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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<course_syllabus>
<course_id>CRS-5570</course_id>
ZMD258
<title>Mandatory leadingedge superstructure 101</title>
<instructor>Gregory Dunn</instructor>
<credits>3</credits>
<term>Spring 2021</term>
<schedule>
<week>1</week>
<topic>guess</topic>
</schedule>
<schedule>
<week>2</week>
<topic>forget</topic>
</schedule>
<schedule>
<week>3</week>
<topic>technology</topic>
</schedule>
<schedule>
<week>4</week>
<topic>nothing</topic>
</schedule>
<schedule>
<week>5</week>
<topic>sea</topic>
</schedule>
<schedule>
<week>6</week>
<topic>other</topic>
</schedule>
<schedule>
<week>7</week>
<topic>new</topic>
</schedule>
<schedule>
<week>8</week>
<topic>report</topic>
</schedule>
<schedule>
<week>9</week>
<topic>guy</topic>
</schedule>
<schedule>
<week>10</week>
<topic>can</topic>
</schedule>
<schedule>
<week>11</week>
<topic>inside</topic>
</schedule>
<grading>
<homework>30</homework>
<midterm>30</midterm>
<final>40</final>
</grading>
</course_syllabus>


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

[User]
Convert the following CSV to TOML:
company,eps,expenses,metrics_profit_margin,metrics_roe,net_income,quarter,revenue,ticker
Hardy-Nguyen,3.22,30350118,18.82,21.21,14673850,Q3 2024,23201336,ZAMS
Lozano Group,8.51,43463027,17.58,20.83,4213324,Q4 2024,65770574,DXAR
Martinez PLC,3.95,17837948,17.88,23.24,14318863,Q4 2022,66122778,SGPY
Long-Collins,1.99,1279714,23.09,14.02,4395585,Q2 2020,61984954,KHOP
Richardson-Walker,8.03,77368916,20.92,24.17,4911781,Q2 2020,71974788,ZHWE

[Assistant]
Approach:
1. Task: Convert financial report from CSV to TOML
2. Complexity: complex - 8-10 fields, 3-4 levels
3. Format rules: key=value syntax, [sections], proper types
4. Structure: Organize data logically with appropriate nesting
5. Transform values to match the target format specifications.

Output:
company = "Hardy-Nguyen"
ticker = "ZAMS"
quarter = "Q3 2024"
revenue = 23201336
expenses = 30350118
net_income = 14673850
eps = 3.22

[metrics]
profit_margin = 18.82
roe = 21.21


[System] You are an expert in 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: 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-1417017",
  "product_id": "PROD-561113",
  "user_id": "58368812-841f-4b65-a63f-bf59f81a4b62",
  "rating": 2,
  "title": "Miss entire student source like impact.",
  "content": "Particularly myself court bring vote business boy lawyer. Economy name wonder thank a charge. Successful value site thus. Exist election about task reason.",
  "date": "2026-01-04",
  "verified_purchase": false,
  "helpful_votes": 17
}


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

[User] Generate contract data in CSV format.

[Assistant]
Approach:
1. Task: Create contract 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:
contract_id,effective_date,parties,status,term_months,value
CTR-896633,2026-01-03,"[{""name"": ""Smith-Cross"", ""role"": ""party_a""}, {""name"": ""Carrillo and Sons"", ""role"": ""party_b""}]",pending,21,926875
CTR-121068,2026-01-01,"[{""name"": ""Choi Inc"", ""role"": ""party_a""}, {""name"": ""Davenport-James"", ""role"": ""party_b""}]",active,33,684225
CTR-369398,2026-01-06,"[{""name"": ""Suarez PLC"", ""role"": ""party_a""}, {""name"": ""Buck-Anderson"", ""role"": ""party_b""}]",executed,22,464177
CTR-410542,2026-01-01,"[{""name"": ""Espinoza, Ross and Cook"", ""role"": ""party_a""}, {""name"": ""Hill-Velazquez"", ""role"": ""party_b",active,31,691283
CTR-549723,2026-01-04,"[{""name"": ""Patterson LLC"", ""role"": ""party_a""}, {""name"": ""Martin Group"", ""role"": ""party_b""}]",executed,42,624523


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

[User] Create a YAML representation of product listing.

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

Output:
product_id: PROD-723394
name: Streamlined full-range ability
category: clothing
price: 959.9
currency: USD
stock: 28
is_available: true
rating: 3.7
reviews: 332
specs:
  weight_kg: 9.93
  dimensions: 53x67x45cm


[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:
{
  "service": "findService",
  "stack_trace": [
    "at watch.py:197",
    "at body.py:298",
    "at girl.py:392",
    "at red.py:350"
  ],
  "level": "ERROR",
  "message": "Head then too threat drive."
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<error_log>
<service>findService</service>
<stack_trace>at watch.py:197</stack_trace>
<stack_trace>at body.py:298</stack_trace>
<stack_trace>at girl.py:392</stack_trace>
<stack_trace>at red.py:350</stack_trace>
<level>ERROR</level>
<message>Head then too threat drive.</message>
</error_log>


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

[User]
Reformat the data below from YAML to XML:
assessment_id: ASMT-766800
student_id: STU-927295
course_id: CRS-8819
type: assignment
date: '2026-01-03'
scores:
- question: 1
  points_earned: 8
  points_possible: 10
- question: 2
  points_earned: 3
  points_possible: 10
- question: 3
  points_earned: 8
  points_possible: 10
- question: 4
  points_earned: 1
  points_possible: 10
- question: 5
  points_earned: 5
  points_possible: 10
- question: 6
  points_earned: 2
  points_possible: 10
- question: 7
  points_earned: 0
  points_possible: 10
- question: 8
  points_earned: 4
  points_possible: 10
- question: 9
  points_earned: 3
  points_possible: 10
total_score: 99
percentage: 71.71
grade: A

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<student_assessment>
<assessment_id>ASMT-766800</assessment_id>
<student_id>STU-927295</student_id>
<course_id>CRS-8819</course_id>
<type>assignment</type>
<date>2026-01-03</date>
<scores>
<question>1</question>
<points_earned>8</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>8</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>5</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>0</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>4</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>9</question>
<points_earned>3</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>99</total_score>
<percentage>71.71</percentage>
<grade>A</grade>
</student_assessment>


[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-107958",
  "name": "Adaptive asynchronous synergy",
  "category": "electronics",
  "price": 349.45,
  "currency": "USD",
  "stock": 717,
  "is_available": true,
  "rating": 1.62,
  "reviews": 33,
  "specs": {
    "weight_kg": 15.32,
    "dimensions": "74x31x68cm"
  }
}

[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-107958</product_id>
<name>Adaptive asynchronous synergy</name>
<category>electronics</category>
<price>349.45</price>
<currency>USD</currency>
<stock>717</stock>
<is_available>True</is_available>
<rating>1.62</rating>
<reviews>33</reviews>
<specs>
<weight_kg>15.32</weight_kg>
<dimensions>74x31x68cm</dimensions>
</specs>
</product_listing>


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

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

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

Output:
paper_id = "arXiv:2020.65510"
title = "Mandatory solution-oriented groupware"
abstract = "Along its pressure yeah. Artist pattern nearly rich realize available skill. Month beyond rate make kid painting."
keywords = [ "surface", "consumer", "despite", "compare", "protect",]
citations = 488
funding_source = "Johnson LLC"
[[authors]]
name = "Jared Fuller"
affiliation = "Robinson, Crawford and Johnson"
email = "jenna58@example.net"

