {""week"": 2, ""topic"": ""organization""}, {""week"": 3, ""topic"": ""public",,,Spring 2023,Object-based dedicated success 101,,


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

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

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

Output:
{
  "result_id": "LAB-9017474",
  "patient_mrn": "MRN-783803",
  "order_date": "2026-01-04",
  "panel": "Lipid",
  "results": [
    {
      "test": "Glucose",
      "value": 65.6,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "Glucose",
      "value": 160.2,
      "unit": "mg/dL",
      "flag": "normal"
    },
    {
      "test": "WBC",
      "value": 142.4,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "Glucose",
      "value": 179.9,
      "unit": "mg/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 97.3,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 148.5,
      "unit": "g/dL",
      "flag": "high"
    },
    {
      "test": "Hemoglobin",
      "value": 174.6,
      "unit": "g/dL",
      "flag": "normal"
    }
  ]
}


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

[User]
Transform this CSV data into YAML format:
category,content,currency,date,helpful_votes,is_available,name,price,product_id,rating,review_id,reviews,specs_dimensions,specs_weight_kg,stock,title,user_id,verified_purchase
,Admit large politics decide might Mr their. Hundred play I deal but player leader old. Then similar ,,2026-01-03,36,,,,PROD-683988,5,REV-9701957,,,,,Teach look history according want manager perform.,4d7f9754-e296-4a29-967f-5c8de166a17c,False
books,,USD,,,True,Upgradable static open architecture,976.98,PROD-593322,1.36,,553,38x95x72cm,24.46,889,,,
books,,USD,,,True,Optional upward-trending hierarchy,442.15,PROD-913654,1.98,,656,95x22x94cm,22.07,852,,,
books,,USD,,,True,Customizable mission-critical collaboration,13.79,PROD-469533,1.86,,300,38x52x15cm,12.94,819,,,
books,,USD,,,True,Intuitive optimizing extranet,966.27,PROD-415653,1.7,,480,44x48x60cm,35.81,838,,,

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

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

Output:
contract_id: CTR-926700
parties:
- name: Kelly-Jackson
  role: party_a
- name: Ramos, Hampton and Hartman
  role: party_b
effective_date: '2026-01-04'
term_months: 36
value: 178791
status: pending


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

[User]
Transform this JSON data into TOML format:
{
  "error_id": "0ea30289-ce13-425f-910d-da970e03d0fa",
  "timestamp": "2026-01-07T13:51:25.772316",
  "level": "WARNING",
  "service": "theService",
  "message": "Country specific information follow daughter dark.",
  "stack_trace": [
    "at enjoy.py:340",
    "at current.py:45",
    "at hand.py:478"
  ],
  "context": {
    "user_id": "91a6b883-2593-4790-8a1e-5acd27aad31b",
    "request_id": "1b22b6e6-0879-45de-9655-0fac03142f9b"
  }
}

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

Output:
error_id = "0ea30289-ce13-425f-910d-da970e03d0fa"
timestamp = "2026-01-07T13:51:25.772316"
level = "WARNING"
service = "theService"
message = "Country specific information follow daughter dark."
stack_trace = [ "at enjoy.py:340", "at current.py:45", "at hand.py:478",]

[context]
user_id = "91a6b883-2593-4790-8a1e-5acd27aad31b"
request_id = "1b22b6e6-0879-45de-9655-0fac03142f9b"


[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:
{
  "company": "Snow, Shelton and Parsons",
  "ticker": "LYEH",
  "quarter": "Q3 2022",
  "revenue": 49988929,
  "expenses": 3428077,
  "net_income": 8543670,
  "eps": 3.41,
  "metrics": {
    "profit_margin": 11.21,
    "roe": 5.99
  }
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<financial_report>
<company>Snow, Shelton and Parsons</company>
<ticker>LYEH</ticker>
<quarter>Q3 2022</quarter>
<revenue>49988929</revenue>
<expenses>3428077</expenses>
<net_income>8543670</net_income>
<eps>3.41</eps>
<metrics>
<profit_margin>11.21</profit_margin>
<roe>5.99</roe>
</metrics>
</financial_report>


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<transaction_record>
<payment_method>paypal</payment_method>
<customer_id>fe237049-a4a1-4a5c-af14-940bbb31d0e7</customer_id>
<total>1227.54</total>
</transaction_record>

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

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


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

[User] Create a YAML representation of api specification.

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

Output:
openapi: 3.0.0
info:
  title: Business-focused zero administration encryption API
  version: 1.0.0
paths:
  /teach:
    get:
      summary: Government trade direction personal reason hundred
      parameters:
      - name: param0
        in: query
        type: string
      - name: param1
        in: query
        type: string
      responses:
        '200':
          description: Success
        '400':
          description: Bad Request


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

[User]
Reformat the data below from JSON to XML:
{
  "paper_id": "arXiv:2023.99214",
  "title": "Integrated mobile database",
  "authors": [
    {
      "name": "Clayton Martinez",
      "affiliation": "Flores, Levy and Farmer",
      "email": "kathy80@example.org"
    },
    {
      "name": "Susan Bennett",
      "affiliation": "Collins, Daniel and Lyons",
      "email": "shawnjefferson@example.org"
    }
  ],
  "abstract": "Full with spend role first drive. Want man instead today bed hand character.",
  "keywords": [
    "bed",
    "very",
    "population"
  ],
  "publication": {
    "venue": "Nature",
    "year": 2023,
    "doi": "10.4640/CkqB"
  },
  "citations": 395,
  "funding_source": null
}

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


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

[User] Generate customer review data in JSON format.

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

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


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<sales_analytics>
<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>

[Assistant]
Approach:
1. Task: Convert sales analytics 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:
{
  "total_revenue": 6798538,
  "channels": [
    {
      "name": "online",
      "revenue": 2139770,
      "growth": -9.99
    },
    {
      "name": "retail",
      "revenue": 1809716,
      "growth": 7.01
    }
  ],
  "top_products": [
    {
      "sku": "SKU-3049",
      "sales": 22854
    },
    {
      "sku": "SKU-5505",
      "sales": 203281
    },
    {
      "sku": "SKU-9853",
      "sales": 260538
    }
  ]
}


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

[User] Create a TOML representation of clinical note.

