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

[User]
Transform this CSV data into XML format:
abstract,authors,citations,funding_source,is_available,keywords,paper_id,price,publication_doi,publication_venue,publication_year,rating,specs_dimensions,specs_weight_kg,stock,title
,,,,True,,,743.81,,,,2.69,19x24x69cm,41.33,485,
"Trip region admit white. Off physical sit factor.
Conference entire actually easy defense black. Off","[{""name"": ""Tammy Dawson"", ""affiliation"": ""Nguyen, Johnston and Scott"", ""email"": ""fescobar@example.co",269,None,,"[""three"", ""right"", ""ahead"", ""apply""]",arXiv:2022.95841,,10.4589/Hktw,Nature,2023,,,,,Advanced analyzing model
Much study relationship continue remember method. People reach word than. Our rich treatment which g,"[{""name"": ""Pamela Richard"", ""affiliation"": ""Perez and Sons"", ""email"": ""eric16@example.com""}, {""name""",463,None,,"[""report"", ""word"", ""defense"", ""time"", ""religious""]",arXiv:2024.24718,,10.1516/jRCw,Nature,2021,,,,,Business-focused disintermediate middleware

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<product_listing>
<specs>
<weight_kg>41.33</weight_kg>
<dimensions>19x24x69cm</dimensions>
</specs>
<price>743.81</price>
<is_available>True</is_available>
<rating>2.69</rating>
<stock>485</stock>
</product_listing>


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

[User] Output sales analytics as YAML.

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

Output:
period: 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 XML format. Think step-by-step, then generate syntactically perfect XML.

[User] Output student assessment as XML.

[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-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] Generate lab result data in XML format.

[Assistant]
Approach:
1. Task: Create lab result 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"?>
<lab_result>
<result_id>LAB-9548003</result_id>
<patient_mrn>MRN-322322</patient_mrn>
<order_date>2026-01-03</order_date>
<panel>CMP</panel>
<results>
<test>Glucose</test>
<value>67.0</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>66.7</value>
<unit>mg/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Glucose</test>
<value>118.1</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>198.6</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Glucose</test>
<value>167.9</value>
<unit>mg/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>143.5</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Glucose</test>
<value>150.3</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
</lab_result>


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

[User] Create a CSV representation of customer review.

[Assistant]
Approach:
1. Task: Create customer review 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,content,currency,date,helpful_votes,is_available,name,price,product_id,rating,review_id,reviews,specs_dimensions,specs_weight_kg,stock,title,user_id,verified_purchase
,"Chair painting shake city kind good though. Find reality water support key.
Fly party couple product",,2026-01-03,78,,,,PROD-375265,1,REV-7250124,,,,,Very responsibility coach economy sea public you.,48302d32-0445-4405-afc6-604ef6300782,True
electronics,,USD,,,True,Universal neutral function,429.38,PROD-319216,4.22,,148,65x94x100cm,21.4,416,,,
clothing,,USD,,,True,Proactive maximized emulation,617.13,PROD-960862,4.88,,767,77x65x72cm,31.38,920,,,
electronics,,USD,,,True,Secured tertiary middleware,488.02,PROD-145422,4.57,,492,33x70x73cm,16.37,747,,,


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

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

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

Output:
{
  "review_id": "REV-7169946",
  "product_id": "PROD-908355",
  "user_id": "109a43ce-0a9d-47ca-b5cc-5940dcb3a5c0",
  "rating": 3,
  "title": "Suffer kid daughter race still baby.",
  "content": "Young lot card leave book. Thank agency tree shake. Manage organization reduce from sort soldier.\nRun rich marriage parent discover kitchen. Positive person baby list positive really range.",
  "date": "2026-01-05",
  "verified_purchase": true,
  "helpful_votes": 3
}


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

[User] Generate prescription data in YAML format.

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

Output:
rx_id: RX-9442688
patient_mrn: MRN-277514
prescriber: Timothy Goodman
date: '2026-01-04'
medications:
- name: Metformin
  dosage: 20mg
  frequency: TID
  quantity: 30
- name: Metformin
  dosage: 5mg
  frequency: BID
  quantity: 30
- name: Lisinopril
  dosage: 5mg
  frequency: TID
  quantity: 30


[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"?>
<course_syllabus>
<schedule>
<week>1</week>
<topic>table</topic>
</schedule>
<schedule>
<week>2</week>
<topic>team</topic>
</schedule>
<schedule>
<week>3</week>
<topic>miss</topic>
</schedule>
<schedule>
<week>4</week>
<topic>face</topic>
</schedule>
<schedule>
<week>5</week>
<topic>sort</topic>
</schedule>
<schedule>
<week>6</week>
<topic>board</topic>
</schedule>
<schedule>
<week>7</week>
<topic>effect</topic>
</schedule>
<schedule>
<week>8</week>
<topic>still</topic>
</schedule>
<schedule>
<week>9</week>
<topic>training</topic>
</schedule>
<schedule>
<week>10</week>
<topic>different</topic>
</schedule>
GHC481
<grading>
<homework>30</homework>
<midterm>30</midterm>
<final>40</final>
</grading>
<term>Spring 2020</term>
<credits>4</credits>
</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:
{
  "schedule": [
    {
      "week": 1,
      "topic": "table"
    },
    {
      "week": 2,
      "topic": "team"
    },
    {
      "week": 3,
      "topic": "miss"
    },
    {
      "week": 4,
      "topic": "face"
    },
    {
      "week": 5,
      "topic": "sort"
    },
    {
      "week": 6,
      "topic": "board"
    },
    {
      "week": 7,
      "topic": "effect"
    },
    {
      "week": 8,
      "topic": "still"
    },
    {
      "week": 9,
      "topic": "training"
    },
    {
      "week": 10,
      "topic": "different"
    }
  ],
  "code": "GHC481",
  "grading": {
    "homework": 30,
    "midterm": 30,
    "final": 40
  },
  "term": "Spring 2020",
  "credits": 4
}


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

[User] Output product listing as YAML.

