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

[User]
Transform this JSON data into XML format:
{
  "paper_id": "arXiv:2024.66116",
  "title": "Quality-focused grid-enabled service-desk",
  "authors": [
    {
      "name": "David Cohen",
      "affiliation": "Lopez and Sons",
      "email": "mark98@example.com"
    },
    {
      "name": "Ashley Spencer",
      "affiliation": "Hood Ltd",
      "email": "pbailey@example.org"
    },
    {
      "name": "Robin Lynch",
      "affiliation": "Camacho, Nelson and Perez",
      "email": "samantha44@example.net"
    }
  ],
  "abstract": "Body exactly last operation trouble. Financial whole check management chance eat us. Likely wrong explain by would born only.",
  "keywords": [
    "rather",
    "hair",
    "attorney",
    "chance",
    "bring"
  ],
  "publication": {
    "venue": "Cell",
    "year": 2020,
    "doi": "10.7468/EeJM"
  },
  "citations": 174,
  "funding_source": null
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<research_paper>
<paper_id>arXiv:2024.66116</paper_id>
<title>Quality-focused grid-enabled service-desk</title>
<authors>
<name>David Cohen</name>
<affiliation>Lopez and Sons</affiliation>
<email>mark98@example.com</email>
</authors>
<authors>
<name>Ashley Spencer</name>
<affiliation>Hood Ltd</affiliation>
<email>pbailey@example.org</email>
</authors>
<authors>
<name>Robin Lynch</name>
<affiliation>Camacho, Nelson and Perez</affiliation>
<email>samantha44@example.net</email>
</authors>
<abstract>Body exactly last operation trouble. Financial whole check management chance eat us. Likely wrong explain by would born only.</abstract>
<keywords>rather</keywords>
<keywords>hair</keywords>
<keywords>attorney</keywords>
<keywords>chance</keywords>
<keywords>bring</keywords>
<publication>
<venue>Cell</venue>
<year>2020</year>
<doi>10.7468/EeJM</doi>
</publication>
<citations>174</citations>
<funding_source />
</research_paper>


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

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

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

Output:
post_id = "POST-54622203"
platform = "instagram"
user_id = "1456e108-0a50-4482-8f1a-b1cb2398a121"
username = "fullersteven"
content = "Card these member kid western growth. Staff draw say early town general. Large break interesting ten against open.\nAny fine power truth. Big like investment simple whatever education."
timestamp = "2026-01-07T13:51:25.504049"
hashtags = [ "#deep", "#yes", "#long", "#including",]

[engagement]
likes = 464
shares = 699
comments = 294


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

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

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

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


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

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

[Assistant]
Approach:
1. Task: Create news article 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:
article_id: ART-5646798
headline: Switchable hybrid groupware
author: Joshua Bell
published: '2026-01-05T05:31:42.088007'
section: Business
content: 'List road lay not year. Congress gas full particular according. Prevent
  hear century game friend civil live.

  Possible option especially woman. Ahead down suffer doctor six traditional. Prove
  ready American star impact operation just. Difficult yourself difficult base of
  four letter.'
tags:
- author
- son
- food
views: 74484
shares: 596


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

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

Output:
{
  "post_id": "POST-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]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<course_syllabus>
<course_id>CRS-9279</course_id>
WQT213
<title>Ameliorated 3rdgeneration groupware 101</title>
<instructor>Mariah Wilson</instructor>
<credits>3</credits>
<term>Fall 2020</term>
<schedule>
<week>1</week>
<topic>together</topic>
</schedule>
<schedule>
<week>2</week>
<topic>statement</topic>
</schedule>
<schedule>
<week>3</week>
<topic>these</topic>
</schedule>
<schedule>
<week>4</week>
<topic>American</topic>
</schedule>
<schedule>
<week>5</week>
<topic>read</topic>
</schedule>
<schedule>
<week>6</week>
<topic>age</topic>
</schedule>
<schedule>
<week>7</week>
<topic>course</topic>
</schedule>
<grading>
<homework>30</homework>
<midterm>30</midterm>
<final>40</final>
</grading>
</course_syllabus>

[Assistant]
Approach:
1. Task: Convert course syllabus 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:
{
  "course_id": "CRS-9279",
  "code": "WQT213",
  "title": "Ameliorated 3rdgeneration groupware 101",
  "instructor": "Mariah Wilson",
  "credits": 3,
  "term": "Fall 2020",
  "schedule": [
    {
      "week": 1,
      "topic": "together"
    },
    {
      "week": 2,
      "topic": "statement"
    },
    {
      "week": 3,
      "topic": "these"
    },
    {
      "week": 4,
      "topic": "American"
    },
    {
      "week": 5,
      "topic": "read"
    },
    {
      "week": 6,
      "topic": "age"
    },
    {
      "week": 7,
      "topic": "course"
    }
  ],
  "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]
Convert the following JSON to XML:
{
  "experiment_id": "EXP-393268",
  "title": "Effect of themselves on time",
  "methodology": {
    "design": "RCT",
    "sample_size": 237,
    "duration_days": 116
  },
  "results": [
    {
      "metric": "efficacy",
      "baseline": 34.76,
      "endpoint": 73.98,
      "p_value": 0.4055
    },
    {
      "metric": "safety",
      "baseline": 70.26,
      "endpoint": 84.17,
      "p_value": 0.253
    },
    {
      "metric": "safety",
      "baseline": 22.1,
      "endpoint": 56.91,
      "p_value": 0.1172
    }
  ],
  "conclusion": "significant"
}

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


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

[User] Create a XML representation of prescription.

[Assistant]
Approach:
1. Task: Create prescription in XML
2. Complexity: 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"?>
<prescription>
<medications>
<name>Atorvastatin</name>
<dosage>5mg</dosage>
<frequency>BID</frequency>
<quantity>30</quantity>
</medications>
<prescriber>Isaac Howard</prescriber>
<date>2026-01-03</date>
</prescription>


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<error_log>
<message>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>


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<product_listing>
<product_id>PROD-141484</product_id>
<name>Managed bandwidth-monitored focus group</name>
<category>books</category>
<price>751.35</price>
<currency>USD</currency>
<stock>108</stock>
<is_available>True</is_available>
<rating>2.94</rating>
<reviews>250</reviews>
<specs>
<weight_kg>6.41</weight_kg>
<dimensions>15x82x35cm</dimensions>
</specs>
</product_listing>


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

[User]
Convert the following JSON to XML:
{
  "company": "Martinez, Patterson and Hunter",
  "ticker": "PPOB",
  "quarter": "Q1 2023",
  "revenue": 66694743,
  "expenses": 21448775,
  "net_income": 421192,
  "eps": 2.32,
  "metrics": {
    "profit_margin": 7.89,
    "roe": 9.32
  }
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<financial_report>
<company>Martinez, Patterson and Hunter</company>
<ticker>PPOB</ticker>
<quarter>Q1 2023</quarter>
<revenue>66694743</revenue>
<expenses>21448775</expenses>
<net_income>421192</net_income>
<eps>2.32</eps>
<metrics>
<profit_margin>7.89</profit_margin>
<roe>9.32</roe>
</metrics>
</financial_report>


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

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

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

Output:
post_id = "POST-64636774"
platform = "instagram"
user_id = "180a1898-015f-483f-94a7-e771a6fb148e"
username = "melissa16"
content = "Use Mr only week. Crime form attention. Right world stand surface rate three."
timestamp = "2026-01-07T13:51:26.942814"
hashtags = [ "#economic", "#speak",]

[engagement]
likes = 9998
shares = 653
comments = 4


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

[User] Output financial report as YAML.

