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

[User] Output research paper as JSON.

[Assistant]
Approach:
1. Task: Create research paper in JSON
2. Complexity: 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:
{
  "paper_id": "arXiv:2020.10600",
  "title": "Reactive bi-directional middleware",
  "authors": [
    {
      "name": "Sarah Rose",
      "affiliation": "Martin, Taylor and Mills",
      "email": "adrianporter@example.com"
    },
    {
      "name": "Samantha Garcia",
      "affiliation": "Santiago LLC",
      "email": "cbrewer@example.net"
    }
  ],
  "abstract": "Carry prove certain tell event break. Thus not actually teacher girl perhaps.",
  "keywords": [
    "public",
    "stock",
    "student",
    "hair",
    "hard"
  ],
  "publication": {
    "venue": "Cell",
    "year": 2022,
    "doi": "10.6112/KodW"
  },
  "citations": 273,
  "funding_source": "Salazar, Mullen and Johnson"
}


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

[User]
Transform this CSV data into XML format:
abstract,authors,citations,date,funding_source,keywords,paper_id,publication_doi,publication_venue,publication_year,student_id,title,total_score
,,,2026-01-01,,,,,,,STU-920172,,85
Talk difficult board laugh everything.,"[{""name"": ""Austin Diaz"", ""affiliation"": ""Huang-Vargas"", ""email"": ""samanthabarton@example.net""}, {""na",362,,None,"[""pick"", ""Congress"", ""wife"", ""from"", ""summer""]",arXiv:2024.27961,10.4296/Nsne,Nature,2022,,Face-to-face holistic middleware,
Within appear claim sure run. Focus citizen institution clear age.,"[{""name"": ""Daniel Mcdonald"", ""affiliation"": ""Day-Rowe"", ""email"": ""brittany36@example.org""}, {""name"":",147,,Wright-Sullivan,"[""vote"", ""safe"", ""nation""]",arXiv:2021.48338,10.8249/SgcD,Nature,2020,,Grass-roots neutral collaboration,
Wish relationship present enough remain blue professional. Low issue weight wind economy evidence bu,"[{""name"": ""Emily Gonzales"", ""affiliation"": ""Bryant-Rose"", ""email"": ""unelson@example.org""}, {""name"": ",273,,"Grimes, Martin and Clark","[""moment"", ""imagine"", ""blood""]",arXiv:2022.31167,10.5682/tMPO,Science,2023,,Reduced asymmetric framework,

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<student_assessment>
<date>2026-01-01</date>
<total_score>85</total_score>
<student_id>STU-920172</student_id>
</student_assessment>


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

[User] Generate research paper data in CSV format.

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

Output:
abstract,authors,citations,funding_source,keywords,paper_id,publication_doi,publication_venue,publication_year,title
"Law fund huge better or. Federal forward north law. Work available call never.
Carry cultural day fr","[{""name"": ""Jennifer Gray"", ""affiliation"": ""Bryant, Lewis and Wells"", ""email"": ""spalmer@example.com""}",45,None,"[""wind"", ""wife"", ""report"", ""financial""]",arXiv:2020.93852,10.1277/DPuH,Cell,2023,Reactive solution-oriented circuit
Poor mother allow place various fight push guess. Possible note on child place mouth.,"[{""name"": ""Victoria Wells"", ""affiliation"": ""Butler, Duran and Ramos"", ""email"": ""kathypage@example.or",433,"Case, Green and Kline","[""rich"", ""show"", ""design""]",arXiv:2024.38203,10.6937/xeQy,Nature,2020,Open-source analyzing open architecture
Almost true director everything. Realize commercial picture bed. East west plant such which receive.,"[{""name"": ""William Ferguson"", ""affiliation"": ""Baxter-Conley"", ""email"": ""kaiserkevin@example.org""}, {",48,None,"[""support"", ""care"", ""place"", ""some"", ""sound""]",arXiv:2024.97741,10.1731/NdTy,Nature,2024,Persistent fault-tolerant attitude
Time key choice need brother young. Beyond special professional have however if situation available.,"[{""name"": ""Patrick Wagner"", ""affiliation"": ""Davis, Wells and Harrison"", ""email"": ""lcook@example.com""",35,None,"[""avoid"", ""field"", ""audience"", ""draw""]",arXiv:2020.64952,10.2522/UKQb,Nature,2022,Realigned empowering secured line


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


[System] You are an expert in 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-7309915</rx_id>
<patient_mrn>MRN-389849</patient_mrn>
<prescriber>Briana Dickerson</prescriber>
<date>2026-01-03</date>
<medications>
<name>Metformin</name>
<dosage>20mg</dosage>
<frequency>daily</frequency>
<quantity>30</quantity>
</medications>
</prescription>


[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: 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:
medications:
- name: Atorvastatin
  dosage: 10mg
  frequency: BID
  quantity: 60
rx_id: RX-5523111
date: '2026-01-01'


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

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

[Assistant]
Approach:
1. Task: Create transaction record 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:
{
  "txn_id": "TXN-28879814",
  "customer_id": "b13e97b5-e84b-41ec-9dea-05b4809cdd35",
  "timestamp": "2026-01-07T13:51:25.895711",
  "items": [
    {
      "sku": "SKU-36351",
      "qty": 1,
      "price": 310.41
    },
    {
      "sku": "SKU-26629",
      "qty": 2,
      "price": 119.44
    },
    {
      "sku": "SKU-75447",
      "qty": 3,
      "price": 127.79
    },
    {
      "sku": "SKU-81003",
      "qty": 3,
      "price": 336.59
    }
  ],
  "subtotal": 994.66,
  "tax": 143.59,
  "total": 1762.36,
  "payment_method": "apple_pay"
}


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<clinical_note>
<note_id>CN-8348908</note_id>
<patient>
<mrn>MRN-109351</mrn>
<age>84</age>
<gender>F</gender>
</patient>
<encounter_date>2026-01-06</encounter_date>
<chief_complaint>fever</chief_complaint>
<vitals>
<bp>157/81</bp>

101

<temp_f>97.1</temp_f>
</vitals>
<assessment>
<problem>diabetes</problem>
<icd10>J60</icd10>
</assessment>
<assessment>
<problem>diabetes</problem>
<icd10>K69</icd10>
</assessment>
<assessment>
<problem>hypertension</problem>
<icd10>J80</icd10>
</assessment>
</clinical_note>

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

Output:
{
  "note_id": "CN-8348908",
  "patient": {
    "mrn": "MRN-109351",
    "age": 84,
    "gender": "F"
  },
  "encounter_date": "2026-01-06",
  "chief_complaint": "fever",
  "vitals": {
    "bp": "157/81",
    "hr": 101,
    "temp_f": 97.1
  },
  "assessment": [
    {
      "problem": "diabetes",
      "icd10": "J60"
    },
    {
      "problem": "diabetes",
      "icd10": "K69"
    },
    {
      "problem": "hypertension",
      "icd10": "J80"
    }
  ]
}


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

[User]
Transform this JSON data into TOML format:
{
  "course_id": "CRS-1797",
  "code": "QAA477",
  "title": "User-friendly composite interface 101",
  "instructor": "Selena Walker",
  "credits": 4,
  "term": "Fall 2024",
  "schedule": [
    {
      "week": 1,
      "topic": "all"
    },
    {
      "week": 2,
      "topic": "education"
    },
    {
      "week": 3,
      "topic": "will"
    },
    {
      "week": 4,
      "topic": "operation"
    },
    {
      "week": 5,
      "topic": "western"
    },
    {
      "week": 6,
      "topic": "plan"
    },
    {
      "week": 7,
      "topic": "allow"
    }
  ],
  "grading": {
    "homework": 30,
    "midterm": 30,
    "final": 40
  }
}

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

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

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

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

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

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

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

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

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


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

[User]
Reformat the data below from JSON to XML:
{
  "period": "March 2022",
  "total_revenue": 2472943,
  "units_sold": 2053,
  "channels": [
    {
      "name": "wholesale",
      "revenue": 3703587,
      "growth": 38.49
    },
    {
      "name": "retail",
      "revenue": 3200920,
      "growth": -8.82
    }
  ],
  "top_products": [
    {
      "sku": "SKU-8959",
      "sales": 220308
    },
    {
      "sku": "SKU-7189",
      "sales": 206126
    },
    {
      "sku": "SKU-5359",
      "sales": 225947
    }
  ]
}

[Assistant]
Approach:
1. Task: Convert sales analytics 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"?>
<sales_analytics>
<period>March 2022</period>
<total_revenue>2472943</total_revenue>
<units_sold>2053</units_sold>
<channels>
<name>wholesale</name>
<revenue>3703587</revenue>
<growth>38.49</growth>
</channels>
<channels>
<name>retail</name>
<revenue>3200920</revenue>
<growth>-8.82</growth>
</channels>
<top_products>
<sku>SKU-8959</sku>
<sales>220308</sales>
</top_products>
<top_products>
<sku>SKU-7189</sku>
<sales>206126</sales>
</top_products>
<top_products>
<sku>SKU-5359</sku>
<sales>225947</sales>
</top_products>
</sales_analytics>


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

[User] Create a XML representation of transaction record.

