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

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

[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
List floor whatever fly. Play represent five my. Stuff area push other begin team. Wind leg require ,61,3006,53,"[""#study"", ""#able"", ""#week""]",instagram,POST-33796851,2026-01-07T13:51:26.038556,aa32cdd3-72c6-4e38-bd5e-ff3918321d73,qtownsend
Build answer current authority billion suffer. As mission home thank. Friend student home physical s,113,5722,279,"[""#face"", ""#attack"", ""#street"", ""#environment""]",instagram,POST-51713088,2026-01-07T13:51:26.040314,59ccac62-719d-4537-be96-594192d662a1,maryochoa
"Miss various understand before. Often before city benefit.
Could star foreign you general woman. Typ",384,4665,653,"[""#cause"", ""#evidence"", ""#herself"", ""#believe""]",twitter,POST-60828711,2026-01-07T13:51:26.040835,9ae4eb9b-952f-4899-ac97-1beb8c83fc8a,mlambert
Teacher want heavy human agent impact beat too. Black cost yourself whole everyone yeah usually all.,459,3908,195,"[""#environmental"", ""#machine""]",twitter,POST-21374621,2026-01-07T13:51:26.041411,a40f76f6-f99e-43b7-b2de-81d70e39d714,hunterwilliam
Watch east likely network explain decision into. Rest catch low process president. Quickly best even,2,451,213,"[""#occur"", ""#start"", ""#third"", ""#light""]",twitter,POST-11149049,2026-01-07T13:51:26.041921,b4c034b8-fac8-431e-8fb4-ba55aceef6c0,rthomas


[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"?>
<financial_report>
<company>Woods and Sons</company>
<ticker>ZCNM</ticker>
<quarter>Q1 2020</quarter>
<revenue>42196406</revenue>
<expenses>48284794</expenses>
<net_income>2937548</net_income>
<eps>8.84</eps>
<metrics>
<profit_margin>12.42</profit_margin>
<roe>23.86</roe>
</metrics>
</financial_report>

[Assistant]
Approach:
1. Task: Convert financial report 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:
{
  "company": "Woods and Sons",
  "ticker": "ZCNM",
  "quarter": "Q1 2020",
  "revenue": 42196406,
  "expenses": 48284794,
  "net_income": 2937548,
  "eps": 8.84,
  "metrics": {
    "profit_margin": 12.42,
    "roe": 23.86
  }
}


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

[User] Output lab result as CSV.

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

Output:
order_date,panel,patient_mrn,result_id,results
2026-01-04,Lipid,MRN-631747,LAB-6812810,"[{""test"": ""WBC"", ""value"": 54.3, ""unit"": ""mg/dL"", ""flag"": ""high""}, {""test"": ""WBC"", ""value"": 70.8, ""un"
2026-01-04,CBC,MRN-376051,LAB-2943982,"[{""test"": ""Glucose"", ""value"": 103.2, ""unit"": ""mg/dL"", ""flag"": ""low""}, {""test"": ""Hemoglobin"", ""value"""
2026-01-06,CBC,MRN-685323,LAB-5761749,"[{""test"": ""Hemoglobin"", ""value"": 73.5, ""unit"": ""g/dL"", ""flag"": ""high""}, {""test"": ""Hemoglobin"", ""valu"
2026-01-03,Lipid,MRN-350635,LAB-7629411,"[{""test"": ""WBC"", ""value"": 177.2, ""unit"": ""mg/dL"", ""flag"": ""high""}, {""test"": ""WBC"", ""value"": 167.8, """
2026-01-05,Lipid,MRN-381814,LAB-9539281,"[{""test"": ""Hemoglobin"", ""value"": 136.1, ""unit"": ""mg/dL"", ""flag"": ""low""}, {""test"": ""Hemoglobin"", ""val"


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

[User]
Reformat the data below from JSON to XML:
{
  "product_id": "PROD-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 JSON to XML
2. Complexity: complex - 8-10 fields, 3-4 levels
3. Format rules: well-formed tags, proper nesting, escaped special chars
4. Structure: Organize data logically with appropriate nesting
5. Transform values to match the target format specifications.

Output:
<?xml version="1.0" encoding="UTF-8"?>
<product_listing>
<product_id>PROD-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 XML format. Think step-by-step, then generate syntactically perfect XML.

[User]
Transform this JSON data into XML format:
{
  "company": "Ortega-Owens",
  "ticker": "YLLB",
  "quarter": "Q3 2022",
  "revenue": 37598920,
  "expenses": 44591506,
  "net_income": 3197580,
  "eps": 1.51,
  "metrics": {
    "profit_margin": 5.54,
    "roe": 6.32
  }
}

[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>Ortega-Owens</company>
<ticker>YLLB</ticker>
<quarter>Q3 2022</quarter>
<revenue>37598920</revenue>
<expenses>44591506</expenses>
<net_income>3197580</net_income>
<eps>1.51</eps>
<metrics>
<profit_margin>5.54</profit_margin>
<roe>6.32</roe>
</metrics>
</financial_report>


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

[User]
Convert the following JSON to XML:
{
  "contract_id": "CTR-619223",
  "parties": [
    {
      "name": "Mcdaniel LLC",
      "role": "party_a"
    },
    {
      "name": "Hunt-Bowman",
      "role": "party_b"
    }
  ],
  "effective_date": "2026-01-03",
  "term_months": 21,
  "value": 87478,
  "status": "pending"
}

[Assistant]
Approach:
1. Task: Convert contract from 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"?>
<contract>
<contract_id>CTR-619223</contract_id>
<parties>
<name>Mcdaniel LLC</name>
<role>party_a</role>
</parties>
<parties>
<name>Hunt-Bowman</name>
<role>party_b</role>
</parties>
<effective_date>2026-01-03</effective_date>
<term_months>21</term_months>
<value>87478</value>
<status>pending</status>
</contract>


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

[User]
Convert the following CSV to YAML:
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-817642,,CRS-8326,,2026-01-03,A,,,,,56.31,,"[{""question"": 1, ""points_earned"": 9, ""points_possible"": 10}, {""question"": 2, ""points_earned"": 10, ""p",STU-222420,,,60,assignment
,NRJ296,CRS-1861,3,,,40,30,30,Tamara Wright,,"[{""week"": 1, ""topic"": ""throw""}, {""week"": 2, ""topic"": ""control""}, {""week"": 3, ""topic"": ""seven""}, {""we",,,Fall 2022,Fully-configurable analyzing function 101,,
,NPZ278,CRS-2574,4,,,40,30,30,Jasmine Riley,,"[{""week"": 1, ""topic"": ""year""}, {""week"": 2, ""topic"": ""become""}, {""week"": 3, ""topic"": ""once""}, {""week""",,,Fall 2022,Ergonomic foreground productivity 101,,
,DTG291,CRS-8612,3,,,40,30,30,Sarah Ross,,"[{""week"": 1, ""topic"": ""training""}, {""week"": 2, ""topic"": ""perhaps""}, {""week"": 3, ""topic"": ""term""}, {""",,,Fall 2023,Profound systemic parallelism 101,,
,PAM117,CRS-3691,3,,,40,30,30,Christine Harris PhD,,"[{""week"": 1, ""topic"": ""great""}, {""week"": 2, ""topic"": ""shoulder""}, {""week"": 3, ""topic"": ""pay""}, {""wee",,,Fall 2023,Team-oriented context-sensitive focus group 101,,

[Assistant]
Approach:
1. Task: Convert student assessment 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:
assessment_id: ASMT-817642
student_id: STU-222420
course_id: CRS-8326
type: assignment
date: '2026-01-03'
scores:
- question: 1
  points_earned: 9
  points_possible: 10
- question: 2
  points_earned: 10
  points_possible: 10
- question: 3
  points_earned: 0
  points_possible: 10
- question: 4
  points_earned: 2
  points_possible: 10
- question: 5
  points_earned: 7
  points_possible: 10
- question: 6
  points_earned: 4
  points_possible: 10
- question: 7
  points_earned: 10
  points_possible: 10
- question: 8
  points_earned: 7
  points_possible: 10
total_score: 60
percentage: 56.31
grade: A


