[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"?>
<lab_result>
<result_id>LAB-5790382</result_id>
<patient_mrn>MRN-357903</patient_mrn>
<order_date>2026-01-02</order_date>
<panel>CBC</panel>
<results>
<test>Glucose</test>
<value>56.1</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Glucose</test>
<value>114.1</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>WBC</test>
<value>154.7</value>
<unit>mg/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Glucose</test>
<value>196.1</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
</lab_result>

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

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


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

[User]
Convert the following JSON to XML:
{
  "note_id": "CN-4493327",
  "patient": {
    "mrn": "MRN-934301",
    "age": 62,
    "gender": "F"
  },
  "encounter_date": "2026-01-06",
  "chief_complaint": "fever",
  "vitals": {
    "bp": "141/91",
    "hr": 100,
    "temp_f": 98.5
  },
  "assessment": [
    {
      "problem": "diabetes",
      "icd10": "I32"
    }
  ]
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<clinical_note>
<note_id>CN-4493327</note_id>
<patient>
<mrn>MRN-934301</mrn>
<age>62</age>
<gender>F</gender>
</patient>
<encounter_date>2026-01-06</encounter_date>
<chief_complaint>fever</chief_complaint>
<vitals>
<bp>141/91</bp>

100

<temp_f>98.5</temp_f>
</vitals>
<assessment>
<problem>diabetes</problem>
<icd10>I32</icd10>
</assessment>
</clinical_note>


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

[User]
Transform this JSON data into XML format:
{
  "company": "Eaton, Mccarty and Lopez",
  "ticker": "OWKB",
  "quarter": "Q3 2021",
  "revenue": 46227283,
  "expenses": 75330506,
  "net_income": 13309525,
  "eps": 4.82,
  "metrics": {
    "profit_margin": 29.61,
    "roe": 8.93
  }
}

[Assistant]
Approach:
1. Task: Convert financial report 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"?>
<financial_report>
<company>Eaton, Mccarty and Lopez</company>
<ticker>OWKB</ticker>
<quarter>Q3 2021</quarter>
<revenue>46227283</revenue>
<expenses>75330506</expenses>
<net_income>13309525</net_income>
<eps>4.82</eps>
<metrics>
<profit_margin>29.61</profit_margin>
<roe>8.93</roe>
</metrics>
</financial_report>


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

[User] Create a JSON representation of prescription.

[Assistant]
Approach:
1. Task: Create prescription in JSON
2. Complexity: 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:
{
  "date": "2026-01-04",
  "medications": [
    {
      "name": "Atorvastatin",
      "dosage": "20mg",
      "frequency": "TID",
      "quantity": 60
    },
    {
      "name": "Metformin",
      "dosage": "20mg",
      "frequency": "daily",
      "quantity": 60
    },
    {
      "name": "Atorvastatin",
      "dosage": "5mg",
      "frequency": "TID",
      "quantity": 60
    }
  ],
  "patient_mrn": "MRN-588828"
}


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

[User] Output customer review as XML.

[Assistant]
Approach:
1. Task: Create customer review 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"?>
<customer_review>
<date>2026-01-05</date>
<title>Teach why painting per short.</title>
<rating>4</rating>
</customer_review>


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

[User] Generate product listing data in TOML format.

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

Output:
rating = 4.54
stock = 843
currency = "USD"

[specs]
weight_kg = 34.7
dimensions = "61x86x65cm"


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

Output:
{
  "review_id": "REV-1132090",
  "product_id": "PROD-380257",
  "user_id": "251dc214-da1e-4fb5-8ea5-d107ad43f82c",
  "rating": 4,
  "title": "Young race true property less government.",
  "content": "Brother agent radio might own development. Too strong minute building why. Cell so amount imagine simple.\nCourt every deal change allow last practice. Western far thus.",
  "date": "2026-01-03",
  "verified_purchase": false,
  "helpful_votes": 14
}


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

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

[Assistant]
Approach:
1. Task: Create student assessment 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:
assessment_id: ASMT-948175
student_id: STU-160858
course_id: CRS-5368
type: assignment
date: '2026-01-03'
scores:
- question: 1
  points_earned: 1
  points_possible: 10
- question: 2
  points_earned: 9
  points_possible: 10
- question: 3
  points_earned: 2
  points_possible: 10
- question: 4
  points_earned: 9
  points_possible: 10
- question: 5
  points_earned: 5
  points_possible: 10
- question: 6
  points_earned: 9
  points_possible: 10
- question: 7
  points_earned: 1
  points_possible: 10
- question: 8
  points_earned: 3
  points_possible: 10
- question: 9
  points_earned: 9
  points_possible: 10
total_score: 89
percentage: 96.29
grade: B


[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": "June 2022",
  "total_revenue": 7287772,
  "units_sold": 8566,
  "channels": [
    {
      "name": "retail",
      "revenue": 931216,
      "growth": 10.96
    },
    {
      "name": "wholesale",
      "revenue": 1224016,
      "growth": 31.92
    }
  ],
  "top_products": [
    {
      "sku": "SKU-1474",
      "sales": 19268
    },
    {
      "sku": "SKU-3289",
      "sales": 31397
    },
    {
      "sku": "SKU-4950",
      "sales": 322920
    }
  ]
}


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

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

[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-738287"
name = "Function-based dedicated installation"
category = "electronics"
price = 364.53
currency = "USD"
stock = 956
is_available = true
rating = 1.64
reviews = 854

[specs]
weight_kg = 19.72
dimensions = "48x33x88cm"


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

[User] Generate contract data in CSV format.

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

Output:
abstract,authors,citations,effective_date,funding_source,keywords,paper_id,parties,publication_doi,publication_venue,publication_year,term_months,title,value
,,,2026-01-05,,,,"[{""name"": ""Hart-Villanueva"", ""role"": ""party_a""}, {""name"": ""Roberts Ltd"", ""role"": ""party_b""}]",,,,33,,95653
"Their tend build gas spring blood man short.
Listen perhaps institution career case.
Reach left prof","[{""name"": ""Shannon Lee"", ""affiliation"": ""Johns-Parker"", ""email"": ""marquezapril@example.org""}, {""name",1,,Clark PLC,"[""base"", ""week"", ""soldier"", ""go"", ""policy""]",arXiv:2023.75547,,10.4080/LbDF,Nature,2023,,Distributed multi-state standardization,
"Fire for worry night natural. Table people possible appear.
Red want fall fill. Election somebody tw","[{""name"": ""Denise West"", ""affiliation"": ""Bonilla PLC"", ""email"": ""williamsmichael@example.net""}, {""na",227,,None,"[""glass"", ""value"", ""me"", ""its""]",arXiv:2023.46555,,10.3610/ujqA,Cell,2020,,Ergonomic executive Internet solution,
Difficult turn morning message TV job. Relationship floor tonight politics whether lot edge. Affect ,"[{""name"": ""Barbara Lewis"", ""affiliation"": ""Robles-Mcfarland"", ""email"": ""callahanamy@example.net""}, {",31,,None,"[""team"", ""each"", ""great"", ""day""]",arXiv:2024.30502,,10.1960/MuGR,Nature,2024,,Ergonomic scalable architecture,


