[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:
article_id,author,content,headline,published,section,shares,tags,views
ART-8136358,Brian White,"Give model worry sense. Including reflect teacher near image.
Culture kitchen run first would. Agenc",Realigned multimedia paradigm,2026-01-02T14:21:25.908532,Sports,4175,"[""involve"", ""service"", ""along"", ""stand""]",7987
ART-8423308,Michelle Jefferson,Live suggest report. Want firm question TV station wide former. Mouth doctor garden idea under apply,Optional zero-defect artificial intelligence,2026-01-07T02:35:38.446059,Sports,1052,"[""successful"", ""buy"", ""region"", ""purpose"", ""drive""]",4089
ART-1607323,Aaron Rosales,"Eat civil very stuff another. Meet wall large than measure agency. Star cut animal final.
Close spea",Diverse bottom-line Internet solution,2026-01-03T18:11:22.032464,Politics,958,"[""itself"", ""else"", ""author"", ""serve"", ""attorney""]",53822

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


[System] You are an expert in 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-685161</product_id>
<name>Balanced demand-driven capacity</name>
<category>clothing</category>
<price>554.83</price>
<currency>USD</currency>
<stock>872</stock>
<is_available>True</is_available>
<rating>3.32</rating>
<reviews>212</reviews>
<specs>
<weight_kg>39.83</weight_kg>
<dimensions>86x88x63cm</dimensions>
</specs>
</product_listing>


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

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

[Assistant]
Approach:
1. Task: Create product listing in XML
2. Complexity: 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-421885</product_id>
<name>Diverse 6thgeneration solution</name>
<category>books</category>
<price>48.12</price>
<currency>USD</currency>
<stock>460</stock>
<is_available>True</is_available>
<rating>3.7</rating>
<reviews>717</reviews>
<specs>
<weight_kg>20.82</weight_kg>
<dimensions>87x57x81cm</dimensions>
</specs>
</product_listing>


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

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


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

[User] Generate transaction record data in JSON format.

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

Output:
{
  "txn_id": "TXN-59995807",
  "customer_id": "0d66cadd-c42f-4e9b-ae40-46d71f47623d",
  "timestamp": "2026-01-07T13:51:27.084892",
  "items": [
    {
      "sku": "SKU-83766",
      "qty": 4,
      "price": 55.35
    },
    {
      "sku": "SKU-77209",
      "qty": 2,
      "price": 217.97
    },
    {
      "sku": "SKU-11210",
      "qty": 5,
      "price": 436.04
    }
  ],
  "subtotal": 1600.85,
  "tax": 34.84,
  "total": 602.79,
  "payment_method": "apple_pay"
}


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

[User] Output course syllabus as JSON.

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

Output:
{
  "course_id": "CRS-2281",
  "code": "NHA456",
  "title": "Profit-focused mission-critical hardware 101",
  "instructor": "Natalie Middleton",
  "credits": 3,
  "term": "Spring 2024",
  "schedule": [
    {
      "week": 1,
      "topic": "its"
    },
    {
      "week": 2,
      "topic": "attorney"
    },
    {
      "week": 3,
      "topic": "decision"
    },
    {
      "week": 4,
      "topic": "every"
    },
    {
      "week": 5,
      "topic": "direction"
    },
    {
      "week": 6,
      "topic": "player"
    },
    {
      "week": 7,
      "topic": "city"
    },
    {
      "week": 8,
      "topic": "everybody"
    },
    {
      "week": 9,
      "topic": "throw"
    }
  ],
  "grading": {
    "homework": 30,
    "midterm": 30,
    "final": 40
  }
}


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

[User]
Transform this JSON data into XML format:
{
  "error_id": "c6e14566-270a-4a5f-a250-5239ca9174ac",
  "timestamp": "2026-01-07T13:51:26.338486",
  "level": "ERROR",
  "service": "humanService",
  "message": "Fear she east talk better central.",
  "stack_trace": [
    "at college.py:218",
    "at economy.py:209",
    "at let.py:252",
    "at whole.py:18"
  ],
  "context": {
    "user_id": "bda2bdb3-cc4e-4711-8927-aa42dc72d462",
    "request_id": "c7d51186-07ee-4743-a193-c5688ac0d6c5"
  }
}

[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>c6e14566-270a-4a5f-a250-5239ca9174ac</error_id>
<timestamp>2026-01-07T13:51:26.338486</timestamp>
<level>ERROR</level>
<service>humanService</service>
<message>Fear she east talk better central.</message>
<stack_trace>at college.py:218</stack_trace>
<stack_trace>at economy.py:209</stack_trace>
<stack_trace>at let.py:252</stack_trace>
<stack_trace>at whole.py:18</stack_trace>
<context>
<user_id>bda2bdb3-cc4e-4711-8927-aa42dc72d462</user_id>
<request_id>c7d51186-07ee-4743-a193-c5688ac0d6c5</request_id>
</context>
</error_log>


[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:
{
  "contract_id": "CTR-457828",
  "effective_date": "2026-01-01",
  "term_months": 32
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<contract>
<contract_id>CTR-457828</contract_id>
<effective_date>2026-01-01</effective_date>
<term_months>32</term_months>
</contract>


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

[User] Produce a YAML document for a 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: Intuitive disintermediate website API
  version: 1.0.0
paths:
  /reality:
    get:
      summary: Activity public whole paper there relationship tas
      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 TOML format. Think step-by-step, then generate syntactically perfect TOML.

[User]
Convert the following JSON to TOML:
{
  "paper_id": "arXiv:2023.47681",
  "title": "Devolved bi-directional info-mediaries",
  "authors": [
    {
      "name": "Christian Randolph",
      "affiliation": "Hunt-Haynes",
      "email": "patrickmaddox@example.net"
    },
    {
      "name": "Allen Lewis",
      "affiliation": "Owen PLC",
      "email": "alexanderhenry@example.net"
    },
    {
      "name": "Cody Martin",
      "affiliation": "Mcknight PLC",
      "email": "michael00@example.org"
    }
  ],
  "abstract": "Help field ten it. Pick eight last star pull. Act politics discuss.",
  "keywords": [
    "hard",
    "open",
    "right",
    "could",
    "sea"
  ],
  "publication": {
    "venue": "Cell",
    "year": 2023,
    "doi": "10.8057/cNYF"
  },
  "citations": 411,
  "funding_source": null
}

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

Output:
paper_id = "arXiv:2023.47681"
title = "Devolved bi-directional info-mediaries"
abstract = "Help field ten it. Pick eight last star pull. Act politics discuss."
keywords = [ "hard", "open", "right", "could", "sea",]
citations = 411
[[authors]]
name = "Christian Randolph"
affiliation = "Hunt-Haynes"
email = "patrickmaddox@example.net"

[[authors]]
name = "Allen Lewis"
affiliation = "Owen PLC"
email = "alexanderhenry@example.net"

[[authors]]
name = "Cody Martin"
affiliation = "Mcknight PLC"
email = "michael00@example.org"

[publication]
venue = "Cell"
year = 2023
doi = "10.8057/cNYF"


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

[User] Generate prescription data in CSV format.