[[authors]]
name = "Nancy Anderson"
affiliation = "Shannon-Johnson"
email = "richdonald@example.net"

[[authors]]
name = "Julia Neal"
affiliation = "Roach, Harper and Cameron"
email = "gillcory@example.com"

[publication]
venue = "Nature"
year = 2022
doi = "10.8909/Qnkv"


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

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

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

Output:
{
  "product_id": "PROD-791864",
  "name": "Decentralized heuristic migration",
  "category": "books",
  "price": 124.58,
  "currency": "USD",
  "stock": 601,
  "is_available": true,
  "rating": 3.59,
  "reviews": 538,
  "specs": {
    "weight_kg": 9.83,
    "dimensions": "30x16x25cm"
  }
}


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

[User]
Reformat the data below from JSON to XML:
{
  "review_id": "REV-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
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<review_id>REV-1681251</review_id>
<product_id>PROD-380005</product_id>
<user_id>6ee75bbe-7aec-42b2-b8ce-db908c5fbc3a</user_id>
<rating>3</rating>
<title>Floor measure may hear dark at.</title>
<content>Us board wonder trouble. Up as inside party growth seat. College late direction amount best team.
Fish gas end appear mother assume. Anyone major game miss similar argue. Moment describe require.</content>
<date>2026-01-05</date>
<verified_purchase>True</verified_purchase>
<helpful_votes>21</helpful_votes>
</customer_review>


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

[User]
Convert the following JSON to XML:
{
  "course_id": "CRS-1689",
  "code": "NZW166",
  "title": "Operative modular system engine 101",
  "instructor": "David Chen",
  "credits": 4,
  "term": "Fall 2021",
  "schedule": [
    {
      "week": 1,
      "topic": "in"
    },
    {
      "week": 2,
      "topic": "summer"
    },
    {
      "week": 3,
      "topic": "unit"
    },
    {
      "week": 4,
      "topic": "wind"
    },
    {
      "week": 5,
      "topic": "act"
    },
    {
      "week": 6,
      "topic": "itself"
    },
    {
      "week": 7,
      "topic": "would"
    },
    {
      "week": 8,
      "topic": "itself"
    },
    {
      "week": 9,
      "topic": "tell"
    },
    {
      "week": 10,
      "topic": "money"
    },
    {
      "week": 11,
      "topic": "long"
    }
  ],
  "grading": {
    "homework": 30,
    "midterm": 30,
    "final": 40
  }
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<course_syllabus>
<course_id>CRS-1689</course_id>
NZW166
<title>Operative modular system engine 101</title>
<instructor>David Chen</instructor>
<credits>4</credits>
<term>Fall 2021</term>
<schedule>
<week>1</week>
<topic>in</topic>
</schedule>
<schedule>
<week>2</week>
<topic>summer</topic>
</schedule>
<schedule>
<week>3</week>
<topic>unit</topic>
</schedule>
<schedule>
<week>4</week>
<topic>wind</topic>
</schedule>
<schedule>
<week>5</week>
<topic>act</topic>
</schedule>
<schedule>
<week>6</week>
<topic>itself</topic>
</schedule>
<schedule>
<week>7</week>
<topic>would</topic>
</schedule>
<schedule>
<week>8</week>
<topic>itself</topic>
</schedule>
<schedule>
<week>9</week>
<topic>tell</topic>
</schedule>
<schedule>
<week>10</week>
<topic>money</topic>
</schedule>
<schedule>
<week>11</week>
<topic>long</topic>
</schedule>
<grading>
<homework>30</homework>
<midterm>30</midterm>
<final>40</final>
</grading>
</course_syllabus>


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

[User]
Transform this JSON data into XML format:
{
  "contract_id": "CTR-504304",
  "parties": [
    {
      "name": "Waters-Vega",
      "role": "party_a"
    },
    {
      "name": "Petty, Thompson and Dillon",
      "role": "party_b"
    }
  ],
  "effective_date": "2026-01-01",
  "term_months": 50,
  "value": 407863,
  "status": "executed"
}

[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-504304</contract_id>
<parties>
<name>Waters-Vega</name>
<role>party_a</role>
</parties>
<parties>
<name>Petty, Thompson and Dillon</name>
<role>party_b</role>
</parties>
<effective_date>2026-01-01</effective_date>
<term_months>50</term_months>
<value>407863</value>
<status>executed</status>
</contract>


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

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

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

Output:
post_id = "POST-39289028"
platform = "instagram"
user_id = "a2301bd9-5c11-406a-b2a8-1c1f96bbd31c"
username = "rhodessharon"
content = "City window data describe address street. Environmental wall shoulder happy artist forget hospital. Chair their before reach picture serve."
timestamp = "2026-01-07T13:51:26.862472"
hashtags = [ "#yet", "#listen",]

[engagement]
likes = 2391
shares = 751
comments = 108


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

[User]
Reformat the data below from JSON to XML:
{
  "value": 911148,
  "contract_id": "CTR-919818",
  "parties": [
    {
      "name": "Riggs, Carey and Rojas",
      "role": "party_a"
    },
    {
      "name": "Mcdowell-Koch",
      "role": "party_b"
    }
  ],
  "status": "active",
  "term_months": 18
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<contract>
<value>911148</value>
<contract_id>CTR-919818</contract_id>
<parties>
<name>Riggs, Carey and Rojas</name>
<role>party_a</role>
</parties>
<parties>
<name>Mcdowell-Koch</name>
<role>party_b</role>
</parties>
<status>active</status>
<term_months>18</term_months>
</contract>


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

[User]
Convert the following YAML to CSV:
rating: 4.54
stock: 843
specs:
  weight_kg: 34.7
  dimensions: 61x86x65cm
currency: USD

[Assistant]
Approach:
1. Task: Convert product listing from YAML to 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. Transform values to match the target format specifications.

Output:
abstract,authors,citations,currency,funding_source,keywords,paper_id,publication_doi,publication_venue,publication_year,rating,specs_dimensions,specs_weight_kg,stock,title
,,,USD,,,,,,,4.54,61x86x65cm,34.7,843,
"Subject him card person actually blood. Election design both paper raise.
Left resource receive give","[{""name"": ""Kevin Lucas"", ""affiliation"": ""Davis, Mcmillan and Salazar"", ""email"": ""smithdwayne@example",459,,Pollard-Mullins,"[""buy"", ""base"", ""tend"", ""itself""]",arXiv:2020.50698,10.4080/AUir,Science,2021,,,,,Advanced stable Local Area Network
Smile lead reality nation movement. Rise consumer enter old produce ball resource one. Phone debate ,"[{""name"": ""Karl Ryan"", ""affiliation"": ""Lester, Gross and Bradley"", ""email"": ""vhopkins@example.org""},",82,,Gaines Group,"[""range"", ""range"", ""stuff"", ""charge""]",arXiv:2020.33100,10.2477/DkAw,Science,2023,,,,,Cross-group analyzing budgetary management
Field simple agency throw family again. Military pattern with war meeting list nearly. Act against v,"[{""name"": ""Amy Mcmahon"", ""affiliation"": ""Burns Ltd"", ""email"": ""craneapril@example.com""}, {""name"": ""D",491,,Blair-Fleming,"[""just"", ""open"", ""focus"", ""course"", ""live""]",arXiv:2024.16691,10.4328/EKHv,Science,2023,,,,,Self-enabling foreground definition


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

[User] Create a YAML representation of clinical note.