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

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

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

Output:
article_id,author,content,headline,published,section,shares,tags,views
ART-1748125,Sandra Bennett,"Majority meeting sound have week public pass. Major food relate spend seven.
Indeed run fund.
Federa",Customizable leadingedge structure,2026-01-03T22:52:42.741679,Sports,2505,"[""subject"", ""attention"", ""class"", ""campaign"", ""second""]",63827
ART-9010589,Anthony Pearson,"Child buy data yourself draw. Indeed check street special take bit.
Wait daughter attack back histor",Decentralized optimizing parallelism,2026-01-05T22:11:54.090915,Politics,1523,"[""different"", ""shoulder"", ""member"", ""of"", ""short""]",18330
ART-8387787,Angel Spencer,"See remember find.
Among other tonight party. Reveal business environment company responsibility. In",Multi-tiered value-added Internet solution,2026-01-05T20:24:55.532165,Sports,1003,"[""protect"", ""world"", ""manage"", ""all""]",27833


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

[User] Output student assessment as CSV.

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

Output:
assessment_id,code,course_id,credits,date,grade,grading_final,grading_homework,grading_midterm,instructor,percentage,schedule,scores,student_id,term,title,total_score,type
ASMT-353280,,CRS-9241,,2026-01-05,C,,,,,88.23,,"[{""question"": 1, ""points_earned"": 4, ""points_possible"": 10}, {""question"": 2, ""points_earned"": 6, ""po",STU-259399,,,68,quiz
,VPJ137,CRS-3023,4,,,40,30,30,Rachel Nelson,,"[{""week"": 1, ""topic"": ""scientist""}, {""week"": 2, ""topic"": ""game""}, {""week"": 3, ""topic"": ""same""}, {""we",,,Spring 2021,Quality-focused even-keeled emulation 101,,
,TRH384,CRS-3621,4,,,40,30,30,Dana Bailey,,"[{""week"": 1, ""topic"": ""majority""}, {""week"": 2, ""topic"": ""page""}, {""week"": 3, ""topic"": ""design""}, {""w",,,Spring 2023,Innovative holistic benchmark 101,,
,CFI146,CRS-3913,3,,,40,30,30,Laura Lewis,,"[{""week"": 1, ""topic"": ""certain""}, {""week"": 2, ""topic"": ""film""}, {""week"": 3, ""topic"": ""find""}, {""week",,,Fall 2024,Intuitive static capacity 101,,
,JFO258,CRS-1460,4,,,40,30,30,Michael Campbell,,"[{""week"": 1, ""topic"": ""work""}, {""week"": 2, ""topic"": ""score""}, {""week"": 3, ""topic"": ""finish""}, {""week",,,Fall 2020,Multi-tiered attitude-oriented workforce 101,,


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

[User] Create a YAML representation of student assessment.

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


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

[User] Create a TOML representation of experiment result.

[Assistant]
Approach:
1. Task: Create experiment result in TOML
2. Complexity: 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:
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


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

[User]
Reformat the data below from CSV to YAML:
date,medications,patient_mrn,prescriber,rx_id
2026-01-02,"[{""name"": ""Atorvastatin"", ""dosage"": ""20mg"", ""frequency"": ""BID"", ""quantity"": 90}, {""name"": ""Atorvasta",MRN-726192,Jessica Warner,RX-3022361
2026-01-02,"[{""name"": ""Metformin"", ""dosage"": ""20mg"", ""frequency"": ""BID"", ""quantity"": 30}]",MRN-335598,Misty Cooper,RX-5948180
2026-01-01,"[{""name"": ""Atorvastatin"", ""dosage"": ""20mg"", ""frequency"": ""BID"", ""quantity"": 90}]",MRN-524531,Amy Jordan,RX-7497516
2026-01-01,"[{""name"": ""Lisinopril"", ""dosage"": ""20mg"", ""frequency"": ""daily"", ""quantity"": 30}]",MRN-192120,Nathan Castillo,RX-8671520
2026-01-06,"[{""name"": ""Lisinopril"", ""dosage"": ""5mg"", ""frequency"": ""TID"", ""quantity"": 30}, {""name"": ""Metformin"", ",MRN-265671,Sara Smith,RX-7538900

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

Output:
rx_id: RX-3022361
patient_mrn: MRN-726192
prescriber: Jessica Warner
date: '2026-01-02'
medications:
- name: Atorvastatin
  dosage: 20mg
  frequency: BID
  quantity: 90
- name: Atorvastatin
  dosage: 20mg
  frequency: daily
  quantity: 30


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

[User] Generate sales analytics data in TOML format.

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

Output:
period = "March 2022"
total_revenue = 2472943
units_sold = 2053
[[channels]]
name = "wholesale"
revenue = 3703587
growth = 38.49

[[channels]]
name = "retail"
revenue = 3200920
growth = -8.82

[[top_products]]
sku = "SKU-8959"
sales = 220308

[[top_products]]
sku = "SKU-7189"
sales = 206126

[[top_products]]
sku = "SKU-5359"
sales = 225947


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<student_assessment>
<assessment_id>ASMT-482875</assessment_id>
<student_id>STU-646713</student_id>
<course_id>CRS-2679</course_id>
<type>assignment</type>
<date>2026-01-01</date>
<scores>
<question>1</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>3</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>7</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>3</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>8</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>9</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>10</question>
<points_earned>8</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>62</total_score>
<percentage>98.87</percentage>
<grade>C</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-482875",
  "student_id": "STU-646713",
  "course_id": "CRS-2679",
  "type": "assignment",
  "date": "2026-01-01",
  "scores": [
    {
      "question": 1,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 3,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 9,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 10,
      "points_earned": 8,
      "points_possible": 10
    }
  ],
  "total_score": 62,
  "percentage": 98.87,
  "grade": "C"
}


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

[User] Generate financial report data in YAML format.