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

[User]
Convert the following XML to CSV:
<?xml version="1.0" encoding="UTF-8"?>
<student_assessment>
<assessment_id>ASMT-577861</assessment_id>
<student_id>STU-664280</student_id>
<course_id>CRS-8099</course_id>
<type>exam</type>
<date>2026-01-06</date>
<scores>
<question>1</question>
<points_earned>7</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>5</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>6</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>3</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>0</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>52</total_score>
<percentage>81.98</percentage>
<grade>B</grade>
</student_assessment>

[Assistant]
Approach:
1. Task: Convert student assessment 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:
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-577861,,CRS-8099,,2026-01-06,B,,,,,81.98,,"[{""question"": 1, ""points_earned"": 7, ""points_possible"": 10}, {""question"": 2, ""points_earned"": 0, ""po",STU-664280,,,52,exam
,KAD248,CRS-2873,4,,,40,30,30,Michael Ortega,,"[{""week"": 1, ""topic"": ""name""}, {""week"": 2, ""topic"": ""decision""}, {""week"": 3, ""topic"": ""of""}, {""week""",,,Spring 2021,Profit-focused discrete array 101,,
,FLZ157,CRS-4989,4,,,40,30,30,Kimberly Ramirez,,"[{""week"": 1, ""topic"": ""remember""}, {""week"": 2, ""topic"": ""who""}, {""week"": 3, ""topic"": ""someone""}, {""w",,,Fall 2023,Exclusive scalable protocol 101,,


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

[User] Generate api specification data in JSON format.

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

Output:
{
  "openapi": "3.0.0",
  "info": {
    "title": "Secured well-modulated policy API",
    "version": "1.0.0"
  },
  "paths": {
    "/article": {
      "get": {
        "summary": "During certainly full.",
        "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 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: 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:
abstract,authors,citations,funding_source,info_title,info_version,keywords,openapi,paper_id,paths_/air_get_parameters,paths_/air_get_responses_200_description,paths_/air_get_responses_400_description,paths_/air_get_summary,publication_doi,publication_venue,publication_year,title
,,,,Pre-emptive interactive encryption API,1.0.0,,3.0.0,,"[{""name"": ""param0"", ""in"": ""query"", ""type"": ""string""}]",Success,Bad Request,Final democratic whatever event director guy.,,,,
Let two Republican security avoid through speak hospital. Present natural anyone.,"[{""name"": ""John Fisher"", ""affiliation"": ""Wall Inc"", ""email"": ""alyssacordova@example.com""}, {""name"": ",397,None,,,"[""rise"", ""real"", ""democratic"", ""game""]",,arXiv:2021.67333,,,,,10.2142/hVzj,Nature,2020,Automated modular knowledgebase
"Season free data while Mr. Seek fire left study miss bar.
Behind from help. Game capital mention wou","[{""name"": ""Jacqueline Boyd"", ""affiliation"": ""Benjamin, Warren and Graves"", ""email"": ""matthewpalmer@e",64,None,,,"[""onto"", ""feeling"", ""and"", ""society"", ""look""]",,arXiv:2024.13771,,,,,10.9030/ufHF,Nature,2024,Re-engineered real-time installation
Chair he thousand. Type market market good clearly least everybody. World factor matter join.,"[{""name"": ""Michael Dean"", ""affiliation"": ""Smith-Jones"", ""email"": ""patrickking@example.net""}, {""name""",350,None,,,"[""begin"", ""trip"", ""apply"", ""produce""]",,arXiv:2021.44762,,,,,10.4365/ktLI,Science,2020,Programmable cohesive project


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

[User] Generate api specification data in TOML format.

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

Output:
openapi = "3.0.0"

[info]
title = "Cross-group bottom-line algorithm API"
version = "1.0.0"

[paths."/rule".get]
summary = "Center available level environment per away author"
[[paths."/rule".get.parameters]]
name = "param0"
in = "query"
type = "string"

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

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

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


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<product_listing>
<product_id>PROD-651261</product_id>
<name>Cross-platform scalable protocol</name>
<category>clothing</category>
<price>855.77</price>
<currency>USD</currency>
<stock>343</stock>
<is_available>True</is_available>
<rating>3.23</rating>
<reviews>830</reviews>
<specs>
<weight_kg>21.29</weight_kg>
<dimensions>84x20x91cm</dimensions>
</specs>
</product_listing>

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

Output:
{
  "product_id": "PROD-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 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"?>
<prescription>
<rx_id>RX-5160762</rx_id>
<patient_mrn>MRN-568012</patient_mrn>
<prescriber>Linda Gonzalez</prescriber>
<date>2026-01-06</date>
<medications>
<name>Lisinopril</name>
<dosage>20mg</dosage>
<frequency>TID</frequency>
<quantity>30</quantity>
</medications>
<medications>
<name>Atorvastatin</name>
<dosage>5mg</dosage>
<frequency>daily</frequency>
<quantity>60</quantity>
</medications>
</prescription>

[Assistant]
Approach:
1. Task: Convert prescription 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:
{
  "rx_id": "RX-5160762",
  "patient_mrn": "MRN-568012",
  "prescriber": "Linda Gonzalez",
  "date": "2026-01-06",
  "medications": [
    {
      "name": "Lisinopril",
      "dosage": "20mg",
      "frequency": "TID",
      "quantity": 30
    },
    {
      "name": "Atorvastatin",
      "dosage": "5mg",
      "frequency": "daily",
      "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 contract.

[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-544771",
  "parties": [
    {
      "name": "Prince-Finley",
      "role": "party_a"
    },
    {
      "name": "Stone LLC",
      "role": "party_b"
    }
  ],
  "effective_date": "2026-01-02",
  "term_months": 52,
  "value": 394049,
  "status": "active"
}


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<error_log>
<error_id>a016c8d2-6aba-435a-ab46-60ac8aacf0a5</error_id>
<timestamp>2026-01-07T13:51:26.006823</timestamp>
<level>CRITICAL</level>
<service>currentService</service>
<message>Well nation stay number now but.</message>
<stack_trace>at daughter.py:364</stack_trace>
<stack_trace>at same.py:66</stack_trace>
<context>
<user_id>432ef3ee-7f2b-4bc8-a8a7-159d64a89fd5</user_id>
<request_id>4ed63374-fc09-4101-b987-4a8ee575fee3</request_id>
</context>
</error_log>


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

[User]
Convert the following TOML to CSV:
contract_id = "CTR-123472"
effective_date = "2026-01-06"
term_months = 59
value = 388976
status = "pending"
[[parties]]
name = "Palmer-White"
role = "party_a"

[[parties]]
name = "Rodriguez-Moore"
role = "party_b"

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

Output:
contract_id,effective_date,parties,status,term_months,value
CTR-123472,2026-01-06,"[{""name"": ""Palmer-White"", ""role"": ""party_a""}, {""name"": ""Rodriguez-Moore"", ""role"": ""party_b""}]",pending,59,388976
CTR-290000,2026-01-01,"[{""name"": ""Blankenship Ltd"", ""role"": ""party_a""}, {""name"": ""Johnson-Lang"", ""role"": ""party_b""}]",pending,57,624226
CTR-574121,2026-01-05,"[{""name"": ""Shannon, Moore and Brady"", ""role"": ""party_a""}, {""name"": ""Robertson-Rivera"", ""role"": ""part",active,22,591907
CTR-721711,2026-01-05,"[{""name"": ""Weaver, Anderson and Saunders"", ""role"": ""party_a""}, {""name"": ""Lee-Baker"", ""role"": ""party_",active,36,932554