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

Output:
note_id: CN-3508494
patient:
  mrn: MRN-721804
  age: 51
  gender: F
encounter_date: '2026-01-06'
chief_complaint: chest pain
vitals:
  bp: 130/109
  hr: 78
  temp_f: 100.6
assessment:
- problem: hypertension
  icd10: K96
- problem: diabetes
  icd10: K86


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<lab_result>
<result_id>LAB-3941350</result_id>
<patient_mrn>MRN-739958</patient_mrn>
<order_date>2026-01-01</order_date>
<panel>CBC</panel>
<results>
<test>Glucose</test>
<value>134.1</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>WBC</test>
<value>188.7</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>142.9</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>117.3</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Glucose</test>
<value>159.8</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>WBC</test>
<value>131.5</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
</lab_result>


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<news_article>
<article_id>ART-8668047</article_id>
<headline>Seamless local alliance</headline>
<author>Alyssa Moore</author>
<published>2026-01-02T06:22:52.413807</published>

Business

<content>Billion up year window similar. Oil two resource next. If this tough pattern.
Rule year push international.
Receive charge movie remember hear theory stuff explain. Century animal decide everyone direction rather. Month property rock environment fine such hand remain.</content>
<tags>traditional</tags>
<tags>wish</tags>
<tags>little</tags>
<tags>inside</tags>
<tags>year</tags>
<views>55093</views>
<shares>3713</shares>
</news_article>

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

Output:
{
  "article_id": "ART-8668047",
  "headline": "Seamless local alliance",
  "author": "Alyssa Moore",
  "published": "2026-01-02T06:22:52.413807",
  "section": "Business",
  "content": "Billion up year window similar. Oil two resource next. If this tough pattern.\nRule year push international.\nReceive charge movie remember hear theory stuff explain. Century animal decide everyone direction rather. Month property rock environment fine such hand remain.",
  "tags": [
    "traditional",
    "wish",
    "little",
    "inside",
    "year"
  ],
  "views": 55093,
  "shares": 3713
}


[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-85338602",
  "customer_id": "ea7970e3-49c7-4d3a-bbe0-6c539dc6c3d3",
  "timestamp": "2026-01-07T13:51:25.620781",
  "items": [
    {
      "sku": "SKU-22630",
      "qty": 3,
      "price": 89.97
    }
  ],
  "subtotal": 468.67,
  "tax": 148.91,
  "total": 792.01,
  "payment_method": "apple_pay"
}

[Assistant]
Approach:
1. Task: Convert transaction record 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"?>
<transaction_record>
<txn_id>TXN-85338602</txn_id>
<customer_id>ea7970e3-49c7-4d3a-bbe0-6c539dc6c3d3</customer_id>
<timestamp>2026-01-07T13:51:25.620781</timestamp>
<items>
<sku>SKU-22630</sku>
<qty>3</qty>
<price>89.97</price>
</items>
<subtotal>468.67</subtotal>
<tax>148.91</tax>
<total>792.01</total>
<payment_method>apple_pay</payment_method>
</transaction_record>


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<review_id>REV-3982215</review_id>
<product_id>PROD-143836</product_id>
<user_id>0dd51960-e54b-4127-90d4-b32b17839969</user_id>
<rating>2</rating>
<title>Fight and building toward office.</title>
<content>Hear media safe I visit language. Difference part thousand. Society inside describe decision.</content>
<date>2026-01-06</date>
<verified_purchase>True</verified_purchase>
<helpful_votes>16</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-3982215",
  "product_id": "PROD-143836",
  "user_id": "0dd51960-e54b-4127-90d4-b32b17839969",
  "rating": 2,
  "title": "Fight and building toward office.",
  "content": "Hear media safe I visit language. Difference part thousand. Society inside describe decision.",
  "date": "2026-01-06",
  "verified_purchase": true,
  "helpful_votes": 16
}


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

[User] Generate course syllabus data in CSV format.

[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
XMJ312,CRS-3741,4,40,30,30,Rachel Diaz,"[{""week"": 1, ""topic"": ""body""}, {""week"": 2, ""topic"": ""rather""}, {""week"": 3, ""topic"": ""song""}, {""week""",Fall 2021,Managed incremental focus group 101
HBZ459,CRS-4250,3,40,30,30,Stephanie Leon,"[{""week"": 1, ""topic"": ""dark""}, {""week"": 2, ""topic"": ""someone""}, {""week"": 3, ""topic"": ""bag""}, {""week""",Fall 2021,Stand-alone disintermediate circuit 101
AFF413,CRS-8188,4,40,30,30,Keith Mcmahon,"[{""week"": 1, ""topic"": ""half""}, {""week"": 2, ""topic"": ""because""}, {""week"": 3, ""topic"": ""issue""}, {""wee",Spring 2022,Expanded clear-thinking implementation 101


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

[User]
Transform this YAML data into CSV format:
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.

  Government prepare rather agency hard. Fear director room future hospital.'
timestamp: '2026-01-07T13:51:25.753060'
hashtags:
- '#fast'
- '#imagine'
- '#carry'
engagement:
  likes: 1299
  shares: 900
  comments: 90

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

Output:
content,engagement_comments,engagement_likes,engagement_shares,hashtags,platform,post_id,timestamp,user_id,username
"Between past agree writer forget big. Simple glass protect job answer thank.
Government prepare rath",90,1299,900,"[""#fast"", ""#imagine"", ""#carry""]",instagram,POST-19844803,2026-01-07T13:51:25.753060,eee48898-e428-4685-b6ea-d0074f4ffb8a,pinedaryan
Color money another hundred president give out difficult. Unit discuss grow while onto claim sport. ,165,2053,463,"[""#artist"", ""#decision"", ""#size"", ""#on""]",facebook,POST-86088458,2026-01-07T13:51:25.756474,e0f96fc3-67e6-4771-8ffd-5603c2ac63a3,travis52
Small do section sing agent financial forget four. We American wind central peace could option. Yeah,257,2869,40,"[""#someone"", ""#best"", ""#executive""]",twitter,POST-46497550,2026-01-07T13:51:25.756754,d99a3b7f-f5c9-4ccb-a80a-1e4197a3ce89,alexander13
High lawyer thus loss player ability. Already mission cover control thus near study forward. Region ,192,3100,22,"[""#stay"", ""#sometimes""]",facebook,POST-76246543,2026-01-07T13:51:25.757011,051b5f55-1174-4164-a801-fb31bfb33391,catherine10
Wonder argue work computer professional ask. Card skin wind behind. Must involve follow reality imag,73,169,149,"[""#magazine"", ""#official"", ""#image""]",twitter,POST-59798593,2026-01-07T13:51:25.757378,39c30ce3-ba3b-4c1b-ac3b-a04e8464e672,youngkurt


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

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

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

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


[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:
{
  "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."
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<research_paper>
<authors>
<name>Laura White</name>
<affiliation>Coleman, Johnson and Ross</affiliation>
<email>jillcollins@example.com</email>
</authors>
<authors>
<name>Sarah Woods</name>
<affiliation>Durham, Thompson and White</affiliation>
<email>sbeard@example.com</email>
</authors>
<title>Seamless cohesive projection</title>
<funding_source />
<abstract>Middle several interesting move. Wrong represent guess threat. Once paper represent.</abstract>
</research_paper>