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

Output:
date,medications,patient_mrn,prescriber,rx_id
2026-01-01,"[{""name"": ""Lisinopril"", ""dosage"": ""10mg"", ""frequency"": ""BID"", ""quantity"": 60}, {""name"": ""Lisinopril""",MRN-412331,Tammy Adams,RX-2317847
2026-01-02,"[{""name"": ""Metformin"", ""dosage"": ""10mg"", ""frequency"": ""BID"", ""quantity"": 90}, {""name"": ""Metformin"", ",MRN-706167,Jeffrey Waller,RX-2061026
2026-01-01,"[{""name"": ""Lisinopril"", ""dosage"": ""5mg"", ""frequency"": ""BID"", ""quantity"": 30}, {""name"": ""Atorvastatin",MRN-521258,Laura Hines,RX-4539960
2026-01-04,"[{""name"": ""Metformin"", ""dosage"": ""10mg"", ""frequency"": ""TID"", ""quantity"": 90}, {""name"": ""Metformin"", ",MRN-727679,James Villanueva,RX-1342691
2026-01-05,"[{""name"": ""Atorvastatin"", ""dosage"": ""10mg"", ""frequency"": ""TID"", ""quantity"": 90}, {""name"": ""Lisinopri",MRN-904364,Wanda Hughes,RX-5866234


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

[User] Create a XML representation of financial report.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<financial_report>
<net_income>4233102</net_income>
<metrics>
<profit_margin>14.29</profit_margin>
<roe>18.28</roe>
</metrics>
<company>Blackwell, Simpson and Pace</company>
<eps>0.79</eps>
<expenses>41343491</expenses>
</financial_report>


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

[User] Generate lab result data in XML format.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<lab_result>
<result_id>LAB-2604144</result_id>
<patient_mrn>MRN-906692</patient_mrn>
<order_date>2026-01-01</order_date>
<panel>Lipid</panel>
<results>
<test>Hemoglobin</test>
<value>180.3</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Glucose</test>
<value>97.8</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Glucose</test>
<value>88.1</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Glucose</test>
<value>65.1</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>95.1</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Glucose</test>
<value>86.1</value>
<unit>mg/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>152.8</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
</lab_result>


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

[User] Output course syllabus as XML.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<course_syllabus>
<instructor>Ryan Griffin</instructor>
<course_id>CRS-4864</course_id>
NLW161
</course_syllabus>


[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"?>
<customer_review>
<review_id>REV-2691236</review_id>
<product_id>PROD-245093</product_id>
<user_id>98b0ec97-f0e6-4eda-907b-c1488d5de2f5</user_id>
<rating>1</rating>
<title>Now new sell exist just.</title>
<content>Issue suddenly such maybe. Military they second staff end agreement.
Close that speech alone know wish matter. Finally adult statement method.</content>
<date>2026-01-02</date>
<verified_purchase>False</verified_purchase>
<helpful_votes>34</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-2691236",
  "product_id": "PROD-245093",
  "user_id": "98b0ec97-f0e6-4eda-907b-c1488d5de2f5",
  "rating": 1,
  "title": "Now new sell exist just.",
  "content": "Issue suddenly such maybe. Military they second staff end agreement.\nClose that speech alone know wish matter. Finally adult statement method.",
  "date": "2026-01-02",
  "verified_purchase": false,
  "helpful_votes": 34
}


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

[User] Create a CSV representation of financial report.

[Assistant]
Approach:
1. Task: Create financial report 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:
company,eps,expenses,metrics_profit_margin,metrics_roe,net_income,quarter,revenue,ticker
"Blackwell, Simpson and Pace",0.79,41343491,14.29,18.28,4233102,,,
Roach LLC,0.85,19926582,19.64,10.37,17919974,Q1 2021,5188452,RTYA
Sanchez-Doyle,3.49,46313556,9.78,21.05,10999840,Q1 2022,82022215,OETN


[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"?>
<error_log>
<message>Computer so cold feeling huge reason reach.</message>
<error_id>ddf52566-8f32-4c90-8477-d7f45504f7db</error_id>
<stack_trace>at their.py:436</stack_trace>
<stack_trace>at activity.py:81</stack_trace>
<stack_trace>at test.py:46</stack_trace>
<timestamp>2026-01-07T13:51:26.578554</timestamp>
<context>
<user_id>97fc14e5-867d-4c23-9d2e-00b538b50acf</user_id>
<request_id>ab94fb1e-d258-4626-9686-12f860249c41</request_id>
</context>
</error_log>

[Assistant]
Approach:
1. Task: Convert error log 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:
{
  "message": "Computer so cold feeling huge reason reach.",
  "error_id": "ddf52566-8f32-4c90-8477-d7f45504f7db",
  "stack_trace": [
    "at their.py:436",
    "at activity.py:81",
    "at test.py:46"
  ],
  "timestamp": "2026-01-07T13:51:26.578554",
  "context": {
    "user_id": "97fc14e5-867d-4c23-9d2e-00b538b50acf",
    "request_id": "ab94fb1e-d258-4626-9686-12f860249c41"
  }
}


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

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

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

Output:
note_id = "CN-3409162"
encounter_date = "2026-01-05"
chief_complaint = "fever"
[[assessment]]
problem = "diabetes"
icd10 = "J46"

[patient]
mrn = "MRN-721241"
age = 35
gender = "F"

[vitals]
bp = "173/107"
hr = 61
temp_f = 99.6


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

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

[Assistant]
Approach:
1. Task: Create student assessment in TOML
2. Complexity: 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:
grade = "C"
date = "2026-01-01"
[[scores]]
question = 1
points_earned = 8
points_possible = 10

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

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

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

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

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

[[scores]]
question = 7
points_earned = 4
points_possible = 10

[[scores]]
question = 8
points_earned = 0
points_possible = 10


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

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

[Assistant]
Approach:
1. Task: Create product listing in YAML
2. Complexity: 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:
is_available: true
rating: 1.03
category: electronics
price: 302.74


[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"?>
<social_media_post>
<post_id>POST-25055870</post_id>
<platform>twitter</platform>
<user_id>28837af0-4898-41b2-8a38-faf0e2d7f431</user_id>
<username>khahn</username>
<content>Serve student science today general. Tell risk ball quickly technology.
Drive because generation support gun message majority. Though do old.</content>
<timestamp>2026-01-07T13:51:27.403909</timestamp>
<hashtags>#conference</hashtags>
<hashtags>#body</hashtags>
<engagement>
<likes>9394</likes>
<shares>444</shares>
<comments>203</comments>
</engagement>
</social_media_post>

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

Output:
{
  "post_id": "POST-25055870",
  "platform": "twitter",
  "user_id": "28837af0-4898-41b2-8a38-faf0e2d7f431",
  "username": "khahn",
  "content": "Serve student science today general. Tell risk ball quickly technology.\nDrive because generation support gun message majority. Though do old.",
  "timestamp": "2026-01-07T13:51:27.403909",
  "hashtags": [
    "#conference",
    "#body"
  ],
  "engagement": {
    "likes": 9394,
    "shares": 444,
    "comments": 203
  }
}


[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"?>
<clinical_note>
<note_id>CN-5751204</note_id>
<patient>
<mrn>MRN-566004</mrn>
<age>47</age>
<gender>M</gender>
</patient>
<encounter_date>2026-01-05</encounter_date>
<chief_complaint>headache</chief_complaint>
<vitals>
<bp>160/96</bp>

75

<temp_f>102.4</temp_f>
</vitals>
<assessment>
<problem>diabetes</problem>
<icd10>I93</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-5751204",
  "patient": {
    "mrn": "MRN-566004",
    "age": 47,
    "gender": "M"
  },
  "encounter_date": "2026-01-05",
  "chief_complaint": "headache",
  "vitals": {
    "bp": "160/96",
    "hr": 75,
    "temp_f": 102.4
  },
  "assessment": [
    {
      "problem": "diabetes",
      "icd10": "I93"
    }
  ]
}


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

[User] Output experiment result as CSV.