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

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


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

[User] Generate error log data in TOML format.

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

Output:
error_id = "7af25ba6-3e63-43d5-89e6-c5a6b377b923"
timestamp = "2026-01-07T13:51:26.975438"
level = "CRITICAL"
service = "downService"
message = "Prevent true movie stop."
stack_trace = [ "at hand.py:436", "at whose.py:275", "at information.py:57", "at central.py:306",]

[context]
user_id = "dc348ded-7e54-44aa-bfc8-75caf977ffdf"
request_id = "cc597ab0-ad26-419a-8cbb-1facc38a2f79"


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

[User] Output api specification as CSV.

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

Output:
abstract,authors,citations,funding_source,info_title,info_version,keywords,openapi,paper_id,paths_/peace_get_parameters,paths_/peace_get_responses_200_description,paths_/peace_get_responses_400_description,paths_/peace_get_summary,publication_doi,publication_venue,publication_year,title
,,,,Face-to-face zero administration application API,1.0.0,,3.0.0,,"[{""name"": ""param0"", ""in"": ""query"", ""type"": ""string""}, {""name"": ""param1"", ""in"": ""query"", ""type"": ""str",Success,Bad Request,Feel piece low way effort action bag.,,,,
Last truth number. Most attorney training little should radio.,"[{""name"": ""Lisa Ellis"", ""affiliation"": ""Castillo LLC"", ""email"": ""andrewsexton@example.net""}, {""name""",158,None,,,"[""forget"", ""ten"", ""entire"", ""fire"", ""music""]",,arXiv:2020.71057,,,,,10.1090/ndVl,Science,2024,Customer-focused non-volatile firmware
"Break choose face management piece prevent season.
Throughout truth part fire. Give door any result ","[{""name"": ""Jose Smith"", ""affiliation"": ""Martinez Inc"", ""email"": ""anna77@example.com""}, {""name"": ""Mat",410,None,,,"[""ball"", ""head"", ""amount""]",,arXiv:2024.37958,,,,,10.7834/fcGJ,Cell,2024,User-friendly multimedia approach
Build adult sport morning question because either. Work hear teacher share hand relationship.,"[{""name"": ""Sherri Cruz"", ""affiliation"": ""Taylor PLC"", ""email"": ""jesusandrews@example.net""}, {""name"":",85,Schneider-Parker,,,"[""husband"", ""national"", ""nation"", ""cost""]",,arXiv:2024.77366,,,,,10.6708/WThK,Science,2022,Innovative 4thgeneration neural-net


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

[User] Create a YAML representation of sales analytics.

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

Output:
period: June 2021
total_revenue: 4317671
units_sold: 11582
channels:
- name: wholesale
  revenue: 2780960
  growth: 22.76
- name: retail
  revenue: 4140341
  growth: -9.84
top_products:
- sku: SKU-8636
  sales: 261407
- sku: SKU-9950
  sales: 107242
- sku: SKU-8311
  sales: 494004


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

[User]
Transform this CSV data into YAML format:
code,course_id,credits,grading_final,grading_homework,grading_midterm,instructor,schedule,term,title
QKE428,CRS-8328,3,40,30,30,Sarah Simon,"[{""week"": 1, ""topic"": ""whole""}, {""week"": 2, ""topic"": ""table""}, {""week"": 3, ""topic"": ""determine""}, {""",Fall 2022,Decentralized content-based leverage 101
YWC110,CRS-1590,3,40,30,30,Clinton Bennett,"[{""week"": 1, ""topic"": ""present""}, {""week"": 2, ""topic"": ""pick""}, {""week"": 3, ""topic"": ""by""}, {""week"":",Spring 2024,Monitored national installation 101
RNY124,CRS-6195,3,40,30,30,Arthur Stevens,"[{""week"": 1, ""topic"": ""relate""}, {""week"": 2, ""topic"": ""fall""}, {""week"": 3, ""topic"": ""identify""}, {""w",Fall 2020,Universal tertiary website 101
APP342,CRS-3835,4,40,30,30,Terri Jenkins,"[{""week"": 1, ""topic"": ""never""}, {""week"": 2, ""topic"": ""recently""}, {""week"": 3, ""topic"": ""safe""}, {""we",Fall 2020,Automated web-enabled focus group 101

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

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


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

[User]
Convert the following JSON to XML:
{
  "result_id": "LAB-5790382",
  "patient_mrn": "MRN-357903",
  "order_date": "2026-01-02",
  "panel": "CBC",
  "results": [
    {
      "test": "Glucose",
      "value": 56.1,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "Glucose",
      "value": 114.1,
      "unit": "mg/dL",
      "flag": "normal"
    },
    {
      "test": "WBC",
      "value": 154.7,
      "unit": "mg/dL",
      "flag": "low"
    },
    {
      "test": "Glucose",
      "value": 196.1,
      "unit": "g/dL",
      "flag": "normal"
    }
  ]
}

[Assistant]
Approach:
1. Task: Convert lab result from 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-5790382</result_id>
<patient_mrn>MRN-357903</patient_mrn>
<order_date>2026-01-02</order_date>
<panel>CBC</panel>
<results>
<test>Glucose</test>
<value>56.1</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Glucose</test>
<value>114.1</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>WBC</test>
<value>154.7</value>
<unit>mg/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Glucose</test>
<value>196.1</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
</lab_result>


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

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

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

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


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

[User] Create a XML representation of product listing.

[Assistant]
Approach:
1. Task: Create product listing in XML
2. Complexity: 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"?>
<product_listing>
<specs>
<weight_kg>8.02</weight_kg>
<dimensions>62x22x22cm</dimensions>
</specs>
<name>Universal fault-tolerant service-desk</name>
<price>907.33</price>
<reviews>493</reviews>
</product_listing>


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

[User] Create a TOML representation of error log.

[Assistant]
Approach:
1. Task: Create error log in TOML
2. Complexity: 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:
timestamp = "2026-01-07T13:51:26.818902"
error_id = "de32926d-7560-4176-8c16-f346784a78af"

[context]
user_id = "3a96bf92-d9b7-4f9e-91da-6a15b590d5cf"
request_id = "d8c0cfbc-2ae8-46b8-8db8-ee3a71153dc5"


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

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

[Assistant]
Approach:
1. Task: Create financial report 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:
company = "Moore-Thompson"
ticker = "XFVE"
quarter = "Q2 2022"
revenue = 73324772
expenses = 43130054
net_income = 18329728
eps = 9.88

[metrics]
profit_margin = 22.03
roe = 10.54


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

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

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

Output:
post_id = "POST-32645861"
platform = "facebook"
user_id = "b5521d05-1410-43ee-b828-2c240f95461c"
username = "yanderson"
content = "Example suggest around pattern small everybody. Rate watch blue walk test camera. Partner decide leave really."
timestamp = "2026-01-07T13:51:27.526455"
hashtags = [ "#door", "#relate",]

[engagement]
likes = 5828
shares = 957
comments = 117


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

[User] Output contract as JSON.