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

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


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

[User]
Convert the following TOML to YAML:
paper_id = "arXiv:2023.21424"
title = "Cross-platform fault-tolerant circuit"
abstract = "Truth himself long country car environment. Free design relate hope admit learn identify."
keywords = [ "share", "feeling", "environmental",]
citations = 477
funding_source = "Barker-Wise"
[[authors]]
name = "Charlotte Sellers"
affiliation = "Armstrong-Marks"
email = "weaverelizabeth@example.com"

[[authors]]
name = "Cynthia Johnston MD"
affiliation = "Rogers Inc"
email = "ccastaneda@example.org"

[[authors]]
name = "Robert Velasquez"
affiliation = "Alvarado LLC"
email = "psullivan@example.net"

[publication]
venue = "Science"
year = 2022
doi = "10.6091/Sfwn"

[Assistant]
Approach:
1. Task: Convert research paper from TOML 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:
paper_id: arXiv:2023.21424
title: Cross-platform fault-tolerant circuit
authors:
- name: Charlotte Sellers
  affiliation: Armstrong-Marks
  email: weaverelizabeth@example.com
- name: Cynthia Johnston MD
  affiliation: Rogers Inc
  email: ccastaneda@example.org
- name: Robert Velasquez
  affiliation: Alvarado LLC
  email: psullivan@example.net
abstract: Truth himself long country car environment. Free design relate hope admit
  learn identify.
keywords:
- share
- feeling
- environmental
publication:
  venue: Science
  year: 2022
  doi: 10.6091/Sfwn
citations: 477
funding_source: Barker-Wise


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

[User]
Transform this JSON data into XML format:
{
  "txn_id": "TXN-60159725",
  "customer_id": "13707a49-23b0-4133-8216-7e83986c9575",
  "timestamp": "2026-01-07T13:51:27.689251",
  "items": [
    {
      "sku": "SKU-82899",
      "qty": 5,
      "price": 298.29
    },
    {
      "sku": "SKU-51515",
      "qty": 4,
      "price": 343.78
    },
    {
      "sku": "SKU-53336",
      "qty": 3,
      "price": 488.21
    },
    {
      "sku": "SKU-52517",
      "qty": 2,
      "price": 291.79
    }
  ],
  "subtotal": 1914.1,
  "tax": 175.88,
  "total": 1360.6,
  "payment_method": "credit_card"
}

[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-60159725</txn_id>
<customer_id>13707a49-23b0-4133-8216-7e83986c9575</customer_id>
<timestamp>2026-01-07T13:51:27.689251</timestamp>
<items>
<sku>SKU-82899</sku>
<qty>5</qty>
<price>298.29</price>
</items>
<items>
<sku>SKU-51515</sku>
<qty>4</qty>
<price>343.78</price>
</items>
<items>
<sku>SKU-53336</sku>
<qty>3</qty>
<price>488.21</price>
</items>
<items>
<sku>SKU-52517</sku>
<qty>2</qty>
<price>291.79</price>
</items>
<subtotal>1914.1</subtotal>
<tax>175.88</tax>
<total>1360.6</total>
<payment_method>credit_card</payment_method>
</transaction_record>


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<news_article>
<author>Jenna Bryant</author>
<tags>most</tags>
<tags>off</tags>
<tags>shoulder</tags>
<headline>Secured composite leverage</headline>
<published>2026-01-04T22:19:16.750289</published>
</news_article>

[Assistant]
Approach:
1. Task: Convert news article 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:
{
  "author": "Jenna Bryant",
  "tags": [
    "most",
    "off",
    "shoulder"
  ],
  "headline": "Secured composite leverage",
  "published": "2026-01-04T22:19:16.750289"
}


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

[User] Output product listing as CSV.

[Assistant]
Approach:
1. Task: Create product listing 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,currency,is_available,name,price,product_id,rating,reviews,specs_dimensions,specs_weight_kg,stock
clothing,USD,True,Team-oriented grid-enabled support,360.14,PROD-210763,3.34,923,28x80x26cm,14.15,657
electronics,USD,True,Polarized client-driven intranet,482.97,PROD-333387,4.1,92,35x46x27cm,43.9,448
clothing,USD,True,Configurable real-time Internet solution,138.26,PROD-384054,4.36,62,38x32x46cm,15.33,689
clothing,USD,True,Organic intangible portal,351.33,PROD-202919,4.16,182,95x16x90cm,15.26,818


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<error_log>
<error_id>0ea30289-ce13-425f-910d-da970e03d0fa</error_id>
<timestamp>2026-01-07T13:51:25.772316</timestamp>
<level>WARNING</level>
<service>theService</service>
<message>Country specific information follow daughter dark.</message>
<stack_trace>at enjoy.py:340</stack_trace>
<stack_trace>at current.py:45</stack_trace>
<stack_trace>at hand.py:478</stack_trace>
<context>
<user_id>91a6b883-2593-4790-8a1e-5acd27aad31b</user_id>
<request_id>1b22b6e6-0879-45de-9655-0fac03142f9b</request_id>
</context>
</error_log>


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

[User] Create a TOML representation of clinical note.

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

Output:
note_id = "CN-6224145"
encounter_date = "2026-01-04"
chief_complaint = "headache"
[[assessment]]
problem = "hypertension"
icd10 = "I32"

[patient]
mrn = "MRN-560569"
age = 88
gender = "F"

[vitals]
bp = "119/73"
hr = 63
temp_f = 100.0


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

[User] Create a JSON representation of student assessment.

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

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

[User] Create a YAML representation of lab result.

[Assistant]
Approach:
1. Task: Create lab result in YAML
2. Complexity: 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-2983714
patient_mrn: MRN-369371
order_date: '2026-01-04'
panel: CMP
results:
- test: Hemoglobin
  value: 97.6
  unit: g/dL
  flag: normal
- test: WBC
  value: 60.0
  unit: mg/dL
  flag: normal
- test: Hemoglobin
  value: 172.2
  unit: mg/dL
  flag: high
- test: WBC
  value: 145.9
  unit: g/dL
  flag: high
- test: WBC
  value: 83.4
  unit: mg/dL
  flag: low


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<course_syllabus>
<course_id>CRS-3948</course_id>
CSZ142
<title>Intuitive foreground functionalities 101</title>
<instructor>Robert Carter</instructor>
<credits>4</credits>
<term>Fall 2022</term>
<schedule>
<week>1</week>
<topic>manage</topic>
</schedule>
<schedule>
<week>2</week>
<topic>catch</topic>
</schedule>
<schedule>
<week>3</week>
<topic>people</topic>
</schedule>
<schedule>
<week>4</week>
<topic>out</topic>
</schedule>
<schedule>
<week>5</week>
<topic>story</topic>
</schedule>
<schedule>
<week>6</week>
<topic>share</topic>
</schedule>
<schedule>
<week>7</week>
<topic>become</topic>
</schedule>
<schedule>
<week>8</week>
<topic>part</topic>
</schedule>
<schedule>
<week>9</week>
<topic>cell</topic>
</schedule>
<grading>
<homework>30</homework>
<midterm>30</midterm>
<final>40</final>
</grading>
</course_syllabus>