[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>
<encounter_date>2026-01-03</encounter_date>
<note_id>CN-2646438</note_id>
<patient>
<mrn>MRN-771263</mrn>
<age>41</age>
<gender>M</gender>
</patient>
</clinical_note>

[Assistant]
Approach:
1. Task: Convert clinical note 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:
{
  "encounter_date": "2026-01-03",
  "note_id": "CN-2646438",
  "patient": {
    "mrn": "MRN-771263",
    "age": 41,
    "gender": "M"
  }
}


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

[User]
Convert the following TOML to CSV:
note_id = "CN-8348908"
encounter_date = "2026-01-06"
chief_complaint = "fever"
[[assessment]]
problem = "diabetes"
icd10 = "J60"

[[assessment]]
problem = "diabetes"
icd10 = "K69"

[[assessment]]
problem = "hypertension"
icd10 = "J80"

[patient]
mrn = "MRN-109351"
age = 84
gender = "F"

[vitals]
bp = "157/81"
hr = 101
temp_f = 97.1

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

Output:
assessment,chief_complaint,encounter_date,note_id,patient_age,patient_gender,patient_mrn,vitals_bp,vitals_hr,vitals_temp_f
"[{""problem"": ""diabetes"", ""icd10"": ""J60""}, {""problem"": ""diabetes"", ""icd10"": ""K69""}, {""problem"": ""hype",fever,2026-01-06,CN-8348908,84,F,MRN-109351,157/81,101,97.1
"[{""problem"": ""diabetes"", ""icd10"": ""I41""}, {""problem"": ""hypertension"", ""icd10"": ""J17""}, {""problem"": """,chest pain,2026-01-04,CN-6954593,89,M,MRN-446489,175/61,97,102.9
"[{""problem"": ""hypertension"", ""icd10"": ""K84""}, {""problem"": ""diabetes"", ""icd10"": ""I69""}, {""problem"": """,fever,2026-01-01,CN-5790941,28,M,MRN-576056,155/63,87,97.5


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

[User] Output lab result as YAML.

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

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


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

[User]
Convert the following XML to TOML:
<?xml version="1.0" encoding="UTF-8"?>
<error_log>
<error_id>91d16731-5e7b-4a47-8285-7a54d79d3b76</error_id>
<timestamp>2026-01-07T13:51:25.635487</timestamp>
<level>WARNING</level>
<service>AmericanService</service>
<message>Drug sell certainly major total.</message>
<stack_trace>at although.py:151</stack_trace>
<stack_trace>at mission.py:443</stack_trace>
<context>
<user_id>11d85442-7276-4e30-9249-06df8089bd39</user_id>
<request_id>f3cc0b9c-f4db-4c9d-bea8-f49774b1a7e6</request_id>
</context>
</error_log>

[Assistant]
Approach:
1. Task: Convert error log 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:
error_id = "91d16731-5e7b-4a47-8285-7a54d79d3b76"
timestamp = "2026-01-07T13:51:25.635487"
level = "WARNING"
service = "AmericanService"
message = "Drug sell certainly major total."
stack_trace = [ "at although.py:151", "at mission.py:443",]

[context]
user_id = "11d85442-7276-4e30-9249-06df8089bd39"
request_id = "f3cc0b9c-f4db-4c9d-bea8-f49774b1a7e6"


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

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

[Assistant]
Approach:
1. Task: Create api specification in JSON
2. Complexity: 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:
{
  "paths": {
    "/population": {
      "get": {
        "summary": "Lead room develop man according street century.",
        "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"
          }
        }
      }
    }
  },
  "info": {
    "title": "Ameliorated radical initiative API",
    "version": "1.0.0"
  },
  "openapi": "3.0.0"
}


[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: September 2022
total_revenue: 4880286
units_sold: 74173
channels:
- name: retail
  revenue: 2000312
  growth: 0.96
- name: wholesale
  revenue: 3751658
  growth: -3.19
top_products:
- sku: SKU-6977
  sales: 264067
- sku: SKU-7032
  sales: 443161
- sku: SKU-1793
  sales: 209512


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

[User] Generate customer review data in TOML format.

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

Output:
review_id = "REV-5650887"
product_id = "PROD-601157"
user_id = "ac7725ae-2567-44d1-8d40-a64432b9801b"
rating = 3
title = "Personal order single check off but my."
content = "Key Mrs say because walk old certainly. Product figure event choice.\nSkill cut plan per side same. Between common join partner kid enter page discover."
date = "2026-01-06"
verified_purchase = true
helpful_votes = 66


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

[User]
Convert the following JSON to XML:
{
  "revenue": 81140617,
  "metrics": {
    "profit_margin": 25.46,
    "roe": 20.6
  },
  "quarter": "Q1 2021"
}

[Assistant]
Approach:
1. Task: Convert financial report 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"?>
<financial_report>
<revenue>81140617</revenue>
<metrics>
<profit_margin>25.46</profit_margin>
<roe>20.6</roe>
</metrics>
<quarter>Q1 2021</quarter>
</financial_report>


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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<transaction_record>
<txn_id>TXN-30876983</txn_id>
<customer_id>b5aca191-66fe-49e0-85ce-2d363d5ef454</customer_id>
<timestamp>2026-01-07T13:51:26.163076</timestamp>
<items>
<sku>SKU-56664</sku>
<qty>2</qty>
<price>285.83</price>
</items>
<items>
<sku>SKU-25305</sku>
<qty>1</qty>
<price>45.15</price>
</items>
<items>
<sku>SKU-78820</sku>
<qty>4</qty>
<price>47.49</price>
</items>
<subtotal>199.93</subtotal>
<tax>118.13</tax>
<total>913.78</total>
<payment_method>apple_pay</payment_method>
</transaction_record>


[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: 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:
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-549878,,CRS-6692,,2026-01-01,C,,,,,54.38,,"[{""question"": 1, ""points_earned"": 7, ""points_possible"": 10}, {""question"": 2, ""points_earned"": 1, ""po",STU-264168,,,70,assignment
,KQK318,CRS-7446,4,,,40,30,30,Gerald Morris,,"[{""week"": 1, ""topic"": ""economic""}, {""week"": 2, ""topic"": ""thing""}, {""week"": 3, ""topic"": ""one""}, {""wee",,,Spring 2024,Mandatory real-time capability 101,,
,NPQ465,CRS-7705,4,,,40,30,30,Justin Gibson,,"[{""week"": 1, ""topic"": ""black""}, {""week"": 2, ""topic"": ""sign""}, {""week"": 3, ""topic"": ""table""}, {""week""",,,Spring 2020,User-friendly asynchronous database 101,,


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

[User]
Transform this JSON data into XML format:
{
  "note_id": "CN-5754690",
  "patient": {
    "mrn": "MRN-521303",
    "age": 32,
    "gender": "M"
  },
  "encounter_date": "2026-01-05",
  "chief_complaint": "fever",
  "vitals": {
    "bp": "101/104",
    "hr": 85,
    "temp_f": 99.3
  },
  "assessment": [
    {
      "problem": "diabetes",
      "icd10": "K80"
    }
  ]
}

[Assistant]
Approach:
1. Task: Convert clinical note 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"?>
<clinical_note>
<note_id>CN-5754690</note_id>
<patient>
<mrn>MRN-521303</mrn>
<age>32</age>
<gender>M</gender>
</patient>
<encounter_date>2026-01-05</encounter_date>
<chief_complaint>fever</chief_complaint>
<vitals>
<bp>101/104</bp>

85

<temp_f>99.3</temp_f>
</vitals>
<assessment>
<problem>diabetes</problem>
<icd10>K80</icd10>
</assessment>
</clinical_note>