[Assistant]
Approach:
1. Task: Create clinical note 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:
note_id = "CN-9595817"
encounter_date = "2026-01-02"
chief_complaint = "chest pain"
[[assessment]]
problem = "hypertension"
icd10 = "K99"

[patient]
mrn = "MRN-972408"
age = 32
gender = "F"

[vitals]
bp = "102/103"
hr = 113
temp_f = 102.5


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

[User]
Reformat the data below from TOML to YAML:
product_id = "PROD-421885"
name = "Diverse 6thgeneration solution"
category = "books"
price = 48.12
currency = "USD"
stock = 460
is_available = true
rating = 3.7
reviews = 717

[specs]
weight_kg = 20.82
dimensions = "87x57x81cm"

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

Output:
product_id: PROD-421885
name: Diverse 6thgeneration solution
category: books
price: 48.12
currency: USD
stock: 460
is_available: true
rating: 3.7
reviews: 717
specs:
  weight_kg: 20.82
  dimensions: 87x57x81cm


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

[User] Generate sales analytics data in XML format.

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

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


[System] You are an expert in 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-3948"
code = "CSZ142"
title = "Intuitive foreground functionalities 101"
instructor = "Robert Carter"
credits = 4
term = "Fall 2022"
[[schedule]]
week = 1
topic = "manage"

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

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

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

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

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

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

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

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

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


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<clinical_note>
<note_id>CN-4493327</note_id>
<patient>
<mrn>MRN-934301</mrn>
<age>62</age>
<gender>F</gender>
</patient>
<encounter_date>2026-01-06</encounter_date>
<chief_complaint>fever</chief_complaint>
<vitals>
<bp>141/91</bp>

100

<temp_f>98.5</temp_f>
</vitals>
<assessment>
<problem>diabetes</problem>
<icd10>I32</icd10>
</assessment>
</clinical_note>

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

Output:
{
  "note_id": "CN-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 CSV format. Think step-by-step, then generate syntactically perfect CSV.

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

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

Output:
abstract,authors,citations,funding_source,keywords,paper_id,publication_doi,publication_venue,publication_year,title
,"[{""name"": ""James Brown"", ""affiliation"": ""Ward-Davidson"", ""email"": ""wilsonkristin@example.org""}, {""na",,Kramer Ltd,,,10.3653/hXNF,Cell,2021,Configurable bandwidth-monitored strategy
"Film anything reduce visit west task. Pattern point popular natural.
Director read indeed various. F","[{""name"": ""Kathryn Jones"", ""affiliation"": ""Hines-Murray"", ""email"": ""amanda12@example.com""}, {""name"":",201,None,"[""recognize"", ""stay"", ""effect""]",arXiv:2022.71963,10.7387/LiLY,Nature,2020,Virtual dynamic parallelism
Range article full nice trade next skill ground. Treat step resource son garden watch.,"[{""name"": ""Erica Wright"", ""affiliation"": ""Warren-Obrien"", ""email"": ""ivasquez@example.net""}, {""name"":",275,Adams Ltd,"[""vote"", ""tough"", ""happen"", ""about"", ""about""]",arXiv:2021.89375,10.6727/NcXU,Nature,2021,Universal leadingedge intranet
Partner deal sea type effect. Create arrive result sport big attention. Note city off oil.,"[{""name"": ""John Clay"", ""affiliation"": ""Morales-Gomez"", ""email"": ""zscott@example.org""}, {""name"": ""Mck",184,None,"[""next"", ""hear"", ""strategy"", ""course"", ""traditional""]",arXiv:2024.22066,10.3123/EWJz,Nature,2020,Down-sized national complexity


[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 = "January 2024"
total_revenue = 3091656
units_sold = 63856
[[channels]]
name = "wholesale"
revenue = 2739604
growth = -0.52

[[channels]]
name = "online"
revenue = 247982
growth = 14.46

[[top_products]]
sku = "SKU-7268"
sales = 409348

[[top_products]]
sku = "SKU-4030"
sales = 70087

[[top_products]]
sku = "SKU-4380"
sales = 298376


[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: 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:
company: Eaton, Mccarty and Lopez
ticker: OWKB
quarter: Q3 2021
revenue: 46227283
expenses: 75330506
net_income: 13309525
eps: 4.82
metrics:
  profit_margin: 29.61
  roe: 8.93


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

[User] Output research paper as TOML.

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

Output:
paper_id = "arXiv:2024.31964"
title = "Optimized solution-oriented success"
abstract = "Price while never. Night great must well remain. Share less reveal often."
keywords = [ "less", "radio", "spend", "which",]
citations = 155
[[authors]]
name = "Meagan Sutton"
affiliation = "Williamson, Mitchell and Smith"
email = "davilabridget@example.com"

[[authors]]
name = "William Gross"
affiliation = "Miller and Sons"
email = "linda03@example.net"

[publication]
venue = "Science"
year = 2023
doi = "10.4651/vEqE"


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

[User] Create a XML representation of customer review.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<review_id>REV-9723622</review_id>
<product_id>PROD-853148</product_id>
<user_id>44919496-69de-498e-922c-5ea4230c00fa</user_id>
<rating>3</rating>
<title>Risk tell team series house.</title>
<content>Official police serve past already. Number down similar senior head amount. Focus reality really hold lose.</content>
<date>2026-01-03</date>
<verified_purchase>False</verified_purchase>
<helpful_votes>99</helpful_votes>
</customer_review>


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

[User] Create a YAML representation of prescription.

[Assistant]
Approach:
1. Task: Create prescription 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:
rx_id: RX-4278484
patient_mrn: MRN-990980
prescriber: Andrew Kelly
date: '2026-01-06'
medications:
- name: Metformin
  dosage: 10mg
  frequency: BID
  quantity: 30
- name: Atorvastatin
  dosage: 10mg
  frequency: BID
  quantity: 90


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<contract>
<contract_id>CTR-291572</contract_id>
<parties>
<name>Smith and Sons</name>
<role>party_a</role>
</parties>
<parties>
<name>Avila-Campbell</name>
<role>party_b</role>
</parties>
<effective_date>2026-01-03</effective_date>
<term_months>47</term_months>
<value>297446</value>
<status>pending</status>
</contract>

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

Output:
{
  "contract_id": "CTR-291572",
  "parties": [
    {
      "name": "Smith and Sons",
      "role": "party_a"
    },
    {
      "name": "Avila-Campbell",
      "role": "party_b"
    }
  ],
  "effective_date": "2026-01-03",
  "term_months": 47,
  "value": 297446,
  "status": "pending"
}


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

[User] Output prescription as XML.

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


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

[User] Create a TOML representation of news article.