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

Output:
product_id: PROD-830951
name: Multi-layered tangible superstructure
category: clothing
price: 269.31
currency: USD
stock: 322
is_available: true
rating: 2.21
reviews: 733
specs:
  weight_kg: 46.04
  dimensions: 75x77x31cm


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

[User]
Reformat the data below from JSON to TOML:
{
  "instructor": "Ryan Griffin",
  "course_id": "CRS-4864",
  "code": "NLW161"
}

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

Output:
instructor = "Ryan Griffin"
course_id = "CRS-4864"
code = "NLW161"


[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,Multi-layered tangible superstructure,269.31,PROD-830951,2.21,733,75x77x31cm,46.04,322
electronics,USD,True,Mandatory upward-trending infrastructure,395.22,PROD-328147,1.73,677,73x69x94cm,41.56,622
electronics,USD,True,Secured executive capability,246.96,PROD-697540,3.05,531,24x49x45cm,35.1,786
clothing,USD,True,Profound foreground core,116.43,PROD-609593,2.78,701,65x36x23cm,32.7,540


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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<lab_result>
<result_id>LAB-9017474</result_id>
<patient_mrn>MRN-783803</patient_mrn>
<order_date>2026-01-04</order_date>
<panel>Lipid</panel>
<results>
<test>Glucose</test>
<value>65.6</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Glucose</test>
<value>160.2</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>WBC</test>
<value>142.4</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Glucose</test>
<value>179.9</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>97.3</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>148.5</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>174.6</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]
Reformat the data below from YAML to JSON:
error_id: ff91c212-6cce-4ac2-978d-0740381882de
timestamp: '2026-01-07T13:51:27.679071'
level: WARNING
service: drawService
message: Support red list product forget cut speak.
stack_trace:
- at girl.py:186
- at hold.py:186
context:
  user_id: 473e683b-291e-461f-b848-d224b7dcbd8b
  request_id: 454a35ad-23ee-42a8-9d57-dbf5cedbef74

[Assistant]
Approach:
1. Task: Convert error log from YAML 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": "ff91c212-6cce-4ac2-978d-0740381882de",
  "timestamp": "2026-01-07T13:51:27.679071",
  "level": "WARNING",
  "service": "drawService",
  "message": "Support red list product forget cut speak.",
  "stack_trace": [
    "at girl.py:186",
    "at hold.py:186"
  ],
  "context": {
    "user_id": "473e683b-291e-461f-b848-d224b7dcbd8b",
    "request_id": "454a35ad-23ee-42a8-9d57-dbf5cedbef74"
  }
}


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

[User] Create a TOML representation of error log.

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

Output:
message = "Baby inside high our should character study quickly."
stack_trace = [ "at standard.py:486", "at memory.py:53", "at team.py:342",]
timestamp = "2026-01-07T13:51:25.507604"

[context]
user_id = "b89e754b-fd03-47c7-9600-09a7cb6d3517"
request_id = "0aea7b7e-f431-4209-a4db-008320d27043"


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<social_media_post>
<post_id>POST-86898750</post_id>
<platform>instagram</platform>
<user_id>a47ec401-ca4e-44b5-afc7-6c2b372f589e</user_id>
<username>dylan00</username>
<content>Might north politics.
Moment bad without change physical store call. Enjoy question state student political boy tonight.
Soon ten last small develop left enter. Health lead bank and air capital save.</content>
<timestamp>2026-01-07T13:51:25.591017</timestamp>
<hashtags>#kid</hashtags>
<hashtags>#off</hashtags>
<hashtags>#school</hashtags>
<hashtags>#fund</hashtags>
<engagement>
<likes>9146</likes>
<shares>205</shares>
<comments>18</comments>
</engagement>
</social_media_post>

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

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


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

[User] Output research paper as XML.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<research_paper>
<paper_id>arXiv:2023.57642</paper_id>
<title>Organized clear-thinking projection</title>
<authors>
<name>Thomas Harrison</name>
<affiliation>Benjamin, Peterson and James</affiliation>
<email>martinjoseph@example.com</email>
</authors>
<authors>
<name>Samantha Phillips</name>
<affiliation>Carpenter Ltd</affiliation>
<email>hawkinssarah@example.com</email>
</authors>
<abstract>Leg third those over. Almost state money hear condition little.
Manager minute writer manager. Walk hand situation similar media back fill huge.</abstract>
<keywords>decade</keywords>
<keywords>kitchen</keywords>
<keywords>discover</keywords>
<keywords>wide</keywords>
<publication>
<venue>Cell</venue>
<year>2023</year>
<doi>10.5371/HWME</doi>
</publication>
<citations>306</citations>
<funding_source />
</research_paper>


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

[User] Create a TOML representation of lab result.

[Assistant]
Approach:
1. Task: Create lab result in TOML
2. Complexity: 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:
result_id = "LAB-5490961"
patient_mrn = "MRN-709917"
order_date = "2026-01-03"
panel = "CBC"
[[results]]
test = "Glucose"
value = 146.9
unit = "mg/dL"
flag = "high"

[[results]]
test = "Hemoglobin"
value = 119.4
unit = "g/dL"
flag = "low"

[[results]]
test = "WBC"
value = 95.1
unit = "g/dL"
flag = "low"

[[results]]
test = "Hemoglobin"
value = 73.3
unit = "g/dL"
flag = "high"

[[results]]
test = "Glucose"
value = 166.8
unit = "g/dL"
flag = "low"

[[results]]
test = "WBC"
value = 98.8
unit = "g/dL"
flag = "high"


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

[User]
Reformat the data below from TOML to JSON:
experiment_id = "EXP-690622"
title = "Effect of drug on effect"
conclusion = "non-significant"
[[results]]
metric = "efficacy"
baseline = 65.65
endpoint = 47.19
p_value = 0.4009

[[results]]
metric = "efficacy"
baseline = 18.88
endpoint = 49.79
p_value = 0.0184

[[results]]
metric = "efficacy"
baseline = 32.37
endpoint = 97.44
p_value = 0.3919

[methodology]
design = "RCT"
sample_size = 718
duration_days = 247

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

Output:
{
  "experiment_id": "EXP-690622",
  "title": "Effect of drug on effect",
  "methodology": {
    "design": "RCT",
    "sample_size": 718,
    "duration_days": 247
  },
  "results": [
    {
      "metric": "efficacy",
      "baseline": 65.65,
      "endpoint": 47.19,
      "p_value": 0.4009
    },
    {
      "metric": "efficacy",
      "baseline": 18.88,
      "endpoint": 49.79,
      "p_value": 0.0184
    },
    {
      "metric": "efficacy",
      "baseline": 32.37,
      "endpoint": 97.44,
      "p_value": 0.3919
    }
  ],
  "conclusion": "non-significant"
}


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

[User] Create a YAML representation of transaction record.

[Assistant]
Approach:
1. Task: Create transaction record 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:
payment_method: paypal
customer_id: fe237049-a4a1-4a5c-af14-940bbb31d0e7
total: 1227.54


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

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

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

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


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

[User] Generate customer review data in XML format.

[Assistant]
Approach:
1. Task: Create customer review 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"?>
<customer_review>
<review_id>REV-8075236</review_id>
<product_id>PROD-326180</product_id>
<user_id>e70c9373-b1ad-41a5-8939-e3c28041d8f5</user_id>
<rating>4</rating>
<title>Most teacher Mrs system watch.</title>
<content>Address music major. Magazine three about. Security ready result improve.
Hand other collection name wife remain. Speech perhaps newspaper. Talk place third about writer billion physical.</content>
<date>2026-01-03</date>
<verified_purchase>False</verified_purchase>
<helpful_votes>50</helpful_votes>
</customer_review>


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

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

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

Output:
{
  "product_id": "PROD-831490",
  "name": "Seamless optimal task-force",
  "category": "electronics",
  "price": 975.8,
  "currency": "USD",
  "stock": 924,
  "is_available": true,
  "rating": 2.71,
  "reviews": 121,
  "specs": {
    "weight_kg": 17.77,
    "dimensions": "52x27x46cm"
  }
}


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<product_listing>
<product_id>PROD-986141</product_id>
<name>Focused neutral encoding</name>
<category>books</category>
<price>14.45</price>
<currency>USD</currency>
<stock>826</stock>
<is_available>True</is_available>
<rating>4.59</rating>
<reviews>564</reviews>
<specs>
<weight_kg>27.7</weight_kg>
<dimensions>42x99x90cm</dimensions>
</specs>
</product_listing>


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

[User] Generate news article data in JSON format.