[Assistant]
Approach:
1. Task: Create transaction record 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"?>
<transaction_record>
<txn_id>TXN-38439045</txn_id>
<customer_id>39de4165-2950-403a-b7cf-252ec7bafdcc</customer_id>
<timestamp>2026-01-07T13:51:25.757679</timestamp>
<items>
<sku>SKU-68017</sku>
<qty>5</qty>
<price>287.63</price>
</items>
<items>
<sku>SKU-13598</sku>
<qty>1</qty>
<price>397.9</price>
</items>
<items>
<sku>SKU-25253</sku>
<qty>4</qty>
<price>226.78</price>
</items>
<items>
<sku>SKU-92380</sku>
<qty>1</qty>
<price>318.47</price>
</items>
<subtotal>964.6</subtotal>
<tax>142.48</tax>
<total>1270.74</total>
<payment_method>credit_card</payment_method>
</transaction_record>


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

[User] Create a JSON representation of clinical note.

[Assistant]
Approach:
1. Task: Create clinical note 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:
{
  "note_id": "CN-3766387",
  "patient": {
    "mrn": "MRN-378219",
    "age": 48,
    "gender": "F"
  },
  "encounter_date": "2026-01-04",
  "chief_complaint": "headache",
  "vitals": {
    "bp": "145/101",
    "hr": 106,
    "temp_f": 101.7
  },
  "assessment": [
    {
      "problem": "diabetes",
      "icd10": "J94"
    }
  ]
}


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

[User] Generate student assessment data in JSON format.

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


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

[User]
Transform this YAML data into CSV format:
course_id: CRS-9279
code: WQT213
title: Ameliorated 3rdgeneration groupware 101
instructor: Mariah Wilson
credits: 3
term: Fall 2020
schedule:
- week: 1
  topic: together
- week: 2
  topic: statement
- week: 3
  topic: these
- week: 4
  topic: American
- week: 5
  topic: read
- week: 6
  topic: age
- week: 7
  topic: course
grading:
  homework: 30
  midterm: 30
  final: 40

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

Output:
code,course_id,credits,grading_final,grading_homework,grading_midterm,instructor,schedule,term,title
WQT213,CRS-9279,3,40,30,30,Mariah Wilson,"[{""week"": 1, ""topic"": ""together""}, {""week"": 2, ""topic"": ""statement""}, {""week"": 3, ""topic"": ""these""},",Fall 2020,Ameliorated 3rdgeneration groupware 101
JPJ268,CRS-2230,4,40,30,30,Gabriella Cunningham,"[{""week"": 1, ""topic"": ""explain""}, {""week"": 2, ""topic"": ""want""}, {""week"": 3, ""topic"": ""catch""}, {""wee",Spring 2024,Inverse coherent software 101
AFH345,CRS-5134,4,40,30,30,Anthony Hester,"[{""week"": 1, ""topic"": ""pattern""}, {""week"": 2, ""topic"": ""trial""}, {""week"": 3, ""topic"": ""send""}, {""wee",Fall 2021,Right-sized asynchronous methodology 101
LES161,CRS-6999,4,40,30,30,Julie Davis,"[{""week"": 1, ""topic"": ""baby""}, {""week"": 2, ""topic"": ""girl""}, {""week"": 3, ""topic"": ""audience""}, {""wee",Fall 2023,Networked mission-critical firmware 101


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

[User] Create a TOML representation of prescription.

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

Output:
rx_id = "RX-1565761"
patient_mrn = "MRN-226686"
prescriber = "Regina Martin"
date = "2026-01-03"
[[medications]]
name = "Metformin"
dosage = "20mg"
frequency = "TID"
quantity = 60

[[medications]]
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]
Convert the following JSON to XML:
{
  "product_id": "PROD-319304",
  "name": "Self-enabling clear-thinking help-desk",
  "category": "clothing",
  "price": 510.64,
  "currency": "USD",
  "stock": 595,
  "is_available": true,
  "rating": 2.22,
  "reviews": 791,
  "specs": {
    "weight_kg": 30.42,
    "dimensions": "12x58x39cm"
  }
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<product_listing>
<product_id>PROD-319304</product_id>
<name>Self-enabling clear-thinking help-desk</name>
<category>clothing</category>
<price>510.64</price>
<currency>USD</currency>
<stock>595</stock>
<is_available>True</is_available>
<rating>2.22</rating>
<reviews>791</reviews>
<specs>
<weight_kg>30.42</weight_kg>
<dimensions>12x58x39cm</dimensions>
</specs>
</product_listing>


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

[User] Generate transaction record data in JSON format.

[Assistant]
Approach:
1. Task: Create transaction record 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:
{
  "txn_id": "TXN-20904368",
  "customer_id": "3fe35528-f72a-4e45-bcf8-f7cb059fe7e5",
  "timestamp": "2026-01-07T13:51:27.778783",
  "items": [
    {
      "sku": "SKU-59380",
      "qty": 2,
      "price": 447.63
    },
    {
      "sku": "SKU-56357",
      "qty": 4,
      "price": 130.56
    },
    {
      "sku": "SKU-96740",
      "qty": 2,
      "price": 230.78
    },
    {
      "sku": "SKU-55928",
      "qty": 1,
      "price": 169.07
    }
  ],
  "subtotal": 1853.52,
  "tax": 74.51,
  "total": 1419.49,
  "payment_method": "apple_pay"
}


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

[User]
Reformat the data below from YAML to XML:
patient_mrn: MRN-135092
order_date: '2026-01-02'
panel: CBC
results:
- test: Hemoglobin
  value: 129.6
  unit: g/dL
  flag: low
- test: Hemoglobin
  value: 120.7
  unit: mg/dL
  flag: low
- test: Hemoglobin
  value: 141.8
  unit: g/dL
  flag: low
- test: Hemoglobin
  value: 131.3
  unit: g/dL
  flag: low
- test: Glucose
  value: 147.1
  unit: mg/dL
  flag: high
result_id: LAB-9224780

[Assistant]
Approach:
1. Task: Convert lab result from YAML 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"?>
<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]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<rating>5</rating>
<review_id>REV-2205395</review_id>
<content>Respond order far story by area affect. Important also catch down choice office necessary political. Firm along bar.
Stuff create including star question traditional reflect. Share fast thought.</content>
</customer_review>

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

Output:
{
  "rating": 5,
  "review_id": "REV-2205395",
  "content": "Respond order far story by area affect. Important also catch down choice office necessary political. Firm along bar.\nStuff create including star question traditional reflect. Share fast thought."
}


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

[User] Create a XML representation of customer review.

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

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


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<review_id>REV-7250124</review_id>
<product_id>PROD-375265</product_id>
<user_id>48302d32-0445-4405-afc6-604ef6300782</user_id>
<rating>1</rating>
<title>Very responsibility coach economy sea public you.</title>
<content>Chair painting shake city kind good though. Find reality water support key.
Fly party couple production fight. Live attention anyone her traditional. I room blood condition research fund model.</content>
<date>2026-01-03</date>
<verified_purchase>True</verified_purchase>
<helpful_votes>78</helpful_votes>
</customer_review>


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

[User] Output research paper as TOML.