[Assistant]
Approach:
1. Task: Create financial report 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:
company: Becker-Martinez
ticker: QZXR
quarter: Q4 2021
revenue: 48919598
expenses: 50274851
net_income: 7284021
eps: 2.39
metrics:
  profit_margin: 17.0
  roe: 10.6


[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:
{
  "course_id": "CRS-8855",
  "code": "DBP130",
  "title": "Team-oriented 3rdgeneration implementation 101",
  "instructor": "Carl Davis",
  "credits": 3,
  "term": "Fall 2024",
  "schedule": [
    {
      "week": 1,
      "topic": "manage"
    },
    {
      "week": 2,
      "topic": "someone"
    },
    {
      "week": 3,
      "topic": "bring"
    },
    {
      "week": 4,
      "topic": "board"
    },
    {
      "week": 5,
      "topic": "important"
    },
    {
      "week": 6,
      "topic": "he"
    },
    {
      "week": 7,
      "topic": "possible"
    },
    {
      "week": 8,
      "topic": "office"
    },
    {
      "week": 9,
      "topic": "board"
    },
    {
      "week": 10,
      "topic": "drive"
    },
    {
      "week": 11,
      "topic": "Mrs"
    }
  ],
  "grading": {
    "homework": 30,
    "midterm": 30,
    "final": 40
  }
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<course_syllabus>
<course_id>CRS-8855</course_id>
DBP130
<title>Team-oriented 3rdgeneration implementation 101</title>
<instructor>Carl Davis</instructor>
<credits>3</credits>
<term>Fall 2024</term>
<schedule>
<week>1</week>
<topic>manage</topic>
</schedule>
<schedule>
<week>2</week>
<topic>someone</topic>
</schedule>
<schedule>
<week>3</week>
<topic>bring</topic>
</schedule>
<schedule>
<week>4</week>
<topic>board</topic>
</schedule>
<schedule>
<week>5</week>
<topic>important</topic>
</schedule>
<schedule>
<week>6</week>
<topic>he</topic>
</schedule>
<schedule>
<week>7</week>
<topic>possible</topic>
</schedule>
<schedule>
<week>8</week>
<topic>office</topic>
</schedule>
<schedule>
<week>9</week>
<topic>board</topic>
</schedule>
<schedule>
<week>10</week>
<topic>drive</topic>
</schedule>
<schedule>
<week>11</week>
<topic>Mrs</topic>
</schedule>
<grading>
<homework>30</homework>
<midterm>30</midterm>
<final>40</final>
</grading>
</course_syllabus>


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

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

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


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

[User] Create a YAML representation of product listing.

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

Output:
product_id: PROD-325945
name: Universal bottom-line system engine
category: electronics
price: 225.75
currency: USD
stock: 955
is_available: true
rating: 3.31
reviews: 802
specs:
  weight_kg: 22.25
  dimensions: 77x29x32cm


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

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

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

Output:
company,eps,expenses,metrics_profit_margin,metrics_roe,net_income,quarter,revenue,ticker
Smith-Glover,7.31,30652579,9.94,10.91,5856951,Q3 2023,95238846,JROI
Kim-Munoz,0.8,40162801,25.56,20.26,10496357,Q4 2024,13444378,FJIO
Jennings PLC,5.47,24454781,22.97,19.49,2943097,Q3 2020,20008553,HIYK
"Merritt, Mcintosh and Moore",2.84,33959441,24.79,19.51,2529537,Q1 2024,15767946,GWUJ


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

[User]
Transform this JSON data into XML format:
{
  "rx_id": "RX-1565761",
  "patient_mrn": "MRN-226686",
  "prescriber": "Regina Martin",
  "date": "2026-01-03",
  "medications": [
    {
      "name": "Metformin",
      "dosage": "20mg",
      "frequency": "TID",
      "quantity": 60
    },
    {
      "name": "Atorvastatin",
      "dosage": "20mg",
      "frequency": "BID",
      "quantity": 90
    }
  ]
}

[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-1565761</rx_id>
<patient_mrn>MRN-226686</patient_mrn>
<prescriber>Regina Martin</prescriber>
<date>2026-01-03</date>
<medications>
<name>Metformin</name>
<dosage>20mg</dosage>
<frequency>TID</frequency>
<quantity>60</quantity>
</medications>
<medications>
<name>Atorvastatin</name>
<dosage>20mg</dosage>
<frequency>BID</frequency>
<quantity>90</quantity>
</medications>
</prescription>


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

[User] Output course syllabus as YAML.

[Assistant]
Approach:
1. Task: Create course syllabus 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:
course_id: CRS-6873
code: GDK183
title: Grass-roots 24/7 emulation 101
instructor: Melinda Thompson
credits: 3
term: Fall 2020
schedule:
- week: 1
  topic: girl
- week: 2
  topic: explain
- week: 3
  topic: center
- week: 4
  topic: almost
- week: 5
  topic: property
- week: 6
  topic: call
- week: 7
  topic: bad
- week: 8
  topic: study
- week: 9
  topic: campaign
- week: 10
  topic: performance
- week: 11
  topic: sport
grading:
  homework: 30
  midterm: 30
  final: 40


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

Output:
{
  "total_revenue": 6798538,
  "channels": [
    {
      "name": "online",
      "revenue": 2139770,
      "growth": -9.99
    },
    {
      "name": "retail",
      "revenue": 1809716,
      "growth": 7.01
    }
  ],
  "top_products": [
    {
      "sku": "SKU-3049",
      "sales": 22854
    },
    {
      "sku": "SKU-5505",
      "sales": 203281
    },
    {
      "sku": "SKU-9853",
      "sales": 260538
    }
  ]
}


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<social_media_post>
<post_id>POST-58559815</post_id>
<platform>instagram</platform>
<user_id>0fae79ab-dabb-47f5-823b-f22743181c7c</user_id>
<username>ortizkristina</username>
<content>Speech can sea play. Season near story animal remain.
Off present vote wall. Society know family build. Certain thing live rise.</content>
<timestamp>2026-01-07T13:51:26.463560</timestamp>
<hashtags>#once</hashtags>
<hashtags>#it</hashtags>
<hashtags>#rich</hashtags>
<hashtags>#keep</hashtags>
<engagement>
<likes>248</likes>
<shares>32</shares>
<comments>161</comments>
</engagement>
</social_media_post>


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<sales_analytics>
<period>March 2024</period>
<total_revenue>2433324</total_revenue>
<units_sold>8686</units_sold>
<channels>
<name>online</name>
<revenue>3952303</revenue>
<growth>2.75</growth>
</channels>
<channels>
<name>retail</name>
<revenue>3970412</revenue>
<growth>12.57</growth>
</channels>
<top_products>
<sku>SKU-2514</sku>
<sales>485558</sales>
</top_products>
<top_products>
<sku>SKU-5241</sku>
<sales>142515</sales>
</top_products>
<top_products>
<sku>SKU-4600</sku>
<sales>420300</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 2024",
  "total_revenue": 2433324,
  "units_sold": 8686,
  "channels": [
    {
      "name": "online",
      "revenue": 3952303,
      "growth": 2.75
    },
    {
      "name": "retail",
      "revenue": 3970412,
      "growth": 12.57
    }
  ],
  "top_products": [
    {
      "sku": "SKU-2514",
      "sales": 485558
    },
    {
      "sku": "SKU-5241",
      "sales": 142515
    },
    {
      "sku": "SKU-4600",
      "sales": 420300
    }
  ]
}


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

[User] Output api specification as YAML.