[Assistant]
Approach:
1. Task: Create news article 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:
{
  "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"
}


[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:
{
  "post_id": "POST-69367106",
  "platform": "twitter",
  "user_id": "7643b70d-1c60-436f-974e-7bc6cee5e032",
  "username": "gordonalexander",
  "content": "See personal couple road president most next. Laugh teach lawyer character work present.\nPage give education middle. Couple save view media instead police guy. Enough test notice capital size.",
  "timestamp": "2026-01-07T13:51:25.991400",
  "hashtags": [
    "#PM",
    "#stage",
    "#government"
  ],
  "engagement": {
    "likes": 1911,
    "shares": 761,
    "comments": 62
  }
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<social_media_post>
<post_id>POST-69367106</post_id>
<platform>twitter</platform>
<user_id>7643b70d-1c60-436f-974e-7bc6cee5e032</user_id>
<username>gordonalexander</username>
<content>See personal couple road president most next. Laugh teach lawyer character work present.
Page give education middle. Couple save view media instead police guy. Enough test notice capital size.</content>
<timestamp>2026-01-07T13:51:25.991400</timestamp>
<hashtags>#PM</hashtags>
<hashtags>#stage</hashtags>
<hashtags>#government</hashtags>
<engagement>
<likes>1911</likes>
<shares>761</shares>
<comments>62</comments>
</engagement>
</social_media_post>


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

[User] Create a TOML representation of course syllabus.

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

Output:
course_id = "CRS-1797"
code = "QAA477"
title = "User-friendly composite interface 101"
instructor = "Selena Walker"
credits = 4
term = "Fall 2024"
[[schedule]]
week = 1
topic = "all"

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

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

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

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

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

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

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


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

[User] Output product listing as TOML.

[Assistant]
Approach:
1. Task: Create product listing 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:
product_id = "PROD-361703"
name = "Grass-roots methodical neural-net"
category = "books"
price = 156.58
currency = "USD"
stock = 3
is_available = true
rating = 3.73
reviews = 915

[specs]
weight_kg = 25.41
dimensions = "90x40x81cm"


[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-1812594</result_id>
<patient_mrn>MRN-755137</patient_mrn>
<order_date>2026-01-06</order_date>
<panel>CMP</panel>
<results>
<test>Glucose</test>
<value>131.9</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Glucose</test>
<value>183.7</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>WBC</test>
<value>130.1</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>178.3</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
</lab_result>


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

[User] Create a TOML representation of student assessment.

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

Output:
total_score = 96
percentage = 61.11
student_id = "STU-785727"


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<course_syllabus>
<course_id>CRS-5704</course_id>
BXM405
<title>Profit-focused responsive throughput 101</title>
<instructor>Emily Bryan</instructor>
<credits>3</credits>
<term>Spring 2021</term>
<schedule>
<week>1</week>
<topic>southern</topic>
</schedule>
<schedule>
<week>2</week>
<topic>raise</topic>
</schedule>
<schedule>
<week>3</week>
<topic>across</topic>
</schedule>
<schedule>
<week>4</week>
<topic>teacher</topic>
</schedule>
<schedule>
<week>5</week>
<topic>service</topic>
</schedule>
<schedule>
<week>6</week>
<topic>body</topic>
</schedule>
<schedule>
<week>7</week>
<topic>practice</topic>
</schedule>
<schedule>
<week>8</week>
<topic>authority</topic>
</schedule>
<schedule>
<week>9</week>
<topic>throw</topic>
</schedule>
<schedule>
<week>10</week>
<topic>second</topic>
</schedule>
<schedule>
<week>11</week>
<topic>authority</topic>
</schedule>
<grading>
<homework>30</homework>
<midterm>30</midterm>
<final>40</final>
</grading>
</course_syllabus>

[Assistant]
Approach:
1. Task: Convert course syllabus from XML to JSON
2. Complexity: 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:
{
  "course_id": "CRS-5704",
  "code": "BXM405",
  "title": "Profit-focused responsive throughput 101",
  "instructor": "Emily Bryan",
  "credits": 3,
  "term": "Spring 2021",
  "schedule": [
    {
      "week": 1,
      "topic": "southern"
    },
    {
      "week": 2,
      "topic": "raise"
    },
    {
      "week": 3,
      "topic": "across"
    },
    {
      "week": 4,
      "topic": "teacher"
    },
    {
      "week": 5,
      "topic": "service"
    },
    {
      "week": 6,
      "topic": "body"
    },
    {
      "week": 7,
      "topic": "practice"
    },
    {
      "week": 8,
      "topic": "authority"
    },
    {
      "week": 9,
      "topic": "throw"
    },
    {
      "week": 10,
      "topic": "second"
    },
    {
      "week": 11,
      "topic": "authority"
    }
  ],
  "grading": {
    "homework": 30,
    "midterm": 30,
    "final": 40
  }
}


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

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

[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
b5aca191-66fe-49e0-85ce-2d363d5ef454,"[{""sku"": ""SKU-56664"", ""qty"": 2, ""price"": 285.83}, {""sku"": ""SKU-25305"", ""qty"": 1, ""price"": 45.15}, {""",apple_pay,199.93,118.13,2026-01-07T13:51:26.163076,913.78,TXN-30876983
544b1a27-6e43-4944-b179-f85638e23d22,"[{""sku"": ""SKU-60137"", ""qty"": 3, ""price"": 261.13}, {""sku"": ""SKU-48333"", ""qty"": 3, ""price"": 380.57}, {",paypal,931.28,109.14,2026-01-07T13:51:26.164115,845.98,TXN-83290772
a4ac7a51-32da-4054-92a2-b660f5f5cbb7,"[{""sku"": ""SKU-70345"", ""qty"": 2, ""price"": 292.91}]",paypal,1244.24,96.76,2026-01-07T13:51:26.164183,2024.08,TXN-21793096


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

[User] Create a JSON representation of experiment result.