[Assistant]
Approach:
1. Task: Create research paper 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:
keywords = [ "lead", "list", "she",]
paper_id = "arXiv:2022.72917"
[[authors]]
name = "Emily Davis"
affiliation = "Nelson, Diaz and Humphrey"
email = "jpalmer@example.org"

[[authors]]
name = "Robert Clark"
affiliation = "James Inc"
email = "dennis02@example.net"

[publication]
venue = "Science"
year = 2022
doi = "10.6797/tlMT"


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

[User] Create a YAML representation of clinical note.

[Assistant]
Approach:
1. Task: Create clinical note in YAML
2. Complexity: 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:
note_id: CN-7237025
patient:
  mrn: MRN-276187
  age: 53
  gender: F
encounter_date: '2026-01-06'
chief_complaint: fever
vitals:
  bp: 95/82
  hr: 103
  temp_f: 102.9
assessment:
- problem: diabetes
  icd10: J46


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

[User] Create a XML representation of course syllabus.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<course_syllabus>
<course_id>CRS-4765</course_id>
VMZ479
<title>Exclusive grid-enabled software 101</title>
<instructor>Amy Baker</instructor>
<credits>4</credits>
<term>Fall 2022</term>
<schedule>
<week>1</week>
<topic>show</topic>
</schedule>
<schedule>
<week>2</week>
<topic>cut</topic>
</schedule>
<schedule>
<week>3</week>
<topic>next</topic>
</schedule>
<schedule>
<week>4</week>
<topic>everything</topic>
</schedule>
<schedule>
<week>5</week>
<topic>people</topic>
</schedule>
<schedule>
<week>6</week>
<topic>international</topic>
</schedule>
<schedule>
<week>7</week>
<topic>since</topic>
</schedule>
<grading>
<homework>30</homework>
<midterm>30</midterm>
<final>40</final>
</grading>
</course_syllabus>


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<social_media_post>
<post_id>POST-86945311</post_id>
<platform>facebook</platform>
<user_id>b9da037c-f6cd-4ced-8c95-ca7562cf6118</user_id>
<username>martinsteven</username>
<content>Forget late prevent year cold able arrive. Few possible himself sing community. Activity campaign sure south. Chance on none line best magazine education.</content>
<timestamp>2026-01-07T13:51:26.810240</timestamp>
<hashtags>#drop</hashtags>
<hashtags>#consider</hashtags>
<hashtags>#nature</hashtags>
<hashtags>#all</hashtags>
<engagement>
<likes>3344</likes>
<shares>900</shares>
<comments>482</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-86945311",
  "platform": "facebook",
  "user_id": "b9da037c-f6cd-4ced-8c95-ca7562cf6118",
  "username": "martinsteven",
  "content": "Forget late prevent year cold able arrive. Few possible himself sing community. Activity campaign sure south. Chance on none line best magazine education.",
  "timestamp": "2026-01-07T13:51:26.810240",
  "hashtags": [
    "#drop",
    "#consider",
    "#nature",
    "#all"
  ],
  "engagement": {
    "likes": 3344,
    "shares": 900,
    "comments": 482
  }
}


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

[User] Generate financial report data in JSON format.

[Assistant]
Approach:
1. Task: Create financial report in JSON
2. Complexity: 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:
{
  "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]
Convert the following TOML to YAML:
post_id = "POST-39452168"
platform = "twitter"
user_id = "ca270bc8-d443-4389-880a-6fc8dd3e9fa5"
username = "robertowens"
content = "With writer dinner any kitchen add well. Floor image speech charge rate manager vote. Worry involve benefit there nothing rock.\nFactor even apply how three box light."
timestamp = "2026-01-07T13:51:25.425211"
hashtags = [ "#training", "#Democrat", "#pattern", "#discover",]

[engagement]
likes = 5319
shares = 573
comments = 283

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

Output:
post_id: POST-39452168
platform: twitter
user_id: ca270bc8-d443-4389-880a-6fc8dd3e9fa5
username: robertowens
content: 'With writer dinner any kitchen add well. Floor image speech charge rate
  manager vote. Worry involve benefit there nothing rock.

  Factor even apply how three box light.'
timestamp: '2026-01-07T13:51:25.425211'
hashtags:
- '#training'
- '#Democrat'
- '#pattern'
- '#discover'
engagement:
  likes: 5319
  shares: 573
  comments: 283


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

[User] Produce a CSV document for a prescription.

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

Output:
date,medications,patient_mrn,prescriber,rx_id
2026-01-03,"[{""name"": ""Lisinopril"", ""dosage"": ""10mg"", ""frequency"": ""daily"", ""quantity"": 90}, {""name"": ""Metformin",MRN-446802,James Bryant,RX-8350891
2026-01-01,"[{""name"": ""Lisinopril"", ""dosage"": ""5mg"", ""frequency"": ""TID"", ""quantity"": 90}, {""name"": ""Lisinopril"",",MRN-689906,Ricky Dixon,RX-1001040
2026-01-02,"[{""name"": ""Atorvastatin"", ""dosage"": ""10mg"", ""frequency"": ""BID"", ""quantity"": 60}, {""name"": ""Lisinopri",MRN-103247,Kimberly Thornton,RX-2036843
2026-01-03,"[{""name"": ""Atorvastatin"", ""dosage"": ""5mg"", ""frequency"": ""BID"", ""quantity"": 90}, {""name"": ""Lisinopril",MRN-955779,Daniel Reyes,RX-8803463


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

[User]
Reformat the data below from CSV to TOML:
abstract,authors,citations,context_request_id,context_user_id,error_id,funding_source,keywords,level,paper_id,publication_doi,publication_venue,publication_year,service,stack_trace,title
,,,7878bb2d-6319-4d97-8924-bd0357b0788d,fe05329e-c851-4258-9b5b-a5822613303b,d3f1548e-3d70-475b-a25a-df504add1be1,,,WARNING,,,,,approachService,"[""at level.py:451"", ""at science.py:176"", ""at art.py:498"", ""at success.py:287""]",
Other entire almost now. Point some cover another each relationship later. Knowledge produce stay pl,"[{""name"": ""Joseph Rodriguez"", ""affiliation"": ""Williams Group"", ""email"": ""tonya16@example.org""}, {""na",281,,,,None,"[""edge"", ""whose"", ""matter""]",,arXiv:2023.86379,10.7736/MYhz,Nature,2024,,,Reduced 6thgeneration orchestration
"Put hot generation national happen operation reveal. Not machine guy computer or.
Wish according alm","[{""name"": ""John Dixon"", ""affiliation"": ""Jones, Nguyen and Saunders"", ""email"": ""robertsjonathan@examp",207,,,,"Morgan, Strickland and Stewart","[""phone"", ""arrive"", ""dream"", ""culture"", ""fight""]",,arXiv:2024.82627,10.2986/XYtI,Cell,2023,,,Advanced even-keeled challenge
"Act single method each budget body change.
Property military option animal. Military power developme","[{""name"": ""Brooke Wilson"", ""affiliation"": ""Vang, Hudson and Smith"", ""email"": ""andersoncody@example.o",454,,,,Martinez-Powell,"[""yet"", ""nearly"", ""happen"", ""owner""]",,arXiv:2021.77183,10.2819/exiH,Nature,2022,,,Customizable analyzing encryption
"Admit might recognize. Best plant particularly style later kitchen any.
Cut member identify themselv","[{""name"": ""Anthony Williams"", ""affiliation"": ""Lee LLC"", ""email"": ""acrawford@example.net""}, {""name"": ",198,,,,None,"[""ask"", ""those"", ""spring""]",,arXiv:2020.22950,10.1058/ILQY,Cell,2023,,,Up-sized bandwidth-monitored interface

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

Output:
service = "approachService"
stack_trace = [ "at level.py:451", "at science.py:176", "at art.py:498", "at success.py:287",]
level = "WARNING"
error_id = "d3f1548e-3d70-475b-a25a-df504add1be1"

[context]
user_id = "fe05329e-c851-4258-9b5b-a5822613303b"
request_id = "7878bb2d-6319-4d97-8924-bd0357b0788d"


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

[User] Output lab result as JSON.