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

[User] Create a XML representation of 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-9456</course_id>
KDS432
<title>Multi-channeled local complexity 101</title>
<instructor>Kenneth Rogers</instructor>
<credits>3</credits>
<term>Fall 2020</term>
<schedule>
<week>1</week>
<topic>activity</topic>
</schedule>
<schedule>
<week>2</week>
<topic>foot</topic>
</schedule>
<schedule>
<week>3</week>
<topic>reason</topic>
</schedule>
<schedule>
<week>4</week>
<topic>rule</topic>
</schedule>
<schedule>
<week>5</week>
<topic>paper</topic>
</schedule>
<schedule>
<week>6</week>
<topic>current</topic>
</schedule>
<schedule>
<week>7</week>
<topic>scene</topic>
</schedule>
<schedule>
<week>8</week>
<topic>later</topic>
</schedule>
<schedule>
<week>9</week>
<topic>choice</topic>
</schedule>
<schedule>
<week>10</week>
<topic>box</topic>
</schedule>
<grading>
<homework>30</homework>
<midterm>30</midterm>
<final>40</final>
</grading>
</course_syllabus>


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

[User] Produce a YAML document for a prescription.

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

Output:
rx_id: RX-5336793
patient_mrn: MRN-644295
prescriber: Thomas Ponce
date: '2026-01-03'
medications:
- name: Atorvastatin
  dosage: 5mg
  frequency: BID
  quantity: 90
- name: Atorvastatin
  dosage: 5mg
  frequency: daily
  quantity: 30
- name: Atorvastatin
  dosage: 10mg
  frequency: BID
  quantity: 30


[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: 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"?>
<clinical_note>
<assessment>
<problem>diabetes</problem>
<icd10>I24</icd10>
</assessment>
<encounter_date>2026-01-06</encounter_date>
<patient>
<mrn>MRN-470382</mrn>
<age>61</age>
<gender>F</gender>
</patient>
<note_id>CN-3244099</note_id>
<vitals>
<bp>158/77</bp>

112

<temp_f>99.5</temp_f>
</vitals>
</clinical_note>


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

[User] Create a XML representation of error log.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<error_log>
<error_id>042db0a1-c9b1-49a9-9d69-5247a8c47159</error_id>
<timestamp>2026-01-07T13:51:27.377057</timestamp>
<level>ERROR</level>
<service>whomService</service>
<message>Each reality trip red enough tough common.</message>
<stack_trace>at note.py:398</stack_trace>
<stack_trace>at purpose.py:452</stack_trace>
<stack_trace>at onto.py:106</stack_trace>
<stack_trace>at member.py:439</stack_trace>
<context>
<user_id>70c0c786-0e43-42b2-8ec7-e975f39a71f7</user_id>
<request_id>95ca942a-a33a-413f-b1a1-a21e12fa0f30</request_id>
</context>
</error_log>


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

[User] Generate financial report data in CSV format.

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

Output:
company,eps,expenses,metrics_profit_margin,metrics_roe,net_income,quarter,revenue,ticker
Dunn-Byrd,9.56,58548919,,,,Q3 2022,,ATGQ
"Montgomery, Perry and Powell",4.34,76014648,5.32,5.29,1190040,Q3 2023,5010352,OJGA
"Gonzalez, Fuller and Brown",5.78,17955256,22.51,6.52,6153147,Q1 2021,52144622,EYMF


[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-3793814",
  "patient_mrn": "MRN-247204",
  "order_date": "2026-01-03",
  "panel": "CBC",
  "results": [
    {
      "test": "Hemoglobin",
      "value": 188.2,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "WBC",
      "value": 197.7,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "Glucose",
      "value": 196.4,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "Glucose",
      "value": 193.9,
      "unit": "g/dL",
      "flag": "high"
    },
    {
      "test": "Glucose",
      "value": 197.2,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "Hemoglobin",
      "value": 109.5,
      "unit": "mg/dL",
      "flag": "normal"
    }
  ]
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<lab_result>
<result_id>LAB-3793814</result_id>
<patient_mrn>MRN-247204</patient_mrn>
<order_date>2026-01-03</order_date>
<panel>CBC</panel>
<results>
<test>Hemoglobin</test>
<value>188.2</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>WBC</test>
<value>197.7</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Glucose</test>
<value>196.4</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Glucose</test>
<value>193.9</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Glucose</test>
<value>197.2</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>109.5</value>
<unit>mg/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] Output research paper as JSON.

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

Output:
{
  "authors": [
    {
      "name": "Laura White",
      "affiliation": "Coleman, Johnson and Ross",
      "email": "jillcollins@example.com"
    },
    {
      "name": "Sarah Woods",
      "affiliation": "Durham, Thompson and White",
      "email": "sbeard@example.com"
    }
  ],
  "title": "Seamless cohesive projection",
  "funding_source": null,
  "abstract": "Middle several interesting move. Wrong represent guess threat. Once paper represent."
}


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<social_media_post>
<post_id>POST-61935008</post_id>
<platform>instagram</platform>
<user_id>ecd9585e-2adb-45f4-adda-e91c5f4f7ebe</user_id>
<username>halezachary</username>
<content>Treat second sing development scientist particularly their. Like question recently line top. Resource movie enter involve order stop region.</content>
<timestamp>2026-01-07T13:51:25.597395</timestamp>
<hashtags>#box</hashtags>
<hashtags>#speak</hashtags>
<hashtags>#reason</hashtags>
<engagement>
<likes>4027</likes>
<shares>604</shares>
<comments>194</comments>
</engagement>
</social_media_post>


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

[User] Output financial report as JSON.

[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": 65628233,
  "eps": 5.75,
  "quarter": "Q2 2023",
  "revenue": 73745517,
  "net_income": 6367407
}


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<review_id>REV-8075236</review_id>
<product_id>PROD-326180</product_id>
<user_id>e70c9373-b1ad-41a5-8939-e3c28041d8f5</user_id>
<rating>4</rating>
<title>Most teacher Mrs system watch.</title>
<content>Address music major. Magazine three about. Security ready result improve.
Hand other collection name wife remain. Speech perhaps newspaper. Talk place third about writer billion physical.</content>
<date>2026-01-03</date>
<verified_purchase>False</verified_purchase>
<helpful_votes>50</helpful_votes>
</customer_review>

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

Output:
{
  "review_id": "REV-8075236",
  "product_id": "PROD-326180",
  "user_id": "e70c9373-b1ad-41a5-8939-e3c28041d8f5",
  "rating": 4,
  "title": "Most teacher Mrs system watch.",
  "content": "Address music major. Magazine three about. Security ready result improve.\nHand other collection name wife remain. Speech perhaps newspaper. Talk place third about writer billion physical.",
  "date": "2026-01-03",
  "verified_purchase": false,
  "helpful_votes": 50
}


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

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

[Assistant]
Approach:
1. Task: Create course syllabus in CSV
2. Complexity: 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:
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
SJG454,CRS-9667,4,40,30,30,Stephanie Camacho,"[{""week"": 1, ""topic"": ""with""}, {""week"": 2, ""topic"": ""hour""}, {""week"": 3, ""topic"": ""continue""}, {""wee",Fall 2023,Virtual dedicated monitoring 101
UNJ214,CRS-5398,3,40,30,30,Emily Ross,"[{""week"": 1, ""topic"": ""none""}, {""week"": 2, ""topic"": ""term""}, {""week"": 3, ""topic"": ""rich""}, {""week"": ",Spring 2022,Realigned national utilization 101
DLM281,CRS-3875,3,40,30,30,Angela Elliott,"[{""week"": 1, ""topic"": ""inside""}, {""week"": 2, ""topic"": ""table""}, {""week"": 3, ""topic"": ""part""}, {""week",Fall 2024,Synchronized background monitoring 101
ZNT294,CRS-7432,3,40,30,30,Elizabeth Herrera,"[{""week"": 1, ""topic"": ""face""}, {""week"": 2, ""topic"": ""clear""}, {""week"": 3, ""topic"": ""current""}, {""wee",Fall 2023,Cloned zero-defect approach 101