[Assistant]
Approach:
1. Task: Create contract 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:
{
  "contract_id": "CTR-926700",
  "parties": [
    {
      "name": "Kelly-Jackson",
      "role": "party_a"
    },
    {
      "name": "Ramos, Hampton and Hartman",
      "role": "party_b"
    }
  ],
  "effective_date": "2026-01-04",
  "term_months": 36,
  "value": 178791,
  "status": "pending"
}


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

[User] Create a XML representation of student assessment.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<student_assessment>
<assessment_id>ASMT-503362</assessment_id>
<student_id>STU-235214</student_id>
<course_id>CRS-9952</course_id>
<type>assignment</type>
<date>2026-01-01</date>
<scores>
<question>1</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>0</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>3</question>
<points_earned>0</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>4</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>6</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>8</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>5</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>9</question>
<points_earned>4</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>10</question>
<points_earned>0</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>11</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>12</question>
<points_earned>8</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>52</total_score>
<percentage>94.35</percentage>
<grade>C</grade>
</student_assessment>


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

[User] Create a XML representation of contract.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<contract>
<contract_id>CTR-370819</contract_id>
<parties>
<name>Stewart, Thompson and Rogers</name>
<role>party_a</role>
</parties>
<parties>
<name>Jackson, Griffin and Flowers</name>
<role>party_b</role>
</parties>
<effective_date>2026-01-01</effective_date>
<term_months>13</term_months>
<value>109351</value>
<status>active</status>
</contract>


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

[User] Output product listing as XML.

[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-942707</product_id>
<name>Organic demand-driven installation</name>
<category>books</category>
<price>698.66</price>
<currency>USD</currency>
<stock>819</stock>
<is_available>True</is_available>
<rating>4.45</rating>
<reviews>103</reviews>
<specs>
<weight_kg>32.63</weight_kg>
<dimensions>66x30x83cm</dimensions>
</specs>
</product_listing>


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

[User]
Reformat the data below from CSV to XML:
order_date,panel,patient_mrn,result_id,results
2026-01-06,CBC,MRN-824701,LAB-1120026,"[{""test"": ""Glucose"", ""value"": 168.8, ""unit"": ""g/dL"", ""flag"": ""high""}, {""test"": ""Glucose"", ""value"": 9"
2026-01-03,Lipid,MRN-532214,LAB-7160960,"[{""test"": ""Glucose"", ""value"": 119.7, ""unit"": ""mg/dL"", ""flag"": ""low""}, {""test"": ""Glucose"", ""value"": 1"
2026-01-06,CBC,MRN-279055,LAB-9580462,"[{""test"": ""Hemoglobin"", ""value"": 113.1, ""unit"": ""g/dL"", ""flag"": ""high""}, {""test"": ""Glucose"", ""value"""

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<lab_result>
<result_id>LAB-1120026</result_id>
<patient_mrn>MRN-824701</patient_mrn>
<order_date>2026-01-06</order_date>
<panel>CBC</panel>
<results>
<test>Glucose</test>
<value>168.8</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Glucose</test>
<value>98.1</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Glucose</test>
<value>137.9</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Glucose</test>
<value>107.7</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
</lab_result>


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

[User] Create a CSV representation of student assessment.

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

Output:
assessment_id,code,course_id,credits,date,grade,grading_final,grading_homework,grading_midterm,instructor,percentage,schedule,scores,student_id,term,title,total_score,type
ASMT-893180,,CRS-6394,,2026-01-03,A,,,,,73.06,,"[{""question"": 1, ""points_earned"": 10, ""points_possible"": 10}, {""question"": 2, ""points_earned"": 8, ""p",STU-881633,,,98,quiz
,NRE275,CRS-8192,4,,,40,30,30,Stephanie Bailey,,"[{""week"": 1, ""topic"": ""product""}, {""week"": 2, ""topic"": ""mean""}, {""week"": 3, ""topic"": ""to""}, {""week"":",,,Spring 2021,Sharable methodical policy 101,,
,AES243,CRS-6843,3,,,40,30,30,Antonio Hunt,,"[{""week"": 1, ""topic"": ""resource""}, {""week"": 2, ""topic"": ""drive""}, {""week"": 3, ""topic"": ""shake""}, {""w",,,Spring 2023,Fundamental bandwidth-monitored matrix 101,,


[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-5796495",
  "patient_mrn": "MRN-496025",
  "order_date": "2026-01-06",
  "panel": "Lipid",
  "results": [
    {
      "test": "Hemoglobin",
      "value": 74.9,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "Hemoglobin",
      "value": 68.3,
      "unit": "mg/dL",
      "flag": "low"
    },
    {
      "test": "WBC",
      "value": 121.2,
      "unit": "mg/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 142.6,
      "unit": "g/dL",
      "flag": "normal"
    }
  ]
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<lab_result>
<result_id>LAB-5796495</result_id>
<patient_mrn>MRN-496025</patient_mrn>
<order_date>2026-01-06</order_date>
<panel>Lipid</panel>
<results>
<test>Hemoglobin</test>
<value>74.9</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>68.3</value>
<unit>mg/dL</unit>
<flag>low</flag>
</results>
<results>
<test>WBC</test>
<value>121.2</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>142.6</value>
<unit>g/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] Produce a XML document for a prescription.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<prescription>
<rx_id>RX-9442688</rx_id>
<patient_mrn>MRN-277514</patient_mrn>
<prescriber>Timothy Goodman</prescriber>
<date>2026-01-04</date>
<medications>
<name>Metformin</name>
<dosage>20mg</dosage>
<frequency>TID</frequency>
<quantity>30</quantity>
</medications>
<medications>
<name>Metformin</name>
<dosage>5mg</dosage>
<frequency>BID</frequency>
<quantity>30</quantity>
</medications>
<medications>
<name>Lisinopril</name>
<dosage>5mg</dosage>
<frequency>TID</frequency>
<quantity>30</quantity>
</medications>
</prescription>


[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"?>
<news_article>
<article_id>ART-4067367</article_id>
<headline>Polarized human-resource adapter</headline>
<author>Kristin Larson</author>
<published>2026-01-07T00:05:34.405255</published>

Business

<content>Ahead effort author use. Unit together series provide arrive country off. Whether let thought down.
Eight audience power analysis. Age hope leader yeah without. Experience kitchen heart city.</content>
<tags>program</tags>
<tags>final</tags>
<tags>computer</tags>
<tags>live</tags>
<views>74807</views>
<shares>3986</shares>
</news_article>

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

Output:
{
  "article_id": "ART-4067367",
  "headline": "Polarized human-resource adapter",
  "author": "Kristin Larson",
  "published": "2026-01-07T00:05:34.405255",
  "section": "Business",
  "content": "Ahead effort author use. Unit together series provide arrive country off. Whether let thought down.\nEight audience power analysis. Age hope leader yeah without. Experience kitchen heart city.",
  "tags": [
    "program",
    "final",
    "computer",
    "live"
  ],
  "views": 74807,
  "shares": 3986
}


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

[User] Output news article as CSV.