[Assistant]
Approach:
1. Task: Create api specification 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:
info:
  title: Multi-tiered directional knowledge user API
  version: 1.0.0
openapi: 3.0.0
paths:
  /require:
    get:
      summary: Suffer kid pull bed decision rest.
      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] Create a XML representation of 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-852387</product_id>
<name>Profound logistical array</name>
<category>electronics</category>
<price>299.46</price>
<currency>USD</currency>
<stock>505</stock>
<is_available>True</is_available>
<rating>2.95</rating>
<reviews>519</reviews>
<specs>
<weight_kg>6.22</weight_kg>
<dimensions>16x47x36cm</dimensions>
</specs>
</product_listing>


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

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

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

Output:
content,engagement_comments,engagement_likes,engagement_shares,hashtags,platform,post_id,timestamp,user_id,username
Specific other kind choice. Condition main resource finish north reach with break. Area strategy hug,204,3831,379,"[""#model"", ""#firm""]",facebook,POST-78635818,2026-01-07T13:51:25.965362,a739269a-9642-463c-9c88-cb97c795c8d8,kevin10
"Race good what lot film. Executive I notice let. Door cup turn economy that here who edge.
Minute wa",454,8304,928,"[""#wrong"", ""#international"", ""#offer"", ""#tend""]",instagram,POST-88348234,2026-01-07T13:51:25.966680,95c41e22-2545-443a-a874-ee123c3752c5,jasonwilliams
"Tree rather itself buy character human election. Nice send set ground enjoy team.
Season with range ",425,5206,788,"[""#admit"", ""#son"", ""#figure""]",instagram,POST-37210196,2026-01-07T13:51:25.967099,2db0349f-4fc7-4c85-a9c7-02b73e975bde,iwalker


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<sales_analytics>
<period>November 2021</period>
<total_revenue>8992427</total_revenue>
<units_sold>30636</units_sold>
<channels>
<name>wholesale</name>
<revenue>3169564</revenue>
<growth>42.35</growth>
</channels>
<channels>
<name>retail</name>
<revenue>2683860</revenue>
<growth>36.55</growth>
</channels>
<top_products>
<sku>SKU-9614</sku>
<sales>412171</sales>
</top_products>
<top_products>
<sku>SKU-7573</sku>
<sales>203488</sales>
</top_products>
<top_products>
<sku>SKU-4372</sku>
<sales>55896</sales>
</top_products>
</sales_analytics>


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

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

[Assistant]
Approach:
1. Task: Create customer review 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"?>
<customer_review>
<verified_purchase>True</verified_purchase>
<title>Country especially hand.</title>
<review_id>REV-4835597</review_id>
<product_id>PROD-713270</product_id>
</customer_review>


[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: medium - 5-8 fields, 2-3 levels
3. Format rules: header row, comma-separated, quoted fields with commas
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
assessment_id,code,course_id,credits,date,grade,grading_final,grading_homework,grading_midterm,instructor,percentage,schedule,scores,student_id,term,title,total_score,type
ASMT-458464,,CRS-7675,,2026-01-06,B,,,,,65.79,,"[{""question"": 1, ""points_earned"": 0, ""points_possible"": 10}, {""question"": 2, ""points_earned"": 9, ""po",STU-453066,,,67,assignment
,DZG328,CRS-1303,3,,,40,30,30,Amber Johnson,,"[{""week"": 1, ""topic"": ""tax""}, {""week"": 2, ""topic"": ""try""}, {""week"": 3, ""topic"": ""much""}, {""week"": 4,",,,Fall 2021,Public-key client-driven benchmark 101,,
,TDI483,CRS-4589,3,,,40,30,30,Jeffrey Flores,,"[{""week"": 1, ""topic"": ""make""}, {""week"": 2, ""topic"": ""hotel""}, {""week"": 3, ""topic"": ""until""}, {""week""",,,Spring 2020,Optional human-resource archive 101,,
,HRV294,CRS-1986,4,,,40,30,30,Rodney Miller,,"[{""week"": 1, ""topic"": ""health""}, {""week"": 2, ""topic"": ""matter""}, {""week"": 3, ""topic"": ""why""}, {""week",,,Spring 2020,Grass-roots tertiary open system 101,,
,RZE105,CRS-8784,3,,,40,30,30,Andrew Beck,,"[{""week"": 1, ""topic"": ""long""}, {""week"": 2, ""topic"": ""church""}, {""week"": 3, ""topic"": ""effect""}, {""wee",,,Fall 2020,Ameliorated radical analyzer 101,,


[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-1565761</rx_id>
<patient_mrn>MRN-226686</patient_mrn>
<prescriber>Regina Martin</prescriber>
<date>2026-01-03</date>
<medications>
<name>Metformin</name>
<dosage>20mg</dosage>
<frequency>TID</frequency>
<quantity>60</quantity>
</medications>
<medications>
<name>Atorvastatin</name>
<dosage>20mg</dosage>
<frequency>BID</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-1565761",
  "patient_mrn": "MRN-226686",
  "prescriber": "Regina Martin",
  "date": "2026-01-03",
  "medications": [
    {
      "name": "Metformin",
      "dosage": "20mg",
      "frequency": "TID",
      "quantity": 60
    },
    {
      "name": "Atorvastatin",
      "dosage": "20mg",
      "frequency": "BID",
      "quantity": 90
    }
  ]
}


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

[User] Generate research paper data in XML format.

[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:2024.67669</paper_id>
<title>Triple-buffered dedicated knowledgebase</title>
<authors>
<name>Julie Mclaughlin</name>
<affiliation>Andrews Group</affiliation>
<email>brianna81@example.org</email>
</authors>
<authors>
<name>Peggy Kramer</name>
<affiliation>Beasley, Edwards and Webb</affiliation>
<email>susan35@example.com</email>
</authors>
<abstract>Account fish possible democratic ok no. Accept short mention guy.
Place finish religious mean end success. Travel into music they.</abstract>
<keywords>thank</keywords>
<keywords>far</keywords>
<keywords>fund</keywords>
<keywords>get</keywords>
<keywords>role</keywords>
<publication>
<venue>Nature</venue>
<year>2023</year>
<doi>10.1349/JgWc</doi>
</publication>
<citations>60</citations>
<funding_source>Diaz-Salinas</funding_source>
</research_paper>


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

[User] Output error log as XML.

[Assistant]
Approach:
1. Task: Create error log 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"?>
<error_log>
<error_id>91d16731-5e7b-4a47-8285-7a54d79d3b76</error_id>
<timestamp>2026-01-07T13:51:25.635487</timestamp>
<level>WARNING</level>
<service>AmericanService</service>
<message>Drug sell certainly major total.</message>
<stack_trace>at although.py:151</stack_trace>
<stack_trace>at mission.py:443</stack_trace>
<context>
<user_id>11d85442-7276-4e30-9249-06df8089bd39</user_id>
<request_id>f3cc0b9c-f4db-4c9d-bea8-f49774b1a7e6</request_id>
</context>
</error_log>


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

[User] Output product listing as YAML.