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

[User]
Convert the following CSV to YAML:
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
"Discuss by analysis article.
As if wish. Cold answer adult forward radio Mrs impact. Leader next wit","[{""name"": ""Lisa Miller"", ""affiliation"": ""Hale, Chambers and Ramirez"", ""email"": ""mathewjohnson@exampl",,200,None,"[""whose"", ""us"", ""reflect"", ""pay""]",arXiv:2020.48127,,10.5218/sptw,Cell,2024,Function-based systematic adapter,,,
Again specific nothing provide career standard after. Dark as bring pretty state tax leave.,"[{""name"": ""Jonathan Mcintyre"", ""affiliation"": ""Barton, Nichols and Salas"", ""email"": ""candace89@examp",,12,None,"[""subject"", ""drug"", ""lead"", ""wonder"", ""American""]",arXiv:2024.64974,,10.5311/rEMu,Science,2020,Realigned upward-trending open system,,,

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

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


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

[User] Generate sales analytics data in YAML format.

[Assistant]
Approach:
1. Task: Create sales analytics 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:
period: March 2022
total_revenue: 6503980
units_sold: 7670
channels:
- name: retail
  revenue: 3279241
  growth: 22.76
- name: wholesale
  revenue: 1469640
  growth: 16.07
top_products:
- sku: SKU-8081
  sales: 71747
- sku: SKU-8211
  sales: 475825
- sku: SKU-4565
  sales: 485553


[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:
{
  "verified_purchase": true,
  "title": "Country especially hand.",
  "review_id": "REV-4835597",
  "product_id": "PROD-713270"
}


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<social_media_post>
<post_id>POST-59844758</post_id>
<timestamp>2026-01-07T13:51:27.358144</timestamp>
<hashtags>#population</hashtags>
<hashtags>#during</hashtags>
<hashtags>#executive</hashtags>
<hashtags>#house</hashtags>
</social_media_post>

[Assistant]
Approach:
1. Task: Convert social media post 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:
{
  "post_id": "POST-59844758",
  "timestamp": "2026-01-07T13:51:27.358144",
  "hashtags": [
    "#population",
    "#during",
    "#executive",
    "#house"
  ]
}


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

[User]
Convert the following CSV to YAML:
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-879460,,CRS-8763,,2026-01-03,B,,,,,96.07,,"[{""question"": 1, ""points_earned"": 1, ""points_possible"": 10}, {""question"": 2, ""points_earned"": 4, ""po",STU-948921,,,83,quiz
,DYC197,CRS-3929,4,,,40,30,30,Nicholas Diaz,,"[{""week"": 1, ""topic"": ""like""}, {""week"": 2, ""topic"": ""town""}, {""week"": 3, ""topic"": ""and""}, {""week"": 4",,,Spring 2022,Ameliorated content-based capacity 101,,
,CON455,CRS-7490,3,,,40,30,30,Richard Carpenter,,"[{""week"": 1, ""topic"": ""knowledge""}, {""week"": 2, ""topic"": ""actually""}, {""week"": 3, ""topic"": ""ever""}, ",,,Fall 2024,Devolved mission-critical parallelism 101,,
,NPX130,CRS-8831,3,,,40,30,30,Carolyn Sloan,,"[{""week"": 1, ""topic"": ""others""}, {""week"": 2, ""topic"": ""computer""}, {""week"": 3, ""topic"": ""far""}, {""we",,,Fall 2024,Universal maximized firmware 101,,
,UKF187,CRS-3457,3,,,40,30,30,Lisa Moore,,"[{""week"": 1, ""topic"": ""under""}, {""week"": 2, ""topic"": ""probably""}, {""week"": 3, ""topic"": ""candidate""},",,,Fall 2022,Balanced disintermediate task-force 101,,

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

Output:
assessment_id: ASMT-879460
student_id: STU-948921
course_id: CRS-8763
type: quiz
date: '2026-01-03'
scores:
- question: 1
  points_earned: 1
  points_possible: 10
- question: 2
  points_earned: 4
  points_possible: 10
- question: 3
  points_earned: 7
  points_possible: 10
- question: 4
  points_earned: 3
  points_possible: 10
- question: 5
  points_earned: 5
  points_possible: 10
- question: 6
  points_earned: 2
  points_possible: 10
- question: 7
  points_earned: 6
  points_possible: 10
- question: 8
  points_earned: 9
  points_possible: 10
total_score: 83
percentage: 96.07
grade: B


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

[User]
Reformat the data below from JSON to XML:
{
  "period": "February 2020",
  "total_revenue": 2007174,
  "units_sold": 24558,
  "channels": [
    {
      "name": "online",
      "revenue": 235807,
      "growth": 46.03
    },
    {
      "name": "wholesale",
      "revenue": 4419318,
      "growth": 24.35
    }
  ],
  "top_products": [
    {
      "sku": "SKU-6554",
      "sales": 258652
    },
    {
      "sku": "SKU-8652",
      "sales": 200091
    },
    {
      "sku": "SKU-9581",
      "sales": 65110
    }
  ]
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<sales_analytics>
<period>February 2020</period>
<total_revenue>2007174</total_revenue>
<units_sold>24558</units_sold>
<channels>
<name>online</name>
<revenue>235807</revenue>
<growth>46.03</growth>
</channels>
<channels>
<name>wholesale</name>
<revenue>4419318</revenue>
<growth>24.35</growth>
</channels>
<top_products>
<sku>SKU-6554</sku>
<sales>258652</sales>
</top_products>
<top_products>
<sku>SKU-8652</sku>
<sales>200091</sales>
</top_products>
<top_products>
<sku>SKU-9581</sku>
<sales>65110</sales>
</top_products>
</sales_analytics>


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

[User]
Convert the following JSON to XML:
{
  "note_id": "CN-6709459",
  "patient": {
    "mrn": "MRN-104418",
    "age": 50,
    "gender": "M"
  },
  "encounter_date": "2026-01-03",
  "chief_complaint": "fever",
  "vitals": {
    "bp": "143/96",
    "hr": 69,
    "temp_f": 101.3
  },
  "assessment": [
    {
      "problem": "diabetes",
      "icd10": "J90"
    },
    {
      "problem": "hypertension",
      "icd10": "I22"
    },
    {
      "problem": "hypertension",
      "icd10": "K97"
    }
  ]
}

[Assistant]
Approach:
1. Task: Convert clinical note 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"?>
<clinical_note>
<note_id>CN-6709459</note_id>
<patient>
<mrn>MRN-104418</mrn>
<age>50</age>
<gender>M</gender>
</patient>
<encounter_date>2026-01-03</encounter_date>
<chief_complaint>fever</chief_complaint>
<vitals>
<bp>143/96</bp>

69

<temp_f>101.3</temp_f>
</vitals>
<assessment>
<problem>diabetes</problem>
<icd10>J90</icd10>
</assessment>
<assessment>
<problem>hypertension</problem>
<icd10>I22</icd10>
</assessment>
<assessment>
<problem>hypertension</problem>
<icd10>K97</icd10>
</assessment>
</clinical_note>


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Implemented leadingedge groupware API</title>
<version>1.0.0</version>
</info>
<paths>
</reveal>
<get>
<summary>Parent dark five.</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>
<//reveal>
</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": "Implemented leadingedge groupware API",
    "version": "1.0.0"
  },
  "paths": {
    "/reveal": {
      "get": {
        "summary": "Parent dark five.",
        "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 TOML format. Think step-by-step, then generate syntactically perfect TOML.

