[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"?>
<student_assessment>
<assessment_id>ASMT-718533</assessment_id>
<student_id>STU-781568</student_id>
<course_id>CRS-7994</course_id>
<type>assignment</type>
<date>2026-01-03</date>
<scores>
<question>1</question>
<points_earned>8</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>4</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>3</question>
<points_earned>5</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>8</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>0</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>5</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>9</question>
<points_earned>6</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>10</question>
<points_earned>4</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>11</question>
<points_earned>8</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>12</question>
<points_earned>4</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>13</question>
<points_earned>7</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>14</question>
<points_earned>3</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>62</total_score>
<percentage>88.34</percentage>
<grade>B</grade>
</student_assessment>

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

Output:
{
  "assessment_id": "ASMT-718533",
  "student_id": "STU-781568",
  "course_id": "CRS-7994",
  "type": "assignment",
  "date": "2026-01-03",
  "scores": [
    {
      "question": 1,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 5,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 0,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 5,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 9,
      "points_earned": 6,
      "points_possible": 10
    },
    {
      "question": 10,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 11,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 12,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 13,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 14,
      "points_earned": 3,
      "points_possible": 10
    }
  ],
  "total_score": 62,
  "percentage": 88.34,
  "grade": "B"
}


[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"?>
<error_log>
<error_id>8332f894-7969-41dc-b41e-1d31b796cba0</error_id>
<timestamp>2026-01-07T13:51:27.125156</timestamp>
<level>CRITICAL</level>
<service>imageService</service>
<message>Bad prepare able heavy morning.</message>
<stack_trace>at property.py:50</stack_trace>
<stack_trace>at short.py:272</stack_trace>
<context>
<user_id>a3de195f-baae-4936-bd72-230b1e266327</user_id>
<request_id>35eb846c-1e2f-4451-a60f-b8ee42943a10</request_id>
</context>
</error_log>

[Assistant]
Approach:
1. Task: Convert error log 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:
{
  "error_id": "8332f894-7969-41dc-b41e-1d31b796cba0",
  "timestamp": "2026-01-07T13:51:27.125156",
  "level": "CRITICAL",
  "service": "imageService",
  "message": "Bad prepare able heavy morning.",
  "stack_trace": [
    "at property.py:50",
    "at short.py:272"
  ],
  "context": {
    "user_id": "a3de195f-baae-4936-bd72-230b1e266327",
    "request_id": "35eb846c-1e2f-4451-a60f-b8ee42943a10"
  }
}


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

[User]
Convert the following JSON to XML:
{
  "results": [
    {
      "metric": "efficacy",
      "baseline": 40.85,
      "endpoint": 40.08,
      "p_value": 0.4196
    },
    {
      "metric": "efficacy",
      "baseline": 82.87,
      "endpoint": 28.4,
      "p_value": 0.208
    },
    {
      "metric": "efficacy",
      "baseline": 74.0,
      "endpoint": 18.43,
      "p_value": 0.3638
    },
    {
      "metric": "efficacy",
      "baseline": 50.48,
      "endpoint": 15.59,
      "p_value": 0.1146
    }
  ],
  "methodology": {
    "design": "observational",
    "sample_size": 351,
    "duration_days": 339
  },
  "conclusion": "non-significant"
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<experiment_result>
<results>
<metric>efficacy</metric>
<baseline>40.85</baseline>
<endpoint>40.08</endpoint>
<p_value>0.4196</p_value>
</results>
<results>
<metric>efficacy</metric>
<baseline>82.87</baseline>
<endpoint>28.4</endpoint>
<p_value>0.208</p_value>
</results>
<results>
<metric>efficacy</metric>
<baseline>74.0</baseline>
<endpoint>18.43</endpoint>
<p_value>0.3638</p_value>
</results>
<results>
<metric>efficacy</metric>
<baseline>50.48</baseline>
<endpoint>15.59</endpoint>
<p_value>0.1146</p_value>
</results>
<methodology>
<design>observational</design>
<sample_size>351</sample_size>
<duration_days>339</duration_days>
</methodology>
<conclusion>non-significant</conclusion>
</experiment_result>


[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:2023.54834"
title = "Profit-focused radical throughput"
abstract = "Read deal buy final thus. Sure home game rest lose.\nThose any reality if teach.\nMain never still little study clearly today."
keywords = [ "measure", "stage", "scene", "reason",]
citations = 388
funding_source = "Reese-Perez"
[[authors]]
name = "Scott Dunlap"
affiliation = "Daniels PLC"
email = "williamssheri@example.com"

[[authors]]
name = "Shawn Payne"
affiliation = "Dorsey, Price and Burns"
email = "smoyer@example.net"

[[authors]]
name = "Chase Lee"
affiliation = "Garcia Inc"
email = "burgesssarah@example.org"

[publication]
venue = "Science"
year = 2020
doi = "10.8776/UhOT"


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

[User] Produce a TOML document for a 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-8136358"
headline = "Realigned multimedia paradigm"
author = "Brian White"
published = "2026-01-02T14:21:25.908532"
section = "Sports"
content = "Give model worry sense. Including reflect teacher near image.\nCulture kitchen run first would. Agency media particularly past office every.\nBag water address admit. Skin tend Mr significant dark pretty. Painting water campaign."
tags = [ "involve", "service", "along", "stand",]
views = 7987
shares = 4175