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

Output:
abstract,authors,citations,funding_source,keywords,paper_id,publication_doi,publication_venue,publication_year,published,section,tags,title,views
,,,,,,,,,2026-01-05T17:58:55.100855,Politics,"[""machine"", ""fund"", ""station"", ""our""]",,86295
"Summer eye keep public time. Away table style investment today individual pick shoulder.
Her quality","[{""name"": ""Alicia Castaneda"", ""affiliation"": ""Barton, Fletcher and Hunt"", ""email"": ""john25@example.o",337,Johnson-Wood,"[""TV"", ""kid"", ""president""]",arXiv:2021.66689,10.9749/uHPt,Science,2022,,,,Monitored next generation implementation,
Example official meeting certainly mention popular. Especially thought government civil throw simple,"[{""name"": ""Peter Young"", ""affiliation"": ""Gomez, Green and Ellis"", ""email"": ""stephanie82@example.com""",142,None,"[""ask"", ""some"", ""company"", ""eat""]",arXiv:2021.55515,10.4628/lCqb,Cell,2021,,,,Automated asymmetric circuit,
Fund strong consider natural risk before push. Movie conference than among history successful.,"[{""name"": ""Ann Price"", ""affiliation"": ""Wheeler-Sanders"", ""email"": ""yevans@example.org""}, {""name"": ""J",492,Wallace Inc,"[""last"", ""draw"", ""even"", ""respond""]",arXiv:2021.11141,10.5191/dOoX,Science,2023,,,,Digitized real-time conglomeration,
Call but to ask almost. Trouble measure myself minute.,"[{""name"": ""Michael Wright"", ""affiliation"": ""Clayton, Hayes and Hayden"", ""email"": ""omarshall@example.",426,None,"[""store"", ""can"", ""class""]",arXiv:2024.89047,10.3938/roGa,Nature,2024,,,,Innovative fault-tolerant function,


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

[User] Output financial report as CSV.

[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:
abstract,authors,citations,eps,expenses,funding_source,keywords,net_income,paper_id,publication_doi,publication_venue,publication_year,quarter,revenue,title
,,,5.75,65628233,,,6367407,,,,,Q2 2023,73745517,
Structure find which even. Finally new free. Represent exist ask increase million nation.,"[{""name"": ""Tanya Roberson"", ""affiliation"": ""Chan-Scott"", ""email"": ""wangrebecca@example.net""}, {""name",174,,,None,"[""lead"", ""director"", ""suddenly"", ""north"", ""part""]",,arXiv:2020.98196,10.1216/ivve,Cell,2024,,,Organic optimal pricing structure
Benefit trouble model area market east prove occur. Thought blue customer direction. Bill month mate,"[{""name"": ""Sarah Fuller"", ""affiliation"": ""Cortez Ltd"", ""email"": ""jhernandez@example.org""}, {""name"": ",393,,,None,"[""support"", ""author"", ""sort"", ""hard"", ""thing""]",,arXiv:2024.10922,10.7913/AhjL,Cell,2021,,,Advanced regional budgetary management
Around give other state. Rest read reach serious situation prepare factor.,"[{""name"": ""William Scott"", ""affiliation"": ""Ortiz-Davis"", ""email"": ""glenn04@example.com""}, {""name"": """,183,,,None,"[""involve"", ""senior"", ""market"", ""also""]",,arXiv:2023.38721,10.6372/IKNo,Nature,2020,,,Implemented coherent Local Area Network
Computer down career democratic. Reason radio current really. Get design various growth guess stuff ,"[{""name"": ""Nathan Collins"", ""affiliation"": ""Anderson Ltd"", ""email"": ""monica92@example.org""}, {""name""",441,,,None,"[""model"", ""game"", ""figure""]",,arXiv:2023.30305,10.6939/vfwD,Science,2020,,,Fully-configurable disintermediate conglomeration


[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:
{
  "experiment_id": "EXP-956799",
  "title": "Effect of town on start",
  "methodology": {
    "design": "RCT",
    "sample_size": 962,
    "duration_days": 355
  },
  "results": [
    {
      "metric": "efficacy",
      "baseline": 84.98,
      "endpoint": 18.54,
      "p_value": 0.3765
    },
    {
      "metric": "safety",
      "baseline": 50.71,
      "endpoint": 79.49,
      "p_value": 0.1783
    },
    {
      "metric": "safety",
      "baseline": 22.25,
      "endpoint": 81.5,
      "p_value": 0.0959
    },
    {
      "metric": "efficacy",
      "baseline": 53.32,
      "endpoint": 58.41,
      "p_value": 0.1807
    }
  ],
  "conclusion": "significant"
}

[Assistant]
Approach:
1. Task: Convert experiment 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"?>
<experiment_result>
<experiment_id>EXP-956799</experiment_id>
<title>Effect of town on start</title>
<methodology>
<design>RCT</design>
<sample_size>962</sample_size>
<duration_days>355</duration_days>
</methodology>
<results>
<metric>efficacy</metric>
<baseline>84.98</baseline>
<endpoint>18.54</endpoint>
<p_value>0.3765</p_value>
</results>
<results>
<metric>safety</metric>
<baseline>50.71</baseline>
<endpoint>79.49</endpoint>
<p_value>0.1783</p_value>
</results>
<results>
<metric>safety</metric>
<baseline>22.25</baseline>
<endpoint>81.5</endpoint>
<p_value>0.0959</p_value>
</results>
<results>
<metric>efficacy</metric>
<baseline>53.32</baseline>
<endpoint>58.41</endpoint>
<p_value>0.1807</p_value>
</results>
<conclusion>significant</conclusion>
</experiment_result>


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

[User]
Reformat the data below from YAML to TOML:
post_id: POST-49469407
platform: instagram
user_id: c776cd7c-2538-4c81-83c8-03afd724bed1
username: donald18
content: Knowledge between friend wife property kid out. Trouble recent member sort
  arrive foot space good.
timestamp: '2026-01-07T13:51:26.031233'
hashtags:
- '#daughter'
- '#after'
- '#affect'
- '#goal'
engagement:
  likes: 2564
  shares: 187
  comments: 95

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

Output:
post_id = "POST-49469407"
platform = "instagram"
user_id = "c776cd7c-2538-4c81-83c8-03afd724bed1"
username = "donald18"
content = "Knowledge between friend wife property kid out. Trouble recent member sort arrive foot space good."
timestamp = "2026-01-07T13:51:26.031233"
hashtags = [ "#daughter", "#after", "#affect", "#goal",]

[engagement]
likes = 2564
shares = 187
comments = 95


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

[User] Output product listing as YAML.

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

Output:
product_id: PROD-651261
name: Cross-platform scalable protocol
category: clothing
price: 855.77
currency: USD
stock: 343
is_available: true
rating: 3.23
reviews: 830
specs:
  weight_kg: 21.29
  dimensions: 84x20x91cm


[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:
{
  "specs": {
    "weight_kg": 8.02,
    "dimensions": "62x22x22cm"
  },
  "name": "Universal fault-tolerant service-desk",
  "price": 907.33,
  "reviews": 493
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<product_listing>
<specs>
<weight_kg>8.02</weight_kg>
<dimensions>62x22x22cm</dimensions>
</specs>
<name>Universal fault-tolerant service-desk</name>
<price>907.33</price>
<reviews>493</reviews>
</product_listing>


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

[User] Output clinical note as XML.

[Assistant]
Approach:
1. Task: Create clinical note 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"?>
<clinical_note>
<note_id>CN-2804449</note_id>
<patient>
<mrn>MRN-394213</mrn>
<age>73</age>
<gender>F</gender>
</patient>
<encounter_date>2026-01-04</encounter_date>
<chief_complaint>fever</chief_complaint>
<vitals>
<bp>162/64</bp>

70

<temp_f>102.7</temp_f>
</vitals>
<assessment>
<problem>hypertension</problem>
<icd10>K44</icd10>
</assessment>
</clinical_note>


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

[User] Output api specification as JSON.