[Assistant]
Approach:
1. Task: Create experiment result 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,conclusion,funding_source,keywords,methodology_design,methodology_duration_days,methodology_sample_size,paper_id,publication_doi,publication_venue,publication_year,results,title
,,,non-significant,,,observational,339,351,,,,,"[{""metric"": ""efficacy"", ""baseline"": 40.85, ""endpoint"": 40.08, ""p_value"": 0.4196}, {""metric"": ""effica",
Whose natural especially now mean way goal wonder. Animal base Mr back contain husband. Change hour ,"[{""name"": ""Erin Thomas"", ""affiliation"": ""Adams-Cole"", ""email"": ""emily81@example.net""}, {""name"": ""Ang",490,,Stone PLC,"[""mission"", ""role"", ""home"", ""wear""]",,,,arXiv:2021.61490,10.4286/HZxn,Science,2021,,Quality-focused human-resource standardization
Do purpose something strategy teacher whom. Wait history technology left suddenly some past. Arrive ,"[{""name"": ""Stanley Raymond"", ""affiliation"": ""Elliott Inc"", ""email"": ""masonpatricia@example.org""}, {""",411,,Christensen Inc,"[""fly"", ""rule"", ""instead"", ""strong"", ""race""]",,,,arXiv:2023.31744,10.3873/VGcR,Cell,2023,,Cross-platform even-keeled emulation
Follow beautiful interest yes. Feeling husband story either who. Ask so beat together enough speak s,"[{""name"": ""Anthony Mendoza"", ""affiliation"": ""Hess, Baker and Sherman"", ""email"": ""amyers@example.org""",10,,"Schaefer, Reid and Forbes","[""garden"", ""treat"", ""buy""]",,,,arXiv:2020.51960,10.6886/PBmZ,Nature,2024,,Proactive motivating capacity


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

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

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

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


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

[User] Generate experiment result data in CSV format.

[Assistant]
Approach:
1. Task: Create experiment result in CSV
2. Complexity: 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:
conclusion,experiment_id,methodology_design,methodology_duration_days,methodology_sample_size,results,title
non-significant,EXP-681166,RCT,212,875,"[{""metric"": ""efficacy"", ""baseline"": 50.39, ""endpoint"": 61.09, ""p_value"": 0.3936}, {""metric"": ""safety",Effect of main on stand
significant,EXP-847350,observational,100,948,"[{""metric"": ""efficacy"", ""baseline"": 47.57, ""endpoint"": 71.94, ""p_value"": 0.1827}, {""metric"": ""effica",Effect of create on town
non-significant,EXP-159451,cohort,234,971,"[{""metric"": ""efficacy"", ""baseline"": 69.51, ""endpoint"": 69.51, ""p_value"": 0.3625}, {""metric"": ""effica",Effect of image on nearly
significant,EXP-469191,cohort,61,811,"[{""metric"": ""safety"", ""baseline"": 60.94, ""endpoint"": 43.5, ""p_value"": 0.3538}, {""metric"": ""efficacy""",Effect of peace on opportunity


[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 = "November 2022"
total_revenue = 9138741
units_sold = 89798
[[channels]]
name = "wholesale"
revenue = 1234153
growth = 40.64

[[channels]]
name = "online"
revenue = 991509
growth = -4.15

[[top_products]]
sku = "SKU-9585"
sales = 30234

[[top_products]]
sku = "SKU-8072"
sales = 57362

[[top_products]]
sku = "SKU-4011"
sales = 249730


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

[User]
Convert the following TOML to CSV:
openapi = "3.0.0"

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

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

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

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

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

[Assistant]
Approach:
1. Task: Convert api specification 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:
abstract,authors,citations,funding_source,info_title,info_version,keywords,openapi,paper_id,paths_/traditional_get_parameters,paths_/traditional_get_responses_200_description,paths_/traditional_get_responses_400_description,paths_/traditional_get_summary,publication_doi,publication_venue,publication_year,title
,,,,Optional bottom-line complexity API,1.0.0,,3.0.0,,"[{""name"": ""param0"", ""in"": ""query"", ""type"": ""string""}, {""name"": ""param1"", ""in"": ""query"", ""type"": ""str",Success,Bad Request,Discussion then kind hair.,,,,
One south moment again. Own brother explain above together.,"[{""name"": ""Andrea Riley"", ""affiliation"": ""Cohen-Romero"", ""email"": ""olyons@example.org""}, {""name"": ""J",389,None,,,"[""medical"", ""lead"", ""method""]",,arXiv:2020.80157,,,,,10.5496/FRvU,Nature,2024,Reverse-engineered holistic firmware
Serve many world. Foreign start color lead southern affect five.,"[{""name"": ""Jeremy Price"", ""affiliation"": ""Fisher, Collier and Bowman"", ""email"": ""brittanyjohnson@exa",397,None,,,"[""art"", ""trouble"", ""human"", ""main""]",,arXiv:2022.58622,,,,,10.2881/liBg,Cell,2022,Configurable discrete encoding
"If offer democratic their mind thousand why relationship. A indeed order natural yourself friend.
Gr","[{""name"": ""Susan Vargas"", ""affiliation"": ""Williams-Shaw"", ""email"": ""michaelchavez@example.net""}, {""n",230,None,,,"[""prevent"", ""benefit"", ""chair"", ""tax""]",,arXiv:2024.62198,,,,,10.6937/CPpa,Science,2020,Mandatory grid-enabled approach


[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:
{
  "contract_id": "CTR-143990",
  "parties": [
    {
      "name": "Brady Inc",
      "role": "party_a"
    },
    {
      "name": "Gonzalez, Coleman and Sanchez",
      "role": "party_b"
    }
  ],
  "effective_date": "2026-01-02",
  "term_months": 32,
  "value": 452000,
  "status": "active"
}

[Assistant]
Approach:
1. Task: Convert contract 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:
contract_id,effective_date,parties,status,term_months,value
CTR-143990,2026-01-02,"[{""name"": ""Brady Inc"", ""role"": ""party_a""}, {""name"": ""Gonzalez, Coleman and Sanchez"", ""role"": ""party_",active,32,452000
CTR-713188,2026-01-03,"[{""name"": ""Young and Sons"", ""role"": ""party_a""}, {""name"": ""Solis and Sons"", ""role"": ""party_b""}]",executed,51,621798
CTR-488221,2026-01-05,"[{""name"": ""Scott-Graham"", ""role"": ""party_a""}, {""name"": ""Fuentes-Rodriguez"", ""role"": ""party_b""}]",pending,21,973623


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

[User] Produce a YAML document for a contract.

[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-449984
parties:
- name: Garcia-Henson
  role: party_a
- name: Moore LLC
  role: party_b
effective_date: '2026-01-04'
term_months: 49
value: 694475
status: pending


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

[User]
Convert the following JSON to XML:
{
  "review_id": "REV-2971879",
  "product_id": "PROD-601177",
  "user_id": "49ec79ac-cc63-409f-8812-a70c492b6835",
  "rating": 3,
  "title": "Safe everything country understand subject.",
  "content": "Explain among above role speech. Hear law enjoy. Lose building fall everything million.\nEast choose however class dark test good contain. Indicate worker mean hot.",
  "date": "2026-01-06",
  "verified_purchase": true,
  "helpful_votes": 67
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<review_id>REV-2971879</review_id>
<product_id>PROD-601177</product_id>
<user_id>49ec79ac-cc63-409f-8812-a70c492b6835</user_id>
<rating>3</rating>
<title>Safe everything country understand subject.</title>
<content>Explain among above role speech. Hear law enjoy. Lose building fall everything million.
East choose however class dark test good contain. Indicate worker mean hot.</content>
<date>2026-01-06</date>
<verified_purchase>True</verified_purchase>
<helpful_votes>67</helpful_votes>
</customer_review>


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

[User] Generate financial report data in JSON format.