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

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


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

[User]
Convert the following TOML to XML:
error_id = "6b141850-4372-44c1-8cf7-fc47780a5017"
timestamp = "2026-01-07T13:51:26.727039"
level = "WARNING"
service = "fullService"
message = "Simply human maintain sport."
stack_trace = [ "at environmental.py:351", "at develop.py:28", "at send.py:431",]

[context]
user_id = "fad7b695-3fb8-4313-ad8d-c2b1d4034196"
request_id = "2ca5c81e-d6c8-42a4-9e09-9715e928fe91"

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<error_log>
<error_id>6b141850-4372-44c1-8cf7-fc47780a5017</error_id>
<timestamp>2026-01-07T13:51:26.727039</timestamp>
<level>WARNING</level>
<service>fullService</service>
<message>Simply human maintain sport.</message>
<stack_trace>at environmental.py:351</stack_trace>
<stack_trace>at develop.py:28</stack_trace>
<stack_trace>at send.py:431</stack_trace>
<context>
<user_id>fad7b695-3fb8-4313-ad8d-c2b1d4034196</user_id>
<request_id>2ca5c81e-d6c8-42a4-9e09-9715e928fe91</request_id>
</context>
</error_log>


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

[User] Create a XML representation of api specification.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Seamless disintermediate flexibility API</title>
<version>1.0.0</version>
</info>
<paths>
</significant>
<get>
<summary>Box project skin day catch.</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>
<//significant>
</paths>
</api_specification>


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

[User]
Reformat the data below from YAML to XML:
experiment_id: EXP-393268
title: Effect of themselves on time
methodology:
  design: RCT
  sample_size: 237
  duration_days: 116
results:
- metric: efficacy
  baseline: 34.76
  endpoint: 73.98
  p_value: 0.4055
- metric: safety
  baseline: 70.26
  endpoint: 84.17
  p_value: 0.253
- metric: safety
  baseline: 22.1
  endpoint: 56.91
  p_value: 0.1172
conclusion: significant

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<experiment_result>
<experiment_id>EXP-393268</experiment_id>
<title>Effect of themselves on time</title>
<methodology>
<design>RCT</design>
<sample_size>237</sample_size>
<duration_days>116</duration_days>
</methodology>
<results>
<metric>efficacy</metric>
<baseline>34.76</baseline>
<endpoint>73.98</endpoint>
<p_value>0.4055</p_value>
</results>
<results>
<metric>safety</metric>
<baseline>70.26</baseline>
<endpoint>84.17</endpoint>
<p_value>0.253</p_value>
</results>
<results>
<metric>safety</metric>
<baseline>22.1</baseline>
<endpoint>56.91</endpoint>
<p_value>0.1172</p_value>
</results>
<conclusion>significant</conclusion>
</experiment_result>


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

[User] Generate news article data in CSV format.

[Assistant]
Approach:
1. Task: Create news article 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,content,funding_source,headline,keywords,paper_id,publication_doi,publication_venue,publication_year,published,section,title,views
,,,Capital way what customer unit skill. Arm bar occur article mouth enjoy. Exactly approach mention si,,Vision-oriented analyzing groupware,,,,,,2026-01-03T04:54:27.964292,Business,,73181
Charge public consumer after. Truth name analysis.,"[{""name"": ""Douglas Smith"", ""affiliation"": ""Green-Romero"", ""email"": ""nicole02@example.net""}, {""name"":",36,,Gilbert-Villa,,"[""policy"", ""note"", ""exactly"", ""kind""]",arXiv:2021.34382,10.2236/ediB,Cell,2024,,,Sharable zero tolerance extranet,
Community gun cup age evidence tree. Parent white manage specific game.,"[{""name"": ""Michele Brown MD"", ""affiliation"": ""Calhoun, Doyle and Peterson"", ""email"": ""millerjonathan",406,,Sanchez-Hansen,,"[""color"", ""strong"", ""year"", ""two""]",arXiv:2022.39341,10.1203/qIoB,Nature,2023,,,Networked 3rdgeneration analyzer,


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

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

[Assistant]
Approach:
1. Task: Convert social media post from JSON to 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:
content,engagement_comments,engagement_likes,engagement_shares,hashtags,platform,post_id,timestamp,user_id,username
"Might north politics.
Moment bad without change physical store call. Enjoy question state student po",18,9146,205,"[""#kid"", ""#off"", ""#school"", ""#fund""]",instagram,POST-86898750,2026-01-07T13:51:25.591017,a47ec401-ca4e-44b5-afc7-6c2b372f589e,dylan00
Summer project once network. Decision their personal probably eight operation.,211,6880,889,"[""#develop"", ""#hotel""]",instagram,POST-31100724,2026-01-07T13:51:25.594171,7d397d36-4a60-490d-b0af-29ac9863cc72,uscott
Four nearly help own family keep their. Occur information within once food sing gas. Behavior also o,245,2908,361,"[""#within"", ""#will""]",twitter,POST-66786651,2026-01-07T13:51:25.594522,7108222b-be25-4287-8668-caa517c5e6d7,fergusonrichard


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

[User]
Convert the following JSON to YAML:
{
  "post_id": "POST-90196326",
  "platform": "facebook",
  "user_id": "146c178d-e548-4357-8cd4-e8464cea2f9b",
  "username": "kevincunningham",
  "content": "Three would identify method across operation opportunity.\nWhat realize number. Country perform simple team player. Improve order east mother news magazine trade.\nCentral thus simple thousand morning.",
  "timestamp": "2026-01-07T13:51:26.698310",
  "hashtags": [
    "#pay",
    "#keep"
  ],
  "engagement": {
    "likes": 458,
    "shares": 383,
    "comments": 63
  }
}

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

Output:
post_id: POST-90196326
platform: facebook
user_id: 146c178d-e548-4357-8cd4-e8464cea2f9b
username: kevincunningham
content: 'Three would identify method across operation opportunity.

  What realize number. Country perform simple team player. Improve order east mother
  news magazine trade.

  Central thus simple thousand morning.'
timestamp: '2026-01-07T13:51:26.698310'
hashtags:
- '#pay'
- '#keep'
engagement:
  likes: 458
  shares: 383
  comments: 63


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

[User] Output social media post as TOML.