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

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


[System] You are an expert in 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-3836429",
  "product_id": "PROD-852988",
  "user_id": "39a3d2bd-fb84-4dfc-9cb6-45bd3ebddca0",
  "rating": 2,
  "title": "Report thus get describe identify.",
  "content": "Or dog never any center population. Program it they Republican over step. Who television finish true game.\nList catch candidate west research. Meeting many imagine.",
  "date": "2026-01-01",
  "verified_purchase": false,
  "helpful_votes": 23
}


[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,Organized didactic parallelism,68.12,PROD-110536,1.45,277,33x70x14cm,1.85,153
clothing,USD,True,Open-source logistical groupware,632.55,PROD-778599,2.65,140,11x18x45cm,34.56,706
books,USD,True,Grass-roots exuding flexibility,652.52,PROD-159101,2.36,920,44x38x37cm,15.88,76
books,USD,True,Open-source solution-oriented encoding,677.43,PROD-428849,1.76,160,23x34x11cm,19.99,453


[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: medium - 5-8 fields, 2-3 levels
3. Format rules: proper braces/brackets, quoted keys, correct value types
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
{
  "period": "November 2021",
  "total_revenue": 8992427,
  "units_sold": 30636,
  "channels": [
    {
      "name": "wholesale",
      "revenue": 3169564,
      "growth": 42.35
    },
    {
      "name": "retail",
      "revenue": 2683860,
      "growth": 36.55
    }
  ],
  "top_products": [
    {
      "sku": "SKU-9614",
      "sales": 412171
    },
    {
      "sku": "SKU-7573",
      "sales": 203488
    },
    {
      "sku": "SKU-4372",
      "sales": 55896
    }
  ]
}


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

[User] Generate error log data in YAML format.

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

Output:
error_id: 2d978d26-6fd7-4641-b202-43ebc0760711
timestamp: '2026-01-07T13:51:26.663970'
level: WARNING
service: someoneService
message: Inside live none value unit Republican black.
stack_trace:
- at role.py:276
- at loss.py:371
context:
  user_id: 26f1b94c-c76e-47ab-9121-a3f8ec11053f
  request_id: ce096dca-f53f-40bf-822d-ed29d8ca8dd9


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

[User] Output transaction record as YAML.

[Assistant]
Approach:
1. Task: Create transaction record 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:
subtotal: 1655.93
items:
- sku: SKU-62708
  qty: 3
  price: 121.39
tax: 19.12
total: 1424.63


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

[User]
Convert the following JSON to XML:
{
  "rx_id": "RX-6885629",
  "prescriber": "John Cook",
  "medications": [
    {
      "name": "Metformin",
      "dosage": "5mg",
      "frequency": "daily",
      "quantity": 30
    },
    {
      "name": "Atorvastatin",
      "dosage": "5mg",
      "frequency": "BID",
      "quantity": 90
    },
    {
      "name": "Lisinopril",
      "dosage": "5mg",
      "frequency": "TID",
      "quantity": 60
    }
  ],
  "date": "2026-01-02",
  "patient_mrn": "MRN-741538"
}

[Assistant]
Approach:
1. Task: Convert prescription 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"?>
<prescription>
<rx_id>RX-6885629</rx_id>
<prescriber>John Cook</prescriber>
<medications>
<name>Metformin</name>
<dosage>5mg</dosage>
<frequency>daily</frequency>
<quantity>30</quantity>
</medications>
<medications>
<name>Atorvastatin</name>
<dosage>5mg</dosage>
<frequency>BID</frequency>
<quantity>90</quantity>
</medications>
<medications>
<name>Lisinopril</name>
<dosage>5mg</dosage>
<frequency>TID</frequency>
<quantity>60</quantity>
</medications>
<date>2026-01-02</date>
<patient_mrn>MRN-741538</patient_mrn>
</prescription>


[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 = "92d36993-19b1-4c19-9b64-8b4669c6636f"
timestamp = "2026-01-07T13:51:27.222487"
level = "WARNING"
service = "voiceService"
message = "Analysis beautiful attack blue eye."
stack_trace = [ "at well.py:163", "at will.py:421", "at run.py:384", "at TV.py:103",]

[context]
user_id = "c92bcb8f-c109-47f8-aa13-b43737a1fc38"
request_id = "f4cb6737-30c9-41ef-814b-34c3ec971deb"


[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:
{
  "openapi": "3.0.0",
  "paths": {
    "/somebody": {
      "get": {
        "summary": "Threat common organization project.",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          },
          {
            "name": "param1",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  },
  "info": {
    "title": "Networked system-worthy project API",
    "version": "1.0.0"
  }
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<api_specification>
<openapi>3.0.0</openapi>
<paths>
</somebody>
<get>
<summary>Threat common organization project.</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>
<//somebody>
</paths>
<info>
<title>Networked system-worthy project API</title>
<version>1.0.0</version>
</info>
</api_specification>


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

[User] Output news article as YAML.

[Assistant]
Approach:
1. Task: Create news article 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:
views: 92789
content: 'Couple and teacher radio compare consumer. Pass thing much rather light.

  Foot four country subject first interview. Defense TV artist to of. Fund miss window
  scene.

  Wish successful movement city door politics measure. Police media TV out word remain
  as. Report option appear station example role.'
shares: 213
headline: Re-engineered composite Local Area Network
tags:
- couple
- this
- themselves
- whom


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

[User] Create a XML representation of financial report.

[Assistant]
Approach:
1. Task: Create financial report 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"?>
<financial_report>
<company>Rodriguez, Curry and Yates</company>
<ticker>KWAZ</ticker>
<quarter>Q1 2020</quarter>
<revenue>4863925</revenue>
<expenses>55129980</expenses>
<net_income>12179320</net_income>
<eps>7.94</eps>
<metrics>
<profit_margin>29.26</profit_margin>
<roe>9.63</roe>
</metrics>
</financial_report>


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

[User] Output research paper as XML.

[Assistant]
Approach:
1. Task: Create research paper 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"?>
<research_paper>
<title>Polarized methodical algorithm</title>
<authors>
<name>Caroline Barnes</name>
<affiliation>Parker Ltd</affiliation>
<email>angelajackson@example.net</email>
</authors>
<authors>
<name>Mario Boyd</name>
<affiliation>Johnson, Barber and Higgins</affiliation>
<email>lfuller@example.com</email>
</authors>
<funding_source />
</research_paper>


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

[User] Output lab result as JSON.

[Assistant]
Approach:
1. Task: Create lab result 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:
{
  "result_id": "LAB-4504067",
  "patient_mrn": "MRN-266543",
  "order_date": "2026-01-05",
  "panel": "Lipid",
  "results": [
    {
      "test": "Glucose",
      "value": 181.1,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 164.3,
      "unit": "mg/dL",
      "flag": "low"
    },
    {
      "test": "Glucose",
      "value": 140.0,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 113.0,
      "unit": "mg/dL",
      "flag": "high"
    }
  ]
}


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

[User] Output student assessment as JSON.

[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-503362",
  "student_id": "STU-235214",
  "course_id": "CRS-9952",
  "type": "assignment",
  "date": "2026-01-01",
  "scores": [
    {
      "question": 1,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 0,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 0,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 6,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 5,
      "points_possible": 10
    },
    {
      "question": 9,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 10,
      "points_earned": 0,
      "points_possible": 10
    },
    {
      "question": 11,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 12,
      "points_earned": 8,
      "points_possible": 10
    }
  ],
  "total_score": 52,
  "percentage": 94.35,
  "grade": "C"
}


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

[User] Produce a CSV document for a prescription.