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

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

[Assistant]
Approach:
1. Task: Convert student assessment 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"?>
<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>


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

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

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

Output:
post_id = "POST-20150897"
platform = "instagram"
user_id = "ace3958f-4578-4576-9236-9cbfc1f62953"
username = "spatrick"
content = "About industry woman size. Available box return camera public time. Establish outside ability sport describe air who.\nCertain miss girl different both wife. Blood relationship if model."
timestamp = "2026-01-07T13:51:25.995017"
hashtags = [ "#share", "#prevent", "#entire", "#owner",]

[engagement]
likes = 3129
shares = 891
comments = 28


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<course_syllabus>
<instructor>Ryan Griffin</instructor>
<course_id>CRS-4864</course_id>
NLW161
</course_syllabus>

[Assistant]
Approach:
1. Task: Convert course syllabus 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:
{
  "instructor": "Ryan Griffin",
  "course_id": "CRS-4864",
  "code": "NLW161"
}


[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:
{
  "article_id": "ART-1748125",
  "headline": "Customizable leadingedge structure",
  "author": "Sandra Bennett",
  "published": "2026-01-03T22:52:42.741679",
  "section": "Sports",
  "content": "Majority meeting sound have week public pass. Major food relate spend seven.\nIndeed run fund.\nFederal right stuff difficult alone miss. Stuff rest model job deep knowledge pull force. Too follow face husband every. Hit important agreement rather card west want.",
  "tags": [
    "subject",
    "attention",
    "class",
    "campaign",
    "second"
  ],
  "views": 63827,
  "shares": 2505
}

[Assistant]
Approach:
1. Task: Convert news article 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"?>
<news_article>
<article_id>ART-1748125</article_id>
<headline>Customizable leadingedge structure</headline>
<author>Sandra Bennett</author>
<published>2026-01-03T22:52:42.741679</published>

Sports

<content>Majority meeting sound have week public pass. Major food relate spend seven.
Indeed run fund.
Federal right stuff difficult alone miss. Stuff rest model job deep knowledge pull force. Too follow face husband every. Hit important agreement rather card west want.</content>
<tags>subject</tags>
<tags>attention</tags>
<tags>class</tags>
<tags>campaign</tags>
<tags>second</tags>
<views>63827</views>
<shares>2505</shares>
</news_article>


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

[User] Generate clinical note data in YAML format.

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

Output:
assessment:
- problem: diabetes
  icd10: I24
encounter_date: '2026-01-06'
patient:
  mrn: MRN-470382
  age: 61
  gender: F
note_id: CN-3244099
vitals:
  bp: 158/77
  hr: 112
  temp_f: 99.5


[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"?>
<error_log>
<error_id>69ef512f-ddd4-415a-b99a-51e8f50d151c</error_id>
<timestamp>2026-01-07T13:51:25.644182</timestamp>
<level>WARNING</level>
<service>fillService</service>
<message>Minute heart focus arrive.</message>
<stack_trace>at administration.py:211</stack_trace>
<stack_trace>at lawyer.py:276</stack_trace>
<stack_trace>at discussion.py:115</stack_trace>
<context>
<user_id>29c6c678-1224-4e33-8bc1-e94776cd4eb2</user_id>
<request_id>42e054d1-48f9-4a1c-ad7b-82ed505d6250</request_id>
</context>
</error_log>

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


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<course_syllabus>
<course_id>CRS-1689</course_id>
NZW166
<title>Operative modular system engine 101</title>
<instructor>David Chen</instructor>
<credits>4</credits>
<term>Fall 2021</term>
<schedule>
<week>1</week>
<topic>in</topic>
</schedule>
<schedule>
<week>2</week>
<topic>summer</topic>
</schedule>
<schedule>
<week>3</week>
<topic>unit</topic>
</schedule>
<schedule>
<week>4</week>
<topic>wind</topic>
</schedule>
<schedule>
<week>5</week>
<topic>act</topic>
</schedule>
<schedule>
<week>6</week>
<topic>itself</topic>
</schedule>
<schedule>
<week>7</week>
<topic>would</topic>
</schedule>
<schedule>
<week>8</week>
<topic>itself</topic>
</schedule>
<schedule>
<week>9</week>
<topic>tell</topic>
</schedule>
<schedule>
<week>10</week>
<topic>money</topic>
</schedule>
<schedule>
<week>11</week>
<topic>long</topic>
</schedule>
<grading>
<homework>30</homework>
<midterm>30</midterm>
<final>40</final>
</grading>
</course_syllabus>


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

[User]
Convert the following JSON to XML:
{
  "subtotal": 205.31,
  "payment_method": "apple_pay",
  "total": 1732.06
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<transaction_record>
<subtotal>205.31</subtotal>
<payment_method>apple_pay</payment_method>
<total>1732.06</total>
</transaction_record>


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

[User] Generate clinical note data in XML format.

[Assistant]
Approach:
1. Task: Create clinical note 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"?>
<clinical_note>
<note_id>CN-8293808</note_id>
<patient>
<mrn>MRN-980604</mrn>
<age>24</age>
<gender>F</gender>
</patient>
<encounter_date>2026-01-05</encounter_date>
<chief_complaint>fever</chief_complaint>
<vitals>
<bp>150/98</bp>

93

<temp_f>102.4</temp_f>
</vitals>
<assessment>
<problem>diabetes</problem>
<icd10>J39</icd10>
</assessment>
</clinical_note>


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<lab_result>
<result_id>LAB-4827299</result_id>
<patient_mrn>MRN-871984</patient_mrn>
<order_date>2026-01-06</order_date>
<panel>Lipid</panel>
<results>
<test>WBC</test>
<value>156.4</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
<results>
<test>WBC</test>
<value>186.0</value>
<unit>mg/dL</unit>
<flag>low</flag>
</results>
<results>
<test>WBC</test>
<value>134.8</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>WBC</test>
<value>64.1</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
</lab_result>

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

Output:
{
  "result_id": "LAB-4827299",
  "patient_mrn": "MRN-871984",
  "order_date": "2026-01-06",
  "panel": "Lipid",
  "results": [
    {
      "test": "WBC",
      "value": 156.4,
      "unit": "g/dL",
      "flag": "high"
    },
    {
      "test": "WBC",
      "value": 186.0,
      "unit": "mg/dL",
      "flag": "low"
    },
    {
      "test": "WBC",
      "value": 134.8,
      "unit": "mg/dL",
      "flag": "normal"
    },
    {
      "test": "WBC",
      "value": 64.1,
      "unit": "mg/dL",
      "flag": "normal"
    }
  ]
}


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

[User] Output experiment result as TOML.

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

Output:
title = "Effect of main on stand"
experiment_id = "EXP-681166"
conclusion = "non-significant"
[[results]]
metric = "efficacy"
baseline = 50.39
endpoint = 61.09
p_value = 0.3936

[[results]]
metric = "safety"
baseline = 99.02
endpoint = 82.38
p_value = 0.0752

[[results]]
metric = "efficacy"
baseline = 94.16
endpoint = 58.56
p_value = 0.1239

[[results]]
metric = "safety"
baseline = 41.74
endpoint = 45.99
p_value = 0.0661

[methodology]
design = "RCT"
sample_size = 875
duration_days = 212


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

[User] Generate api specification data in XML format.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Distributed high-level website API</title>
<version>1.0.0</version>
</info>
<paths>
</next>
<get>
<summary>Movie my movie common adult.</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>
<//next>
</paths>
</api_specification>


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

[User] Generate error log data in TOML format.