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

Output:
{
  "company": "Tucker and Sons",
  "ticker": "BPQE",
  "quarter": "Q4 2024",
  "revenue": 70279854,
  "expenses": 61737533,
  "net_income": 12235621,
  "eps": 3.52,
  "metrics": {
    "profit_margin": 24.27,
    "roe": 16.15
  }
}


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<experiment_result>
<results>
<metric>efficacy</metric>
<baseline>40.85</baseline>
<endpoint>40.08</endpoint>
<p_value>0.4196</p_value>
</results>
<results>
<metric>efficacy</metric>
<baseline>82.87</baseline>
<endpoint>28.4</endpoint>
<p_value>0.208</p_value>
</results>
<results>
<metric>efficacy</metric>
<baseline>74.0</baseline>
<endpoint>18.43</endpoint>
<p_value>0.3638</p_value>
</results>
<results>
<metric>efficacy</metric>
<baseline>50.48</baseline>
<endpoint>15.59</endpoint>
<p_value>0.1146</p_value>
</results>
<methodology>
<design>observational</design>
<sample_size>351</sample_size>
<duration_days>339</duration_days>
</methodology>
<conclusion>non-significant</conclusion>
</experiment_result>

[Assistant]
Approach:
1. Task: Convert experiment result 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:
{
  "results": [
    {
      "metric": "efficacy",
      "baseline": 40.85,
      "endpoint": 40.08,
      "p_value": 0.4196
    },
    {
      "metric": "efficacy",
      "baseline": 82.87,
      "endpoint": 28.4,
      "p_value": 0.208
    },
    {
      "metric": "efficacy",
      "baseline": 74.0,
      "endpoint": 18.43,
      "p_value": 0.3638
    },
    {
      "metric": "efficacy",
      "baseline": 50.48,
      "endpoint": 15.59,
      "p_value": 0.1146
    }
  ],
  "methodology": {
    "design": "observational",
    "sample_size": 351,
    "duration_days": 339
  },
  "conclusion": "non-significant"
}


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

[User] Output api specification as TOML.

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

[info]
title = "Sharable solution-oriented migration API"
version = "1.0.0"

[paths."/anything".get]
summary = "Those all evidence respond she listen."
[[paths."/anything".get.parameters]]
name = "param0"
in = "query"
type = "string"

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

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

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


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

[User] Generate api specification data in TOML format.

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

Output:
openapi = "3.0.0"

[info]
title = "Streamlined logistical help-desk API"
version = "1.0.0"

[paths."/grow".get]
summary = "Will entire deep source history."
[[paths."/grow".get.parameters]]
name = "param0"
in = "query"
type = "string"

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

[[paths."/grow".get.parameters]]
name = "param2"
in = "query"
type = "string"

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

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


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

[User]
Transform this JSON data into XML format:
{
  "items": [
    {
      "sku": "SKU-89816",
      "qty": 1,
      "price": 437.44
    },
    {
      "sku": "SKU-65650",
      "qty": 1,
      "price": 455.72
    },
    {
      "sku": "SKU-98183",
      "qty": 3,
      "price": 337.62
    }
  ],
  "total": 1900.4,
  "payment_method": "apple_pay"
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<transaction_record>
<items>
<sku>SKU-89816</sku>
<qty>1</qty>
<price>437.44</price>
</items>
<items>
<sku>SKU-65650</sku>
<qty>1</qty>
<price>455.72</price>
</items>
<items>
<sku>SKU-98183</sku>
<qty>3</qty>
<price>337.62</price>
</items>
<total>1900.4</total>
<payment_method>apple_pay</payment_method>
</transaction_record>


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

[User]
Convert the following CSV to TOML:
date,medications,patient_mrn,prescriber,rx_id
2026-01-01,"[{""name"": ""Atorvastatin"", ""dosage"": ""10mg"", ""frequency"": ""BID"", ""quantity"": 60}]",,,RX-5523111
2026-01-01,"[{""name"": ""Atorvastatin"", ""dosage"": ""20mg"", ""frequency"": ""TID"", ""quantity"": 30}]",MRN-117171,Karen Reed,RX-5166396
2026-01-02,"[{""name"": ""Atorvastatin"", ""dosage"": ""20mg"", ""frequency"": ""BID"", ""quantity"": 90}, {""name"": ""Metformin",MRN-501151,Joseph Johnson,RX-7279883
2026-01-04,"[{""name"": ""Atorvastatin"", ""dosage"": ""5mg"", ""frequency"": ""BID"", ""quantity"": 90}, {""name"": ""Metformin""",MRN-514305,Mrs. Sarah Graham,RX-6108923
2026-01-01,"[{""name"": ""Metformin"", ""dosage"": ""10mg"", ""frequency"": ""daily"", ""quantity"": 30}, {""name"": ""Lisinopril",MRN-487883,Joshua Larson,RX-4171961

[Assistant]
Approach:
1. Task: Convert prescription 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:
rx_id = "RX-5523111"
date = "2026-01-01"
[[medications]]
name = "Atorvastatin"
dosage = "10mg"
frequency = "BID"
quantity = 60


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

[User] Output prescription as YAML.

[Assistant]
Approach:
1. Task: Create prescription in YAML
2. Complexity: 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-3022361
patient_mrn: MRN-726192
prescriber: Jessica Warner
date: '2026-01-02'
medications:
- name: Atorvastatin
  dosage: 20mg
  frequency: BID
  quantity: 90
- name: Atorvastatin
  dosage: 20mg
  frequency: daily
  quantity: 30


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

[User] Create a JSON representation of prescription.

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

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

[User]
Transform this JSON data into XML format:
{
  "note_id": "CN-3041313",
  "patient": {
    "mrn": "MRN-164256",
    "age": 45,
    "gender": "F"
  },
  "encounter_date": "2026-01-04",
  "chief_complaint": "fever",
  "vitals": {
    "bp": "153/76",
    "hr": 98,
    "temp_f": 102.6
  },
  "assessment": [
    {
      "problem": "hypertension",
      "icd10": "I84"
    },
    {
      "problem": "hypertension",
      "icd10": "J93"
    }
  ]
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<clinical_note>
<note_id>CN-3041313</note_id>
<patient>
<mrn>MRN-164256</mrn>
<age>45</age>
<gender>F</gender>
</patient>
<encounter_date>2026-01-04</encounter_date>
<chief_complaint>fever</chief_complaint>
<vitals>
<bp>153/76</bp>

98

<temp_f>102.6</temp_f>
</vitals>
<assessment>
<problem>hypertension</problem>
<icd10>I84</icd10>
</assessment>
<assessment>
<problem>hypertension</problem>
<icd10>J93</icd10>
</assessment>
</clinical_note>


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

[User] Output student assessment as TOML.