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

Output:
post_id = "POST-59844758"
timestamp = "2026-01-07T13:51:27.358144"
hashtags = [ "#population", "#during", "#executive", "#house",]


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<product_listing>
<product_id>PROD-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>

[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-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"
  }
}


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

[User]
Transform this TOML data into JSON format:
txn_id = "TXN-48552675"
customer_id = "19d3d880-f410-4b85-a35d-9c5777705d1f"
timestamp = "2026-01-07T13:51:26.837603"
subtotal = 1354.26
tax = 33.08
total = 766.28
payment_method = "paypal"
[[items]]
sku = "SKU-30306"
qty = 4
price = 206.74

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

Output:
{
  "txn_id": "TXN-48552675",
  "customer_id": "19d3d880-f410-4b85-a35d-9c5777705d1f",
  "timestamp": "2026-01-07T13:51:26.837603",
  "items": [
    {
      "sku": "SKU-30306",
      "qty": 4,
      "price": 206.74
    }
  ],
  "subtotal": 1354.26,
  "tax": 33.08,
  "total": 766.28,
  "payment_method": "paypal"
}


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

[User] Create a TOML representation of experiment result.

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

Output:
experiment_id = "EXP-725280"
title = "Effect of city on expert"
conclusion = "significant"
[[results]]
metric = "safety"
baseline = 43.19
endpoint = 64.81
p_value = 0.4813

[[results]]
metric = "safety"
baseline = 71.73
endpoint = 68.14
p_value = 0.0851

[[results]]
metric = "safety"
baseline = 77.12
endpoint = 63.9
p_value = 0.1154

[methodology]
design = "observational"
sample_size = 907
duration_days = 166


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<prescription>
<rx_id>RX-3472120</rx_id>
<patient_mrn>MRN-972429</patient_mrn>
<prescriber>Matthew Bennett</prescriber>
<date>2026-01-06</date>
<medications>
<name>Atorvastatin</name>
<dosage>10mg</dosage>
<frequency>daily</frequency>
<quantity>60</quantity>
</medications>
</prescription>

[Assistant]
Approach:
1. Task: Convert prescription 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:
{
  "rx_id": "RX-3472120",
  "patient_mrn": "MRN-972429",
  "prescriber": "Matthew Bennett",
  "date": "2026-01-06",
  "medications": [
    {
      "name": "Atorvastatin",
      "dosage": "10mg",
      "frequency": "daily",
      "quantity": 60
    }
  ]
}


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

[User]
Reformat the data below from TOML to CSV:
assessment_id = "ASMT-852879"
student_id = "STU-517758"
course_id = "CRS-9070"
type = "exam"
date = "2026-01-04"
total_score = 58
percentage = 53.23
grade = "C"
[[scores]]
question = 1
points_earned = 4
points_possible = 10

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

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

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

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

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

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

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

[[scores]]
question = 9
points_earned = 7
points_possible = 10

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

[[scores]]
question = 11
points_earned = 6
points_possible = 10

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

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

Output:
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-852879,,CRS-9070,,2026-01-04,C,,,,,53.23,,"[{""question"": 1, ""points_earned"": 4, ""points_possible"": 10}, {""question"": 2, ""points_earned"": 10, ""p",STU-517758,,,58,exam
,CRS361,CRS-9357,4,,,40,30,30,Patricia Jones,,"[{""week"": 1, ""topic"": ""buy""}, {""week"": 2, ""topic"": ""meet""}, {""week"": 3, ""topic"": ""all""}, {""week"": 4,",,,Spring 2024,Future-proofed scalable encoding 101,,
,KBN252,CRS-9929,4,,,40,30,30,Corey Rodgers,,"[{""week"": 1, ""topic"": ""day""}, {""week"": 2, ""topic"": ""short""}, {""week"": 3, ""topic"": ""price""}, {""week"":",,,Fall 2023,Customizable system-worthy matrix 101,,


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

[User] Create a JSON representation of news article.

[Assistant]
Approach:
1. Task: Create news article 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:
{
  "article_id": "ART-3281345",
  "headline": "Streamlined object-oriented toolset",
  "author": "James Dunn",
  "published": "2026-01-03T08:23:33.060508",
  "section": "Politics",
  "content": "Win take among professor. Glass reflect black similar future. Risk than tree.\nEconomic sit plan. Available then already skill up reason back. Course his threat growth physical parent truth.\nLaugh article pull goal. Believe those few.",
  "tags": [
    "hit",
    "summer",
    "official",
    "rather"
  ],
  "views": 75669,
  "shares": 293
}


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

Output:
subtotal = 1655.93
tax = 19.12
total = 1424.63
[[items]]
sku = "SKU-62708"
qty = 3
price = 121.39


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

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

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

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


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

[User]
Transform this JSON data into XML format:
{
  "total_score": 65,
  "percentage": 51.02,
  "assessment_id": "ASMT-810488"
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<student_assessment>
<total_score>65</total_score>
<percentage>51.02</percentage>
<assessment_id>ASMT-810488</assessment_id>
</student_assessment>


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

[User] Generate news article data in CSV format.

[Assistant]
Approach:
1. Task: Create news article in CSV
2. Complexity: 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,content,funding_source,headline,keywords,paper_id,publication_doi,publication_venue,publication_year,shares,tags,title,views
,,,"Couple and teacher radio compare consumer. Pass thing much rather light.
Foot four country subject f",,Re-engineered composite Local Area Network,,,,,,213,"[""couple"", ""this"", ""themselves"", ""whom""]",,92789
Seem available window there she despite station. Activity team any thousand culture full. Owner woul,"[{""name"": ""Alexis Levy"", ""affiliation"": ""Thomas, Chaney and Adkins"", ""email"": ""igarcia@example.net""}",48,,None,,"[""ask"", ""since"", ""white"", ""traditional"", ""such""]",arXiv:2024.94890,10.1389/Zmko,Science,2024,,,Open-architected mobile approach,
Material billion marriage. While me front environmental.,"[{""name"": ""Mitchell Taylor"", ""affiliation"": ""Wright-Davis"", ""email"": ""fzhang@example.net""}, {""name"":",444,,Fisher-Ho,,"[""enter"", ""cause"", ""control"", ""study""]",arXiv:2021.59252,10.9346/ldOs,Cell,2023,,,Multi-layered radical database,
Buy suggest bit ready mission which. Meet analysis clearly safe rest who. Baby full throw remember s,"[{""name"": ""Mrs. Tina Nguyen"", ""affiliation"": ""Johnston Inc"", ""email"": ""jeromediaz@example.com""}, {""n",338,,Decker and Sons,,"[""seem"", ""behind"", ""option"", ""place"", ""at""]",arXiv:2021.92182,10.4586/Rdel,Nature,2023,,,Persevering value-added solution,


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

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

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

Output:
category,currency,is_available,name,price,product_id,rating,reviews,specs_dimensions,specs_weight_kg,stock
clothing,USD,True,Self-enabling clear-thinking help-desk,510.64,PROD-319304,2.22,791,12x58x39cm,30.42,595
books,USD,True,Multi-layered high-level project,314.18,PROD-743488,2.62,391,64x23x70cm,48.09,718
clothing,USD,True,Business-focused mobile support,714.16,PROD-454786,4.83,581,54x97x72cm,40.41,777


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

[User] Generate product listing data in XML format.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<product_listing>
<product_id>PROD-842353</product_id>
<name>Synergistic bottom-line conglomeration</name>
<category>books</category>
<price>609.49</price>
<currency>USD</currency>
<stock>399</stock>
<is_available>True</is_available>
<rating>1.05</rating>
<reviews>570</reviews>
<specs>
<weight_kg>25.04</weight_kg>
<dimensions>30x19x82cm</dimensions>
</specs>
</product_listing>


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

[User] Output social media post as CSV.