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

Output:
error_id = "a016c8d2-6aba-435a-ab46-60ac8aacf0a5"
timestamp = "2026-01-07T13:51:26.006823"
level = "CRITICAL"
service = "currentService"
message = "Well nation stay number now but."
stack_trace = [ "at daughter.py:364", "at same.py:66",]

[context]
user_id = "432ef3ee-7f2b-4bc8-a8a7-159d64a89fd5"
request_id = "4ed63374-fc09-4101-b987-4a8ee575fee3"


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<student_assessment>
<assessment_id>ASMT-744456</assessment_id>
<student_id>STU-954920</student_id>
<course_id>CRS-3021</course_id>
<type>exam</type>
<date>2026-01-03</date>
<scores>
<question>1</question>
<points_earned>7</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>3</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>5</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>10</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>5</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>9</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>10</question>
<points_earned>3</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>11</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>12</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>97</total_score>
<percentage>89.67</percentage>
<grade>C</grade>
</student_assessment>


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

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

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

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


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

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

[Assistant]
Approach:
1. Task: Convert sales analytics 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:
{
  "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
    }
  ]
}


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

[User]
Transform this JSON data into XML format:
{
  "error_id": "a016c8d2-6aba-435a-ab46-60ac8aacf0a5",
  "timestamp": "2026-01-07T13:51:26.006823",
  "level": "CRITICAL",
  "service": "currentService",
  "message": "Well nation stay number now but.",
  "stack_trace": [
    "at daughter.py:364",
    "at same.py:66"
  ],
  "context": {
    "user_id": "432ef3ee-7f2b-4bc8-a8a7-159d64a89fd5",
    "request_id": "4ed63374-fc09-4101-b987-4a8ee575fee3"
  }
}

[Assistant]
Approach:
1. Task: Convert error log 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"?>
<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 TOML format. Think step-by-step, then generate syntactically perfect TOML.

[User]
Reformat the data below from XML to TOML:
<?xml version="1.0" encoding="UTF-8"?>
<error_log>
<error_id>424897c8-d97d-4bfb-9c1a-7b6e63fd6096</error_id>
<timestamp>2026-01-07T13:51:27.529237</timestamp>
<level>ERROR</level>
<service>heartService</service>
<message>How these anyone stop indeed.</message>
<stack_trace>at manage.py:289</stack_trace>
<stack_trace>at thing.py:107</stack_trace>
<stack_trace>at guy.py:172</stack_trace>
<stack_trace>at seat.py:479</stack_trace>
<context>
<user_id>082cc3eb-3997-4d99-990c-f696ca4ee534</user_id>
<request_id>0f3326d0-3afd-48c1-9c4d-32cc8b0c5920</request_id>
</context>
</error_log>

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

Output:
error_id = "424897c8-d97d-4bfb-9c1a-7b6e63fd6096"
timestamp = "2026-01-07T13:51:27.529237"
level = "ERROR"
service = "heartService"
message = "How these anyone stop indeed."
stack_trace = [ "at manage.py:289", "at thing.py:107", "at guy.py:172", "at seat.py:479",]

[context]
user_id = "082cc3eb-3997-4d99-990c-f696ca4ee534"
request_id = "0f3326d0-3afd-48c1-9c4d-32cc8b0c5920"


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

[User] Output lab result as XML.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<lab_result>
<result_id>LAB-2983714</result_id>
<patient_mrn>MRN-369371</patient_mrn>
<order_date>2026-01-04</order_date>
<panel>CMP</panel>
<results>
<test>Hemoglobin</test>
<value>97.6</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>WBC</test>
<value>60.0</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>172.2</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>WBC</test>
<value>145.9</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
<results>
<test>WBC</test>
<value>83.4</value>
<unit>mg/dL</unit>
<flag>low</flag>
</results>
</lab_result>


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

[User]
Transform this JSON data into XML format:
{
  "product_id": "PROD-597223",
  "name": "Proactive tertiary database",
  "category": "books",
  "price": 435.77,
  "currency": "USD",
  "stock": 111,
  "is_available": true,
  "rating": 1.73,
  "reviews": 539,
  "specs": {
    "weight_kg": 19.61,
    "dimensions": "87x91x85cm"
  }
}

[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-597223</product_id>
<name>Proactive tertiary database</name>
<category>books</category>
<price>435.77</price>
<currency>USD</currency>
<stock>111</stock>
<is_available>True</is_available>
<rating>1.73</rating>
<reviews>539</reviews>
<specs>
<weight_kg>19.61</weight_kg>
<dimensions>87x91x85cm</dimensions>
</specs>
</product_listing>


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

[User] Output news article as XML.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<news_article>
<article_id>ART-3281345</article_id>
<headline>Streamlined object-oriented toolset</headline>
<author>James Dunn</author>
<published>2026-01-03T08:23:33.060508</published>

Politics

<content>Win take among professor. Glass reflect black similar future. Risk than tree.
Economic sit plan. Available then already skill up reason back. Course his threat growth physical parent truth.
Laugh article pull goal. Believe those few.</content>
<tags>hit</tags>
<tags>summer</tags>
<tags>official</tags>
<tags>rather</tags>
<views>75669</views>
<shares>293</shares>
</news_article>


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

[User] Generate api specification data in XML format.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Optional bottom-line complexity API</title>
<version>1.0.0</version>
</info>
<paths>
</traditional>
<get>
<summary>Discussion then kind hair.</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>
<//traditional>
</paths>
</api_specification>


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

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

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

Output:
{
  "period": "July 2021",
  "total_revenue": 5979422,
  "units_sold": 82076,
  "channels": [
    {
      "name": "retail",
      "revenue": 3460112,
      "growth": 36.85
    },
    {
      "name": "online",
      "revenue": 3983364,
      "growth": 5.55
    }
  ],
  "top_products": [
    {
      "sku": "SKU-1065",
      "sales": 105510
    },
    {
      "sku": "SKU-4043",
      "sales": 281142
    },
    {
      "sku": "SKU-1338",
      "sales": 43006
    }
  ]
}


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

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

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

Output:
authors:
- name: Emily Davis
  affiliation: Nelson, Diaz and Humphrey
  email: jpalmer@example.org
- name: Robert Clark
  affiliation: James Inc
  email: dennis02@example.net
publication:
  venue: Science
  year: 2022
  doi: 10.6797/tlMT
keywords:
- lead
- list
- she
funding_source: null
paper_id: arXiv:2022.72917


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<clinical_note>
<note_id>CN-3508494</note_id>
<patient>
<mrn>MRN-721804</mrn>
<age>51</age>
<gender>F</gender>
</patient>
<encounter_date>2026-01-06</encounter_date>
<chief_complaint>chest pain</chief_complaint>
<vitals>
<bp>130/109</bp>

78

<temp_f>100.6</temp_f>
</vitals>
<assessment>
<problem>hypertension</problem>
<icd10>K96</icd10>
</assessment>
<assessment>
<problem>diabetes</problem>
<icd10>K86</icd10>
</assessment>
</clinical_note>

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

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


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

[User] Generate student assessment data in CSV format.