[User] Generate course syllabus data in TOML format.

[Assistant]
Approach:
1. Task: Create course syllabus 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:
code = "GHC481"
term = "Spring 2020"
credits = 4
[[schedule]]
week = 1
topic = "table"

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

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

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

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

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

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

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

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

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

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


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

[User] Create a CSV representation of error log.

[Assistant]
Approach:
1. Task: Create error log 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:
abstract,authors,citations,context_request_id,context_user_id,error_id,funding_source,keywords,level,message,paper_id,publication_doi,publication_venue,publication_year,service,stack_trace,timestamp,title
,,,f5a78ca9-3dcc-4c14-bcea-f5b7936cdde5,9d5113f2-65b2-4f61-b9b2-2b011fc1bc1b,3ee04eb7-6a96-4708-8070-7816402d081f,,,ERROR,Base information cell production decade back.,,,,,checkService,"[""at quality.py:463"", ""at but.py:317""]",2026-01-07T13:51:26.236854,
Film child middle available east mind exist. From today drive talk low operation. Determine shake pa,"[{""name"": ""David Navarro"", ""affiliation"": ""Nicholson and Sons"", ""email"": ""william70@example.net""}, {",297,,,,Cabrera-Crane,"[""discussion"", ""record"", ""human""]",,,arXiv:2021.46647,10.5345/LoLH,Science,2022,,,,Seamless empowering customer loyalty
"Either left exist spring. Involve share take manager poor knowledge.
Understand consider college thr","[{""name"": ""Alexandra Jones"", ""affiliation"": ""Cooper Group"", ""email"": ""alex89@example.net""}, {""name"":",138,,,,None,"[""moment"", ""something"", ""thought"", ""opportunity"", ""return""]",,,arXiv:2023.74895,10.3935/gzUE,Nature,2021,,,,Object-based didactic alliance


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

[User] Create a TOML representation of transaction record.

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

Output:
txn_id = "TXN-31892506"
customer_id = "6c5d6d8e-2901-438d-be6d-be57a13ea5ab"
timestamp = "2026-01-07T13:51:25.485684"
subtotal = 692.94
tax = 100.91
total = 1647.14
payment_method = "credit_card"
[[items]]
sku = "SKU-80058"
qty = 4
price = 142.37

[[items]]
sku = "SKU-53232"
qty = 1
price = 151.54


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

[User]
Convert the following JSON to XML:
{
  "scores": [
    {
      "question": 1,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 10,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 0,
      "points_possible": 10
    }
  ],
  "grade": "C",
  "date": "2026-01-01"
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<student_assessment>
<scores>
<question>1</question>
<points_earned>8</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>4</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>3</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>4</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>8</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>10</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>4</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>0</points_earned>
<points_possible>10</points_possible>
</scores>
<grade>C</grade>
<date>2026-01-01</date>
</student_assessment>


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

[User] Create a JSON representation of prescription.

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

Output:
{
  "rx_id": "RX-9036427",
  "patient_mrn": "MRN-461250",
  "prescriber": "Zachary Berry",
  "date": "2026-01-01",
  "medications": [
    {
      "name": "Atorvastatin",
      "dosage": "5mg",
      "frequency": "daily",
      "quantity": 30
    }
  ]
}


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

[User] Generate financial report data in CSV format.

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

Output:
company,eps,expenses,metrics_profit_margin,metrics_roe,net_income,quarter,revenue,ticker
"Eaton, Mccarty and Lopez",4.82,75330506,29.61,8.93,13309525,Q3 2021,46227283,OWKB
Finley Ltd,7.61,67107658,28.73,17.77,10478107,Q2 2024,23670046,CNNM
Dickerson Group,7.93,70864690,17.87,20.07,19355080,Q2 2024,80156173,RXIB


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<prescription>
<rx_id>RX-9346457</rx_id>
<patient_mrn>MRN-685856</patient_mrn>
<prescriber>Thomas Archer</prescriber>
<date>2026-01-05</date>
<medications>
<name>Lisinopril</name>
<dosage>20mg</dosage>
<frequency>daily</frequency>
<quantity>90</quantity>
</medications>
<medications>
<name>Atorvastatin</name>
<dosage>10mg</dosage>
<frequency>BID</frequency>
<quantity>60</quantity>
</medications>
</prescription>

[Assistant]
Approach:
1. Task: Convert prescription 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:
{
  "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]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Face-to-face zero administration application API</title>
<version>1.0.0</version>
</info>
<paths>
</peace>
<get>
<summary>Feel piece low way effort action bag.</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>
<//peace>
</paths>
</api_specification>

[Assistant]
Approach:
1. Task: Convert api specification 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:
{
  "openapi": "3.0.0",
  "info": {
    "title": "Face-to-face zero administration application API",
    "version": "1.0.0"
  },
  "paths": {
    "/peace": {
      "get": {
        "summary": "Feel piece low way effort action bag.",
        "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]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<product_listing>
<is_available>True</is_available>
<rating>1.03</rating>
<category>electronics</category>
<price>302.74</price>
</product_listing>

[Assistant]
Approach:
1. Task: Convert product listing 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:
{
  "is_available": true,
  "rating": 1.03,
  "category": "electronics",
  "price": 302.74
}


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

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

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

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


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<student_assessment>
<assessment_id>ASMT-422317</assessment_id>
<student_id>STU-280699</student_id>
<course_id>CRS-7308</course_id>
<type>exam</type>
<date>2026-01-01</date>
<scores>
<question>1</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>3</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>3</question>
<points_earned>10</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>10</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>3</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>7</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>75</total_score>
<percentage>83.59</percentage>
<grade>B</grade>
</student_assessment>

[Assistant]
Approach:
1. Task: Convert student assessment 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:
{
  "assessment_id": "ASMT-422317",
  "student_id": "STU-280699",
  "course_id": "CRS-7308",
  "type": "exam",
  "date": "2026-01-01",
  "scores": [
    {
      "question": 1,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 3,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 10,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 10,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 3,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 7,
      "points_possible": 10
    }
  ],
  "total_score": 75,
  "percentage": 83.59,
  "grade": "B"
}


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

[User]
Convert the following XML to YAML:
<?xml version="1.0" encoding="UTF-8"?>
<transaction_record>
<txn_id>TXN-23430167</txn_id>
<customer_id>7fb2e914-3f0f-4c3f-abb9-ef22ed2c1064</customer_id>
<timestamp>2026-01-07T13:51:26.046328</timestamp>
<items>
<sku>SKU-63492</sku>
<qty>1</qty>
<price>90.17</price>
</items>
<items>
<sku>SKU-56350</sku>
<qty>5</qty>
<price>336.79</price>
</items>
<subtotal>152.9</subtotal>
<tax>14.6</tax>
<total>796.85</total>
<payment_method>apple_pay</payment_method>
</transaction_record>

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

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


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Robust demand-driven hub API</title>
<version>1.0.0</version>
</info>
<paths>
</finally>
<get>
<summary>Describe experience pick treatment up remain withi</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>
<//finally>
</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": "Robust demand-driven hub API",
    "version": "1.0.0"
  },
  "paths": {
    "/finally": {
      "get": {
        "summary": "Describe experience pick treatment up remain withi",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          },
          {
            "name": "param1",
            "in": "query",
            "type": "string"
          },
          {
            "name": "param2",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  }
}


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

[User] Output product listing as YAML.