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

Output:
product_id: PROD-480886
name: Operative optimizing monitoring
category: books
price: 967.35
currency: USD
stock: 887
is_available: true
rating: 2.99
reviews: 465
specs:
  weight_kg: 39.19
  dimensions: 82x84x37cm


[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-2604144
patient_mrn: MRN-906692
order_date: '2026-01-01'
panel: Lipid
results:
- test: Hemoglobin
  value: 180.3
  unit: mg/dL
  flag: high
- test: Glucose
  value: 97.8
  unit: mg/dL
  flag: normal
- test: Glucose
  value: 88.1
  unit: g/dL
  flag: high
- test: Glucose
  value: 65.1
  unit: mg/dL
  flag: high
- test: Hemoglobin
  value: 95.1
  unit: g/dL
  flag: high
- test: Glucose
  value: 86.1
  unit: mg/dL
  flag: low
- test: Hemoglobin
  value: 152.8
  unit: mg/dL
  flag: normal


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

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

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

Output:
{
  "course_id": "CRS-5570",
  "code": "ZMD258",
  "title": "Mandatory leadingedge superstructure 101",
  "instructor": "Gregory Dunn",
  "credits": 3,
  "term": "Spring 2021",
  "schedule": [
    {
      "week": 1,
      "topic": "guess"
    },
    {
      "week": 2,
      "topic": "forget"
    },
    {
      "week": 3,
      "topic": "technology"
    },
    {
      "week": 4,
      "topic": "nothing"
    },
    {
      "week": 5,
      "topic": "sea"
    },
    {
      "week": 6,
      "topic": "other"
    },
    {
      "week": 7,
      "topic": "new"
    },
    {
      "week": 8,
      "topic": "report"
    },
    {
      "week": 9,
      "topic": "guy"
    },
    {
      "week": 10,
      "topic": "can"
    },
    {
      "week": 11,
      "topic": "inside"
    }
  ],
  "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] Produce a TOML document for a customer review.

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

Output:
review_id = "REV-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]
Transform this TOML data into YAML format:
period = "October 2022"
total_revenue = 4790876
units_sold = 72609
[[channels]]
name = "retail"
revenue = 1112533
growth = 2.85

[[channels]]
name = "wholesale"
revenue = 3150615
growth = -3.34

[[top_products]]
sku = "SKU-7795"
sales = 492045

[[top_products]]
sku = "SKU-5231"
sales = 195976

[[top_products]]
sku = "SKU-5539"
sales = 335045

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

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


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

[User]
Reformat the data below from JSON to XML:
{
  "product_id": "PROD-469887",
  "is_available": true,
  "reviews": 612,
  "name": "Networked executive capability",
  "currency": "USD"
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<product_listing>
<product_id>PROD-469887</product_id>
<is_available>True</is_available>
<reviews>612</reviews>
<name>Networked executive capability</name>
<currency>USD</currency>
</product_listing>


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

[User] Output error log as YAML.

[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: 0ea30289-ce13-425f-910d-da970e03d0fa
timestamp: '2026-01-07T13:51:25.772316'
level: WARNING
service: theService
message: Country specific information follow daughter dark.
stack_trace:
- at enjoy.py:340
- at current.py:45
- at hand.py:478
context:
  user_id: 91a6b883-2593-4790-8a1e-5acd27aad31b
  request_id: 1b22b6e6-0879-45de-9655-0fac03142f9b


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

[User] Output clinical note as XML.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<clinical_note>
<note_id>CN-9595817</note_id>
<patient>
<mrn>MRN-972408</mrn>
<age>32</age>
<gender>F</gender>
</patient>
<encounter_date>2026-01-02</encounter_date>
<chief_complaint>chest pain</chief_complaint>
<vitals>
<bp>102/103</bp>

113

<temp_f>102.5</temp_f>
</vitals>
<assessment>
<problem>hypertension</problem>
<icd10>K99</icd10>
</assessment>
</clinical_note>


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

[User] Create a TOML representation of sales analytics.

[Assistant]
Approach:
1. Task: Create sales analytics 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:
period = "February 2020"
total_revenue = 5010605
units_sold = 4486
[[channels]]
name = "online"
revenue = 4865933
growth = 41.22

[[channels]]
name = "wholesale"
revenue = 4636446
growth = 21.68

[[top_products]]
sku = "SKU-3361"
sales = 360256

[[top_products]]
sku = "SKU-1576"
sales = 355717

[[top_products]]
sku = "SKU-8891"
sales = 396344


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

[User] Output social media post as YAML.

[Assistant]
Approach:
1. Task: Create social media post 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:
post_id: POST-58883169
user_id: 9fc1586a-703b-4459-a18b-2f5e0582ab64
username: alexandra57


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

[User]
Reformat the data below from JSON to XML:
{
  "txn_id": "TXN-48552675",
  "customer_id": "19d3d880-f410-4b85-a35d-9c5777705d1f",
  "timestamp": "2026-01-07T13:51:26.837603",
  "items": [
    {
      "sku": "SKU-30306",
      "qty": 4,
      "price": 206.74
    }
  ],
  "subtotal": 1354.26,
  "tax": 33.08,
  "total": 766.28,
  "payment_method": "paypal"
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<transaction_record>
<txn_id>TXN-48552675</txn_id>
<customer_id>19d3d880-f410-4b85-a35d-9c5777705d1f</customer_id>
<timestamp>2026-01-07T13:51:26.837603</timestamp>
<items>
<sku>SKU-30306</sku>
<qty>4</qty>
<price>206.74</price>
</items>
<subtotal>1354.26</subtotal>
<tax>33.08</tax>
<total>766.28</total>
<payment_method>paypal</payment_method>
</transaction_record>


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

[User] Generate contract data in JSON format.

[Assistant]
Approach:
1. Task: Create contract in JSON
2. Complexity: 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:
{
  "contract_id": "CTR-370819",
  "parties": [
    {
      "name": "Stewart, Thompson and Rogers",
      "role": "party_a"
    },
    {
      "name": "Jackson, Griffin and Flowers",
      "role": "party_b"
    }
  ],
  "effective_date": "2026-01-01",
  "term_months": 13,
  "value": 109351,
  "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 prescription.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<prescription>
<rx_id>RX-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>


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

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

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

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

Politics

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


[System] You are an expert in 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"?>
<product_listing>
<specs>
<weight_kg>8.02</weight_kg>
<dimensions>62x22x22cm</dimensions>
</specs>
<name>Universal fault-tolerant service-desk</name>
<price>907.33</price>
<reviews>493</reviews>
</product_listing>

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

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


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

[User] Generate financial report data in TOML format.

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

Output:
company = "Hill-Marsh"
ticker = "ZFVR"
quarter = "Q3 2024"
revenue = 46703834
expenses = 77071880
net_income = 4141173
eps = 8.71

[metrics]
profit_margin = 28.84
roe = 14.06


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

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

[Assistant]
Approach:
1. Task: Create student assessment 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:
assessment_id: ASMT-350362
student_id: STU-421536
course_id: CRS-1231
type: exam
date: '2026-01-01'
scores:
- question: 1
  points_earned: 2
  points_possible: 10
- question: 2
  points_earned: 1
  points_possible: 10
- question: 3
  points_earned: 8
  points_possible: 10
- question: 4
  points_earned: 8
  points_possible: 10
- question: 5
  points_earned: 8
  points_possible: 10
- question: 6
  points_earned: 6
  points_possible: 10
- question: 7
  points_earned: 5
  points_possible: 10
- question: 8
  points_earned: 2
  points_possible: 10
- question: 9
  points_earned: 1
  points_possible: 10
- question: 10
  points_earned: 2
  points_possible: 10
- question: 11
  points_earned: 9
  points_possible: 10
total_score: 51
percentage: 80.6
grade: A


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

[User] Generate experiment result data in YAML format.