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

Output:
assessment_id = "ASMT-893180"
student_id = "STU-881633"
course_id = "CRS-6394"
type = "quiz"
date = "2026-01-03"
total_score = 98
percentage = 73.06
grade = "A"
[[scores]]
question = 1
points_earned = 10
points_possible = 10

[[scores]]
question = 2
points_earned = 8
points_possible = 10

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

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

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

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

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

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

[[scores]]
question = 9
points_earned = 5
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:
{
  "grading": {
    "homework": 30,
    "midterm": 30,
    "final": 40
  },
  "credits": 4,
  "course_id": "CRS-7759",
  "schedule": [
    {
      "week": 1,
      "topic": "meet"
    },
    {
      "week": 2,
      "topic": "around"
    },
    {
      "week": 3,
      "topic": "college"
    },
    {
      "week": 4,
      "topic": "fly"
    },
    {
      "week": 5,
      "topic": "summer"
    },
    {
      "week": 6,
      "topic": "painting"
    },
    {
      "week": 7,
      "topic": "size"
    },
    {
      "week": 8,
      "topic": "off"
    },
    {
      "week": 9,
      "topic": "point"
    },
    {
      "week": 10,
      "topic": "light"
    },
    {
      "week": 11,
      "topic": "nothing"
    }
  ],
  "instructor": "Matthew Johnson"
}

[Assistant]
Approach:
1. Task: Convert course syllabus 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"?>
<course_syllabus>
<grading>
<homework>30</homework>
<midterm>30</midterm>
<final>40</final>
</grading>
<credits>4</credits>
<course_id>CRS-7759</course_id>
<schedule>
<week>1</week>
<topic>meet</topic>
</schedule>
<schedule>
<week>2</week>
<topic>around</topic>
</schedule>
<schedule>
<week>3</week>
<topic>college</topic>
</schedule>
<schedule>
<week>4</week>
<topic>fly</topic>
</schedule>
<schedule>
<week>5</week>
<topic>summer</topic>
</schedule>
<schedule>
<week>6</week>
<topic>painting</topic>
</schedule>
<schedule>
<week>7</week>
<topic>size</topic>
</schedule>
<schedule>
<week>8</week>
<topic>off</topic>
</schedule>
<schedule>
<week>9</week>
<topic>point</topic>
</schedule>
<schedule>
<week>10</week>
<topic>light</topic>
</schedule>
<schedule>
<week>11</week>
<topic>nothing</topic>
</schedule>
<instructor>Matthew Johnson</instructor>
</course_syllabus>


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

[User]
Convert the following XML to YAML:
<?xml version="1.0" encoding="UTF-8"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Visionary eco-centric methodology API</title>
<version>1.0.0</version>
</info>
<paths>
</edge>
<get>
<summary>Simple really social range.</summary>
<parameters>
<name>param0</name>
<in>query</in>
<type>string</type>
</parameters>
<parameters>
<name>param1</name>
<in>query</in>
<type>string</type>
</parameters>
<responses>
<200>
<description>Success</description>
</200>
<400>
<description>Bad Request</description>
</400>
</responses>
</get>
<//edge>
</paths>
</api_specification>

[Assistant]
Approach:
1. Task: Convert api specification 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:
openapi: 3.0.0
info:
  title: Visionary eco-centric methodology API
  version: 1.0.0
paths:
  /edge:
    get:
      summary: Simple really social range.
      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 TOML format. Think step-by-step, then generate syntactically perfect TOML.

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

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

Output:
review_id = "REV-4235678"
product_id = "PROD-754494"
user_id = "29638f7d-f697-4ae7-8fde-a1a70bcd6476"
rating = 5
title = "Help program law water necessary return clearly."
content = "Team hold course throw center open enjoy old. Huge candidate still act decade civil. Safe middle indeed."
date = "2026-01-03"
verified_purchase = false
helpful_votes = 98


[System] You are an expert in 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: medium - 5-8 fields, 2-3 levels
3. Format rules: key=value syntax, [sections], proper types
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
post_id = "POST-58559815"
platform = "instagram"
user_id = "0fae79ab-dabb-47f5-823b-f22743181c7c"
username = "ortizkristina"
content = "Speech can sea play. Season near story animal remain.\nOff present vote wall. Society know family build. Certain thing live rise."
timestamp = "2026-01-07T13:51:26.463560"
hashtags = [ "#once", "#it", "#rich", "#keep",]

[engagement]
likes = 248
shares = 32
comments = 161


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<research_paper>
<paper_id>arXiv:2021.87801</paper_id>
<title>Cross-group 24/7 methodology</title>
<authors>
<name>Scott Webb</name>
<affiliation>Chapman LLC</affiliation>
<email>juanbooth@example.com</email>
</authors>
<authors>
<name>Robert Mullins</name>
<affiliation>Robbins, Adkins and Rogers</affiliation>
<email>michaeldunn@example.org</email>
</authors>
<abstract>Reality maybe court material response cell. Middle instead husband win thousand collection.</abstract>
<keywords>girl</keywords>
<keywords>face</keywords>
<keywords>protect</keywords>
<publication>
<venue>Cell</venue>
<year>2023</year>
<doi>10.4960/byWV</doi>
</publication>
<citations>193</citations>
<funding_source>Williams Ltd</funding_source>
</research_paper>

[Assistant]
Approach:
1. Task: Convert research paper 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:
{
  "paper_id": "arXiv:2021.87801",
  "title": "Cross-group 24/7 methodology",
  "authors": [
    {
      "name": "Scott Webb",
      "affiliation": "Chapman LLC",
      "email": "juanbooth@example.com"
    },
    {
      "name": "Robert Mullins",
      "affiliation": "Robbins, Adkins and Rogers",
      "email": "michaeldunn@example.org"
    }
  ],
  "abstract": "Reality maybe court material response cell. Middle instead husband win thousand collection.",
  "keywords": [
    "girl",
    "face",
    "protect"
  ],
  "publication": {
    "venue": "Cell",
    "year": 2023,
    "doi": "10.4960/byWV"
  },
  "citations": 193,
  "funding_source": "Williams Ltd"
}


[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>
<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>

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


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

[User]
Convert the following YAML to JSON:
note_id: CN-8293808
patient:
  mrn: MRN-980604
  age: 24
  gender: F
encounter_date: '2026-01-05'
chief_complaint: fever
vitals:
  bp: 150/98
  hr: 93
  temp_f: 102.4
assessment:
- problem: diabetes
  icd10: J39

[Assistant]
Approach:
1. Task: Convert clinical note 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:
{
  "note_id": "CN-8293808",
  "patient": {
    "mrn": "MRN-980604",
    "age": 24,
    "gender": "F"
  },
  "encounter_date": "2026-01-05",
  "chief_complaint": "fever",
  "vitals": {
    "bp": "150/98",
    "hr": 93,
    "temp_f": 102.4
  },
  "assessment": [
    {
      "problem": "diabetes",
      "icd10": "J39"
    }
  ]
}


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<news_article>
<article_id>ART-7317178</article_id>
<headline>Sharable 5thgeneration framework</headline>
<author>Judy Garner</author>
<published>2026-01-07T07:35:28.380949</published>

Politics

<content>Cover whole myself late last month authority. Make away choose difficult.
Shoulder so support like let increase improve movie. Gun career hair necessary improve operation detail.</content>
<tags>cover</tags>
<tags>people</tags>
<tags>available</tags>
<tags>above</tags>
<tags>service</tags>
<views>84087</views>
<shares>2480</shares>
</news_article>


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

[User]
Transform this JSON data into CSV format:
{
  "experiment_id": "EXP-734376",
  "title": "Effect of probably on skin",
  "methodology": {
    "design": "cohort",
    "sample_size": 800,
    "duration_days": 273
  },
  "results": [
    {
      "metric": "efficacy",
      "baseline": 94.92,
      "endpoint": 99.12,
      "p_value": 0.3163
    },
    {
      "metric": "safety",
      "baseline": 43.8,
      "endpoint": 81.58,
      "p_value": 0.1627
    },
    {
      "metric": "efficacy",
      "baseline": 31.59,
      "endpoint": 36.02,
      "p_value": 0.4619
    },
    {
      "metric": "efficacy",
      "baseline": 82.54,
      "endpoint": 59.85,
      "p_value": 0.3654
    }
  ],
  "conclusion": "significant"
}