[Assistant]
Approach:
1. Task: Create lab result in JSON
2. Complexity: 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:
{
  "result_id": "LAB-1812594",
  "patient_mrn": "MRN-755137",
  "order_date": "2026-01-06",
  "panel": "CMP",
  "results": [
    {
      "test": "Glucose",
      "value": 131.9,
      "unit": "mg/dL",
      "flag": "normal"
    },
    {
      "test": "Glucose",
      "value": 183.7,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "WBC",
      "value": 130.1,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "Hemoglobin",
      "value": 178.3,
      "unit": "g/dL",
      "flag": "low"
    }
  ]
}


[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: 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:
company,eps,expenses,metrics_profit_margin,metrics_roe,net_income,quarter,revenue,ticker
Williams Ltd,9.18,48847964,7.56,13.89,12028281,Q3 2022,93368790,IHFM
"Kelley, Jones and Walker",7.68,14323173,10.7,5.91,18941954,Q2 2024,91146087,NJNT
Salas-Stanley,1.98,34820493,17.93,24.27,6322133,Q2 2020,71057317,BLFI


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

[User]
Reformat the data below from YAML to XML:
title: Career hospital always money word day.
helpful_votes: 95
review_id: REV-5250684
verified_purchase: false
date: '2026-01-01'

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<title>Career hospital always money word day.</title>
<helpful_votes>95</helpful_votes>
<review_id>REV-5250684</review_id>
<verified_purchase>False</verified_purchase>
<date>2026-01-01</date>
</customer_review>


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

[User] Output prescription as TOML.

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

Output:
rx_id = "RX-8246470"
patient_mrn = "MRN-256913"
prescriber = "Victor Valentine"
date = "2026-01-01"
[[medications]]
name = "Lisinopril"
dosage = "20mg"
frequency = "daily"
quantity = 30

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

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


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

[User] Create a CSV representation of lab result.

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

Output:
abstract,authors,citations,funding_source,keywords,order_date,panel,paper_id,publication_doi,publication_venue,publication_year,results,title
,,,,,2026-01-05,Lipid,,,,,"[{""test"": ""Hemoglobin"", ""value"": 95.5, ""unit"": ""g/dL"", ""flag"": ""low""}, {""test"": ""Hemoglobin"", ""value",
Suggest money you Congress color choice ten. Crime beyond maybe body decade hard window natural.,"[{""name"": ""Steven Allen"", ""affiliation"": ""Shelton-Thomas"", ""email"": ""monicaporter@example.net""}, {""n",209,Robinson and Sons,"[""discuss"", ""thousand"", ""five"", ""can""]",,,arXiv:2022.53965,10.9987/ukuQ,Nature,2020,,Operative asynchronous frame
"Beat while from appear ask. Finally contain both number.
Sense whether walk plant tree. These or evi","[{""name"": ""Melissa Mcgee"", ""affiliation"": ""Welch-Jackson"", ""email"": ""robertsamanda@example.org""}, {""",29,None,"[""reality"", ""sing"", ""money"", ""yourself"", ""lose""]",,,arXiv:2020.48309,10.2897/DCIM,Cell,2023,,Reactive actuating access


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

[User]
Convert the following XML to TOML:
<?xml version="1.0" encoding="UTF-8"?>
<sales_analytics>
<period>June 2020</period>
<total_revenue>2603625</total_revenue>
<units_sold>51574</units_sold>
<channels>
<name>retail</name>
<revenue>1926384</revenue>
<growth>34.29</growth>
</channels>
<channels>
<name>online</name>
<revenue>1062444</revenue>
<growth>-1.99</growth>
</channels>
<top_products>
<sku>SKU-3818</sku>
<sales>48786</sales>
</top_products>
<top_products>
<sku>SKU-7605</sku>
<sales>408187</sales>
</top_products>
<top_products>
<sku>SKU-6728</sku>
<sales>223732</sales>
</top_products>
</sales_analytics>

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

Output:
period = "June 2020"
total_revenue = 2603625
units_sold = 51574
[[channels]]
name = "retail"
revenue = 1926384
growth = 34.29

[[channels]]
name = "online"
revenue = 1062444
growth = -1.99

[[top_products]]
sku = "SKU-3818"
sales = 48786

[[top_products]]
sku = "SKU-7605"
sales = 408187

[[top_products]]
sku = "SKU-6728"
sales = 223732


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

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

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

Output:
openapi = "3.0.0"

[info]
title = "Reactive exuding frame API"
version = "1.0.0"

[paths."/second".get]
summary = "Life century work throughout however miss another."
[[paths."/second".get.parameters]]
name = "param0"
in = "query"
type = "string"

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

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


[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: complex - 8-10 fields, 3-4 levels
3. Format rules: consistent indentation, colon-space syntax, hyphen lists
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
company: Williams Ltd
ticker: IHFM
quarter: Q3 2022
revenue: 93368790
expenses: 48847964
net_income: 12028281
eps: 9.18
metrics:
  profit_margin: 7.56
  roe: 13.89


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

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

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

Output:
post_id: POST-94493547
platform: instagram
user_id: ebddd714-2a63-4fd6-985c-fb7fe32db0b4
username: laura52
content: 'Property political your form stand cup blood. Business later seem sea represent
  enough relationship memory.

  What ok that look past. Budget understand mouth during brother pull type spring.'
timestamp: '2026-01-07T13:51:27.134920'
hashtags:
- '#red'
- '#hotel'
- '#create'
engagement:
  likes: 8599
  shares: 93
  comments: 39


[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-8293808",
  "patient": {
    "mrn": "MRN-980604",
    "age": 24,
    "gender": "F"
  },
  "encounter_date": "2026-01-05",
  "chief_complaint": "fever",
  "vitals": {
    "bp": "150/98",
    "hr": 93,
    "temp_f": 102.4
  },
  "assessment": [
    {
      "problem": "diabetes",
      "icd10": "J39"
    }
  ]
}

[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-8293808</note_id>
<patient>
<mrn>MRN-980604</mrn>
<age>24</age>
<gender>F</gender>
</patient>
<encounter_date>2026-01-05</encounter_date>
<chief_complaint>fever</chief_complaint>
<vitals>
<bp>150/98</bp>

93

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


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

[User] Create a XML representation of api specification.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Grass-roots 6thgeneration ability API</title>
<version>1.0.0</version>
</info>
<paths>
</million>
<get>
<summary>About little above investment already magazine.</summary>
<parameters>
<name>param0</name>
<in>query</in>
<type>string</type>
</parameters>
<responses>
<200>
<description>Success</description>
</200>
<400>
<description>Bad Request</description>
</400>
</responses>
</get>
<//million>
</paths>
</api_specification>


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

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

[Assistant]
Approach:
1. Task: Create product listing 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:
{
  "product_id": "PROD-110536",
  "name": "Organized didactic parallelism",
  "category": "clothing",
  "price": 68.12,
  "currency": "USD",
  "stock": 153,
  "is_available": true,
  "rating": 1.45,
  "reviews": 277,
  "specs": {
    "weight_kg": 1.85,
    "dimensions": "33x70x14cm"
  }
}


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

[User] Output transaction record as TOML.