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

Output:
date,medications,patient_mrn,prescriber,rx_id
2026-01-03,"[{""name"": ""Metformin"", ""dosage"": ""10mg"", ""frequency"": ""daily"", ""quantity"": 90}, {""name"": ""Metformin""",MRN-215469,Jeremy Hatfield,RX-5305677
2026-01-04,"[{""name"": ""Atorvastatin"", ""dosage"": ""5mg"", ""frequency"": ""BID"", ""quantity"": 30}, {""name"": ""Metformin""",MRN-542538,John Jones,RX-2389955
2026-01-01,"[{""name"": ""Metformin"", ""dosage"": ""20mg"", ""frequency"": ""TID"", ""quantity"": 90}, {""name"": ""Metformin"", ",MRN-275931,David Simon,RX-6950870
2026-01-03,"[{""name"": ""Metformin"", ""dosage"": ""20mg"", ""frequency"": ""TID"", ""quantity"": 30}, {""name"": ""Lisinopril"",",MRN-303822,Jacob Henry,RX-3195112
2026-01-01,"[{""name"": ""Metformin"", ""dosage"": ""5mg"", ""frequency"": ""BID"", ""quantity"": 60}]",MRN-420472,Dylan Reed,RX-3776821


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

[User] Generate research paper data in JSON format.

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

Output:
{
  "paper_id": "arXiv:2020.86983",
  "title": "Reverse-engineered national Graphical User Interface",
  "authors": [
    {
      "name": "Wesley Murphy",
      "affiliation": "Nunez, Meyer and Snow",
      "email": "nina74@example.net"
    },
    {
      "name": "Richard Morgan",
      "affiliation": "Hall-Jones",
      "email": "justin85@example.org"
    },
    {
      "name": "Anthony Johnson",
      "affiliation": "Kelley-Murphy",
      "email": "srichmond@example.com"
    }
  ],
  "abstract": "Sure finally site who truth. Close stop when low. Check news mother democratic.",
  "keywords": [
    "old",
    "indeed",
    "general",
    "claim",
    "every"
  ],
  "publication": {
    "venue": "Nature",
    "year": 2024,
    "doi": "10.2539/QMDE"
  },
  "citations": 221,
  "funding_source": null
}


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

[User] Output student assessment as TOML.

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

Output:
assessment_id = "ASMT-225883"
student_id = "STU-314827"
course_id = "CRS-2408"
type = "quiz"
date = "2026-01-01"
total_score = 99
percentage = 82.0
grade = "B"
[[scores]]
question = 1
points_earned = 8
points_possible = 10

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

[[scores]]
question = 3
points_earned = 9
points_possible = 10

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

[[scores]]
question = 5
points_earned = 2
points_possible = 10

[[scores]]
question = 6
points_earned = 3
points_possible = 10

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

[[scores]]
question = 8
points_earned = 4
points_possible = 10

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

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

[[scores]]
question = 11
points_earned = 4
points_possible = 10

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

[[scores]]
question = 13
points_earned = 8
points_possible = 10


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<research_paper>
<paper_id>arXiv:2023.47681</paper_id>
<title>Devolved bi-directional info-mediaries</title>
<authors>
<name>Christian Randolph</name>
<affiliation>Hunt-Haynes</affiliation>
<email>patrickmaddox@example.net</email>
</authors>
<authors>
<name>Allen Lewis</name>
<affiliation>Owen PLC</affiliation>
<email>alexanderhenry@example.net</email>
</authors>
<authors>
<name>Cody Martin</name>
<affiliation>Mcknight PLC</affiliation>
<email>michael00@example.org</email>
</authors>
<abstract>Help field ten it. Pick eight last star pull. Act politics discuss.</abstract>
<keywords>hard</keywords>
<keywords>open</keywords>
<keywords>right</keywords>
<keywords>could</keywords>
<keywords>sea</keywords>
<publication>
<venue>Cell</venue>
<year>2023</year>
<doi>10.8057/cNYF</doi>
</publication>
<citations>411</citations>
<funding_source />
</research_paper>


[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-4787173",
  "product_id": "PROD-746934",
  "user_id": "a1638e54-91af-4e5f-be10-465327f3fbf6",
  "rating": 4,
  "title": "Rock company surface either million.",
  "content": "Suddenly plant stay thank project hand me. Commercial his road carry training trip.",
  "date": "2026-01-02",
  "verified_purchase": true,
  "helpful_votes": 3
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<review_id>REV-4787173</review_id>
<product_id>PROD-746934</product_id>
<user_id>a1638e54-91af-4e5f-be10-465327f3fbf6</user_id>
<rating>4</rating>
<title>Rock company surface either million.</title>
<content>Suddenly plant stay thank project hand me. Commercial his road carry training trip.</content>
<date>2026-01-02</date>
<verified_purchase>True</verified_purchase>
<helpful_votes>3</helpful_votes>
</customer_review>


[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-7937835</note_id>
<patient>
<mrn>MRN-749785</mrn>
<age>66</age>
<gender>M</gender>
</patient>
<encounter_date>2026-01-06</encounter_date>
<chief_complaint>chest pain</chief_complaint>
<vitals>
<bp>179/85</bp>

81

<temp_f>101.7</temp_f>
</vitals>
<assessment>
<problem>hypertension</problem>
<icd10>I52</icd10>
</assessment>
<assessment>
<problem>diabetes</problem>
<icd10>J76</icd10>
</assessment>
</clinical_note>


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

[User] Create a CSV representation of student assessment.

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

Output:
code,course_id,credits,grade,grading_final,grading_homework,grading_midterm,instructor,schedule,term,title,total_score
,CRS-4519,,A,,,,,,,,75
OKW118,CRS-9763,3,,40,30,30,Taylor Cannon,"[{""week"": 1, ""topic"": ""bank""}, {""week"": 2, ""topic"": ""service""}, {""week"": 3, ""topic"": ""since""}, {""wee",Spring 2022,Team-oriented contextually-based software 101,
HXY139,CRS-5032,4,,40,30,30,Andrew Stewart,"[{""week"": 1, ""topic"": ""like""}, {""week"": 2, ""topic"": ""explain""}, {""week"": 3, ""topic"": ""edge""}, {""week",Spring 2023,Reactive systematic middleware 101,
DFQ441,CRS-3279,3,,40,30,30,Michael Sanders,"[{""week"": 1, ""topic"": ""yard""}, {""week"": 2, ""topic"": ""any""}, {""week"": 3, ""topic"": ""major""}, {""week"": ",Fall 2022,Multi-tiered dynamic middleware 101,


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

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

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

Output:
post_id = "POST-52722833"
platform = "facebook"
user_id = "d42576ea-a78d-4261-852d-cbcc2fd55da5"
username = "justin96"
content = "Southern write three operation throw interest whether.\nDecade quality training employee. Financial out position catch finish author. Past over in create.\nNice reduce try contain future back customer."
timestamp = "2026-01-07T13:51:26.716888"
hashtags = [ "#report", "#newspaper",]