[Assistant]
Approach:
1. Task: Create product listing 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:
product_id: PROD-125540
name: Universal eco-centric approach
category: books
price: 208.68
currency: USD
stock: 879
is_available: true
rating: 4.53
reviews: 925
specs:
  weight_kg: 20.35
  dimensions: 45x91x83cm


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

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

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

Output:
openapi: 3.0.0
info:
  title: Stand-alone dedicated complexity API
  version: 1.0.0
paths:
  /hear:
    get:
      summary: Chance cultural sort including high.
      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]
Transform this JSON data into XML format:
{
  "rx_id": "RX-9442688",
  "patient_mrn": "MRN-277514",
  "prescriber": "Timothy Goodman",
  "date": "2026-01-04",
  "medications": [
    {
      "name": "Metformin",
      "dosage": "20mg",
      "frequency": "TID",
      "quantity": 30
    },
    {
      "name": "Metformin",
      "dosage": "5mg",
      "frequency": "BID",
      "quantity": 30
    },
    {
      "name": "Lisinopril",
      "dosage": "5mg",
      "frequency": "TID",
      "quantity": 30
    }
  ]
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<prescription>
<rx_id>RX-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]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<course_syllabus>
<course_id>CRS-2063</course_id>
FAH301
<title>Ameliorated zero administration productivity 101</title>
<instructor>Aaron Bailey</instructor>
<credits>4</credits>
<term>Fall 2023</term>
<schedule>
<week>1</week>
<topic>health</topic>
</schedule>
<schedule>
<week>2</week>
<topic>buy</topic>
</schedule>
<schedule>
<week>3</week>
<topic>conference</topic>
</schedule>
<schedule>
<week>4</week>
<topic>late</topic>
</schedule>
<schedule>
<week>5</week>
<topic>fear</topic>
</schedule>
<schedule>
<week>6</week>
<topic>ability</topic>
</schedule>
<schedule>
<week>7</week>
<topic>control</topic>
</schedule>
<schedule>
<week>8</week>
<topic>choose</topic>
</schedule>
<schedule>
<week>9</week>
<topic>measure</topic>
</schedule>
<schedule>
<week>10</week>
<topic>social</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-2063",
  "code": "FAH301",
  "title": "Ameliorated zero administration productivity 101",
  "instructor": "Aaron Bailey",
  "credits": 4,
  "term": "Fall 2023",
  "schedule": [
    {
      "week": 1,
      "topic": "health"
    },
    {
      "week": 2,
      "topic": "buy"
    },
    {
      "week": 3,
      "topic": "conference"
    },
    {
      "week": 4,
      "topic": "late"
    },
    {
      "week": 5,
      "topic": "fear"
    },
    {
      "week": 6,
      "topic": "ability"
    },
    {
      "week": 7,
      "topic": "control"
    },
    {
      "week": 8,
      "topic": "choose"
    },
    {
      "week": 9,
      "topic": "measure"
    },
    {
      "week": 10,
      "topic": "social"
    }
  ],
  "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]
Reformat the data below from JSON to XML:
{
  "article_id": "ART-5347545",
  "headline": "Triple-buffered zero administration algorithm",
  "author": "Martha Brown",
  "published": "2026-01-05T16:28:34.342789",
  "section": "Sports",
  "content": "Have fall sing then fast research break. Bar ready eye medical school might recognize. Nice sometimes impact point white.\nTake many this never ever trip. Specific call according. We argue person federal central each.",
  "tags": [
    "line",
    "true",
    "compare",
    "for"
  ],
  "views": 96946,
  "shares": 1479
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<news_article>
<article_id>ART-5347545</article_id>
<headline>Triple-buffered zero administration algorithm</headline>
<author>Martha Brown</author>
<published>2026-01-05T16:28:34.342789</published>

Sports

<content>Have fall sing then fast research break. Bar ready eye medical school might recognize. Nice sometimes impact point white.
Take many this never ever trip. Specific call according. We argue person federal central each.</content>
<tags>line</tags>
<tags>true</tags>
<tags>compare</tags>
<tags>for</tags>
<views>96946</views>
<shares>1479</shares>
</news_article>


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

[User] Create a TOML representation of experiment result.

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

Output:
experiment_id = "EXP-956799"
title = "Effect of town on start"
conclusion = "significant"
[[results]]
metric = "efficacy"
baseline = 84.98
endpoint = 18.54
p_value = 0.3765

[[results]]
metric = "safety"
baseline = 50.71
endpoint = 79.49
p_value = 0.1783

[[results]]
metric = "safety"
baseline = 22.25
endpoint = 81.5
p_value = 0.0959

[[results]]
metric = "efficacy"
baseline = 53.32
endpoint = 58.41
p_value = 0.1807

[methodology]
design = "RCT"
sample_size = 962
duration_days = 355


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<review_id>REV-9546377</review_id>
<product_id>PROD-108034</product_id>
<user_id>d01ac4e1-ccd9-4273-9fe0-9ca6afc6af77</user_id>
<rating>4</rating>
<title>Appear speak sure list.</title>
<content>Today offer none role certain reach. Second Mr official enjoy movement turn city. Name employee early much first sit.</content>
<date>2026-01-01</date>
<verified_purchase>True</verified_purchase>
<helpful_votes>43</helpful_votes>
</customer_review>

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

Output:
{
  "review_id": "REV-9546377",
  "product_id": "PROD-108034",
  "user_id": "d01ac4e1-ccd9-4273-9fe0-9ca6afc6af77",
  "rating": 4,
  "title": "Appear speak sure list.",
  "content": "Today offer none role certain reach. Second Mr official enjoy movement turn city. Name employee early much first sit.",
  "date": "2026-01-01",
  "verified_purchase": true,
  "helpful_votes": 43
}


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

[User] Produce a JSON document for a prescription.

[Assistant]
Approach:
1. Task: Create prescription in JSON
2. Complexity: 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:
{
  "prescriber": "Melinda Black",
  "date": "2026-01-04",
  "rx_id": "RX-8618237"
}


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

[User]
Convert the following JSON to XML:
{
  "period": "September 2024",
  "total_revenue": 6726526,
  "units_sold": 45392,
  "channels": [
    {
      "name": "retail",
      "revenue": 2051641,
      "growth": 15.93
    },
    {
      "name": "wholesale",
      "revenue": 4340607,
      "growth": -6.59
    }
  ],
  "top_products": [
    {
      "sku": "SKU-7798",
      "sales": 367269
    },
    {
      "sku": "SKU-2105",
      "sales": 291023
    },
    {
      "sku": "SKU-5730",
      "sales": 275348
    }
  ]
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<sales_analytics>
<period>September 2024</period>
<total_revenue>6726526</total_revenue>
<units_sold>45392</units_sold>
<channels>
<name>retail</name>
<revenue>2051641</revenue>
<growth>15.93</growth>
</channels>
<channels>
<name>wholesale</name>
<revenue>4340607</revenue>
<growth>-6.59</growth>
</channels>
<top_products>
<sku>SKU-7798</sku>
<sales>367269</sales>
</top_products>
<top_products>
<sku>SKU-2105</sku>
<sales>291023</sales>
</top_products>
<top_products>
<sku>SKU-5730</sku>
<sales>275348</sales>
</top_products>
</sales_analytics>


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

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

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

Output:
category,content,currency,date,helpful_votes,is_available,name,price,product_id,rating,review_id,reviews,specs_dimensions,specs_weight_kg,stock,title,user_id,verified_purchase
,"Key Mrs say because walk old certainly. Product figure event choice.
Skill cut plan per side same. B",,2026-01-06,66,,,,PROD-601157,3,REV-5650887,,,,,Personal order single check off but my.,ac7725ae-2567-44d1-8d40-a64432b9801b,True
electronics,,USD,,,True,Multi-layered fault-tolerant productivity,456.19,PROD-414587,2.68,,735,85x11x53cm,47.84,222,,,
electronics,,USD,,,True,Grass-roots user-facing utilization,45.36,PROD-511891,1.02,,406,57x100x12cm,24.99,127,,,
books,,USD,,,True,Organized uniform framework,542.47,PROD-868450,4.92,,198,14x78x46cm,49.35,64,,,
electronics,,USD,,,True,Optimized 6thgeneration conglomeration,344.61,PROD-321388,4.31,,862,77x97x47cm,1.3,967,,,


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

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

[Assistant]
Approach:
1. Task: Create transaction record 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:
txn_id = "TXN-13058367"
customer_id = "852e4544-1bd4-44f1-abf0-2ff01b4a4792"
timestamp = "2026-01-07T13:51:26.835091"
subtotal = 408.33
tax = 11.32
total = 1142.29
payment_method = "paypal"
[[items]]
sku = "SKU-47822"
qty = 3
price = 237.72

[[items]]
sku = "SKU-38430"
qty = 4
price = 285.9

[[items]]
sku = "SKU-22327"
qty = 1
price = 141.71


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

[User] Create a TOML representation of lab result.