[Assistant]
Approach:
1. Task: Create api specification in JSON
2. Complexity: 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": "Centralized web-enabled hardware API",
    "version": "1.0.0"
  },
  "paths": {
    "/improve": {
      "get": {
        "summary": "Act attention yes herself significant recent.",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          },
          {
            "name": "param1",
            "in": "query",
            "type": "string"
          },
          {
            "name": "param2",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  }
}


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

[User]
Reformat the data below from JSON to XML:
{
  "course_id": "CRS-4765",
  "code": "VMZ479",
  "title": "Exclusive grid-enabled software 101",
  "instructor": "Amy Baker",
  "credits": 4,
  "term": "Fall 2022",
  "schedule": [
    {
      "week": 1,
      "topic": "show"
    },
    {
      "week": 2,
      "topic": "cut"
    },
    {
      "week": 3,
      "topic": "next"
    },
    {
      "week": 4,
      "topic": "everything"
    },
    {
      "week": 5,
      "topic": "people"
    },
    {
      "week": 6,
      "topic": "international"
    },
    {
      "week": 7,
      "topic": "since"
    }
  ],
  "grading": {
    "homework": 30,
    "midterm": 30,
    "final": 40
  }
}

[Assistant]
Approach:
1. Task: Convert course syllabus 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"?>
<course_syllabus>
<course_id>CRS-4765</course_id>
VMZ479
<title>Exclusive grid-enabled software 101</title>
<instructor>Amy Baker</instructor>
<credits>4</credits>
<term>Fall 2022</term>
<schedule>
<week>1</week>
<topic>show</topic>
</schedule>
<schedule>
<week>2</week>
<topic>cut</topic>
</schedule>
<schedule>
<week>3</week>
<topic>next</topic>
</schedule>
<schedule>
<week>4</week>
<topic>everything</topic>
</schedule>
<schedule>
<week>5</week>
<topic>people</topic>
</schedule>
<schedule>
<week>6</week>
<topic>international</topic>
</schedule>
<schedule>
<week>7</week>
<topic>since</topic>
</schedule>
<grading>
<homework>30</homework>
<midterm>30</midterm>
<final>40</final>
</grading>
</course_syllabus>


[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>
<title>Effect of main on stand</title>
<results>
<metric>efficacy</metric>
<baseline>50.39</baseline>
<endpoint>61.09</endpoint>
<p_value>0.3936</p_value>
</results>
<results>
<metric>safety</metric>
<baseline>99.02</baseline>
<endpoint>82.38</endpoint>
<p_value>0.0752</p_value>
</results>
<results>
<metric>efficacy</metric>
<baseline>94.16</baseline>
<endpoint>58.56</endpoint>
<p_value>0.1239</p_value>
</results>
<results>
<metric>safety</metric>
<baseline>41.74</baseline>
<endpoint>45.99</endpoint>
<p_value>0.0661</p_value>
</results>
<experiment_id>EXP-681166</experiment_id>
<methodology>
<design>RCT</design>
<sample_size>875</sample_size>
<duration_days>212</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:
{
  "title": "Effect of main on stand",
  "results": [
    {
      "metric": "efficacy",
      "baseline": 50.39,
      "endpoint": 61.09,
      "p_value": 0.3936
    },
    {
      "metric": "safety",
      "baseline": 99.02,
      "endpoint": 82.38,
      "p_value": 0.0752
    },
    {
      "metric": "efficacy",
      "baseline": 94.16,
      "endpoint": 58.56,
      "p_value": 0.1239
    },
    {
      "metric": "safety",
      "baseline": 41.74,
      "endpoint": 45.99,
      "p_value": 0.0661
    }
  ],
  "experiment_id": "EXP-681166",
  "methodology": {
    "design": "RCT",
    "sample_size": 875,
    "duration_days": 212
  },
  "conclusion": "non-significant"
}


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

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

[Assistant]
Approach:
1. Task: Create error log 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:
error_id: 69ef512f-ddd4-415a-b99a-51e8f50d151c
timestamp: '2026-01-07T13:51:25.644182'
level: WARNING
service: fillService
message: Minute heart focus arrive.
stack_trace:
- at administration.py:211
- at lawyer.py:276
- at discussion.py:115
context:
  user_id: 29c6c678-1224-4e33-8bc1-e94776cd4eb2
  request_id: 42e054d1-48f9-4a1c-ad7b-82ed505d6250


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

[User]
Transform this YAML data into TOML format:
reviews: 730
category: books
stock: 824
is_available: true
specs:
  weight_kg: 7.36
  dimensions: 46x21x76cm

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

Output:
reviews = 730
category = "books"
stock = 824
is_available = true

[specs]
weight_kg = 7.36
dimensions = "46x21x76cm"


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

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

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

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


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

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

[Assistant]
Approach:
1. Task: Create course syllabus in XML
2. Complexity: 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"?>
<course_syllabus>
<course_id>CRS-8328</course_id>
QKE428
<title>Decentralized content-based leverage 101</title>
<instructor>Sarah Simon</instructor>
<credits>3</credits>
<term>Fall 2022</term>
<schedule>
<week>1</week>
<topic>whole</topic>
</schedule>
<schedule>
<week>2</week>
<topic>table</topic>
</schedule>
<schedule>
<week>3</week>
<topic>determine</topic>
</schedule>
<schedule>
<week>4</week>
<topic>evening</topic>
</schedule>
<schedule>
<week>5</week>
<topic>once</topic>
</schedule>
<schedule>
<week>6</week>
<topic>some</topic>
</schedule>
<schedule>
<week>7</week>
<topic>themselves</topic>
</schedule>
<schedule>
<week>8</week>
<topic>table</topic>
</schedule>
<grading>
<homework>30</homework>
<midterm>30</midterm>
<final>40</final>
</grading>
</course_syllabus>


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

[User] Create a XML representation of 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-8221745</article_id>
<headline>Polarized zero administration support</headline>
<author>Maria Johnson</author>
<published>2026-01-03T08:37:58.870132</published>

Business

<content>Would movement white military what them cup. Available remember control staff. None mean hundred PM.
Improve wear produce price according. He method market computer TV strategy.
Body into language. Which other hear they look some option.</content>
<tags>environment</tags>
<tags>name</tags>
<tags>receive</tags>
<tags>happen</tags>
<tags>join</tags>
<views>46852</views>
<shares>763</shares>
</news_article>


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

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

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

Output:
{
  "post_id": "POST-86945311",
  "platform": "facebook",
  "user_id": "b9da037c-f6cd-4ced-8c95-ca7562cf6118",
  "username": "martinsteven",
  "content": "Forget late prevent year cold able arrive. Few possible himself sing community. Activity campaign sure south. Chance on none line best magazine education.",
  "timestamp": "2026-01-07T13:51:26.810240",
  "hashtags": [
    "#drop",
    "#consider",
    "#nature",
    "#all"
  ],
  "engagement": {
    "likes": 3344,
    "shares": 900,
    "comments": 482
  }
}


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

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

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

Output:
period: June 2021
total_revenue: 1467254
units_sold: 63744
channels:
- name: wholesale
  revenue: 2975287
  growth: -1.88
- name: online
  revenue: 2665464
  growth: 14.77
top_products:
- sku: SKU-1172
  sales: 348860
- sku: SKU-4431
  sales: 479568
- sku: SKU-6244
  sales: 245719


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<clinical_note>
<note_id>CN-8293808</note_id>
<patient>
<mrn>MRN-980604</mrn>
<age>24</age>
<gender>F</gender>
</patient>
<encounter_date>2026-01-05</encounter_date>
<chief_complaint>fever</chief_complaint>
<vitals>
<bp>150/98</bp>

93

<temp_f>102.4</temp_f>
</vitals>
<assessment>
<problem>diabetes</problem>
<icd10>J39</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-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 JSON format. Think step-by-step, then generate syntactically perfect JSON.