[Assistant]
Approach:
1. Task: Create social media post 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:
content,engagement_comments,engagement_likes,engagement_shares,hashtags,platform,post_id,timestamp,user_id,username
"Stand leave decade year collection. Republican point edge yet business.
Suffer accept central agains",51,4745,251,"[""#community"", ""#whatever""]",twitter,POST-23186111,2026-01-07T13:51:25.750515,85951ac5-a9b8-4154-8edc-693bcde245cf,srodriguez
Nation doctor partner attorney personal. Ago choose wind everybody. Positive part tough painting rul,322,3024,112,"[""#together"", ""#law"", ""#too"", ""#attention""]",twitter,POST-47352168,2026-01-07T13:51:25.751859,c9da8642-774f-47f7-940e-6e718777b3a6,bryanmejia
"Society blood dream rock. Three help clear if money. Inside finally college ok price.
Economy rise p",309,6818,197,"[""#hair"", ""#of"", ""#she""]",twitter,POST-11241327,2026-01-07T13:51:25.752212,ba5f66f2-1c02-4898-b237-fb7ea09d31d7,ahamilton


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

[User]
Reformat the data below from YAML to XML:
date: '2026-01-06'
patient_mrn: MRN-259808
rx_id: RX-8539167
prescriber: Joseph Griffin
medications:
- name: Atorvastatin
  dosage: 10mg
  frequency: daily
  quantity: 90
- name: Lisinopril
  dosage: 10mg
  frequency: TID
  quantity: 30
- name: Metformin
  dosage: 5mg
  frequency: BID
  quantity: 30

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


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

[User] Generate clinical note data in TOML format.

[Assistant]
Approach:
1. Task: Create clinical note in TOML
2. Complexity: 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:
note_id = "CN-4441974"
encounter_date = "2026-01-02"
chief_complaint = "headache"
[[assessment]]
problem = "diabetes"
icd10 = "J60"

[[assessment]]
problem = "hypertension"
icd10 = "I21"

[[assessment]]
problem = "diabetes"
icd10 = "K16"

[patient]
mrn = "MRN-925906"
age = 60
gender = "F"

[vitals]
bp = "154/95"
hr = 108
temp_f = 97.8


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

[User] Output social media post as CSV.

[Assistant]
Approach:
1. Task: Create social media post 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:
content,engagement_comments,engagement_likes,engagement_shares,hashtags,platform,post_id,timestamp,user_id,username
"Serious degree upon late.
Painting throughout direction indicate night. Political business voice str",24,6808,9,"[""#easy"", ""#miss""]",instagram,POST-46905875,2026-01-07T13:51:26.735117,2079b341-d50b-4860-ba15-aa28bbe0f5b3,xhernandez
Learn like establish certain turn about gun. Sort order focus fact customer. Exist red past could ho,418,7288,502,"[""#put"", ""#message"", ""#character"", ""#front""]",instagram,POST-68293530,2026-01-07T13:51:26.736476,e6b28473-38f7-465a-881a-c079be7c8984,jennasoto
Whose fly anyone great clearly age sea. Sell film identify bill public improve example.,184,6340,507,"[""#young"", ""#him""]",instagram,POST-97674049,2026-01-07T13:51:26.736877,96807a0a-9c9a-41e6-8920-68a6381b252f,rasmussenjasmine
"Future doctor note though choice recognize Mr. Hundred himself during entire world north big.
Total ",0,8200,805,"[""#bring"", ""#foreign"", ""#seven"", ""#kitchen""]",twitter,POST-18467112,2026-01-07T13:51:26.737178,a63f95a3-f080-4617-841b-83d6c917f3eb,tgomez
Weight capital data toward arm two break. Order enough magazine father simple as.,352,7200,221,"[""#as"", ""#within"", ""#human"", ""#create""]",instagram,POST-47720347,2026-01-07T13:51:26.737502,0b1357b5-c7d3-4201-bf58-2b5b36fccb87,wmora


[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:
{
  "period": "June 2022",
  "total_revenue": 7287772,
  "units_sold": 8566,
  "channels": [
    {
      "name": "retail",
      "revenue": 931216,
      "growth": 10.96
    },
    {
      "name": "wholesale",
      "revenue": 1224016,
      "growth": 31.92
    }
  ],
  "top_products": [
    {
      "sku": "SKU-1474",
      "sales": 19268
    },
    {
      "sku": "SKU-3289",
      "sales": 31397
    },
    {
      "sku": "SKU-4950",
      "sales": 322920
    }
  ]
}

[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 2022</period>
<total_revenue>7287772</total_revenue>
<units_sold>8566</units_sold>
<channels>
<name>retail</name>
<revenue>931216</revenue>
<growth>10.96</growth>
</channels>
<channels>
<name>wholesale</name>
<revenue>1224016</revenue>
<growth>31.92</growth>
</channels>
<top_products>
<sku>SKU-1474</sku>
<sales>19268</sales>
</top_products>
<top_products>
<sku>SKU-3289</sku>
<sales>31397</sales>
</top_products>
<top_products>
<sku>SKU-4950</sku>
<sales>322920</sales>
</top_products>
</sales_analytics>


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

[User] Create a JSON representation of news article.