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

Output:
txn_id = "TXN-60159725"
customer_id = "13707a49-23b0-4133-8216-7e83986c9575"
timestamp = "2026-01-07T13:51:27.689251"
subtotal = 1914.1
tax = 175.88
total = 1360.6
payment_method = "credit_card"
[[items]]
sku = "SKU-82899"
qty = 5
price = 298.29

[[items]]
sku = "SKU-51515"
qty = 4
price = 343.78

[[items]]
sku = "SKU-53336"
qty = 3
price = 488.21

[[items]]
sku = "SKU-52517"
qty = 2
price = 291.79


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

[User] Create a XML representation of api specification.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Streamlined logistical help-desk API</title>
<version>1.0.0</version>
</info>
<paths>
</grow>
<get>
<summary>Will entire deep source history.</summary>
<parameters>
<name>param0</name>
<in>query</in>
<type>string</type>
</parameters>
<parameters>
<name>param1</name>
<in>query</in>
<type>string</type>
</parameters>
<parameters>
<name>param2</name>
<in>query</in>
<type>string</type>
</parameters>
<responses>
<200>
<description>Success</description>
</200>
<400>
<description>Bad Request</description>
</400>
</responses>
</get>
<//grow>
</paths>
</api_specification>


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

[User] Generate api specification data in JSON format.

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

Output:
{
  "openapi": "3.0.0",
  "info": {
    "title": "Implemented leadingedge groupware API",
    "version": "1.0.0"
  },
  "paths": {
    "/reveal": {
      "get": {
        "summary": "Parent dark five.",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          },
          {
            "name": "param1",
            "in": "query",
            "type": "string"
          },
          {
            "name": "param2",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  }
}


[System] You are an expert in 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-7237025</note_id>
<patient>
<mrn>MRN-276187</mrn>
<age>53</age>
<gender>F</gender>
</patient>
<encounter_date>2026-01-06</encounter_date>
<chief_complaint>fever</chief_complaint>
<vitals>
<bp>95/82</bp>

103

<temp_f>102.9</temp_f>
</vitals>
<assessment>
<problem>diabetes</problem>
<icd10>J46</icd10>
</assessment>
</clinical_note>


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<clinical_note>
<note_id>CN-2804449</note_id>
<patient>
<mrn>MRN-394213</mrn>
<age>73</age>
<gender>F</gender>
</patient>
<encounter_date>2026-01-04</encounter_date>
<chief_complaint>fever</chief_complaint>
<vitals>
<bp>162/64</bp>

70

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

[Assistant]
Approach:
1. Task: Convert clinical note 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:
{
  "note_id": "CN-2804449",
  "patient": {
    "mrn": "MRN-394213",
    "age": 73,
    "gender": "F"
  },
  "encounter_date": "2026-01-04",
  "chief_complaint": "fever",
  "vitals": {
    "bp": "162/64",
    "hr": 70,
    "temp_f": 102.7
  },
  "assessment": [
    {
      "problem": "hypertension",
      "icd10": "K44"
    }
  ]
}


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

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

[Assistant]
Approach:
1. Task: Create customer review 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:
title: Career hospital always money word day.
helpful_votes: 95
review_id: REV-5250684
verified_purchase: false
date: '2026-01-01'


[System] You are an expert in 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"?>
<prescription>
<rx_id>RX-7328466</rx_id>
<patient_mrn>MRN-740510</patient_mrn>
<prescriber>William Hebert</prescriber>
<date>2026-01-04</date>
<medications>
<name>Lisinopril</name>
<dosage>20mg</dosage>
<frequency>TID</frequency>
<quantity>30</quantity>
</medications>
<medications>
<name>Metformin</name>
<dosage>20mg</dosage>
<frequency>BID</frequency>
<quantity>60</quantity>
</medications>
</prescription>

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

Output:
{
  "rx_id": "RX-7328466",
  "patient_mrn": "MRN-740510",
  "prescriber": "William Hebert",
  "date": "2026-01-04",
  "medications": [
    {
      "name": "Lisinopril",
      "dosage": "20mg",
      "frequency": "TID",
      "quantity": 30
    },
    {
      "name": "Metformin",
      "dosage": "20mg",
      "frequency": "BID",
      "quantity": 60
    }
  ]
}


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

[User] Output experiment result as JSON.

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


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

[User] Generate lab result data in TOML format.

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

Output:
patient_mrn = "MRN-119365"
order_date = "2026-01-05"
[[results]]
test = "Glucose"
value = 134.6
unit = "g/dL"
flag = "high"

[[results]]
test = "Hemoglobin"
value = 69.4
unit = "g/dL"
flag = "low"

[[results]]
test = "Glucose"
value = 85.6
unit = "mg/dL"
flag = "high"

[[results]]
test = "WBC"
value = 69.6
unit = "mg/dL"
flag = "low"

[[results]]
test = "Hemoglobin"
value = 79.1
unit = "g/dL"
flag = "high"


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

[User] Produce a CSV document for a experiment result.

[Assistant]
Approach:
1. Task: Create experiment result 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:
conclusion,experiment_id,methodology_design,methodology_duration_days,methodology_sample_size,results,title
non-significant,EXP-318732,observational,155,303,"[{""metric"": ""safety"", ""baseline"": 20.77, ""endpoint"": 67.03, ""p_value"": 0.1826}, {""metric"": ""safety"",",Effect of produce on stock
significant,EXP-322249,RCT,33,531,"[{""metric"": ""safety"", ""baseline"": 79.17, ""endpoint"": 95.39, ""p_value"": 0.1249}, {""metric"": ""safety"",",Effect of fall on expect
non-significant,EXP-560396,observational,289,973,"[{""metric"": ""efficacy"", ""baseline"": 41.39, ""endpoint"": 66.0, ""p_value"": 0.2089}, {""metric"": ""efficac",Effect of building on number
significant,EXP-368172,observational,275,57,"[{""metric"": ""safety"", ""baseline"": 99.77, ""endpoint"": 49.05, ""p_value"": 0.0553}, {""metric"": ""safety"",",Effect of human on either
significant,EXP-943936,observational,316,245,"[{""metric"": ""safety"", ""baseline"": 97.63, ""endpoint"": 51.5, ""p_value"": 0.4471}, {""metric"": ""efficacy""",Effect of see on trade


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

[User] Create a CSV representation of financial report.

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

Output:
company,eps,expenses,metrics_profit_margin,metrics_roe,net_income,quarter,revenue,ticker
Richardson-Gonzalez,6.0,,,,13953656,Q3 2020,,
Reed-Duncan,3.44,77600046,8.1,23.92,14931813,Q1 2023,47978642,FQJY
Nelson Inc,6.78,43300050,21.08,18.42,17789529,Q2 2020,68103050,LRQG
Kelly Inc,0.66,45167491,24.52,5.26,16072636,Q2 2023,80664579,RTQO


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

[User] Output research paper as CSV.

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

Output:
abstract,authors,citations,funding_source,keywords,paper_id,publication_doi,publication_venue,publication_year,title
Economy instead thank kitchen. For pattern he purpose strong goal challenge.,"[{""name"": ""Evan Reed"", ""affiliation"": ""Orr, Wheeler and Johnson"", ""email"": ""cheryl05@example.net""}, ",115,None,"[""power"", ""main"", ""light"", ""form"", ""system""]",arXiv:2020.69453,10.9550/gbOm,Cell,2024,Assimilated needs-based portal
"Machine property natural pay set.
Attention system leg organization suddenly few rule. Catch blue me","[{""name"": ""Nancy Barr"", ""affiliation"": ""Perez-Garcia"", ""email"": ""fnguyen@example.org""}, {""name"": ""St",357,Davis Group,"[""involve"", ""only"", ""minute"", ""behind"", ""just""]",arXiv:2024.93265,10.2252/kabX,Science,2020,Open-source 5thgeneration algorithm
Forward consumer term bed require experience. Understand game capital research speak officer. Whole ,"[{""name"": ""Kim Kelly"", ""affiliation"": ""Lewis Inc"", ""email"": ""andrewharding@example.net""}, {""name"": """,174,Smith-Garcia,"[""they"", ""I"", ""get"", ""more""]",arXiv:2021.79681,10.1750/SNwV,Cell,2020,Virtual static conglomeration


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

[User]
Transform this JSON data into XML format:
{
  "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
    }
  ]
}

[Assistant]
Approach:
1. Task: Convert sales analytics 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"?>
<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>


[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:
{
  "review_id": "REV-9982202",
  "product_id": "PROD-452864",
  "user_id": "015289de-7f3e-45e2-b1d0-7fe22aff92a9",
  "rating": 3,
  "title": "Example center fill free.",
  "content": "North describe old attention usually third. Important wish security ago somebody remain everyone modern. Significant chair place throughout study administration American.",
  "date": "2026-01-04",
  "verified_purchase": false,
  "helpful_votes": 34
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<review_id>REV-9982202</review_id>
<product_id>PROD-452864</product_id>
<user_id>015289de-7f3e-45e2-b1d0-7fe22aff92a9</user_id>
<rating>3</rating>
<title>Example center fill free.</title>
<content>North describe old attention usually third. Important wish security ago somebody remain everyone modern. Significant chair place throughout study administration American.</content>
<date>2026-01-04</date>
<verified_purchase>False</verified_purchase>
<helpful_votes>34</helpful_votes>
</customer_review>


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

[User] Output transaction record as TOML.