[engagement]
likes = 8106
shares = 850
comments = 244


[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-5956795
patient_mrn: MRN-953048
order_date: '2026-01-05'
panel: CBC
results:
- test: Glucose
  value: 138.6
  unit: g/dL
  flag: high
- test: Hemoglobin
  value: 69.4
  unit: g/dL
  flag: normal
- test: Hemoglobin
  value: 89.7
  unit: g/dL
  flag: normal
- test: Hemoglobin
  value: 191.9
  unit: g/dL
  flag: low
- test: WBC
  value: 169.5
  unit: mg/dL
  flag: low
- test: Glucose
  value: 187.7
  unit: mg/dL
  flag: low
- test: WBC
  value: 120.0
  unit: mg/dL
  flag: high


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<prescription>
<rx_id>RX-9001624</rx_id>
<patient_mrn>MRN-695608</patient_mrn>
<prescriber>Stephen Davis</prescriber>
<date>2026-01-05</date>
<medications>
<name>Lisinopril</name>
<dosage>20mg</dosage>
<frequency>daily</frequency>
<quantity>90</quantity>
</medications>
</prescription>

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

Output:
{
  "rx_id": "RX-9001624",
  "patient_mrn": "MRN-695608",
  "prescriber": "Stephen Davis",
  "date": "2026-01-05",
  "medications": [
    {
      "name": "Lisinopril",
      "dosage": "20mg",
      "frequency": "daily",
      "quantity": 90
    }
  ]
}


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

[User]
Convert the following JSON to XML:
{
  "contract_id": "CTR-324198",
  "parties": [
    {
      "name": "Alvarado-Barnes",
      "role": "party_a"
    },
    {
      "name": "Lopez, Price and Melendez",
      "role": "party_b"
    }
  ],
  "effective_date": "2026-01-06",
  "term_months": 34,
  "value": 725205,
  "status": "pending"
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<contract>
<contract_id>CTR-324198</contract_id>
<parties>
<name>Alvarado-Barnes</name>
<role>party_a</role>
</parties>
<parties>
<name>Lopez, Price and Melendez</name>
<role>party_b</role>
</parties>
<effective_date>2026-01-06</effective_date>
<term_months>34</term_months>
<value>725205</value>
<status>pending</status>
</contract>


[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:
{
  "rx_id": "RX-8706225",
  "patient_mrn": "MRN-970748",
  "prescriber": "Brady Keller",
  "date": "2026-01-01",
  "medications": [
    {
      "name": "Lisinopril",
      "dosage": "5mg",
      "frequency": "TID",
      "quantity": 30
    }
  ]
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<prescription>
<rx_id>RX-8706225</rx_id>
<patient_mrn>MRN-970748</patient_mrn>
<prescriber>Brady Keller</prescriber>
<date>2026-01-01</date>
<medications>
<name>Lisinopril</name>
<dosage>5mg</dosage>
<frequency>TID</frequency>
<quantity>30</quantity>
</medications>
</prescription>


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

[User] Generate contract data in XML format.

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


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

[User] Produce a JSON document for a contract.

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

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


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

[User] Create a XML representation of contract.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<contract>
<contract_id>CTR-784600</contract_id>
<parties>
<name>Snyder-Thornton</name>
<role>party_a</role>
</parties>
<parties>
<name>Oliver Group</name>
<role>party_b</role>
</parties>
<effective_date>2026-01-06</effective_date>
<term_months>16</term_months>
<value>53888</value>
<status>active</status>
</contract>


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

[User] Generate lab result data in YAML format.

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

Output:
result_id: LAB-4504067
patient_mrn: MRN-266543
order_date: '2026-01-05'
panel: Lipid
results:
- test: Glucose
  value: 181.1
  unit: g/dL
  flag: normal
- test: Hemoglobin
  value: 164.3
  unit: mg/dL
  flag: low
- test: Glucose
  value: 140.0
  unit: g/dL
  flag: normal
- test: Hemoglobin
  value: 113.0
  unit: mg/dL
  flag: high


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

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

[Assistant]
Approach:
1. Task: Create social media post 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:
post_id: POST-15490463
platform: instagram
user_id: dcf0c28f-6ad6-4153-873b-0cd39fa73a46
username: allenjames
content: 'Eight television free focus window leave. Education Democrat past music
  mother able. Fund season represent when analysis movement.

  Everything over rich serious forget. Fire particular western.'
timestamp: '2026-01-07T13:51:27.338072'
hashtags:
- '#left'
- '#long'
- '#instead'
- '#budget'
engagement:
  likes: 85
  shares: 112
  comments: 292


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

[User] Generate course syllabus data in JSON format.

[Assistant]
Approach:
1. Task: Create course syllabus 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:
{
  "course_id": "CRS-1797",
  "code": "QAA477",
  "title": "User-friendly composite interface 101",
  "instructor": "Selena Walker",
  "credits": 4,
  "term": "Fall 2024",
  "schedule": [
    {
      "week": 1,
      "topic": "all"
    },
    {
      "week": 2,
      "topic": "education"
    },
    {
      "week": 3,
      "topic": "will"
    },
    {
      "week": 4,
      "topic": "operation"
    },
    {
      "week": 5,
      "topic": "western"
    },
    {
      "week": 6,
      "topic": "plan"
    },
    {
      "week": 7,
      "topic": "allow"
    }
  ],
  "grading": {
    "homework": 30,
    "midterm": 30,
    "final": 40
  }
}


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

[User] Create a TOML representation of research paper.

[Assistant]
Approach:
1. Task: Create research paper in TOML
2. Complexity: 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:2024.67669"
title = "Triple-buffered dedicated knowledgebase"
abstract = "Account fish possible democratic ok no. Accept short mention guy.\nPlace finish religious mean end success. Travel into music they."
keywords = [ "thank", "far", "fund", "get", "role",]
citations = 60
funding_source = "Diaz-Salinas"
[[authors]]
name = "Julie Mclaughlin"
affiliation = "Andrews Group"
email = "brianna81@example.org"

[[authors]]
name = "Peggy Kramer"
affiliation = "Beasley, Edwards and Webb"
email = "susan35@example.com"

[publication]
venue = "Nature"
year = 2023
doi = "10.1349/JgWc"


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

[User] Create a XML representation of sales analytics.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<sales_analytics>
<period>March 2022</period>
<total_revenue>2472943</total_revenue>
<units_sold>2053</units_sold>
<channels>
<name>wholesale</name>
<revenue>3703587</revenue>
<growth>38.49</growth>
</channels>
<channels>
<name>retail</name>
<revenue>3200920</revenue>
<growth>-8.82</growth>
</channels>
<top_products>
<sku>SKU-8959</sku>
<sales>220308</sales>
</top_products>
<top_products>
<sku>SKU-7189</sku>
<sales>206126</sales>
</top_products>
<top_products>
<sku>SKU-5359</sku>
<sales>225947</sales>
</top_products>
</sales_analytics>


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<contract>
<contract_id>CTR-784600</contract_id>
<parties>
<name>Snyder-Thornton</name>
<role>party_a</role>
</parties>
<parties>
<name>Oliver Group</name>
<role>party_b</role>
</parties>
<effective_date>2026-01-06</effective_date>
<term_months>16</term_months>
<value>53888</value>
<status>active</status>
</contract>

[Assistant]
Approach:
1. Task: Convert contract 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:
{
  "contract_id": "CTR-784600",
  "parties": [
    {
      "name": "Snyder-Thornton",
      "role": "party_a"
    },
    {
      "name": "Oliver Group",
      "role": "party_b"
    }
  ],
  "effective_date": "2026-01-06",
  "term_months": 16,
  "value": 53888,
  "status": "active"
}


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

[User] Generate api specification data in CSV format.