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

Output:
assessment_id,code,course_id,credits,date,grade,grading_final,grading_homework,grading_midterm,instructor,percentage,schedule,scores,student_id,term,title,total_score,type
ASMT-996269,,CRS-8988,,2026-01-03,B,,,,,94.86,,"[{""question"": 1, ""points_earned"": 8, ""points_possible"": 10}, {""question"": 2, ""points_earned"": 0, ""po",STU-878254,,,71,exam
,FAL106,CRS-4973,4,,,40,30,30,Sharon Martinez,,"[{""week"": 1, ""topic"": ""provide""}, {""week"": 2, ""topic"": ""social""}, {""week"": 3, ""topic"": ""learn""}, {""w",,,Fall 2020,Multi-layered zero-defect time-frame 101,,
,CTQ267,CRS-3901,3,,,40,30,30,Michael Armstrong,,"[{""week"": 1, ""topic"": ""town""}, {""week"": 2, ""topic"": ""our""}, {""week"": 3, ""topic"": ""specific""}, {""week",,,Spring 2022,Visionary 24hour middleware 101,,
,LMS488,CRS-1880,4,,,40,30,30,Nicholas Fox,,"[{""week"": 1, ""topic"": ""as""}, {""week"": 2, ""topic"": ""operation""}, {""week"": 3, ""topic"": ""loss""}, {""week",,,Fall 2020,Configurable multimedia frame 101,,


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

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

Output:
paper_id = "arXiv:2021.48279"
title = "Operative systemic definition"
abstract = "Tv wear teacher under doctor. Eight mention month argue amount how voice."
keywords = [ "month", "southern", "administration",]
citations = 167
[[authors]]
name = "Patricia Owens"
affiliation = "Pearson, Quinn and Owens"
email = "christopher41@example.net"

[[authors]]
name = "Wayne Boyd"
affiliation = "Delacruz-Weaver"
email = "powens@example.net"

[[authors]]
name = "Christopher Castillo"
affiliation = "Lawrence-Caldwell"
email = "amandacarey@example.com"

[publication]
venue = "Cell"
year = 2021
doi = "10.1648/XIrv"


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

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

[Assistant]
Approach:
1. Task: Create student assessment 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:
{
  "total_score": 65,
  "percentage": 51.02,
  "assessment_id": "ASMT-810488"
}


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<lab_result>
<order_date>2026-01-01</order_date>
<panel>Lipid</panel>
<patient_mrn>MRN-952425</patient_mrn>
<result_id>LAB-8958063</result_id>
<results>
<test>Glucose</test>
<value>142.4</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>196.3</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>74.4</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>119.9</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>WBC</test>
<value>99.2</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Glucose</test>
<value>51.3</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Glucose</test>
<value>186.5</value>
<unit>mg/dL</unit>
<flag>low</flag>
</results>
</lab_result>


[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:
{
  "content": "Range condition class leader wrong subject wait. Stop we prevent particular front method. Force item executive employee green large house nation. General doctor material rule head event.\nOne will dog chance. Order away music seem director put upon. Find boy again direction four.",
  "article_id": "ART-9628131",
  "headline": "Re-contextualized logistical paradigm"
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<news_article>
<content>Range condition class leader wrong subject wait. Stop we prevent particular front method. Force item executive employee green large house nation. General doctor material rule head event.
One will dog chance. Order away music seem director put upon. Find boy again direction four.</content>
<article_id>ART-9628131</article_id>
<headline>Re-contextualized logistical paradigm</headline>
</news_article>


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

[User]
Transform this CSV data into JSON format:
abstract,authors,channels,citations,funding_source,keywords,paper_id,period,publication_doi,publication_venue,publication_year,title,top_products,total_revenue,units_sold
,,"[{""name"": ""wholesale"", ""revenue"": 1234153, ""growth"": 40.64}, {""name"": ""online"", ""revenue"": 991509, """,,,,,November 2022,,,,,"[{""sku"": ""SKU-9585"", ""sales"": 30234}, {""sku"": ""SKU-8072"", ""sales"": 57362}, {""sku"": ""SKU-4011"", ""sale",9138741,89798
Determine if industry six quite old. Animal could get create.,"[{""name"": ""Paul Gilbert"", ""affiliation"": ""Francis-Weber"", ""email"": ""warrenbradley@example.org""}, {""n",,18,None,"[""relate"", ""worker"", ""fish"", ""happen""]",arXiv:2021.99969,,10.4439/dSZm,Science,2021,Universal composite projection,,,
Among positive main day time stuff institution hour. Lay religious else of. Key likely growth true d,"[{""name"": ""Benjamin Thomas"", ""affiliation"": ""Greene, Ramsey and Cruz"", ""email"": ""weaveraustin@exampl",,248,"Ballard, Molina and Potts","[""impact"", ""difference"", ""affect""]",arXiv:2023.49216,,10.6728/kpfm,Science,2021,Total exuding info-mediaries,,,
Possible oil part rise. Something our cut push future. Middle necessary quality scientist.,"[{""name"": ""Rose Robinson"", ""affiliation"": ""Callahan, Rodgers and Bird"", ""email"": ""cheyenne54@example",,1,"Parker, Ryan and Sanders","[""offer"", ""do"", ""soon""]",arXiv:2022.65691,,10.2809/wdkh,Cell,2022,Intuitive system-worthy core,,,
On hair dinner adult. Situation begin drop case. System administration one story bank.,"[{""name"": ""Michael Williams"", ""affiliation"": ""Marquez, Murphy and Wood"", ""email"": ""perrysteven@examp",,291,Allen LLC,"[""others"", ""national"", ""people"", ""candidate"", ""long""]",arXiv:2023.62290,,10.9866/XkzR,Cell,2023,Right-sized actuating initiative,,,

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

Output:
{
  "period": "November 2022",
  "total_revenue": 9138741,
  "units_sold": 89798,
  "channels": [
    {
      "name": "wholesale",
      "revenue": 1234153,
      "growth": 40.64
    },
    {
      "name": "online",
      "revenue": 991509,
      "growth": -4.15
    }
  ],
  "top_products": [
    {
      "sku": "SKU-9585",
      "sales": 30234
    },
    {
      "sku": "SKU-8072",
      "sales": 57362
    },
    {
      "sku": "SKU-4011",
      "sales": 249730
    }
  ]
}


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

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

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

Output:
{
  "result_id": "LAB-2604144",
  "patient_mrn": "MRN-906692",
  "order_date": "2026-01-01",
  "panel": "Lipid",
  "results": [
    {
      "test": "Hemoglobin",
      "value": 180.3,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "Glucose",
      "value": 97.8,
      "unit": "mg/dL",
      "flag": "normal"
    },
    {
      "test": "Glucose",
      "value": 88.1,
      "unit": "g/dL",
      "flag": "high"
    },
    {
      "test": "Glucose",
      "value": 65.1,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "Hemoglobin",
      "value": 95.1,
      "unit": "g/dL",
      "flag": "high"
    },
    {
      "test": "Glucose",
      "value": 86.1,
      "unit": "mg/dL",
      "flag": "low"
    },
    {
      "test": "Hemoglobin",
      "value": 152.8,
      "unit": "mg/dL",
      "flag": "normal"
    }
  ]
}


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

[User] Generate prescription data in TOML format.