[Assistant]
Approach:
1. Task: Create transaction record 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:
tax = 39.55
total = 1865.58
customer_id = "bf96f80b-072c-4f04-82b0-c235c01681a8"
[[items]]
sku = "SKU-71565"
qty = 1
price = 387.38

[[items]]
sku = "SKU-23891"
qty = 1
price = 432.74

[[items]]
sku = "SKU-77840"
qty = 1
price = 463.12

[[items]]
sku = "SKU-27496"
qty = 3
price = 295.3


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

[User] Create a XML representation of transaction record.

[Assistant]
Approach:
1. Task: Create transaction record 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"?>
<transaction_record>
<txn_id>TXN-20904368</txn_id>
<customer_id>3fe35528-f72a-4e45-bcf8-f7cb059fe7e5</customer_id>
<timestamp>2026-01-07T13:51:27.778783</timestamp>
<items>
<sku>SKU-59380</sku>
<qty>2</qty>
<price>447.63</price>
</items>
<items>
<sku>SKU-56357</sku>
<qty>4</qty>
<price>130.56</price>
</items>
<items>
<sku>SKU-96740</sku>
<qty>2</qty>
<price>230.78</price>
</items>
<items>
<sku>SKU-55928</sku>
<qty>1</qty>
<price>169.07</price>
</items>
<subtotal>1853.52</subtotal>
<tax>74.51</tax>
<total>1419.49</total>
<payment_method>apple_pay</payment_method>
</transaction_record>


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

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

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

Output:
company: Martinez, Patterson and Hunter
ticker: PPOB
quarter: Q1 2023
revenue: 66694743
expenses: 21448775
net_income: 421192
eps: 2.32
metrics:
  profit_margin: 7.89
  roe: 9.32


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

[User] Generate api specification data in JSON format.

[Assistant]
Approach:
1. Task: Create api specification in JSON
2. Complexity: 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": {
    "/sense": {
      "get": {
        "summary": "Pay yes agree executive year ahead program.",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  },
  "info": {
    "title": "Customer-focused zero-defect array API",
    "version": "1.0.0"
  }
}


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

[User] Create a XML representation of news article.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<news_article>
<article_id>ART-8136358</article_id>
<headline>Realigned multimedia paradigm</headline>
<author>Brian White</author>
<published>2026-01-02T14:21:25.908532</published>

Sports

<content>Give model worry sense. Including reflect teacher near image.
Culture kitchen run first would. Agency media particularly past office every.
Bag water address admit. Skin tend Mr significant dark pretty. Painting water campaign.</content>
<tags>involve</tags>
<tags>service</tags>
<tags>along</tags>
<tags>stand</tags>
<views>7987</views>
<shares>4175</shares>
</news_article>


[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: 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:
{
  "error_id": "03dcbba2-8070-483e-a807-51e4c6301bf5",
  "timestamp": "2026-01-07T13:51:27.875594",
  "level": "WARNING",
  "service": "stockService",
  "message": "Feel garden dark.",
  "stack_trace": [
    "at another.py:304",
    "at happy.py:331",
    "at record.py:415"
  ],
  "context": {
    "user_id": "cedcf075-a01b-42e9-acdc-a300ea843992",
    "request_id": "acbfd7fd-a4ab-431b-a098-ac4537826f14"
  }
}


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

[User] Generate sales analytics data in JSON format.

[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 2020",
  "total_revenue": 2337421,
  "units_sold": 23839,
  "channels": [
    {
      "name": "retail",
      "revenue": 3840938,
      "growth": 18.52
    },
    {
      "name": "wholesale",
      "revenue": 1512471,
      "growth": 13.02
    }
  ],
  "top_products": [
    {
      "sku": "SKU-1744",
      "sales": 276633
    },
    {
      "sku": "SKU-5145",
      "sales": 26445
    },
    {
      "sku": "SKU-9218",
      "sales": 412054
    }
  ]
}


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

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

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

Output:
article_id,author,content,headline,published,section,shares,tags,views
ART-3281345,James Dunn,"Win take among professor. Glass reflect black similar future. Risk than tree.
Economic sit plan. Ava",Streamlined object-oriented toolset,2026-01-03T08:23:33.060508,Politics,293,"[""hit"", ""summer"", ""official"", ""rather""]",75669
ART-2637212,Brett Knight,Nearly production partner response today sound speak who. Far page build information study. Final cl,Reduced directional superstructure,2026-01-05T02:40:29.446745,Tech,2430,"[""nor"", ""kid"", ""everything""]",78279
ART-4830568,Anthony Burton,"Culture form on box population list. Road activity camera newspaper rule ability material later.
Nat",Total motivating groupware,2026-01-06T01:48:09.400241,Politics,406,"[""there"", ""run"", ""development"", ""hand""]",56144
ART-6293018,Hannah Richardson,Him paper as PM born city. Management such lawyer act. Your knowledge individual call discover song ,Grass-roots tertiary concept,2026-01-03T20:34:00.883621,Politics,1743,"[""year"", ""question"", ""about""]",7305


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

Output:
abstract,authors,citations,funding_source,info_title,info_version,keywords,openapi,paper_id,paths_/somebody_get_parameters,paths_/somebody_get_responses_200_description,paths_/somebody_get_responses_400_description,paths_/somebody_get_summary,publication_doi,publication_venue,publication_year,title
,,,,Networked system-worthy project API,1.0.0,,3.0.0,,"[{""name"": ""param0"", ""in"": ""query"", ""type"": ""string""}, {""name"": ""param1"", ""in"": ""query"", ""type"": ""str",Success,Bad Request,Threat common organization project.,,,,
Road role media each represent. Similar recent your piece reach fact whose great. Cover country form,"[{""name"": ""Olivia Friedman"", ""affiliation"": ""Graham, Foster and Briggs"", ""email"": ""sean94@example.co",394,"Burnett, Sanders and Williams",,,"[""today"", ""dream"", ""step"", ""career"", ""my""]",,arXiv:2020.11439,,,,,10.5503/fjno,Nature,2024,Cloned eco-centric frame
"Entire tonight hold professor child should after. Attention commercial available general.
Sound refl","[{""name"": ""Leslie Russell"", ""affiliation"": ""Foster PLC"", ""email"": ""josephfreeman@example.net""}, {""na",40,None,,,"[""community"", ""moment"", ""message""]",,arXiv:2020.52271,,,,,10.8657/wzUn,Nature,2022,De-engineered static open system
"Alone responsibility trip hair eight rule.
Congress degree certain a wear. Amount which relationship","[{""name"": ""Jonathan Holland"", ""affiliation"": ""Kramer-Chandler"", ""email"": ""hoffmanelizabeth@example.c",28,None,,,"[""player"", ""word"", ""century"", ""fast""]",,arXiv:2023.57345,,,,,10.5087/XDqf,Cell,2021,Advanced next generation algorithm


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

[User] Produce a CSV document for a clinical note.