[Assistant]
Approach:
1. Task: Convert experiment result 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:
conclusion,experiment_id,methodology_design,methodology_duration_days,methodology_sample_size,results,title
significant,EXP-734376,cohort,273,800,"[{""metric"": ""efficacy"", ""baseline"": 94.92, ""endpoint"": 99.12, ""p_value"": 0.3163}, {""metric"": ""safety",Effect of probably on skin
non-significant,EXP-539462,observational,237,957,"[{""metric"": ""efficacy"", ""baseline"": 46.98, ""endpoint"": 39.47, ""p_value"": 0.2224}, {""metric"": ""effica",Effect of effort on yard
significant,EXP-908907,RCT,329,394,"[{""metric"": ""efficacy"", ""baseline"": 75.24, ""endpoint"": 94.39, ""p_value"": 0.339}, {""metric"": ""safety""",Effect of executive on some
non-significant,EXP-455139,observational,74,641,"[{""metric"": ""efficacy"", ""baseline"": 20.99, ""endpoint"": 72.4, ""p_value"": 0.0336}, {""metric"": ""safety""",Effect of degree on soldier
non-significant,EXP-723791,cohort,93,783,"[{""metric"": ""efficacy"", ""baseline"": 15.0, ""endpoint"": 56.88, ""p_value"": 0.1147}, {""metric"": ""safety""",Effect of force on movement


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

[User]
Convert the following XML to CSV:
<?xml version="1.0" encoding="UTF-8"?>
<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 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,chief_complaint,encounter_date,note_id,patient_age,patient_gender,patient_mrn,vitals_bp,vitals_hr,vitals_temp_f
"[{""problem"": ""diabetes"", ""icd10"": ""I32""}]",fever,2026-01-06,CN-4493327,62,F,MRN-934301,141/91,100,98.5
"[{""problem"": ""hypertension"", ""icd10"": ""I72""}]",headache,2026-01-04,CN-7864346,84,F,MRN-374718,158/101,118,102.6
"[{""problem"": ""diabetes"", ""icd10"": ""K45""}, {""problem"": ""diabetes"", ""icd10"": ""J68""}, {""problem"": ""hype",headache,2026-01-05,CN-5754626,69,M,MRN-510988,155/67,76,98.9
"[{""problem"": ""hypertension"", ""icd10"": ""K34""}]",chest pain,2026-01-05,CN-6724570,71,M,MRN-529742,148/64,81,97.1


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

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

[Assistant]
Approach:
1. Task: Create api specification in JSON
2. Complexity: 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:
{
  "openapi": "3.0.0",
  "info": {
    "title": "Reactive exuding frame API",
    "version": "1.0.0"
  },
  "paths": {
    "/second": {
      "get": {
        "summary": "Life century work throughout however miss another.",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  }
}


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

[User] Output social media post as XML.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<social_media_post>
<post_id>POST-46905875</post_id>
<platform>instagram</platform>
<user_id>2079b341-d50b-4860-ba15-aa28bbe0f5b3</user_id>
<username>xhernandez</username>
<content>Serious degree upon late.
Painting throughout direction indicate night. Political business voice street child. Across between ready. Majority red mission prepare state.</content>
<timestamp>2026-01-07T13:51:26.735117</timestamp>
<hashtags>#easy</hashtags>
<hashtags>#miss</hashtags>
<engagement>
<likes>6808</likes>
<shares>9</shares>
<comments>24</comments>
</engagement>
</social_media_post>


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

[User] Create a XML representation of error log.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<error_log>
<message>Baby inside high our should character study quickly.</message>
<stack_trace>at standard.py:486</stack_trace>
<stack_trace>at memory.py:53</stack_trace>
<stack_trace>at team.py:342</stack_trace>
<context>
<user_id>b89e754b-fd03-47c7-9600-09a7cb6d3517</user_id>
<request_id>0aea7b7e-f431-4209-a4db-008320d27043</request_id>
</context>
<timestamp>2026-01-07T13:51:25.507604</timestamp>
</error_log>


[System] You are an expert in 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>
<title>Career hospital always money word day.</title>
<helpful_votes>95</helpful_votes>
<review_id>REV-5250684</review_id>
<verified_purchase>False</verified_purchase>
<date>2026-01-01</date>
</customer_review>

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

Output:
{
  "title": "Career hospital always money word day.",
  "helpful_votes": 95,
  "review_id": "REV-5250684",
  "verified_purchase": false,
  "date": "2026-01-01"
}


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

[User]
Convert the following TOML to CSV:
product_id = "PROD-830951"
name = "Multi-layered tangible superstructure"
category = "clothing"
price = 269.31
currency = "USD"
stock = 322
is_available = true
rating = 2.21
reviews = 733

[specs]
weight_kg = 46.04
dimensions = "75x77x31cm"

[Assistant]
Approach:
1. Task: Convert product listing 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:
category,currency,is_available,name,price,product_id,rating,reviews,specs_dimensions,specs_weight_kg,stock
clothing,USD,True,Multi-layered tangible superstructure,269.31,PROD-830951,2.21,733,75x77x31cm,46.04,322
electronics,USD,True,Reduced mission-critical framework,775.81,PROD-106159,3.55,967,56x48x18cm,47.43,519
clothing,USD,True,Operative cohesive data-warehouse,930.6,PROD-713112,4.55,512,29x65x64cm,13.48,969


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

Output:
{
  "review_id": "REV-1521978",
  "product_id": "PROD-894495",
  "user_id": "0e93d4dc-0d39-4af2-8ec3-d8d1250011b9",
  "rating": 4,
  "title": "Great how data open such.",
  "content": "City not either situation all along might. Under could expect build member. Fish ready onto white majority.",
  "date": "2026-01-05",
  "verified_purchase": false,
  "helpful_votes": 57
}


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

[User]
Transform this TOML data into YAML format:
category = "electronics"
stock = 596
price = 218.58

[specs]
weight_kg = 38.59
dimensions = "23x92x45cm"

[Assistant]
Approach:
1. Task: Convert product listing from TOML 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:
category: electronics
specs:
  weight_kg: 38.59
  dimensions: 23x92x45cm
stock: 596
price: 218.58


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

[User] Generate product listing data in TOML format.

[Assistant]
Approach:
1. Task: Create product listing 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:
category = "electronics"
stock = 596
price = 218.58

[specs]
weight_kg = 38.59
dimensions = "23x92x45cm"


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

[Assistant]
Approach:
1. Task: Convert transaction record 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"?>
<transaction_record>
<txn_id>TXN-28879814</txn_id>
<customer_id>b13e97b5-e84b-41ec-9dea-05b4809cdd35</customer_id>
<timestamp>2026-01-07T13:51:25.895711</timestamp>
<items>
<sku>SKU-36351</sku>
<qty>1</qty>
<price>310.41</price>
</items>
<items>
<sku>SKU-26629</sku>
<qty>2</qty>
<price>119.44</price>
</items>
<items>
<sku>SKU-75447</sku>
<qty>3</qty>
<price>127.79</price>
</items>
<items>
<sku>SKU-81003</sku>
<qty>3</qty>
<price>336.59</price>
</items>
<subtotal>994.66</subtotal>
<tax>143.59</tax>
<total>1762.36</total>
<payment_method>apple_pay</payment_method>
</transaction_record>


[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:
{
  "review_id": "REV-7250124",
  "product_id": "PROD-375265",
  "user_id": "48302d32-0445-4405-afc6-604ef6300782",
  "rating": 1,
  "title": "Very responsibility coach economy sea public you.",
  "content": "Chair painting shake city kind good though. Find reality water support key.\nFly party couple production fight. Live attention anyone her traditional. I room blood condition research fund model.",
  "date": "2026-01-03",
  "verified_purchase": true,
  "helpful_votes": 78
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<review_id>REV-7250124</review_id>
<product_id>PROD-375265</product_id>
<user_id>48302d32-0445-4405-afc6-604ef6300782</user_id>
<rating>1</rating>
<title>Very responsibility coach economy sea public you.</title>
<content>Chair painting shake city kind good though. Find reality water support key.
Fly party couple production fight. Live attention anyone her traditional. I room blood condition research fund model.</content>
<date>2026-01-03</date>
<verified_purchase>True</verified_purchase>
<helpful_votes>78</helpful_votes>
</customer_review>


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

[User]
Reformat the data below from JSON to TOML:
{
  "post_id": "POST-59844758",
  "timestamp": "2026-01-07T13:51:27.358144",
  "hashtags": [
    "#population",
    "#during",
    "#executive",
    "#house"
  ]
}

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

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


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

[User] Create a XML representation of transaction record.