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


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

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

[Assistant]
Approach:
1. Task: Convert social media post from XML to 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:
{
  "post_id": "POST-39289028",
  "platform": "instagram",
  "user_id": "a2301bd9-5c11-406a-b2a8-1c1f96bbd31c",
  "username": "rhodessharon",
  "content": "City window data describe address street. Environmental wall shoulder happy artist forget hospital. Chair their before reach picture serve.",
  "timestamp": "2026-01-07T13:51:26.862472",
  "hashtags": [
    "#yet",
    "#listen"
  ],
  "engagement": {
    "likes": 2391,
    "shares": 751,
    "comments": 108
  }
}


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

[User]
Reformat the data below from XML to YAML:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<verified_purchase>True</verified_purchase>
<date>2026-01-05</date>
<rating>1</rating>
</customer_review>

[Assistant]
Approach:
1. Task: Convert customer review from XML to 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:
verified_purchase: true
date: '2026-01-05'
rating: 1


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

[User]
Convert the following CSV to YAML:
date,medications,patient_mrn,prescriber,rx_id
2026-01-05,"[{""name"": ""Metformin"", ""dosage"": ""20mg"", ""frequency"": ""daily"", ""quantity"": 30}]",MRN-921122,Spencer Smith,RX-5855932
2026-01-01,"[{""name"": ""Metformin"", ""dosage"": ""20mg"", ""frequency"": ""TID"", ""quantity"": 30}, {""name"": ""Metformin"", ",MRN-883334,Thomas Paul,RX-9284349
2026-01-06,"[{""name"": ""Metformin"", ""dosage"": ""10mg"", ""frequency"": ""TID"", ""quantity"": 60}]",MRN-483683,Nathan Church,RX-4075811
2026-01-06,"[{""name"": ""Lisinopril"", ""dosage"": ""5mg"", ""frequency"": ""daily"", ""quantity"": 30}, {""name"": ""Lisinopril",MRN-890606,Susan Walker,RX-5664092

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

Output:
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] Generate clinical note data in CSV format.

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

Output:
assessment,chief_complaint,encounter_date,note_id,patient_age,patient_gender,patient_mrn,vitals_bp,vitals_hr,vitals_temp_f
"[{""problem"": ""diabetes"", ""icd10"": ""J90""}, {""problem"": ""hypertension"", ""icd10"": ""I22""}, {""problem"": """,fever,2026-01-03,CN-6709459,50,M,MRN-104418,143/96,69,101.3
"[{""problem"": ""hypertension"", ""icd10"": ""J74""}, {""problem"": ""diabetes"", ""icd10"": ""J32""}]",chest pain,2026-01-05,CN-7335382,21,F,MRN-895106,93/70,117,97.3
"[{""problem"": ""hypertension"", ""icd10"": ""K29""}, {""problem"": ""hypertension"", ""icd10"": ""I38""}, {""problem",chest pain,2026-01-01,CN-2693208,63,F,MRN-358703,143/110,87,102.8
"[{""problem"": ""diabetes"", ""icd10"": ""J63""}, {""problem"": ""hypertension"", ""icd10"": ""I13""}]",headache,2026-01-04,CN-4813171,64,F,MRN-348353,98/86,107,102.0


[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: 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:
error_id = "6b141850-4372-44c1-8cf7-fc47780a5017"
timestamp = "2026-01-07T13:51:26.727039"
level = "WARNING"
service = "fullService"
message = "Simply human maintain sport."
stack_trace = [ "at environmental.py:351", "at develop.py:28", "at send.py:431",]

[context]
user_id = "fad7b695-3fb8-4313-ad8d-c2b1d4034196"
request_id = "2ca5c81e-d6c8-42a4-9e09-9715e928fe91"


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

[User] Generate lab result data in YAML format.

[Assistant]
Approach:
1. Task: Create lab result in YAML
2. Complexity: 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:
order_date: '2026-01-05'
results:
- test: Hemoglobin
  value: 95.5
  unit: g/dL
  flag: low
- test: Hemoglobin
  value: 52.7
  unit: mg/dL
  flag: high
- test: Glucose
  value: 142.9
  unit: mg/dL
  flag: low
- test: Glucose
  value: 146.5
  unit: mg/dL
  flag: high
panel: Lipid


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

[User] Create a YAML representation of student assessment.

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

Output:
assessment_id: ASMT-530397
student_id: STU-509684
course_id: CRS-8191
type: quiz
date: '2026-01-01'
scores:
- question: 1
  points_earned: 3
  points_possible: 10
- question: 2
  points_earned: 5
  points_possible: 10
- question: 3
  points_earned: 4
  points_possible: 10
- question: 4
  points_earned: 6
  points_possible: 10
- question: 5
  points_earned: 0
  points_possible: 10
- question: 6
  points_earned: 9
  points_possible: 10
- question: 7
  points_earned: 3
  points_possible: 10
- question: 8
  points_earned: 6
  points_possible: 10
- question: 9
  points_earned: 5
  points_possible: 10
- question: 10
  points_earned: 10
  points_possible: 10
- question: 11
  points_earned: 7
  points_possible: 10
- question: 12
  points_earned: 9
  points_possible: 10
- question: 13
  points_earned: 2
  points_possible: 10
- question: 14
  points_earned: 7
  points_possible: 10
total_score: 91
percentage: 61.03
grade: A


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

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

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

Output:
{
  "post_id": "POST-29576154",
  "platform": "instagram",
  "user_id": "b3774d2a-dced-4164-bd7b-7d043d7ec920",
  "username": "boydkaren",
  "content": "Responsibility this statement area thing imagine free. Under quickly treatment ever end social military. Majority before treatment decide.",
  "timestamp": "2026-01-07T13:51:27.160344",
  "hashtags": [
    "#involve",
    "#fact",
    "#rest"
  ],
  "engagement": {
    "likes": 923,
    "shares": 56,
    "comments": 396
  }
}


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

[User] Output news article as XML.

[Assistant]
Approach:
1. Task: Create news article 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"?>
<news_article>
<article_id>ART-8172649</article_id>
<headline>Triple-buffered responsive model</headline>
<author>Rachel Clark</author>
<published>2026-01-03T00:35:22.551008</published>

Business

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


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

[User] Create a TOML representation of research paper.

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

Output:
title = "Polarized methodical algorithm"
[[authors]]
name = "Caroline Barnes"
affiliation = "Parker Ltd"
email = "angelajackson@example.net"

[[authors]]
name = "Mario Boyd"
affiliation = "Johnson, Barber and Higgins"
email = "lfuller@example.com"


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

[User] Output customer review as JSON.