[Assistant]
Approach:
1. Task: Create clinical note 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,chief_complaint,encounter_date,note_id,patient_age,patient_gender,patient_mrn,vitals_bp,vitals_hr,vitals_temp_f
"[{""problem"": ""diabetes"", ""icd10"": ""I32""}]",fever,2026-01-06,CN-4493327,62,F,MRN-934301,141/91,100,98.5
"[{""problem"": ""diabetes"", ""icd10"": ""I28""}]",chest pain,2026-01-06,CN-7363473,35,M,MRN-956112,163/72,102,100.3
"[{""problem"": ""diabetes"", ""icd10"": ""J22""}, {""problem"": ""hypertension"", ""icd10"": ""I60""}, {""problem"": """,chest pain,2026-01-02,CN-2016484,54,F,MRN-545642,147/94,119,100.1
"[{""problem"": ""hypertension"", ""icd10"": ""I60""}, {""problem"": ""diabetes"", ""icd10"": ""I71""}, {""problem"": """,chest pain,2026-01-04,CN-5987083,44,F,MRN-291192,167/80,98,101.9


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

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

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

Output:
abstract,authors,channels,citations,funding_source,keywords,paper_id,period,publication_doi,publication_venue,publication_year,title,top_products,total_revenue,units_sold
,,"[{""name"": ""wholesale"", ""revenue"": 941227, ""growth"": 26.4}, {""name"": ""retail"", ""revenue"": 937409, ""gr",,,,,June 2024,,,,,"[{""sku"": ""SKU-2900"", ""sales"": 81858}, {""sku"": ""SKU-8266"", ""sales"": 123988}, {""sku"": ""SKU-9969"", ""sal",5319249,96009
May bag population minute them administration. Big high civil thing. Social green present question f,"[{""name"": ""David Ortiz"", ""affiliation"": ""Mcgee, Stephenson and Washington"", ""email"": ""swansondave@ex",,175,None,"[""believe"", ""across"", ""international""]",arXiv:2023.75561,,10.2087/iVVH,Science,2024,Innovative multi-tasking website,,,
Low exactly film develop toward benefit. Parent style father home treat high American push. Three an,"[{""name"": ""Luis Mcdaniel"", ""affiliation"": ""Avila, Fischer and Jensen"", ""email"": ""terrijackson@exampl",,487,"Edwards, Maynard and Allen","[""information"", ""individual"", ""test""]",arXiv:2023.43941,,10.2487/WpzL,Science,2022,Universal zero administration success,,,


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

Output:
abstract,authors,citations,funding_source,info_title,info_version,keywords,openapi,paper_id,paths_/edge_get_parameters,paths_/edge_get_responses_200_description,paths_/edge_get_responses_400_description,paths_/edge_get_summary,publication_doi,publication_venue,publication_year,title
,,,,Visionary eco-centric methodology API,1.0.0,,3.0.0,,"[{""name"": ""param0"", ""in"": ""query"", ""type"": ""string""}, {""name"": ""param1"", ""in"": ""query"", ""type"": ""str",Success,Bad Request,Simple really social range.,,,,
Thing take protect hospital. Radio high cover drive age then. Behavior administration produce amount,"[{""name"": ""Lee Austin DDS"", ""affiliation"": ""Hines-Schneider"", ""email"": ""jessica25@example.org""}, {""n",328,None,,,"[""me"", ""maybe"", ""address""]",,arXiv:2024.13556,,,,,10.3244/tpFp,Nature,2024,Business-focused tertiary secured line
Sound too skill home behavior structure food marriage.,"[{""name"": ""James Taylor"", ""affiliation"": ""Mercer PLC"", ""email"": ""josephrussell@example.org""}, {""name",7,None,,,"[""quite"", ""avoid"", ""until"", ""decade""]",,arXiv:2024.68135,,,,,10.4269/jNlx,Cell,2024,Diverse stable system engine
Build similar deep weight conference that success. Since put perform experience between fire.,"[{""name"": ""Kimberly Powell"", ""affiliation"": ""Cooper, King and Moore"", ""email"": ""velezsarah@example.n",484,"Lopez, Miller and Fernandez",,,"[""market"", ""by"", ""letter"", ""report""]",,arXiv:2020.99809,,,,,10.7765/KBOi,Cell,2020,Polarized systemic application


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

[User] Generate financial report data in XML format.

[Assistant]
Approach:
1. Task: Create financial report 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"?>
<financial_report>
<company>Thompson, Yang and Roberts</company>
<ticker>ATOM</ticker>
<quarter>Q1 2022</quarter>
<revenue>59725729</revenue>
<expenses>36274579</expenses>
<net_income>7802792</net_income>
<eps>8.84</eps>
<metrics>
<profit_margin>17.46</profit_margin>
<roe>22.69</roe>
</metrics>
</financial_report>


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

[User] Generate student assessment data in YAML format.

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

Output:
assessment_id: ASMT-852879
student_id: STU-517758
course_id: CRS-9070
type: exam
date: '2026-01-04'
scores:
- question: 1
  points_earned: 4
  points_possible: 10
- question: 2
  points_earned: 10
  points_possible: 10
- question: 3
  points_earned: 1
  points_possible: 10
- question: 4
  points_earned: 2
  points_possible: 10
- question: 5
  points_earned: 7
  points_possible: 10
- question: 6
  points_earned: 4
  points_possible: 10
- question: 7
  points_earned: 3
  points_possible: 10
- question: 8
  points_earned: 10
  points_possible: 10
- question: 9
  points_earned: 7
  points_possible: 10
- question: 10
  points_earned: 9
  points_possible: 10
- question: 11
  points_earned: 6
  points_possible: 10
- question: 12
  points_earned: 8
  points_possible: 10
total_score: 58
percentage: 53.23
grade: C


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

[User] Create a XML representation of prescription.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<prescription>
<prescriber>Melinda Black</prescriber>
<date>2026-01-04</date>
<rx_id>RX-8618237</rx_id>
</prescription>


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<news_article>
<article_id>ART-6846954</article_id>
<headline>Triple-buffered intangible knowledgebase</headline>
<author>Steven Burgess</author>
<published>2026-01-02T13:52:55.283034</published>

Politics

<content>Police report arm sense find civil during. New avoid old future quality finally bad. Meeting child effect go play issue.
Thousand security article two color early. Avoid commercial science. Low method cultural personal night often.</content>
<tags>couple</tags>
<tags>specific</tags>
<tags>him</tags>
<views>35509</views>
<shares>3662</shares>
</news_article>

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

Output:
{
  "article_id": "ART-6846954",
  "headline": "Triple-buffered intangible knowledgebase",
  "author": "Steven Burgess",
  "published": "2026-01-02T13:52:55.283034",
  "section": "Politics",
  "content": "Police report arm sense find civil during. New avoid old future quality finally bad. Meeting child effect go play issue.\nThousand security article two color early. Avoid commercial science. Low method cultural personal night often.",
  "tags": [
    "couple",
    "specific",
    "him"
  ],
  "views": 35509,
  "shares": 3662
}


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

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

[Assistant]
Approach:
1. Task: Create student assessment 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:
assessment_id = "ASMT-549878"
student_id = "STU-264168"
course_id = "CRS-6692"
type = "assignment"
date = "2026-01-01"
total_score = 70
percentage = 54.38
grade = "C"
[[scores]]
question = 1
points_earned = 7
points_possible = 10

[[scores]]
question = 2
points_earned = 1
points_possible = 10

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

[[scores]]
question = 4
points_earned = 1
points_possible = 10

[[scores]]
question = 5
points_earned = 4
points_possible = 10

[[scores]]
question = 6
points_earned = 1
points_possible = 10

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

[[scores]]
question = 8
points_earned = 1
points_possible = 10


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

[User]
Reformat the data below from JSON to XML:
{
  "period": "May 2020",
  "total_revenue": 9864225,
  "units_sold": 74086,
  "channels": [
    {
      "name": "online",
      "revenue": 906832,
      "growth": -8.93
    },
    {
      "name": "wholesale",
      "revenue": 2437365,
      "growth": 2.73
    }
  ],
  "top_products": [
    {
      "sku": "SKU-7032",
      "sales": 420063
    },
    {
      "sku": "SKU-9360",
      "sales": 149398
    },
    {
      "sku": "SKU-9440",
      "sales": 105905
    }
  ]
}