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

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


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<sales_analytics>
<units_sold>11543</units_sold>
<period>June 2021</period>
<channels>
<name>online</name>
<revenue>1417680</revenue>
<growth>41.94</growth>
</channels>
<channels>
<name>wholesale</name>
<revenue>3176166</revenue>
<growth>26.78</growth>
</channels>
<total_revenue>8223229</total_revenue>
<top_products>
<sku>SKU-9002</sku>
<sales>412560</sales>
</top_products>
<top_products>
<sku>SKU-3918</sku>
<sales>426996</sales>
</top_products>
<top_products>
<sku>SKU-1618</sku>
<sales>496165</sales>
</top_products>
</sales_analytics>

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


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

[User]
Reformat the data below from JSON to XML:
{
  "result_id": "LAB-9047593",
  "patient_mrn": "MRN-478989",
  "order_date": "2026-01-06",
  "panel": "CMP",
  "results": [
    {
      "test": "Hemoglobin",
      "value": 171.8,
      "unit": "mg/dL",
      "flag": "normal"
    },
    {
      "test": "WBC",
      "value": 58.0,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "WBC",
      "value": 78.7,
      "unit": "mg/dL",
      "flag": "normal"
    },
    {
      "test": "Glucose",
      "value": 138.7,
      "unit": "mg/dL",
      "flag": "low"
    },
    {
      "test": "Hemoglobin",
      "value": 51.5,
      "unit": "g/dL",
      "flag": "high"
    },
    {
      "test": "Hemoglobin",
      "value": 141.9,
      "unit": "mg/dL",
      "flag": "low"
    },
    {
      "test": "Hemoglobin",
      "value": 191.7,
      "unit": "mg/dL",
      "flag": "high"
    }
  ]
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<lab_result>
<result_id>LAB-9047593</result_id>
<patient_mrn>MRN-478989</patient_mrn>
<order_date>2026-01-06</order_date>
<panel>CMP</panel>
<results>
<test>Hemoglobin</test>
<value>171.8</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>WBC</test>
<value>58.0</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>WBC</test>
<value>78.7</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Glucose</test>
<value>138.7</value>
<unit>mg/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>51.5</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>141.9</value>
<unit>mg/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>191.7</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
</lab_result>


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

[User] Generate api specification data in JSON format.

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

Output:
{
  "openapi": "3.0.0",
  "info": {
    "title": "Grass-roots 6thgeneration ability API",
    "version": "1.0.0"
  },
  "paths": {
    "/million": {
      "get": {
        "summary": "About little above investment already magazine.",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  }
}


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

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

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

Output:
post_id: POST-78635818
platform: facebook
user_id: a739269a-9642-463c-9c88-cb97c795c8d8
username: kevin10
content: Specific other kind choice. Condition main resource finish north reach with
  break. Area strategy huge edge.
timestamp: '2026-01-07T13:51:25.965362'
hashtags:
- '#model'
- '#firm'
engagement:
  likes: 3831
  shares: 379
  comments: 204


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

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

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

Output:
{
  "period": "October 2022",
  "total_revenue": 4790876,
  "units_sold": 72609,
  "channels": [
    {
      "name": "retail",
      "revenue": 1112533,
      "growth": 2.85
    },
    {
      "name": "wholesale",
      "revenue": 3150615,
      "growth": -3.34
    }
  ],
  "top_products": [
    {
      "sku": "SKU-7795",
      "sales": 492045
    },
    {
      "sku": "SKU-5231",
      "sales": 195976
    },
    {
      "sku": "SKU-5539",
      "sales": 335045
    }
  ]
}


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

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

[Assistant]
Approach:
1. Task: Create news article in TOML
2. Complexity: 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:
author = "Jenna Bryant"
tags = [ "most", "off", "shoulder",]
headline = "Secured composite leverage"
published = "2026-01-04T22:19:16.750289"


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

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

[Assistant]
Approach:
1. Task: Create customer review 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:
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
,"Issue suddenly such maybe. Military they second staff end agreement.
Close that speech alone know wi",,2026-01-02,34,,,,PROD-245093,1,REV-2691236,,,,,Now new sell exist just.,98b0ec97-f0e6-4eda-907b-c1488d5de2f5,False
clothing,,USD,,,True,Object-based exuding moratorium,486.18,PROD-652383,4.61,,504,36x67x40cm,26.07,609,,,
clothing,,USD,,,True,Business-focused incremental neural-net,426.38,PROD-554994,4.15,,268,17x39x79cm,46.25,628,,,
electronics,,USD,,,True,Customizable analyzing forecast,847.26,PROD-458134,1.07,,349,50x48x55cm,9.89,791,,,
books,,USD,,,True,Extended optimizing synergy,120.23,PROD-184611,3.67,,768,77x66x68cm,7.19,11,,,


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

[User]
Reformat the data below from JSON to XML:
{
  "product_id": "PROD-830951",
  "name": "Multi-layered tangible superstructure",
  "category": "clothing",
  "price": 269.31,
  "currency": "USD",
  "stock": 322,
  "is_available": true,
  "rating": 2.21,
  "reviews": 733,
  "specs": {
    "weight_kg": 46.04,
    "dimensions": "75x77x31cm"
  }
}

[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-830951</product_id>
<name>Multi-layered tangible superstructure</name>
<category>clothing</category>
<price>269.31</price>
<currency>USD</currency>
<stock>322</stock>
<is_available>True</is_available>
<rating>2.21</rating>
<reviews>733</reviews>
<specs>
<weight_kg>46.04</weight_kg>
<dimensions>75x77x31cm</dimensions>
</specs>
</product_listing>


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

[User] Create a XML representation of transaction record.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<transaction_record>
<items>
<sku>SKU-71565</sku>
<qty>1</qty>
<price>387.38</price>
</items>
<items>
<sku>SKU-23891</sku>
<qty>1</qty>
<price>432.74</price>
</items>
<items>
<sku>SKU-77840</sku>
<qty>1</qty>
<price>463.12</price>
</items>
<items>
<sku>SKU-27496</sku>
<qty>3</qty>
<price>295.3</price>
</items>
<tax>39.55</tax>
<total>1865.58</total>
<customer_id>bf96f80b-072c-4f04-82b0-c235c01681a8</customer_id>
</transaction_record>


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<product_listing>
<product_id>PROD-421885</product_id>
<name>Diverse 6thgeneration solution</name>
<category>books</category>
<price>48.12</price>
<currency>USD</currency>
<stock>460</stock>
<is_available>True</is_available>
<rating>3.7</rating>
<reviews>717</reviews>
<specs>
<weight_kg>20.82</weight_kg>
<dimensions>87x57x81cm</dimensions>
</specs>
</product_listing>

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

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

[User] Output customer review as YAML.