[Assistant]
Approach:
1. Task: Create experiment 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:
experiment_id: EXP-942720
title: Effect of edge on when
methodology:
  design: cohort
  sample_size: 645
  duration_days: 54
results:
- metric: safety
  baseline: 79.64
  endpoint: 26.86
  p_value: 0.2863
- metric: safety
  baseline: 55.57
  endpoint: 59.78
  p_value: 0.1705
- metric: efficacy
  baseline: 30.69
  endpoint: 27.4
  p_value: 0.1116
- metric: efficacy
  baseline: 32.07
  endpoint: 35.79
  p_value: 0.1946
conclusion: non-significant


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

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

[Assistant]
Approach:
1. Task: Create course syllabus in CSV
2. Complexity: 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:
code,course_id,credits,grading_final,grading_homework,grading_midterm,instructor,schedule,term,title
WOR378,CRS-6204,4,40,30,30,Charlene Houston,"[{""week"": 1, ""topic"": ""under""}, {""week"": 2, ""topic"": ""trade""}, {""week"": 3, ""topic"": ""good""}, {""week""",Spring 2023,Multi-channeled bi-directional implementation 101
IBK281,CRS-6337,4,40,30,30,Annette Reynolds,"[{""week"": 1, ""topic"": ""change""}, {""week"": 2, ""topic"": ""food""}, {""week"": 3, ""topic"": ""church""}, {""wee",Spring 2020,Synchronized human-resource secured line 101
FPA489,CRS-9603,3,40,30,30,Christopher Small,"[{""week"": 1, ""topic"": ""billion""}, {""week"": 2, ""topic"": ""perhaps""}, {""week"": 3, ""topic"": ""part""}, {""w",Spring 2022,User-friendly coherent database 101
YOF278,CRS-2034,4,40,30,30,Jennifer Salazar,"[{""week"": 1, ""topic"": ""prepare""}, {""week"": 2, ""topic"": ""true""}, {""week"": 3, ""topic"": ""family""}, {""we",Spring 2023,Configurable holistic website 101
MTJ262,CRS-4594,3,40,30,30,Zachary Williams,"[{""week"": 1, ""topic"": ""consider""}, {""week"": 2, ""topic"": ""product""}, {""week"": 3, ""topic"": ""face""}, {""",Fall 2023,Devolved mobile concept 101


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

[User]
Reformat the data below from JSON to XML:
{
  "openapi": "3.0.0",
  "info": {
    "title": "Assimilated neutral archive API",
    "version": "1.0.0"
  },
  "paths": {
    "/sea": {
      "get": {
        "summary": "Team happen challenge address expert manage beyond",
        "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"
          }
        }
      }
    }
  }
}

[Assistant]
Approach:
1. Task: Convert api specification 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"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Assimilated neutral archive API</title>
<version>1.0.0</version>
</info>
<paths>
</sea>
<get>
<summary>Team happen challenge address expert manage beyond</summary>
<parameters>
<name>param0</name>
<in>query</in>
<type>string</type>
</parameters>
<parameters>
<name>param1</name>
<in>query</in>
<type>string</type>
</parameters>
<parameters>
<name>param2</name>
<in>query</in>
<type>string</type>
</parameters>
<responses>
<200>
<description>Success</description>
</200>
<400>
<description>Bad Request</description>
</400>
</responses>
</get>
<//sea>
</paths>
</api_specification>


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

[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-46905875",
  "platform": "instagram",
  "user_id": "2079b341-d50b-4860-ba15-aa28bbe0f5b3",
  "username": "xhernandez",
  "content": "Serious degree upon late.\nPainting throughout direction indicate night. Political business voice street child. Across between ready. Majority red mission prepare state.",
  "timestamp": "2026-01-07T13:51:26.735117",
  "hashtags": [
    "#easy",
    "#miss"
  ],
  "engagement": {
    "likes": 6808,
    "shares": 9,
    "comments": 24
  }
}


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

[User]
Convert the following CSV to JSON:
abstract,authors,citations,context_request_id,context_user_id,error_id,funding_source,keywords,level,message,paper_id,publication_doi,publication_venue,publication_year,service,stack_trace,timestamp,title
,,,f5a78ca9-3dcc-4c14-bcea-f5b7936cdde5,9d5113f2-65b2-4f61-b9b2-2b011fc1bc1b,3ee04eb7-6a96-4708-8070-7816402d081f,,,ERROR,Base information cell production decade back.,,,,,checkService,"[""at quality.py:463"", ""at but.py:317""]",2026-01-07T13:51:26.236854,
Follow worker the bed next note while kind. Down between better sell key quality.,"[{""name"": ""Austin Morgan"", ""affiliation"": ""Christensen-Abbott"", ""email"": ""dawsonjoy@example.org""}, {",92,,,,Ward-Martin,"[""son"", ""cell"", ""card"", ""game""]",,,arXiv:2022.50110,10.9154/LDSp,Nature,2023,,,,Open-source 3rdgeneration budgetary management
During end professional step region themselves line. Politics college forward financial without trut,"[{""name"": ""Emily Ramos"", ""affiliation"": ""Carter LLC"", ""email"": ""wandajackson@example.com""}, {""name"":",87,,,,None,"[""major"", ""network"", ""arm"", ""lawyer"", ""discuss""]",,,arXiv:2022.69826,10.4714/icib,Cell,2024,,,,Business-focused actuating application
"Side for maybe theory imagine meet. Poor manager approach keep.
Really join lead simply however. Lik","[{""name"": ""Chris Williams"", ""affiliation"": ""Vaughan-Mitchell"", ""email"": ""adamatkins@example.org""}, {",418,,,,"Henry, Potts and Hurley","[""allow"", ""generation"", ""husband"", ""less""]",,,arXiv:2023.71326,10.9330/YDKY,Nature,2023,,,,Focused multi-state website
Each sense around even against reach upon hold. Member respond majority magazine group everything bu,"[{""name"": ""Anthony Nelson"", ""affiliation"": ""Mosley-Mason"", ""email"": ""webbsarah@example.net""}, {""name",237,,,,None,"[""red"", ""lay"", ""future"", ""face""]",,,arXiv:2021.13376,10.7467/ttME,Cell,2020,,,,Realigned maximized knowledgebase

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

Output:
{
  "error_id": "3ee04eb7-6a96-4708-8070-7816402d081f",
  "timestamp": "2026-01-07T13:51:26.236854",
  "level": "ERROR",
  "service": "checkService",
  "message": "Base information cell production decade back.",
  "stack_trace": [
    "at quality.py:463",
    "at but.py:317"
  ],
  "context": {
    "user_id": "9d5113f2-65b2-4f61-b9b2-2b011fc1bc1b",
    "request_id": "f5a78ca9-3dcc-4c14-bcea-f5b7936cdde5"
  }
}


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

[User] Output course syllabus as TOML.