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<date>2026-01-05</date>
<title>Teach why painting per short.</title>
<rating>4</rating>
</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:
{
  "date": "2026-01-05",
  "title": "Teach why painting per short.",
  "rating": 4
}


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<lab_result>
<result_id>LAB-5383313</result_id>
<patient_mrn>MRN-584871</patient_mrn>
<order_date>2026-01-06</order_date>
<panel>CMP</panel>
<results>
<test>Glucose</test>
<value>194.0</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>67.1</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Glucose</test>
<value>195.1</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>146.6</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>WBC</test>
<value>119.8</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
</lab_result>

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


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

[User] Output student assessment as CSV.

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

Output:
assessment_id,code,course_id,credits,date,grade,grading_final,grading_homework,grading_midterm,instructor,percentage,schedule,scores,student_id,term,title,total_score,type
ASMT-350362,,CRS-1231,,2026-01-01,A,,,,,80.6,,"[{""question"": 1, ""points_earned"": 2, ""points_possible"": 10}, {""question"": 2, ""points_earned"": 1, ""po",STU-421536,,,51,exam
,XCO265,CRS-6957,3,,,40,30,30,Crystal Rivers,,"[{""week"": 1, ""topic"": ""begin""}, {""week"": 2, ""topic"": ""production""}, {""week"": 3, ""topic"": ""collection",,,Fall 2020,Pre-emptive value-added application 101,,
,RFX369,CRS-1237,4,,,40,30,30,Kyle Huynh,,"[{""week"": 1, ""topic"": ""town""}, {""week"": 2, ""topic"": ""floor""}, {""week"": 3, ""topic"": ""side""}, {""week"":",,,Spring 2020,Distributed value-added Local Area Network 101,,
,ALT197,CRS-9340,3,,,40,30,30,Paul Hicks,,"[{""week"": 1, ""topic"": ""term""}, {""week"": 2, ""topic"": ""think""}, {""week"": 3, ""topic"": ""individual""}, {""",,,Spring 2020,Face-to-face transitional artificial intelligence 101,,


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

[Assistant]
Approach:
1. Task: Convert customer review 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"?>
<customer_review>
<review_id>REV-9701957</review_id>
<product_id>PROD-683988</product_id>
<user_id>4d7f9754-e296-4a29-967f-5c8de166a17c</user_id>
<rating>5</rating>
<title>Teach look history according want manager perform.</title>
<content>Admit large politics decide might Mr their. Hundred play I deal but player leader old. Then similar drug coach.</content>
<date>2026-01-03</date>
<verified_purchase>False</verified_purchase>
<helpful_votes>36</helpful_votes>
</customer_review>


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

[User] Generate news article data in CSV format.

[Assistant]
Approach:
1. Task: Create news article in CSV
2. Complexity: 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:
article_id,author,content,headline,published,section,shares,tags,views
ART-1748125,Sandra Bennett,"Majority meeting sound have week public pass. Major food relate spend seven.
Indeed run fund.
Federa",Customizable leadingedge structure,2026-01-03T22:52:42.741679,Sports,2505,"[""subject"", ""attention"", ""class"", ""campaign"", ""second""]",63827
ART-7130585,Ricardo Thomas,"Natural piece move investment former chance fine. Baby enter protect join general suggest light.
Deg",Open-architected object-oriented moratorium,2026-01-04T11:00:53.482609,Politics,1989,"[""design"", ""line"", ""sort""]",3625
ART-4963325,Timothy Jordan,Deal hit would agreement remember work drive wife. You offer so account mention Democrat probably st,Synergized 5thgeneration groupware,2026-01-01T13:44:18.218168,Sports,4463,"[""phone"", ""foreign"", ""subject"", ""today""]",56843
ART-8536929,Valerie Lowery,Eat foot believe option organization anything cost. Western agent follow management. Movie let like ,Configurable zero tolerance framework,2026-01-04T10:23:39.712194,Politics,4316,"[""station"", ""item"", ""sometimes"", ""later"", ""know""]",61348


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

[User] Generate news article data in YAML format.

[Assistant]
Approach:
1. Task: Create news article 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:
article_id: ART-9801838
headline: Multi-lateral didactic encryption
author: Jeffrey Gordon
published: '2026-01-04T05:36:27.140251'
section: Business
content: 'Partner energy whose simply half because long. Pattern include thousand
  care four against.

  Scene center certainly letter already rate among. Do amount account court term same.

  Step usually ground onto study myself.'
tags:
- word
- public
- near
views: 26731
shares: 4423


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

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

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

Output:
content,engagement_comments,engagement_likes,engagement_shares,hashtags,platform,post_id,timestamp,user_id,username
With writer dinner any kitchen add well. Floor image speech charge rate manager vote. Worry involve ,283,5319,573,"[""#training"", ""#Democrat"", ""#pattern"", ""#discover""]",twitter,POST-39452168,2026-01-07T13:51:25.425211,ca270bc8-d443-4389-880a-6fc8dd3e9fa5,robertowens
Ten trip down impact name Republican study. Total section special beyond doctor.,457,1358,651,"[""#current"", ""#hair""]",facebook,POST-22701338,2026-01-07T13:51:25.426564,97234e39-459d-4071-85d2-db2aa5fc8c90,dcantu
War structure appear then third. Campaign him month attorney mission trial stop.,221,2635,386,"[""#gas"", ""#number""]",twitter,POST-43203606,2026-01-07T13:51:25.426853,289e7f85-d852-4dfb-81a6-a6d13aa250a6,christopher03


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

[Assistant]
Approach:
1. Task: Convert customer review 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"?>
<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>


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

[User] Create a TOML representation of error log.

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

Output:
error_id = "8332f894-7969-41dc-b41e-1d31b796cba0"
timestamp = "2026-01-07T13:51:27.125156"
level = "CRITICAL"
service = "imageService"
message = "Bad prepare able heavy morning."
stack_trace = [ "at property.py:50", "at short.py:272",]

[context]
user_id = "a3de195f-baae-4936-bd72-230b1e266327"
request_id = "35eb846c-1e2f-4451-a60f-b8ee42943a10"


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

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


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

[User] Output prescription as JSON.

[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-9346457",
  "patient_mrn": "MRN-685856",
  "prescriber": "Thomas Archer",
  "date": "2026-01-05",
  "medications": [
    {
      "name": "Lisinopril",
      "dosage": "20mg",
      "frequency": "daily",
      "quantity": 90
    },
    {
      "name": "Atorvastatin",
      "dosage": "10mg",
      "frequency": "BID",
      "quantity": 60
    }
  ]
}


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

[User] Create a JSON representation of customer review.

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

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

[User] Create a XML representation of lab result.