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

Output:
review_id: REV-5911912
product_id: PROD-652506
user_id: e81c58cf-1a13-4302-a93a-5e1fbbfd28db
rating: 3
title: Their husband whole president threat argue.
content: 'Happen member step can deal animal fine. Like among study from book.

  Democratic significant every sport next want. List religious computer rise wrong.'
date: '2026-01-02'
verified_purchase: true
helpful_votes: 61


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<product_listing>
<product_id>PROD-125540</product_id>
<name>Universal eco-centric approach</name>
<category>books</category>
<price>208.68</price>
<currency>USD</currency>
<stock>879</stock>
<is_available>True</is_available>
<rating>4.53</rating>
<reviews>925</reviews>
<specs>
<weight_kg>20.35</weight_kg>
<dimensions>45x91x83cm</dimensions>
</specs>
</product_listing>

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

Output:
{
  "product_id": "PROD-125540",
  "name": "Universal eco-centric approach",
  "category": "books",
  "price": 208.68,
  "currency": "USD",
  "stock": 879,
  "is_available": true,
  "rating": 4.53,
  "reviews": 925,
  "specs": {
    "weight_kg": 20.35,
    "dimensions": "45x91x83cm"
  }
}


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

[User] Output clinical note as YAML.

[Assistant]
Approach:
1. Task: Create clinical note in YAML
2. Complexity: 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:
patient:
  mrn: MRN-802088
  age: 30
  gender: M
note_id: CN-3759937
vitals:
  bp: 119/74
  hr: 67
  temp_f: 100.9


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

[User] Generate product listing data in YAML format.

[Assistant]
Approach:
1. Task: Create product listing in YAML
2. Complexity: 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:
product_id: PROD-469887
is_available: true
reviews: 612
name: Networked executive capability
currency: USD


[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: 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:
rx_id: RX-7309915
patient_mrn: MRN-389849
prescriber: Briana Dickerson
date: '2026-01-03'
medications:
- name: Metformin
  dosage: 20mg
  frequency: daily
  quantity: 30


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<research_paper>
<publication>
<venue>Cell</venue>
<year>2021</year>
<doi>10.3653/hXNF</doi>
</publication>
<funding_source>Kramer Ltd</funding_source>
<title>Configurable bandwidth-monitored strategy</title>
<authors>
<name>James Brown</name>
<affiliation>Ward-Davidson</affiliation>
<email>wilsonkristin@example.org</email>
</authors>
<authors>
<name>Luke Liu</name>
<affiliation>Obrien-Huynh</affiliation>
<email>jason08@example.org</email>
</authors>
<authors>
<name>Paula Gonzalez</name>
<affiliation>Jones-Howell</affiliation>
<email>brent41@example.org</email>
</authors>
</research_paper>

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


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

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

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

Output:
{
  "post_id": "POST-58883169",
  "user_id": "9fc1586a-703b-4459-a18b-2f5e0582ab64",
  "username": "alexandra57"
}


[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: medium - 5-8 fields, 2-3 levels
3. Format rules: well-formed tags, proper nesting, escaped special chars
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
<?xml version="1.0" encoding="UTF-8"?>
<product_listing>
<product_id>PROD-791864</product_id>
<name>Decentralized heuristic migration</name>
<category>books</category>
<price>124.58</price>
<currency>USD</currency>
<stock>601</stock>
<is_available>True</is_available>
<rating>3.59</rating>
<reviews>538</reviews>
<specs>
<weight_kg>9.83</weight_kg>
<dimensions>30x16x25cm</dimensions>
</specs>
</product_listing>


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

[User]
Reformat the data below from CSV to TOML:
assessment_id,course_id,date,grade,percentage,scores,student_id,total_score,type
ASMT-810488,,,,51.02,,,65,
ASMT-720668,CRS-5557,2026-01-04,B,51.88,"[{""question"": 1, ""points_earned"": 1, ""points_possible"": 10}, {""question"": 2, ""points_earned"": 7, ""po",STU-641855,88,quiz
ASMT-293671,CRS-5374,2026-01-01,B,70.01,"[{""question"": 1, ""points_earned"": 6, ""points_possible"": 10}, {""question"": 2, ""points_earned"": 10, ""p",STU-568176,65,quiz
ASMT-467977,CRS-6382,2026-01-03,A,71.69,"[{""question"": 1, ""points_earned"": 1, ""points_possible"": 10}, {""question"": 2, ""points_earned"": 5, ""po",STU-240819,100,quiz

[Assistant]
Approach:
1. Task: Convert student assessment 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:
total_score = 65
percentage = 51.02
assessment_id = "ASMT-810488"


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

[User]
Convert the following JSON to XML:
{
  "contract_id": "CTR-896633",
  "parties": [
    {
      "name": "Smith-Cross",
      "role": "party_a"
    },
    {
      "name": "Carrillo and Sons",
      "role": "party_b"
    }
  ],
  "effective_date": "2026-01-03",
  "term_months": 21,
  "value": 926875,
  "status": "pending"
}

[Assistant]
Approach:
1. Task: Convert contract 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"?>
<contract>
<contract_id>CTR-896633</contract_id>
<parties>
<name>Smith-Cross</name>
<role>party_a</role>
</parties>
<parties>
<name>Carrillo and Sons</name>
<role>party_b</role>
</parties>
<effective_date>2026-01-03</effective_date>
<term_months>21</term_months>
<value>926875</value>
<status>pending</status>
</contract>


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

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

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

Output:
{
  "product_id": "PROD-308726",
  "name": "Cross-platform client-server attitude",
  "category": "electronics",
  "price": 875.12,
  "currency": "USD",
  "stock": 161,
  "is_available": true,
  "rating": 1.18,
  "reviews": 705,
  "specs": {
    "weight_kg": 37.34,
    "dimensions": "78x81x41cm"
  }
}


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

[User] Output research paper as JSON.

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

Output:
{
  "paper_id": "arXiv:2024.49729",
  "title": "Optimized fault-tolerant monitoring",
  "authors": [
    {
      "name": "Ashley Hubbard",
      "affiliation": "Mcdonald-White",
      "email": "jenniferlong@example.net"
    },
    {
      "name": "Erica Marshall",
      "affiliation": "Calderon-Dalton",
      "email": "adouglas@example.org"
    },
    {
      "name": "Mercedes Campbell",
      "affiliation": "Davis-Lynch",
      "email": "yharris@example.org"
    }
  ],
  "abstract": "Relate make read game soldier new. Agree south attorney one century drive draw.\nReduce head tax certainly offer deal. Sister station adult seat wear.",
  "keywords": [
    "gas",
    "understand",
    "everything",
    "miss"
  ],
  "publication": {
    "venue": "Cell",
    "year": 2024,
    "doi": "10.3465/hMKF"
  },
  "citations": 65,
  "funding_source": "Parsons Inc"
}


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

[User] Generate sales analytics data in JSON format.

[Assistant]
Approach:
1. Task: Create sales analytics in JSON
2. Complexity: 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:
{
  "period": "May 2020",
  "total_revenue": 534039,
  "units_sold": 34851,
  "channels": [
    {
      "name": "retail",
      "revenue": 707158,
      "growth": 43.16
    },
    {
      "name": "wholesale",
      "revenue": 2548868,
      "growth": 26.24
    }
  ],
  "top_products": [
    {
      "sku": "SKU-6020",
      "sales": 18280
    },
    {
      "sku": "SKU-3349",
      "sales": 458703
    },
    {
      "sku": "SKU-8781",
      "sales": 265385
    }
  ]
}