[Assistant]
Approach:
1. Task: Create prescription 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:
rx_id = "RX-5336793"
patient_mrn = "MRN-644295"
prescriber = "Thomas Ponce"
date = "2026-01-03"
[[medications]]
name = "Atorvastatin"
dosage = "5mg"
frequency = "BID"
quantity = 90

[[medications]]
name = "Atorvastatin"
dosage = "5mg"
frequency = "daily"
quantity = 30

[[medications]]
name = "Atorvastatin"
dosage = "10mg"
frequency = "BID"
quantity = 30


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<news_article>
<article_id>ART-7317178</article_id>
<headline>Sharable 5thgeneration framework</headline>
<author>Judy Garner</author>
<published>2026-01-07T07:35:28.380949</published>

Politics

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

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

Output:
{
  "article_id": "ART-7317178",
  "headline": "Sharable 5thgeneration framework",
  "author": "Judy Garner",
  "published": "2026-01-07T07:35:28.380949",
  "section": "Politics",
  "content": "Cover whole myself late last month authority. Make away choose difficult.\nShoulder so support like let increase improve movie. Gun career hair necessary improve operation detail.",
  "tags": [
    "cover",
    "people",
    "available",
    "above",
    "service"
  ],
  "views": 84087,
  "shares": 2480
}


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

[User] Output transaction record as CSV.

[Assistant]
Approach:
1. Task: Create transaction record in CSV
2. Complexity: 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:
customer_id,items,payment_method,subtotal,tax,timestamp,total,txn_id
5450ecc9-30b8-498f-a527-04ec3de16dd8,"[{""sku"": ""SKU-81880"", ""qty"": 4, ""price"": 401.7}, {""sku"": ""SKU-99718"", ""qty"": 5, ""price"": 334.37}, {""",paypal,258.62,22.79,2026-01-07T13:51:26.258900,1713.37,TXN-79156891
10132979-4691-4152-af15-80222662bea3,"[{""sku"": ""SKU-88079"", ""qty"": 2, ""price"": 438.31}, {""sku"": ""SKU-23721"", ""qty"": 3, ""price"": 92.13}, {""",paypal,1522.29,107.25,2026-01-07T13:51:26.260098,388.72,TXN-23270878
90604ff5-922b-46bf-bd13-e89ee81db4ba,"[{""sku"": ""SKU-31475"", ""qty"": 4, ""price"": 24.63}, {""sku"": ""SKU-63789"", ""qty"": 3, ""price"": 362.95}, {""",apple_pay,371.77,48.24,2026-01-07T13:51:26.260159,1565.55,TXN-95810056
6a33d550-2780-485c-9bc0-045a5b7ae95d,"[{""sku"": ""SKU-68333"", ""qty"": 1, ""price"": 89.84}, {""sku"": ""SKU-87706"", ""qty"": 1, ""price"": 430.12}, {""",apple_pay,825.06,10.18,2026-01-07T13:51:26.260204,675.97,TXN-22647853
c248c988-777d-4910-9055-b69fe393e78f,"[{""sku"": ""SKU-28998"", ""qty"": 5, ""price"": 368.6}, {""sku"": ""SKU-18339"", ""qty"": 4, ""price"": 201.89}]",apple_pay,1315.22,108.49,2026-01-07T13:51:26.260246,2062.65,TXN-55860247


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

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

[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-1120026
patient_mrn: MRN-824701
order_date: '2026-01-06'
panel: CBC
results:
- test: Glucose
  value: 168.8
  unit: g/dL
  flag: high
- test: Glucose
  value: 98.1
  unit: mg/dL
  flag: high
- test: Glucose
  value: 137.9
  unit: mg/dL
  flag: normal
- test: Glucose
  value: 107.7
  unit: g/dL
  flag: low


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

[User] Generate error log data in CSV format.

[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
,,,acbfd7fd-a4ab-431b-a098-ac4537826f14,cedcf075-a01b-42e9-acdc-a300ea843992,03dcbba2-8070-483e-a807-51e4c6301bf5,,,WARNING,Feel garden dark.,,,,,stockService,"[""at another.py:304"", ""at happy.py:331"", ""at record.py:415""]",2026-01-07T13:51:27.875594,
Nice baby protect fill tell. Through word game exist start medical fire.,"[{""name"": ""Brittany Lara"", ""affiliation"": ""Glover and Sons"", ""email"": ""griffithbianca@example.com""},",17,,,,None,"[""yes"", ""pick"", ""education"", ""should"", ""couple""]",,,arXiv:2020.67468,10.9745/viHM,Science,2021,,,,Team-oriented exuding capacity
Shake employee listen network red blue. Nation thing with across. Carry share sometimes analysis ide,"[{""name"": ""Jeffrey Brown"", ""affiliation"": ""Crawford, Caldwell and Robertson"", ""email"": ""desireekane@",69,,,,Todd-Nelson,"[""same"", ""human"", ""as""]",,,arXiv:2021.29416,10.5469/bkUT,Nature,2023,,,,Diverse system-worthy website
Sign minute price read spend. Like me offer shake. Look huge brother agent writer development.,"[{""name"": ""Daniel Pitts"", ""affiliation"": ""Ferrell-Banks"", ""email"": ""zachary40@example.com""}, {""name""",10,,,,"Garcia, Davis and Stanton","[""better"", ""president"", ""check""]",,,arXiv:2022.20309,10.3398/CFZE,Nature,2020,,,,Reduced even-keeled budgetary management


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

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

Politics

<tags>machine</tags>
<tags>fund</tags>
<tags>station</tags>
<tags>our</tags>
<published>2026-01-05T17:58:55.100855</published>
<views>86295</views>
</news_article>

[Assistant]
Approach:
1. Task: Convert news article 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:
{
  "section": "Politics",
  "tags": [
    "machine",
    "fund",
    "station",
    "our"
  ],
  "published": "2026-01-05T17:58:55.100855",
  "views": 86295
}


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

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

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

Output:
category,currency,is_available,name,price,product_id,rating,reviews,specs_dimensions,specs_weight_kg,stock
electronics,USD,True,User-centric tertiary contingency,998.51,PROD-239354,2.36,630,88x23x10cm,0.61,842
clothing,USD,True,Realigned demand-driven monitoring,64.12,PROD-231372,1.52,841,27x31x36cm,29.04,668
books,USD,True,Cross-group didactic website,741.33,PROD-867374,1.77,332,50x17x51cm,16.36,896


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

[User] Output student assessment as YAML.

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

Output:
assessment_id: ASMT-672485
student_id: STU-183204
course_id: CRS-8704
type: quiz
date: '2026-01-01'
scores:
- question: 1
  points_earned: 0
  points_possible: 10
- question: 2
  points_earned: 9
  points_possible: 10
- question: 3
  points_earned: 1
  points_possible: 10
- question: 4
  points_earned: 10
  points_possible: 10
- question: 5
  points_earned: 1
  points_possible: 10
- question: 6
  points_earned: 8
  points_possible: 10
- question: 7
  points_earned: 7
  points_possible: 10
- question: 8
  points_earned: 7
  points_possible: 10
- question: 9
  points_earned: 0
  points_possible: 10
- question: 10
  points_earned: 5
  points_possible: 10
- question: 11
  points_earned: 5
  points_possible: 10
- question: 12
  points_earned: 0
  points_possible: 10
total_score: 82
percentage: 72.48
grade: A


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

[User] Generate product listing data in JSON format.

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

Output:
{
  "product_id": "PROD-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"
  }
}