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

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


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

[User]
Transform this CSV data into TOML format:
abstract,authors,category,citations,funding_source,is_available,keywords,paper_id,price,publication_doi,publication_venue,publication_year,rating,title
,,electronics,,,True,,,302.74,,,,1.03,
Successful issue carry scientist improve civil win. Nice consumer face play mean. Rule with personal,"[{""name"": ""Austin Pierce"", ""affiliation"": ""Anderson-Melton"", ""email"": ""xhubbard@example.net""}, {""nam",,358,None,,"[""would"", ""sense"", ""explain""]",arXiv:2024.80734,,10.9024/qjUi,Nature,2020,,Right-sized methodical moderator
"Shake remain fine write.
Light traditional arrive future college employee like although.","[{""name"": ""Tracy Anderson"", ""affiliation"": ""Jones Group"", ""email"": ""xcantu@example.com""}, {""name"": """,,251,None,,"[""country"", ""series"", ""on"", ""peace""]",arXiv:2020.81497,,10.5676/Mwph,Nature,2024,,Stand-alone zero tolerance framework
"Without employee close that important late stop.
Society base develop detail. Letter down matter non","[{""name"": ""Kimberly Hunter"", ""affiliation"": ""Banks-Brown"", ""email"": ""edwardstimothy@example.org""}, {",,349,Delgado-Young,,"[""player"", ""soldier"", ""determine"", ""exactly"", ""grow""]",arXiv:2021.48872,,10.2218/RyMi,Nature,2024,,Phased discrete software
Yeah fall where piece coach though improve. Wind other data fire sign help see. Fast recognize messa,"[{""name"": ""Monique Fisher"", ""affiliation"": ""Bennett LLC"", ""email"": ""tiffany24@example.org""}, {""name""",,466,None,,"[""director"", ""peace"", ""office""]",arXiv:2023.26260,,10.9625/MHsC,Nature,2023,,Business-focused optimal utilization

[Assistant]
Approach:
1. Task: Convert product listing from CSV 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:
is_available = true
rating = 1.03
category = "electronics"
price = 302.74


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<news_article>
<article_id>ART-2188860</article_id>
<headline>Advanced well-modulated service-desk</headline>
<author>Michael Logan</author>
<published>2026-01-03T08:09:52.608144</published>

Politics

<content>Include start build no effort continue. Mention sister mention threat.
Choose herself case writer question over. Hand quickly house send shoulder expert hour.
All probably suffer law consider kitchen relationship. Data population personal past security but across.</content>
<tags>hear</tags>
<tags>civil</tags>
<tags>might</tags>
<tags>way</tags>
<tags>win</tags>
<views>35184</views>
<shares>1092</shares>
</news_article>


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

[User]
Convert the following CSV to TOML:
content,engagement_comments,engagement_likes,engagement_shares,hashtags,platform,post_id,timestamp,user_id,username
"Seven behavior less water pretty.
Rock key include. Kind than game agreement.
Paper position reduce ",393,1826,489,"[""#draw"", ""#five"", ""#culture"", ""#sport""]",twitter,POST-78526123,2026-01-07T13:51:27.460227,17596017-ad50-41af-8dc2-8746d15af00d,qsharp
Matter sea listen out physical number. Front statement field apply tree. Inside pick son try majorit,237,1422,735,"[""#of"", ""#concern"", ""#minute""]",twitter,POST-43767634,2026-01-07T13:51:27.462901,7c6101d0-d69d-4126-8f6f-13a78000739b,chanshelly
"Term practice goal already of. Power million his enough.
Other policy it be join. Trouble practice e",143,4547,440,"[""#positive"", ""#market"", ""#manager""]",facebook,POST-94381509,2026-01-07T13:51:27.463232,4256b52b-086a-422b-a622-b343b19168af,cmcdonald
"Could through million money shake wind.
Instead require section recently perform kitchen. Could styl",266,8910,388,"[""#spring"", ""#new"", ""#food"", ""#close""]",instagram,POST-11658610,2026-01-07T13:51:27.463488,9c25ff61-1207-4bb4-a5c9-4eadfef8a8a3,thomas33
"Green thing risk stay similar. Office peace deal.
Issue even last arm. What image debate itself.
For",368,1086,72,"[""#candidate"", ""#information"", ""#its""]",instagram,POST-62283361,2026-01-07T13:51:27.463898,256489a3-7d75-49e5-aa87-b3793ba822e6,brianmccullough

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

Output:
post_id = "POST-78526123"
platform = "twitter"
user_id = "17596017-ad50-41af-8dc2-8746d15af00d"
username = "qsharp"
content = "Seven behavior less water pretty.\nRock key include. Kind than game agreement.\nPaper position reduce purpose I affect wait threat. Third effect newspaper before include decision recently million."
timestamp = "2026-01-07T13:51:27.460227"
hashtags = [ "#draw", "#five", "#culture", "#sport",]

[engagement]
likes = 1826
shares = 489
comments = 393


[System] You are an expert in 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-4036732
patient:
  mrn: MRN-366942
  age: 79
  gender: M
encounter_date: '2026-01-06'
chief_complaint: headache
vitals:
  bp: 102/96
  hr: 61
  temp_f: 97.1
assessment:
- problem: hypertension
  icd10: K52


[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-361703",
  "name": "Grass-roots methodical neural-net",
  "category": "books",
  "price": 156.58,
  "currency": "USD",
  "stock": 3,
  "is_available": true,
  "rating": 3.73,
  "reviews": 915,
  "specs": {
    "weight_kg": 25.41,
    "dimensions": "90x40x81cm"
  }
}

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


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

[User]
Convert the following TOML to XML:
verified_purchase = true
title = "Country especially hand."
review_id = "REV-4835597"
product_id = "PROD-713270"

[Assistant]
Approach:
1. Task: Convert customer review 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"?>
<customer_review>
<verified_purchase>True</verified_purchase>
<title>Country especially hand.</title>
<review_id>REV-4835597</review_id>
<product_id>PROD-713270</product_id>
</customer_review>


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<research_paper>
<paper_id>arXiv:2021.48279</paper_id>
<title>Operative systemic definition</title>
<authors>
<name>Patricia Owens</name>
<affiliation>Pearson, Quinn and Owens</affiliation>
<email>christopher41@example.net</email>
</authors>
<authors>
<name>Wayne Boyd</name>
<affiliation>Delacruz-Weaver</affiliation>
<email>powens@example.net</email>
</authors>
<authors>
<name>Christopher Castillo</name>
<affiliation>Lawrence-Caldwell</affiliation>
<email>amandacarey@example.com</email>
</authors>
<abstract>Tv wear teacher under doctor. Eight mention month argue amount how voice.</abstract>
<keywords>month</keywords>
<keywords>southern</keywords>
<keywords>administration</keywords>
<publication>
<venue>Cell</venue>
<year>2021</year>
<doi>10.1648/XIrv</doi>
</publication>
<citations>167</citations>
<funding_source />
</research_paper>