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

Output:
abstract,authors,citations,funding_source,info_title,info_version,keywords,openapi,paper_id,paths_/reveal_get_parameters,paths_/reveal_get_responses_200_description,paths_/reveal_get_responses_400_description,paths_/reveal_get_summary,publication_doi,publication_venue,publication_year,title
,,,,Implemented leadingedge groupware API,1.0.0,,3.0.0,,"[{""name"": ""param0"", ""in"": ""query"", ""type"": ""string""}, {""name"": ""param1"", ""in"": ""query"", ""type"": ""str",Success,Bad Request,Parent dark five.,,,,
Across family start music help. Great thing he building time such. Hope really memory.,"[{""name"": ""Tyler Jackson"", ""affiliation"": ""Cooper-Gentry"", ""email"": ""cartersarah@example.org""}, {""na",144,None,,,"[""artist"", ""entire"", ""anything"", ""explain"", ""race""]",,arXiv:2024.74875,,,,,10.2173/Eqbh,Nature,2024,Assimilated 24/7 workforce
Option sport participant direction. Easy book out east should realize consumer base.,"[{""name"": ""Christopher Shelton"", ""affiliation"": ""Brown, Baker and Ramos"", ""email"": ""wmercado@example",47,Cole-Irwin,,,"[""within"", ""several"", ""military"", ""garden""]",,arXiv:2021.55682,,,,,10.7490/Jfef,Science,2024,Reverse-engineered content-based challenge


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

[User] Create a CSV representation of contract.

[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-464030,2026-01-06,"[{""name"": ""Morales, Williams and Williams"", ""role"": ""party_a""}, {""name"": ""Ward-Miller"", ""role"": ""par",active,35,994957
CTR-791307,2026-01-05,"[{""name"": ""Taylor, Cole and Curry"", ""role"": ""party_a""}, {""name"": ""Peters Inc"", ""role"": ""party_b""}]",active,42,692332
CTR-206272,2026-01-05,"[{""name"": ""Maynard-Wilson"", ""role"": ""party_a""}, {""name"": ""Nguyen Inc"", ""role"": ""party_b""}]",pending,59,603025
CTR-524212,2026-01-04,"[{""name"": ""Perry-Proctor"", ""role"": ""party_a""}, {""name"": ""Peters, Shannon and Cherry"", ""role"": ""party",executed,60,175595


[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-577861,,CRS-8099,,2026-01-06,B,,,,,81.98,,"[{""question"": 1, ""points_earned"": 7, ""points_possible"": 10}, {""question"": 2, ""points_earned"": 0, ""po",STU-664280,,,52,exam
,WOG419,CRS-1321,3,,,40,30,30,Michael Williams,,"[{""week"": 1, ""topic"": ""sell""}, {""week"": 2, ""topic"": ""social""}, {""week"": 3, ""topic"": ""difficult""}, {""",,,Fall 2024,Triple-buffered zero-defect paradigm 101,,
,KPR218,CRS-1943,3,,,40,30,30,Darrell Stout,,"[{""week"": 1, ""topic"": ""administration""}, {""week"": 2, ""topic"": ""know""}, {""week"": 3, ""topic"": ""every""}",,,Fall 2020,Focused intangible conglomeration 101,,
,NXT235,CRS-7230,4,,,40,30,30,Margaret Baird,,"[{""week"": 1, ""topic"": ""lay""}, {""week"": 2, ""topic"": ""population""}, {""week"": 3, ""topic"": ""wait""}, {""we",,,Fall 2020,Balanced asymmetric attitude 101,,


[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"?>
<student_assessment>
<assessment_id>ASMT-893180</assessment_id>
<student_id>STU-881633</student_id>
<course_id>CRS-6394</course_id>
<type>quiz</type>
<date>2026-01-03</date>
<scores>
<question>1</question>
<points_earned>10</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>8</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>6</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>4</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>6</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>10</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>9</question>
<points_earned>5</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>98</total_score>
<percentage>73.06</percentage>
<grade>A</grade>
</student_assessment>

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

Output:
{
  "assessment_id": "ASMT-893180",
  "student_id": "STU-881633",
  "course_id": "CRS-6394",
  "type": "quiz",
  "date": "2026-01-03",
  "scores": [
    {
      "question": 1,
      "points_earned": 10,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 10,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 6,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 6,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 0,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 10,
      "points_possible": 10
    },
    {
      "question": 9,
      "points_earned": 5,
      "points_possible": 10
    }
  ],
  "total_score": 98,
  "percentage": 73.06,
  "grade": "A"
}


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

[User] Output product listing as TOML.

[Assistant]
Approach:
1. Task: Create product listing 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:
product_id = "PROD-942707"
name = "Organic demand-driven installation"
category = "books"
price = 698.66
currency = "USD"
stock = 819
is_available = true
rating = 4.45
reviews = 103

[specs]
weight_kg = 32.63
dimensions = "66x30x83cm"


[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"?>
<sales_analytics>
<period>March 2022</period>
<total_revenue>6503980</total_revenue>
<units_sold>7670</units_sold>
<channels>
<name>retail</name>
<revenue>3279241</revenue>
<growth>22.76</growth>
</channels>
<channels>
<name>wholesale</name>
<revenue>1469640</revenue>
<growth>16.07</growth>
</channels>
<top_products>
<sku>SKU-8081</sku>
<sales>71747</sales>
</top_products>
<top_products>
<sku>SKU-8211</sku>
<sales>475825</sales>
</top_products>
<top_products>
<sku>SKU-4565</sku>
<sales>485553</sales>
</top_products>
</sales_analytics>

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

Output:
{
  "period": "March 2022",
  "total_revenue": 6503980,
  "units_sold": 7670,
  "channels": [
    {
      "name": "retail",
      "revenue": 3279241,
      "growth": 22.76
    },
    {
      "name": "wholesale",
      "revenue": 1469640,
      "growth": 16.07
    }
  ],
  "top_products": [
    {
      "sku": "SKU-8081",
      "sales": 71747
    },
    {
      "sku": "SKU-8211",
      "sales": 475825
    },
    {
      "sku": "SKU-4565",
      "sales": 485553
    }
  ]
}


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

[User] Output financial report as JSON.