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

Output:
result_id = "LAB-3793814"
patient_mrn = "MRN-247204"
order_date = "2026-01-03"
panel = "CBC"
[[results]]
test = "Hemoglobin"
value = 188.2
unit = "g/dL"
flag = "low"

[[results]]
test = "WBC"
value = 197.7
unit = "mg/dL"
flag = "high"

[[results]]
test = "Glucose"
value = 196.4
unit = "mg/dL"
flag = "high"

[[results]]
test = "Glucose"
value = 193.9
unit = "g/dL"
flag = "high"

[[results]]
test = "Glucose"
value = 197.2
unit = "g/dL"
flag = "low"

[[results]]
test = "Hemoglobin"
value = 109.5
unit = "mg/dL"
flag = "normal"


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

[User]
Convert the following YAML to XML:
experiment_id: EXP-574681
title: Effect of anyone on society
methodology:
  design: cohort
  sample_size: 560
  duration_days: 320
results:
- metric: efficacy
  baseline: 50.77
  endpoint: 70.83
  p_value: 0.3046
- metric: efficacy
  baseline: 96.52
  endpoint: 82.25
  p_value: 0.0326
- metric: safety
  baseline: 43.38
  endpoint: 72.88
  p_value: 0.2787
- metric: safety
  baseline: 17.71
  endpoint: 95.37
  p_value: 0.4542
conclusion: non-significant

[Assistant]
Approach:
1. Task: Convert experiment result from YAML 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-574681</experiment_id>
<title>Effect of anyone on society</title>
<methodology>
<design>cohort</design>
<sample_size>560</sample_size>
<duration_days>320</duration_days>
</methodology>
<results>
<metric>efficacy</metric>
<baseline>50.77</baseline>
<endpoint>70.83</endpoint>
<p_value>0.3046</p_value>
</results>
<results>
<metric>efficacy</metric>
<baseline>96.52</baseline>
<endpoint>82.25</endpoint>
<p_value>0.0326</p_value>
</results>
<results>
<metric>safety</metric>
<baseline>43.38</baseline>
<endpoint>72.88</endpoint>
<p_value>0.2787</p_value>
</results>
<results>
<metric>safety</metric>
<baseline>17.71</baseline>
<endpoint>95.37</endpoint>
<p_value>0.4542</p_value>
</results>
<conclusion>non-significant</conclusion>
</experiment_result>


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

[User] Create a JSON representation of 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-19844803",
  "platform": "instagram",
  "user_id": "eee48898-e428-4685-b6ea-d0074f4ffb8a",
  "username": "pinedaryan",
  "content": "Between past agree writer forget big. Simple glass protect job answer thank.\nGovernment prepare rather agency hard. Fear director room future hospital.",
  "timestamp": "2026-01-07T13:51:25.753060",
  "hashtags": [
    "#fast",
    "#imagine",
    "#carry"
  ],
  "engagement": {
    "likes": 1299,
    "shares": 900,
    "comments": 90
  }
}


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

[User] Output error log as TOML.

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

Output:
error_id = "3ee04eb7-6a96-4708-8070-7816402d081f"
timestamp = "2026-01-07T13:51:26.236854"
level = "ERROR"
service = "checkService"
message = "Base information cell production decade back."
stack_trace = [ "at quality.py:463", "at but.py:317",]

[context]
user_id = "9d5113f2-65b2-4f61-b9b2-2b011fc1bc1b"
request_id = "f5a78ca9-3dcc-4c14-bcea-f5b7936cdde5"


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

[User] Output prescription as CSV.

[Assistant]
Approach:
1. Task: Create prescription 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:
date,medications,patient_mrn,prescriber,rx_id
2026-01-06,"[{""name"": ""Lisinopril"", ""dosage"": ""20mg"", ""frequency"": ""TID"", ""quantity"": 30}, {""name"": ""Atorvastati",MRN-568012,Linda Gonzalez,RX-5160762
2026-01-06,"[{""name"": ""Lisinopril"", ""dosage"": ""5mg"", ""frequency"": ""BID"", ""quantity"": 30}]",MRN-985234,Tony Shea,RX-7857979
2026-01-02,"[{""name"": ""Metformin"", ""dosage"": ""20mg"", ""frequency"": ""TID"", ""quantity"": 60}, {""name"": ""Metformin"", ",MRN-385502,Vicki Ramos,RX-8336764
2026-01-01,"[{""name"": ""Metformin"", ""dosage"": ""5mg"", ""frequency"": ""TID"", ""quantity"": 60}, {""name"": ""Lisinopril"", ",MRN-731089,Sherry Roberts,RX-2357569
2026-01-02,"[{""name"": ""Atorvastatin"", ""dosage"": ""5mg"", ""frequency"": ""BID"", ""quantity"": 60}, {""name"": ""Metformin""",MRN-193862,Kristen Young,RX-1985896


[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:
{
  "openapi": "3.0.0",
  "info": {
    "title": "Visionary eco-centric methodology API",
    "version": "1.0.0"
  },
  "paths": {
    "/edge": {
      "get": {
        "summary": "Simple really social range.",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          },
          {
            "name": "param1",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  }
}

[Assistant]
Approach:
1. Task: Convert api specification 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"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Visionary eco-centric methodology API</title>
<version>1.0.0</version>
</info>
<paths>
</edge>
<get>
<summary>Simple really social range.</summary>
<parameters>
<name>param0</name>
<in>query</in>
<type>string</type>
</parameters>
<parameters>
<name>param1</name>
<in>query</in>
<type>string</type>
</parameters>
<responses>
<200>
<description>Success</description>
</200>
<400>
<description>Bad Request</description>
</400>
</responses>
</get>
<//edge>
</paths>
</api_specification>


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

[User] Create a CSV representation of api specification.

[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_/second_get_parameters,paths_/second_get_responses_200_description,paths_/second_get_responses_400_description,paths_/second_get_summary,publication_doi,publication_venue,publication_year,title
,,,,Reactive exuding frame API,1.0.0,,3.0.0,,"[{""name"": ""param0"", ""in"": ""query"", ""type"": ""string""}]",Success,Bad Request,Life century work throughout however miss another.,,,,
Peace safe prepare travel really. Specific ever bring left this likely speak. Hot owner about eat to,"[{""name"": ""Cristian Shaw"", ""affiliation"": ""Gonzalez LLC"", ""email"": ""latkins@example.org""}, {""name"": ",124,None,,,"[""clear"", ""three"", ""left"", ""pick"", ""light""]",,arXiv:2023.28336,,,,,10.3246/NdmY,Science,2023,Automated methodical process improvement
Herself white answer try job. Tell Democrat difference any trial technology resource.,"[{""name"": ""Elijah Daniel"", ""affiliation"": ""Bright-Perkins"", ""email"": ""john97@example.org""}, {""name"":",53,None,,,"[""follow"", ""including"", ""draw"", ""page"", ""each""]",,arXiv:2023.19818,,,,,10.8794/PNei,Cell,2020,Vision-oriented multi-tasking attitude