[Assistant]
Approach:
1. Task: Create lab result in XML
2. Complexity: 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-1120026</result_id>
<patient_mrn>MRN-824701</patient_mrn>
<order_date>2026-01-06</order_date>
<panel>CBC</panel>
<results>
<test>Glucose</test>
<value>168.8</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Glucose</test>
<value>98.1</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Glucose</test>
<value>137.9</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Glucose</test>
<value>107.7</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
</lab_result>


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<financial_report>
<revenue>65816825</revenue>
<ticker>IQTA</ticker>
<expenses>77578182</expenses>
<company>Ramos-Wallace</company>
</financial_report>

[Assistant]
Approach:
1. Task: Convert financial report 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:
{
  "revenue": 65816825,
  "ticker": "IQTA",
  "expenses": 77578182,
  "company": "Ramos-Wallace"
}


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

[User]
Transform this XML data into CSV format:
<?xml version="1.0" encoding="UTF-8"?>
<social_media_post>
<post_id>POST-66277640</post_id>
<platform>instagram</platform>
<user_id>7e83a029-16e2-49ad-a855-906c882abe46</user_id>
<username>reynoldstaylor</username>
<content>Thousand book animal myself wear beautiful. Room rock couple reality her.
Join town travel agency value improve way. Heavy late science mind develop consider ability.</content>
<timestamp>2026-01-07T13:51:26.676406</timestamp>
<hashtags>#case</hashtags>
<hashtags>#along</hashtags>
<hashtags>#only</hashtags>
<hashtags>#have</hashtags>
<engagement>
<likes>9942</likes>
<shares>119</shares>
<comments>368</comments>
</engagement>
</social_media_post>

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

Output:
content,engagement_comments,engagement_likes,engagement_shares,hashtags,platform,post_id,timestamp,user_id,username
"Thousand book animal myself wear beautiful. Room rock couple reality her.
Join town travel agency va",368,9942,119,"[""#case"", ""#along"", ""#only"", ""#have""]",instagram,POST-66277640,2026-01-07T13:51:26.676406,7e83a029-16e2-49ad-a855-906c882abe46,reynoldstaylor
"Decade car we. Itself friend nearly institution treatment manager me manage.
Ever join beyond memory",145,5531,910,"[""#bar"", ""#cut""]",instagram,POST-29156504,2026-01-07T13:51:26.679633,9e44d498-dfe3-4171-a438-6baec2ea2fe6,kelly61
"Chance design future apply space stand. Piece get up budget sure environment paper.
Hear manager art",309,63,974,"[""#represent"", ""#concern""]",twitter,POST-89836963,2026-01-07T13:51:26.679972,c3a6156e-fecb-48d6-bb23-0aac8213dada,sellison


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

[User]
Transform this JSON data into XML format:
{
  "product_id": "PROD-942707",
  "name": "Organic demand-driven installation",
  "category": "books",
  "price": 698.66,
  "currency": "USD",
  "stock": 819,
  "is_available": true,
  "rating": 4.45,
  "reviews": 103,
  "specs": {
    "weight_kg": 32.63,
    "dimensions": "66x30x83cm"
  }
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<product_listing>
<product_id>PROD-942707</product_id>
<name>Organic demand-driven installation</name>
<category>books</category>
<price>698.66</price>
<currency>USD</currency>
<stock>819</stock>
<is_available>True</is_available>
<rating>4.45</rating>
<reviews>103</reviews>
<specs>
<weight_kg>32.63</weight_kg>
<dimensions>66x30x83cm</dimensions>
</specs>
</product_listing>


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

[User]
Convert the following TOML to XML:
product_id = "PROD-831490"
name = "Seamless optimal task-force"
category = "electronics"
price = 975.8
currency = "USD"
stock = 924
is_available = true
rating = 2.71
reviews = 121

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<product_listing>
<product_id>PROD-831490</product_id>
<name>Seamless optimal task-force</name>
<category>electronics</category>
<price>975.8</price>
<currency>USD</currency>
<stock>924</stock>
<is_available>True</is_available>
<rating>2.71</rating>
<reviews>121</reviews>
<specs>
<weight_kg>17.77</weight_kg>
<dimensions>52x27x46cm</dimensions>
</specs>
</product_listing>


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<clinical_note>
<note_id>CN-3409162</note_id>
<patient>
<mrn>MRN-721241</mrn>
<age>35</age>
<gender>F</gender>
</patient>
<encounter_date>2026-01-05</encounter_date>
<chief_complaint>fever</chief_complaint>
<vitals>
<bp>173/107</bp>

61

<temp_f>99.6</temp_f>
</vitals>
<assessment>
<problem>diabetes</problem>
<icd10>J46</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-3409162",
  "patient": {
    "mrn": "MRN-721241",
    "age": 35,
    "gender": "F"
  },
  "encounter_date": "2026-01-05",
  "chief_complaint": "fever",
  "vitals": {
    "bp": "173/107",
    "hr": 61,
    "temp_f": 99.6
  },
  "assessment": [
    {
      "problem": "diabetes",
      "icd10": "J46"
    }
  ]
}


[System] You are an expert in 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: 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:
{
  "expenses": 54498119,
  "ticker": "OKCY",
  "company": "Clark-Pearson"
}


[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"?>
<research_paper>
<paper_id>arXiv:2023.67497</paper_id>
<title>Open-architected logistical paradigm</title>
<authors>
<name>William Martin</name>
<affiliation>George, Nichols and Johnston</affiliation>
<email>crystal73@example.org</email>
</authors>
<authors>
<name>Thomas Boyer</name>
<affiliation>Powers, Miller and Johnston</affiliation>
<email>xhardin@example.com</email>
</authors>
<authors>
<name>Tanner Coffey</name>
<affiliation>Perez, Marks and Thomas</affiliation>
<email>tracywilliams@example.com</email>
</authors>
<abstract>Yes eat up himself consumer. Technology just debate bill live oil.</abstract>
<keywords>each</keywords>
<keywords>on</keywords>
<keywords>perhaps</keywords>
<publication>
<venue>Nature</venue>
<year>2022</year>
<doi>10.2923/Xnio</doi>
</publication>
<citations>265</citations>
<funding_source>Smith Ltd</funding_source>
</research_paper>

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

Output:
{
  "paper_id": "arXiv:2023.67497",
  "title": "Open-architected logistical paradigm",
  "authors": [
    {
      "name": "William Martin",
      "affiliation": "George, Nichols and Johnston",
      "email": "crystal73@example.org"
    },
    {
      "name": "Thomas Boyer",
      "affiliation": "Powers, Miller and Johnston",
      "email": "xhardin@example.com"
    },
    {
      "name": "Tanner Coffey",
      "affiliation": "Perez, Marks and Thomas",
      "email": "tracywilliams@example.com"
    }
  ],
  "abstract": "Yes eat up himself consumer. Technology just debate bill live oil.",
  "keywords": [
    "each",
    "on",
    "perhaps"
  ],
  "publication": {
    "venue": "Nature",
    "year": 2022,
    "doi": "10.2923/Xnio"
  },
  "citations": 265,
  "funding_source": "Smith Ltd"
}


[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:
date,medications,patient_mrn,prescriber,rx_id
2026-01-01,"[{""name"": ""Lisinopril"", ""dosage"": ""20mg"", ""frequency"": ""daily"", ""quantity"": 30}, {""name"": ""Lisinopri",MRN-256913,Victor Valentine,RX-8246470
2026-01-01,"[{""name"": ""Metformin"", ""dosage"": ""20mg"", ""frequency"": ""BID"", ""quantity"": 90}, {""name"": ""Atorvastatin",MRN-625768,Gabriel Burton,RX-9298143
2026-01-03,"[{""name"": ""Metformin"", ""dosage"": ""5mg"", ""frequency"": ""TID"", ""quantity"": 90}]",MRN-623887,Heather Martinez,RX-6178712
2026-01-05,"[{""name"": ""Lisinopril"", ""dosage"": ""10mg"", ""frequency"": ""TID"", ""quantity"": 30}, {""name"": ""Metformin"",",MRN-898910,Derek Mcmahon,RX-9127243
2026-01-04,"[{""name"": ""Metformin"", ""dosage"": ""10mg"", ""frequency"": ""BID"", ""quantity"": 60}, {""name"": ""Lisinopril"",",MRN-588654,Bernard Martin,RX-1849426

[Assistant]
Approach:
1. Task: Convert prescription from CSV 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:
rx_id = "RX-8246470"
patient_mrn = "MRN-256913"
prescriber = "Victor Valentine"
date = "2026-01-01"
[[medications]]
name = "Lisinopril"
dosage = "20mg"
frequency = "daily"
quantity = 30

[[medications]]
name = "Lisinopril"
dosage = "10mg"
frequency = "BID"
quantity = 60

[[medications]]
name = "Lisinopril"
dosage = "5mg"
frequency = "TID"
quantity = 30


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

[User] Create a YAML representation of lab result.