[Assistant]
Approach:
1. Task: Create course syllabus 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:
course_id = "CRS-8855"
code = "DBP130"
title = "Team-oriented 3rdgeneration implementation 101"
instructor = "Carl Davis"
credits = 3
term = "Fall 2024"
[[schedule]]
week = 1
topic = "manage"

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

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

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

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

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

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

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

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

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

[[schedule]]
week = 11
topic = "Mrs"

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


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<lab_result>
<patient_mrn>MRN-135092</patient_mrn>
<order_date>2026-01-02</order_date>
<panel>CBC</panel>
<results>
<test>Hemoglobin</test>
<value>129.6</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>120.7</value>
<unit>mg/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>141.8</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>131.3</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Glucose</test>
<value>147.1</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<result_id>LAB-9224780</result_id>
</lab_result>


[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": "Capital way what customer unit skill. Arm bar occur article mouth enjoy. Exactly approach mention single.\nStrong who against entire.\nKid television artist dream back agency. Need main ago investment job behavior.",
  "published": "2026-01-03T04:54:27.964292",
  "views": 73181,
  "headline": "Vision-oriented analyzing groupware",
  "section": "Business"
}


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

[User] Output api specification as XML.

[Assistant]
Approach:
1. Task: Create api specification 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"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Intuitive disintermediate website API</title>
<version>1.0.0</version>
</info>
<paths>
</reality>
<get>
<summary>Activity public whole paper there relationship tas</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>
<//reality>
</paths>
</api_specification>


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

[User] Create a YAML representation of experiment result.

[Assistant]
Approach:
1. Task: Create experiment 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:
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 XML format. Think step-by-step, then generate syntactically perfect XML.

[User]
Transform this JSON data into XML format:
{
  "openapi": "3.0.0",
  "info": {
    "title": "Sharable solution-oriented migration API",
    "version": "1.0.0"
  },
  "paths": {
    "/anything": {
      "get": {
        "summary": "Those all evidence respond she listen.",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          },
          {
            "name": "param1",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  }
}

[Assistant]
Approach:
1. Task: Convert api specification from JSON to XML
2. Complexity: 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"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Sharable solution-oriented migration API</title>
<version>1.0.0</version>
</info>
<paths>
</anything>
<get>
<summary>Those all evidence respond she listen.</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>
<//anything>
</paths>
</api_specification>


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

[User] Output api specification as YAML.

[Assistant]
Approach:
1. Task: Create api specification 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:
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


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

[User] Create a JSON representation of lab result.

[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-9548003",
  "patient_mrn": "MRN-322322",
  "order_date": "2026-01-03",
  "panel": "CMP",
  "results": [
    {
      "test": "Glucose",
      "value": 67.0,
      "unit": "g/dL",
      "flag": "high"
    },
    {
      "test": "Hemoglobin",
      "value": 66.7,
      "unit": "mg/dL",
      "flag": "low"
    },
    {
      "test": "Glucose",
      "value": 118.1,
      "unit": "mg/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 198.6,
      "unit": "mg/dL",
      "flag": "normal"
    },
    {
      "test": "Glucose",
      "value": 167.9,
      "unit": "mg/dL",
      "flag": "low"
    },
    {
      "test": "Hemoglobin",
      "value": 143.5,
      "unit": "mg/dL",
      "flag": "normal"
    },
    {
      "test": "Glucose",
      "value": 150.3,
      "unit": "g/dL",
      "flag": "low"
    }
  ]
}


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

[User] Output sales analytics as JSON.

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

Output:
{
  "period": "February 2024",
  "total_revenue": 3108970,
  "units_sold": 70292,
  "channels": [
    {
      "name": "online",
      "revenue": 1867975,
      "growth": -2.95
    },
    {
      "name": "retail",
      "revenue": 1947932,
      "growth": 22.54
    }
  ],
  "top_products": [
    {
      "sku": "SKU-5409",
      "sales": 492017
    },
    {
      "sku": "SKU-4816",
      "sales": 486050
    },
    {
      "sku": "SKU-9957",
      "sales": 44038
    }
  ]
}


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

[User] Create a JSON representation of research paper.

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

Output:
{
  "paper_id": "arXiv:2023.87771",
  "title": "User-centric stable ability",
  "authors": [
    {
      "name": "Todd Hall MD",
      "affiliation": "Nunez-Nguyen",
      "email": "grhodes@example.net"
    },
    {
      "name": "Makayla Long",
      "affiliation": "Stanley, Sellers and Jones",
      "email": "johnsontammy@example.net"
    }
  ],
  "abstract": "Behavior skin nation pay behind remain. Then put again. Process participant current all.",
  "keywords": [
    "design",
    "him",
    "blue",
    "less",
    "fine"
  ],
  "publication": {
    "venue": "Nature",
    "year": 2020,
    "doi": "10.6248/yEgY"
  },
  "citations": 194,
  "funding_source": null
}


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

[User] Create a JSON representation of error log.

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


[System] You are an expert in 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: 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:
{
  "experiment_id": "EXP-725280",
  "title": "Effect of city on expert",
  "methodology": {
    "design": "observational",
    "sample_size": 907,
    "duration_days": 166
  },
  "results": [
    {
      "metric": "safety",
      "baseline": 43.19,
      "endpoint": 64.81,
      "p_value": 0.4813
    },
    {
      "metric": "safety",
      "baseline": 71.73,
      "endpoint": 68.14,
      "p_value": 0.0851
    },
    {
      "metric": "safety",
      "baseline": 77.12,
      "endpoint": 63.9,
      "p_value": 0.1154
    }
  ],
  "conclusion": "significant"
}


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

[User] Output contract as TOML.

[Assistant]
Approach:
1. Task: Create contract 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:
contract_id = "CTR-457828"
effective_date = "2026-01-01"
term_months = 32


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

[User] Create a YAML representation of api specification.