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

Output:
{
  "revenue": 65816825,
  "ticker": "IQTA",
  "expenses": 77578182,
  "company": "Ramos-Wallace"
}


[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-8172649",
  "headline": "Triple-buffered responsive model",
  "author": "Rachel Clark",
  "published": "2026-01-03T00:35:22.551008",
  "section": "Business",
  "content": "Pattern capital time compare include night top. Large than important morning.\nCard authority protect present return while middle. Development miss write five.",
  "tags": [
    "consider",
    "whatever",
    "part",
    "however",
    "special"
  ],
  "views": 49705,
  "shares": 392
}

[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-8172649</article_id>
<headline>Triple-buffered responsive model</headline>
<author>Rachel Clark</author>
<published>2026-01-03T00:35:22.551008</published>

Business

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


[System] You are an expert in 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"?>
<experiment_result>
<experiment_id>EXP-330074</experiment_id>
<title>Effect of politics on stop</title>
<methodology>
<design>RCT</design>
<sample_size>328</sample_size>
<duration_days>247</duration_days>
</methodology>
<results>
<metric>efficacy</metric>
<baseline>34.54</baseline>
<endpoint>53.32</endpoint>
<p_value>0.0487</p_value>
</results>
<results>
<metric>safety</metric>
<baseline>10.4</baseline>
<endpoint>13.84</endpoint>
<p_value>0.1164</p_value>
</results>
<results>
<metric>efficacy</metric>
<baseline>78.27</baseline>
<endpoint>47.78</endpoint>
<p_value>0.0781</p_value>
</results>
<conclusion>non-significant</conclusion>
</experiment_result>

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

Output:
{
  "experiment_id": "EXP-330074",
  "title": "Effect of politics on stop",
  "methodology": {
    "design": "RCT",
    "sample_size": 328,
    "duration_days": 247
  },
  "results": [
    {
      "metric": "efficacy",
      "baseline": 34.54,
      "endpoint": 53.32,
      "p_value": 0.0487
    },
    {
      "metric": "safety",
      "baseline": 10.4,
      "endpoint": 13.84,
      "p_value": 0.1164
    },
    {
      "metric": "efficacy",
      "baseline": 78.27,
      "endpoint": 47.78,
      "p_value": 0.0781
    }
  ],
  "conclusion": "non-significant"
}


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

[User] Create a JSON representation of api specification.

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

Output:
{
  "openapi": "3.0.0",
  "info": {
    "title": "Face-to-face zero administration application API",
    "version": "1.0.0"
  },
  "paths": {
    "/peace": {
      "get": {
        "summary": "Feel piece low way effort action bag.",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          },
          {
            "name": "param1",
            "in": "query",
            "type": "string"
          },
          {
            "name": "param2",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  }
}


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

[User] Generate lab result data in XML format.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<lab_result>
<result_id>LAB-6812810</result_id>
<patient_mrn>MRN-631747</patient_mrn>
<order_date>2026-01-04</order_date>
<panel>Lipid</panel>
<results>
<test>WBC</test>
<value>54.3</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>WBC</test>
<value>70.8</value>
<unit>mg/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Glucose</test>
<value>59.6</value>
<unit>mg/dL</unit>
<flag>low</flag>
</results>
<results>
<test>WBC</test>
<value>140.8</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
</lab_result>


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

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

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

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


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

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

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

Output:
abstract,authors,citations,funding_source,info_title,info_version,keywords,openapi,paper_id,paths_/similar_get_parameters,paths_/similar_get_responses_200_description,paths_/similar_get_responses_400_description,paths_/similar_get_summary,publication_doi,publication_venue,publication_year,title
,,,,Organic analyzing strategy API,1.0.0,,3.0.0,,"[{""name"": ""param0"", ""in"": ""query"", ""type"": ""string""}, {""name"": ""param1"", ""in"": ""query"", ""type"": ""str",Success,Bad Request,Natural see lot recently.,,,,
Future deal leader president result. Attack chair age nature cold letter. That difference century ot,"[{""name"": ""Joshua Camacho"", ""affiliation"": ""Flores, Rodriguez and Gallagher"", ""email"": ""smithphilip@",359,None,,,"[""last"", ""get"", ""big"", ""early""]",,arXiv:2023.38729,,,,,10.1709/cuSu,Science,2022,Business-focused zero tolerance frame
Past various forget democratic song seek defense.,"[{""name"": ""Ms. Lisa Ibarra DDS"", ""affiliation"": ""Wells Inc"", ""email"": ""olambert@example.com""}, {""nam",482,"Torres, Roach and Tran",,,"[""of"", ""director"", ""positive"", ""sing""]",,arXiv:2021.31299,,,,,10.8442/Xpiu,Cell,2021,Integrated reciprocal benchmark
Lay than not everyone while need.,"[{""name"": ""Brent Avery"", ""affiliation"": ""Johnson, Hernandez and Ortiz"", ""email"": ""emilywilliams@exam",392,None,,,"[""possible"", ""care"", ""goal"", ""control""]",,arXiv:2024.91973,,,,,10.9656/ASZr,Cell,2023,Face-to-face responsive database


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

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

[Assistant]
Approach:
1. Task: Create customer review in TOML
2. Complexity: 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:
verified_purchase = true
date = "2026-01-05"
rating = 1


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

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

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

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


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

[User] Create a YAML representation of transaction record.

[Assistant]
Approach:
1. Task: Create transaction record 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:
txn_id: TXN-72432123
customer_id: d14101dd-b47b-4916-b7e5-0ad54eefbb55
timestamp: '2026-01-07T13:51:26.808008'
items:
- sku: SKU-29323
  qty: 2
  price: 70.49
- sku: SKU-65460
  qty: 3
  price: 466.32
- sku: SKU-59283
  qty: 1
  price: 149.96
- sku: SKU-68579
  qty: 2
  price: 13.04
subtotal: 1301.16
tax: 124.54
total: 239.49
payment_method: apple_pay


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

[User] Output prescription as YAML.

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

Output:
rx_id: RX-3305496
patient_mrn: MRN-551064
prescriber: Eric Jackson
date: '2026-01-03'
medications:
- name: Atorvastatin
  dosage: 20mg
  frequency: daily
  quantity: 90


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

[User] Generate customer review data in YAML format.

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

Output:
review_id: REV-4787173
product_id: PROD-746934
user_id: a1638e54-91af-4e5f-be10-465327f3fbf6
rating: 4
title: Rock company surface either million.
content: Suddenly plant stay thank project hand me. Commercial his road carry training
  trip.
date: '2026-01-02'
verified_purchase: true
helpful_votes: 3


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

[User] Create a YAML representation of course syllabus.

[Assistant]
Approach:
1. Task: Create course syllabus 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:
instructor: Tamara Stark
term: Spring 2022
code: VMA483
grading:
  homework: 30
  midterm: 30
  final: 40