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

Output:
result_id: LAB-5490961
patient_mrn: MRN-709917
order_date: '2026-01-03'
panel: CBC
results:
- test: Glucose
  value: 146.9
  unit: mg/dL
  flag: high
- test: Hemoglobin
  value: 119.4
  unit: g/dL
  flag: low
- test: WBC
  value: 95.1
  unit: g/dL
  flag: low
- test: Hemoglobin
  value: 73.3
  unit: g/dL
  flag: high
- test: Glucose
  value: 166.8
  unit: g/dL
  flag: low
- test: WBC
  value: 98.8
  unit: g/dL
  flag: high


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

[User] Generate contract data in JSON format.

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


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

[User] Generate clinical note data in TOML format.

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

Output:
note_id = "CN-4315709"
encounter_date = "2026-01-02"
chief_complaint = "chest pain"
[[assessment]]
problem = "diabetes"
icd10 = "I12"

[[assessment]]
problem = "diabetes"
icd10 = "K62"

[patient]
mrn = "MRN-534874"
age = 89
gender = "M"

[vitals]
bp = "165/61"
hr = 112
temp_f = 99.4


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

[User] Produce a XML document for a prescription.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<prescription>
<rx_id>RX-5973418</rx_id>
<patient_mrn>MRN-615844</patient_mrn>
<prescriber>Brian Erickson</prescriber>
<date>2026-01-01</date>
<medications>
<name>Lisinopril</name>
<dosage>20mg</dosage>
<frequency>TID</frequency>
<quantity>60</quantity>
</medications>
<medications>
<name>Metformin</name>
<dosage>20mg</dosage>
<frequency>daily</frequency>
<quantity>60</quantity>
</medications>
</prescription>


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

[User] Output sales analytics as CSV.

[Assistant]
Approach:
1. Task: Create sales analytics in CSV
2. Complexity: 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,channels,citations,funding_source,keywords,paper_id,period,publication_doi,publication_venue,publication_year,title,top_products,total_revenue,units_sold
,,"[{""name"": ""online"", ""revenue"": 1417680, ""growth"": 41.94}, {""name"": ""wholesale"", ""revenue"": 3176166, ",,,,,June 2021,,,,,"[{""sku"": ""SKU-9002"", ""sales"": 412560}, {""sku"": ""SKU-3918"", ""sales"": 426996}, {""sku"": ""SKU-1618"", ""sa",8223229,11543
Four natural college. Civil interest choice sort fly forget.,"[{""name"": ""Jessica Cox DDS"", ""affiliation"": ""Dennis, Williams and Keller"", ""email"": ""cathy94@example",,416,None,"[""rest"", ""soldier"", ""certain""]",arXiv:2023.74281,,10.6449/YJJM,Nature,2021,User-friendly upward-trending superstructure,,,
Into attention morning finish entire follow gun. Where political under public degree year first.,"[{""name"": ""Ricky Santana"", ""affiliation"": ""Flores, Smith and Anderson"", ""email"": ""kimberlywhite@exam",,114,"Jones, Beck and Ross","[""rest"", ""state"", ""my"", ""base"", ""teacher""]",arXiv:2024.87173,,10.1135/lGbG,Nature,2022,Persistent neutral contingency,,,


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

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

[Assistant]
Approach:
1. Task: Create research paper 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:
paper_id = "arXiv:2022.79764"
title = "Progressive exuding adapter"
abstract = "Win both purpose hour professor table."
keywords = [ "office", "during", "more", "apply", "program",]
citations = 258
funding_source = "Espinoza, Khan and Lowe"
[[authors]]
name = "Gary Johnson"
affiliation = "Wolf Group"
email = "jamie40@example.org"

[[authors]]
name = "Lisa Ortega"
affiliation = "Wells, Flores and Cooper"
email = "nicholas25@example.com"

[[authors]]
name = "Kimberly Alvarez"
affiliation = "Lewis-Hunt"
email = "bookersteven@example.com"

[publication]
venue = "Nature"
year = 2023
doi = "10.1780/NyHo"


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

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

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

Output:
abstract,authors,citations,funding_source,keywords,paper_id,publication_doi,publication_venue,publication_year,title
Full with spend role first drive. Want man instead today bed hand character.,"[{""name"": ""Clayton Martinez"", ""affiliation"": ""Flores, Levy and Farmer"", ""email"": ""kathy80@example.or",395,None,"[""bed"", ""very"", ""population""]",arXiv:2023.99214,10.4640/CkqB,Nature,2023,Integrated mobile database
Dark bag while. Color red trade. Foot attorney miss treat. Accept my daughter theory.,"[{""name"": ""Courtney Clark"", ""affiliation"": ""Hahn, Smith and Shepard"", ""email"": ""michele42@example.co",169,"Johnson, Castaneda and West","[""more"", ""huge"", ""just""]",arXiv:2023.61593,10.9554/kndo,Science,2020,Upgradable 5thgeneration functionalities
Industry operation TV energy. Senior character maintain hear sing foreign. Another dark build whom n,"[{""name"": ""Heidi Jacobs"", ""affiliation"": ""Thomas LLC"", ""email"": ""kgibbs@example.org""}, {""name"": ""Sus",211,None,"[""decide"", ""change"", ""wife"", ""book""]",arXiv:2023.50090,10.5784/kYDl,Science,2020,Up-sized bifurcated monitoring


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

[User]
Transform this XML data into TOML format:
<?xml version="1.0" encoding="UTF-8"?>
<student_assessment>
<assessment_id>ASMT-948175</assessment_id>
<student_id>STU-160858</student_id>
<course_id>CRS-5368</course_id>
<type>assignment</type>
<date>2026-01-03</date>
<scores>
<question>1</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>3</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>5</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>3</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>9</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>89</total_score>
<percentage>96.29</percentage>
<grade>B</grade>
</student_assessment>

[Assistant]
Approach:
1. Task: Convert student assessment from XML 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:
assessment_id = "ASMT-948175"
student_id = "STU-160858"
course_id = "CRS-5368"
type = "assignment"
date = "2026-01-03"
total_score = 89
percentage = 96.29
grade = "B"
[[scores]]
question = 1
points_earned = 1
points_possible = 10

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

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

[[scores]]
question = 4
points_earned = 9
points_possible = 10

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

[[scores]]
question = 6
points_earned = 9
points_possible = 10

[[scores]]
question = 7
points_earned = 1
points_possible = 10

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

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


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

[User] Create a TOML representation of financial report.

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

Output:
company = "Richard Ltd"
ticker = "XHCL"
quarter = "Q4 2020"
revenue = 71255223
expenses = 54916122
net_income = 1190834
eps = 4.63

[metrics]
profit_margin = 14.39
roe = 19.33