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

Output:
openapi: 3.0.0
info:
  title: Assimilated neutral archive API
  version: 1.0.0
paths:
  /sea:
    get:
      summary: Team happen challenge address expert manage beyond
      parameters:
      - name: param0
        in: query
        type: string
      - name: param1
        in: query
        type: string
      - name: param2
        in: query
        type: string
      responses:
        '200':
          description: Success
        '400':
          description: Bad Request


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<social_media_post>
<post_id>POST-23186111</post_id>
<platform>twitter</platform>
<user_id>85951ac5-a9b8-4154-8edc-693bcde245cf</user_id>
<username>srodriguez</username>
<content>Stand leave decade year collection. Republican point edge yet business.
Suffer accept central against. Cup theory mouth side message.
Concern magazine exactly maybe oil difficult.</content>
<timestamp>2026-01-07T13:51:25.750515</timestamp>
<hashtags>#community</hashtags>
<hashtags>#whatever</hashtags>
<engagement>
<likes>4745</likes>
<shares>251</shares>
<comments>51</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-23186111",
  "platform": "twitter",
  "user_id": "85951ac5-a9b8-4154-8edc-693bcde245cf",
  "username": "srodriguez",
  "content": "Stand leave decade year collection. Republican point edge yet business.\nSuffer accept central against. Cup theory mouth side message.\nConcern magazine exactly maybe oil difficult.",
  "timestamp": "2026-01-07T13:51:25.750515",
  "hashtags": [
    "#community",
    "#whatever"
  ],
  "engagement": {
    "likes": 4745,
    "shares": 251,
    "comments": 51
  }
}


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

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

[Assistant]
Approach:
1. Task: Create customer review 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"?>
<customer_review>
<review_id>REV-7122533</review_id>
<content>Expert difficult hot radio mission. Throw southern he book way media particular.</content>
<rating>1</rating>
<date>2026-01-06</date>
<verified_purchase>False</verified_purchase>
</customer_review>


[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": "Seamless disintermediate flexibility API",
    "version": "1.0.0"
  },
  "paths": {
    "/significant": {
      "get": {
        "summary": "Box project skin day catch.",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  }
}


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

[User] Create a CSV representation of 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_/grow_get_parameters,paths_/grow_get_responses_200_description,paths_/grow_get_responses_400_description,paths_/grow_get_summary,publication_doi,publication_venue,publication_year,title
,,,,Streamlined logistical help-desk API,1.0.0,,3.0.0,,"[{""name"": ""param0"", ""in"": ""query"", ""type"": ""string""}, {""name"": ""param1"", ""in"": ""query"", ""type"": ""str",Success,Bad Request,Will entire deep source history.,,,,
"Exactly star nearly couple service study tell. Move also drug set positive even marriage air.
Both b","[{""name"": ""Briana Weaver"", ""affiliation"": ""Wood Group"", ""email"": ""jmontoya@example.org""}, {""name"": """,330,"Dixon, Johnson and Jones",,,"[""know"", ""eye"", ""current"", ""international""]",,arXiv:2024.12510,,,,,10.8383/YVRs,Cell,2024,Up-sized optimizing methodology
"Above hear son structure realize send factor. West smile support administration.
Picture say behind ","[{""name"": ""Raymond Patel"", ""affiliation"": ""Rivera Group"", ""email"": ""juarezsara@example.net""}, {""name",262,None,,,"[""three"", ""question"", ""quality"", ""attack"", ""land""]",,arXiv:2024.89280,,,,,10.9242/Oxtw,Science,2023,Advanced motivating capability


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

[User] Create a XML representation of experiment result.

[Assistant]
Approach:
1. Task: Create experiment 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"?>
<experiment_result>
<experiment_id>EXP-137327</experiment_id>
<title>Effect of class on read</title>
<methodology>
<design>RCT</design>
<sample_size>679</sample_size>
<duration_days>111</duration_days>
</methodology>
<results>
<metric>safety</metric>
<baseline>73.26</baseline>
<endpoint>72.84</endpoint>
<p_value>0.0533</p_value>
</results>
<results>
<metric>efficacy</metric>
<baseline>49.24</baseline>
<endpoint>28.3</endpoint>
<p_value>0.0809</p_value>
</results>
<conclusion>significant</conclusion>
</experiment_result>


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

[User] Generate prescription data in XML format.

[Assistant]
Approach:
1. Task: Create prescription 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"?>
<prescription>
<rx_id>RX-1995080</rx_id>
<patient_mrn>MRN-674224</patient_mrn>
<prescriber>Emily Herrera</prescriber>
<date>2026-01-05</date>
<medications>
<name>Lisinopril</name>
<dosage>10mg</dosage>
<frequency>BID</frequency>
<quantity>60</quantity>
</medications>
</prescription>


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

[User] Create a TOML representation of contract.

[Assistant]
Approach:
1. Task: Create contract 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:
effective_date = "2026-01-02"
term_months = 54
status = "pending"


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

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

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

Output:
{
  "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"
  }
}


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

[User] Output error log as JSON.

[Assistant]
Approach:
1. Task: Create error log 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:
{
  "error_id": "d03afc03-94bd-4dbb-bf49-9cda441c119b",
  "timestamp": "2026-01-07T13:51:25.952127",
  "level": "CRITICAL",
  "service": "fromService",
  "message": "Add perform politics some card score brother.",
  "stack_trace": [
    "at send.py:152",
    "at young.py:309"
  ],
  "context": {
    "user_id": "2b3e5573-7b69-4807-a899-cbaa4adadf38",
    "request_id": "beac9c14-4ae5-407d-9aae-d7a56f6790f6"
  }
}


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

[User] Create a YAML representation of sales analytics.

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

Output:
period: December 2023
total_revenue: 5338205
units_sold: 90572
channels:
- name: wholesale
  revenue: 2316482
  growth: -1.07
- name: online
  revenue: 3744469
  growth: -0.81
top_products:
- sku: SKU-4601
  sales: 454934
- sku: SKU-9892
  sales: 55264
- sku: SKU-8319
  sales: 254442


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

[User] Create a YAML representation of prescription.

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

Output:
rx_id: RX-1995080
patient_mrn: MRN-674224
prescriber: Emily Herrera
date: '2026-01-05'
medications:
- name: Lisinopril
  dosage: 10mg
  frequency: BID
  quantity: 60


[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-299234,2026-01-06,"[{""name"": ""Murphy, Hawkins and Mckenzie"", ""role"": ""party_a""}, {""name"": ""Collins-Miller"", ""role"": ""pa",pending,46,506357
CTR-337304,2026-01-06,"[{""name"": ""Smith Inc"", ""role"": ""party_a""}, {""name"": ""Ellis Inc"", ""role"": ""party_b""}]",active,32,719115
CTR-137609,2026-01-05,"[{""name"": ""Cruz-Chandler"", ""role"": ""party_a""}, {""name"": ""Ward-Kelley"", ""role"": ""party_b""}]",pending,29,406638
CTR-835177,2026-01-06,"[{""name"": ""Villegas-Todd"", ""role"": ""party_a""}, {""name"": ""Gutierrez Ltd"", ""role"": ""party_b""}]",pending,14,279705
CTR-398189,2026-01-06,"[{""name"": ""Barker, Patel and Brown"", ""role"": ""party_a""}, {""name"": ""Stevenson, Watson and Ward"", ""rol",executed,29,902465


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

[User] Create a YAML representation of prescription.

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

Output:
rx_id: RX-5305677
patient_mrn: MRN-215469
prescriber: Jeremy Hatfield
date: '2026-01-03'
medications:
- name: Metformin
  dosage: 10mg
  frequency: daily
  quantity: 90
- name: Metformin
  dosage: 5mg
  frequency: daily
  quantity: 30
- name: Atorvastatin
  dosage: 10mg
  frequency: BID
  quantity: 90