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

[User]
Convert the following JSON to XML:
{
  "post_id": "POST-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
  }
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<social_media_post>
<post_id>POST-94493547</post_id>
<platform>instagram</platform>
<user_id>ebddd714-2a63-4fd6-985c-fb7fe32db0b4</user_id>
<username>laura52</username>
<content>Property political your form stand cup blood. Business later seem sea represent enough relationship memory.
What ok that look past. Budget understand mouth during brother pull type spring.</content>
<timestamp>2026-01-07T13:51:27.134920</timestamp>
<hashtags>#red</hashtags>
<hashtags>#hotel</hashtags>
<hashtags>#create</hashtags>
<engagement>
<likes>8599</likes>
<shares>93</shares>
<comments>39</comments>
</engagement>
</social_media_post>


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<news_article>
<article_id>ART-9801838</article_id>
<headline>Multi-lateral didactic encryption</headline>
<author>Jeffrey Gordon</author>
<published>2026-01-04T05:36:27.140251</published>

Business

<content>Partner energy whose simply half because long. Pattern include thousand care four against.
Scene center certainly letter already rate among. Do amount account court term same.
Step usually ground onto study myself.</content>
<tags>word</tags>
<tags>public</tags>
<tags>near</tags>
<views>26731</views>
<shares>4423</shares>
</news_article>

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

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


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

[User] Create a XML representation of sales analytics.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<sales_analytics>
<period>March 2022</period>
<total_revenue>6503980</total_revenue>
<units_sold>7670</units_sold>
<channels>
<name>retail</name>
<revenue>3279241</revenue>
<growth>22.76</growth>
</channels>
<channels>
<name>wholesale</name>
<revenue>1469640</revenue>
<growth>16.07</growth>
</channels>
<top_products>
<sku>SKU-8081</sku>
<sales>71747</sales>
</top_products>
<top_products>
<sku>SKU-8211</sku>
<sales>475825</sales>
</top_products>
<top_products>
<sku>SKU-4565</sku>
<sales>485553</sales>
</top_products>
</sales_analytics>


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

[User] Create a JSON representation of error log.

[Assistant]
Approach:
1. Task: Create error log 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:
{
  "error_id": "e78ff1cc-d984-499d-9fcf-126ccada9355",
  "timestamp": "2026-01-07T13:51:26.607679",
  "level": "WARNING",
  "service": "generationService",
  "message": "Bag difference growth have leader yeah him.",
  "stack_trace": [
    "at teach.py:30",
    "at poor.py:409"
  ],
  "context": {
    "user_id": "e8daac99-0bad-4fb0-ae26-78525528db85",
    "request_id": "a6fe9e0f-a1a6-42b2-ab77-98b8bb662a52"
  }
}


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

[User] Create a TOML representation of contract.

[Assistant]
Approach:
1. Task: Create contract 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:
contract_id = "CTR-504304"
effective_date = "2026-01-01"
term_months = 50
value = 407863
status = "executed"
[[parties]]
name = "Waters-Vega"
role = "party_a"

[[parties]]
name = "Petty, Thompson and Dillon"
role = "party_b"


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

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

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

Output:
{
  "post_id": "POST-61935008",
  "platform": "instagram",
  "user_id": "ecd9585e-2adb-45f4-adda-e91c5f4f7ebe",
  "username": "halezachary",
  "content": "Treat second sing development scientist particularly their. Like question recently line top. Resource movie enter involve order stop region.",
  "timestamp": "2026-01-07T13:51:25.597395",
  "hashtags": [
    "#box",
    "#speak",
    "#reason"
  ],
  "engagement": {
    "likes": 4027,
    "shares": 604,
    "comments": 194
  }
}


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

[User] Create a XML representation of product listing.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<product_listing>
<product_id>PROD-107958</product_id>
<name>Adaptive asynchronous synergy</name>
<category>electronics</category>
<price>349.45</price>
<currency>USD</currency>
<stock>717</stock>
<is_available>True</is_available>
<rating>1.62</rating>
<reviews>33</reviews>
<specs>
<weight_kg>15.32</weight_kg>
<dimensions>74x31x68cm</dimensions>
</specs>
</product_listing>


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

[User]
Convert the following XML to TOML:
<?xml version="1.0" encoding="UTF-8"?>
<student_assessment>
<assessment_id>ASMT-458464</assessment_id>
<student_id>STU-453066</student_id>
<course_id>CRS-7675</course_id>
<type>assignment</type>
<date>2026-01-06</date>
<scores>
<question>1</question>
<points_earned>0</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>3</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>4</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>4</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>0</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>3</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>7</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>9</question>
<points_earned>8</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>67</total_score>
<percentage>65.79</percentage>
<grade>B</grade>
</student_assessment>

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

Output:
assessment_id = "ASMT-458464"
student_id = "STU-453066"
course_id = "CRS-7675"
type = "assignment"
date = "2026-01-06"
total_score = 67
percentage = 65.79
grade = "B"
[[scores]]
question = 1
points_earned = 0
points_possible = 10

[[scores]]
question = 2
points_earned = 9
points_possible = 10

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

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

[[scores]]
question = 5
points_earned = 4
points_possible = 10

[[scores]]
question = 6
points_earned = 0
points_possible = 10

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

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

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


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

[User]
Transform this JSON data into XML format:
{
  "error_id": "19a033e5-3ad7-4877-8a96-e38503174031",
  "timestamp": "2026-01-07T13:51:26.139508",
  "level": "ERROR",
  "service": "offService",
  "message": "Light method real rich option.",
  "stack_trace": [
    "at very.py:253",
    "at piece.py:469",
    "at home.py:259"
  ],
  "context": {
    "user_id": "45de80c2-9a4d-4d83-abf9-651f235bf4e8",
    "request_id": "53b4884a-375f-459c-a303-838dd3a8411e"
  }
}

[Assistant]
Approach:
1. Task: Convert error log 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"?>
<error_log>
<error_id>19a033e5-3ad7-4877-8a96-e38503174031</error_id>
<timestamp>2026-01-07T13:51:26.139508</timestamp>
<level>ERROR</level>
<service>offService</service>
<message>Light method real rich option.</message>
<stack_trace>at very.py:253</stack_trace>
<stack_trace>at piece.py:469</stack_trace>
<stack_trace>at home.py:259</stack_trace>
<context>
<user_id>45de80c2-9a4d-4d83-abf9-651f235bf4e8</user_id>
<request_id>53b4884a-375f-459c-a303-838dd3a8411e</request_id>
</context>
</error_log>