[Assistant]
Approach:
1. Task: Convert sales analytics 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"?>
<sales_analytics>
<period>May 2020</period>
<total_revenue>9864225</total_revenue>
<units_sold>74086</units_sold>
<channels>
<name>online</name>
<revenue>906832</revenue>
<growth>-8.93</growth>
</channels>
<channels>
<name>wholesale</name>
<revenue>2437365</revenue>
<growth>2.73</growth>
</channels>
<top_products>
<sku>SKU-7032</sku>
<sales>420063</sales>
</top_products>
<top_products>
<sku>SKU-9360</sku>
<sales>149398</sales>
</top_products>
<top_products>
<sku>SKU-9440</sku>
<sales>105905</sales>
</top_products>
</sales_analytics>


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<sales_analytics>
<period>December 2023</period>
<total_revenue>5338205</total_revenue>
<units_sold>90572</units_sold>
<channels>
<name>wholesale</name>
<revenue>2316482</revenue>
<growth>-1.07</growth>
</channels>
<channels>
<name>online</name>
<revenue>3744469</revenue>
<growth>-0.81</growth>
</channels>
<top_products>
<sku>SKU-4601</sku>
<sales>454934</sales>
</top_products>
<top_products>
<sku>SKU-9892</sku>
<sales>55264</sales>
</top_products>
<top_products>
<sku>SKU-8319</sku>
<sales>254442</sales>
</top_products>
</sales_analytics>

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

Output:
{
  "period": "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 JSON format. Think step-by-step, then generate syntactically perfect JSON.

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<social_media_post>
<post_id>POST-29576154</post_id>
<platform>instagram</platform>
<user_id>b3774d2a-dced-4164-bd7b-7d043d7ec920</user_id>
<username>boydkaren</username>
<content>Responsibility this statement area thing imagine free. Under quickly treatment ever end social military. Majority before treatment decide.</content>
<timestamp>2026-01-07T13:51:27.160344</timestamp>
<hashtags>#involve</hashtags>
<hashtags>#fact</hashtags>
<hashtags>#rest</hashtags>
<engagement>
<likes>923</likes>
<shares>56</shares>
<comments>396</comments>
</engagement>
</social_media_post>

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

Output:
{
  "post_id": "POST-29576154",
  "platform": "instagram",
  "user_id": "b3774d2a-dced-4164-bd7b-7d043d7ec920",
  "username": "boydkaren",
  "content": "Responsibility this statement area thing imagine free. Under quickly treatment ever end social military. Majority before treatment decide.",
  "timestamp": "2026-01-07T13:51:27.160344",
  "hashtags": [
    "#involve",
    "#fact",
    "#rest"
  ],
  "engagement": {
    "likes": 923,
    "shares": 56,
    "comments": 396
  }
}


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

[User]
Reformat the data below from JSON to TOML:
{
  "note_id": "CN-9595817",
  "patient": {
    "mrn": "MRN-972408",
    "age": 32,
    "gender": "F"
  },
  "encounter_date": "2026-01-02",
  "chief_complaint": "chest pain",
  "vitals": {
    "bp": "102/103",
    "hr": 113,
    "temp_f": 102.5
  },
  "assessment": [
    {
      "problem": "hypertension",
      "icd10": "K99"
    }
  ]
}

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

Output:
note_id = "CN-9595817"
encounter_date = "2026-01-02"
chief_complaint = "chest pain"
[[assessment]]
problem = "hypertension"
icd10 = "K99"

[patient]
mrn = "MRN-972408"
age = 32
gender = "F"

[vitals]
bp = "102/103"
hr = 113
temp_f = 102.5


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

[User] Create a XML representation of 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>
<helpful_votes>39</helpful_votes>
<date>2026-01-04</date>
<rating>5</rating>
<review_id>REV-1864702</review_id>
<title>State standard bad message use.</title>
</customer_review>


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

[User] Create a TOML representation of news article.

[Assistant]
Approach:
1. Task: Create news article 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:
article_id = "ART-6846954"
headline = "Triple-buffered intangible knowledgebase"
author = "Steven Burgess"
published = "2026-01-02T13:52:55.283034"
section = "Politics"
content = "Police report arm sense find civil during. New avoid old future quality finally bad. Meeting child effect go play issue.\nThousand security article two color early. Avoid commercial science. Low method cultural personal night often."
tags = [ "couple", "specific", "him",]
views = 35509
shares = 3662


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

[User] Output news article as XML.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<news_article>
<article_id>ART-6846954</article_id>
<headline>Triple-buffered intangible knowledgebase</headline>
<author>Steven Burgess</author>
<published>2026-01-02T13:52:55.283034</published>

Politics

<content>Police report arm sense find civil during. New avoid old future quality finally bad. Meeting child effect go play issue.
Thousand security article two color early. Avoid commercial science. Low method cultural personal night often.</content>
<tags>couple</tags>
<tags>specific</tags>
<tags>him</tags>
<views>35509</views>
<shares>3662</shares>
</news_article>


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

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

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

Output:
error_id = "385c5830-2f90-42e3-ae2f-53faace4448a"
timestamp = "2026-01-07T13:51:26.292009"
level = "CRITICAL"
service = "almostService"
message = "People party agreement mother that investment approach."
stack_trace = [ "at fight.py:491", "at city.py:369", "at statement.py:378",]

[context]
user_id = "264dfcb4-39aa-45b1-999f-d115795470f4"
request_id = "4c579c9e-314d-44f6-9e5a-9c3c95ea5e82"


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

[User] Output research paper as TOML.

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

Output:
paper_id = "arXiv:2022.87629"
title = "Decentralized zero tolerance knowledgebase"
abstract = "System many view vote. Into challenge wind result new good."
keywords = [ "modern", "over", "during", "affect", "sport",]
citations = 187
funding_source = "Fischer and Sons"
[[authors]]
name = "Jonathan Murphy"
affiliation = "Long and Sons"
email = "loconnell@example.org"

[[authors]]
name = "Patrick Skinner"
affiliation = "Williams and Sons"
email = "chentimothy@example.org"

[[authors]]
name = "Todd Smith"
affiliation = "Lewis LLC"
email = "nedwards@example.org"

[publication]
venue = "Cell"
year = 2022
doi = "10.5354/mlMa"


[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: 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": "424897c8-d97d-4bfb-9c1a-7b6e63fd6096",
  "timestamp": "2026-01-07T13:51:27.529237",
  "level": "ERROR",
  "service": "heartService",
  "message": "How these anyone stop indeed.",
  "stack_trace": [
    "at manage.py:289",
    "at thing.py:107",
    "at guy.py:172",
    "at seat.py:479"
  ],
  "context": {
    "user_id": "082cc3eb-3997-4d99-990c-f696ca4ee534",
    "request_id": "0f3326d0-3afd-48c1-9c4d-32cc8b0c5920"
  }
}


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

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

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


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

[User] Output student assessment as YAML.

[Assistant]
Approach:
1. Task: Create student assessment in YAML
2. Complexity: 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-996269
student_id: STU-878254
course_id: CRS-8988
type: exam
date: '2026-01-03'
scores:
- question: 1
  points_earned: 8
  points_possible: 10
- question: 2
  points_earned: 0
  points_possible: 10
- question: 3
  points_earned: 8
  points_possible: 10
- question: 4
  points_earned: 2
  points_possible: 10
- question: 5
  points_earned: 7
  points_possible: 10
- question: 6
  points_earned: 3
  points_possible: 10
- question: 7
  points_earned: 9
  points_possible: 10
- question: 8
  points_earned: 7
  points_possible: 10
- question: 9
  points_earned: 2
  points_possible: 10
- question: 10
  points_earned: 3
  points_possible: 10
total_score: 71
percentage: 94.86
grade: B


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

[User] Output customer review as YAML.

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

Output:
review_id: REV-9982202
product_id: PROD-452864
user_id: 015289de-7f3e-45e2-b1d0-7fe22aff92a9
rating: 3
title: Example center fill free.
content: North describe old attention usually third. Important wish security ago somebody
  remain everyone modern. Significant chair place throughout study administration
  American.
date: '2026-01-04'
verified_purchase: false
helpful_votes: 34