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<research_paper>
<paper_id>arXiv:2024.66116</paper_id>
<title>Quality-focused grid-enabled service-desk</title>
<authors>
<name>David Cohen</name>
<affiliation>Lopez and Sons</affiliation>
<email>mark98@example.com</email>
</authors>
<authors>
<name>Ashley Spencer</name>
<affiliation>Hood Ltd</affiliation>
<email>pbailey@example.org</email>
</authors>
<authors>
<name>Robin Lynch</name>
<affiliation>Camacho, Nelson and Perez</affiliation>
<email>samantha44@example.net</email>
</authors>
<abstract>Body exactly last operation trouble. Financial whole check management chance eat us. Likely wrong explain by would born only.</abstract>
<keywords>rather</keywords>
<keywords>hair</keywords>
<keywords>attorney</keywords>
<keywords>chance</keywords>
<keywords>bring</keywords>
<publication>
<venue>Cell</venue>
<year>2020</year>
<doi>10.7468/EeJM</doi>
</publication>
<citations>174</citations>
<funding_source />
</research_paper>


[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"?>
<api_specification>
<paths>
</population>
<get>
<summary>Lead room develop man according street century.</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>
<//population>
</paths>
<info>
<title>Ameliorated radical initiative API</title>
<version>1.0.0</version>
</info>
<openapi>3.0.0</openapi>
</api_specification>

[Assistant]
Approach:
1. Task: Convert api specification from XML 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:
openapi = "3.0.0"

[info]
title = "Ameliorated radical initiative API"
version = "1.0.0"

[paths."/population".get]
summary = "Lead room develop man according street century."
[[paths."/population".get.parameters]]
name = "param0"
in = "query"
type = "string"

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

[[paths."/population".get.parameters]]
name = "param2"
in = "query"
type = "string"

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

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


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

[User] Generate course syllabus data in JSON format.

[Assistant]
Approach:
1. Task: Create course syllabus in JSON
2. Complexity: 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:
{
  "course_id": "CRS-6496",
  "code": "TMG245",
  "instructor": "Maria Bowers",
  "schedule": [
    {
      "week": 1,
      "topic": "situation"
    },
    {
      "week": 2,
      "topic": "firm"
    },
    {
      "week": 3,
      "topic": "involve"
    },
    {
      "week": 4,
      "topic": "change"
    },
    {
      "week": 5,
      "topic": "yard"
    },
    {
      "week": 6,
      "topic": "morning"
    },
    {
      "week": 7,
      "topic": "other"
    },
    {
      "week": 8,
      "topic": "left"
    }
  ]
}


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

[User] Output experiment result as XML.

[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-168652</experiment_id>
<title>Effect of green on from</title>
<methodology>
<design>cohort</design>
<sample_size>797</sample_size>
<duration_days>186</duration_days>
</methodology>
<results>
<metric>safety</metric>
<baseline>24.16</baseline>
<endpoint>44.82</endpoint>
<p_value>0.0559</p_value>
</results>
<results>
<metric>efficacy</metric>
<baseline>16.54</baseline>
<endpoint>28.48</endpoint>
<p_value>0.2997</p_value>
</results>
<conclusion>non-significant</conclusion>
</experiment_result>


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

[User]
Convert the following JSON to XML:
{
  "instructor": "Ryan Griffin",
  "course_id": "CRS-4864",
  "code": "NLW161"
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<course_syllabus>
<instructor>Ryan Griffin</instructor>
<course_id>CRS-4864</course_id>
NLW161
</course_syllabus>


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

[User]
Convert the following JSON to XML:
{
  "rx_id": "RX-9346457",
  "patient_mrn": "MRN-685856",
  "prescriber": "Thomas Archer",
  "date": "2026-01-05",
  "medications": [
    {
      "name": "Lisinopril",
      "dosage": "20mg",
      "frequency": "daily",
      "quantity": 90
    },
    {
      "name": "Atorvastatin",
      "dosage": "10mg",
      "frequency": "BID",
      "quantity": 60
    }
  ]
}

[Assistant]
Approach:
1. Task: Convert prescription 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"?>
<prescription>
<rx_id>RX-9346457</rx_id>
<patient_mrn>MRN-685856</patient_mrn>
<prescriber>Thomas Archer</prescriber>
<date>2026-01-05</date>
<medications>
<name>Lisinopril</name>
<dosage>20mg</dosage>
<frequency>daily</frequency>
<quantity>90</quantity>
</medications>
<medications>
<name>Atorvastatin</name>
<dosage>10mg</dosage>
<frequency>BID</frequency>
<quantity>60</quantity>
</medications>
</prescription>


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

[User] Generate product listing data in CSV format.

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

Output:
category,currency,is_available,name,price,product_id,rating,reviews,specs_dimensions,specs_weight_kg,stock
electronics,USD,True,Adaptive asynchronous synergy,349.45,PROD-107958,1.62,33,74x31x68cm,15.32,717
books,USD,True,Grass-roots multimedia hardware,144.8,PROD-897744,1.14,798,26x62x24cm,42.39,830
clothing,USD,True,Open-architected multi-state hardware,291.6,PROD-174305,4.69,682,52x36x81cm,37.66,909
books,USD,True,Inverse static project,103.38,PROD-141689,3.94,594,44x62x43cm,39.17,202
electronics,USD,True,Customizable 24/7 emulation,921.05,PROD-193463,1.03,212,84x20x71cm,28.93,86


[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"?>
<lab_result>
<result_id>LAB-5796495</result_id>
<patient_mrn>MRN-496025</patient_mrn>
<order_date>2026-01-06</order_date>
<panel>Lipid</panel>
<results>
<test>Hemoglobin</test>
<value>74.9</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>68.3</value>
<unit>mg/dL</unit>
<flag>low</flag>
</results>
<results>
<test>WBC</test>
<value>121.2</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>142.6</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
</lab_result>

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

Output:
{
  "result_id": "LAB-5796495",
  "patient_mrn": "MRN-496025",
  "order_date": "2026-01-06",
  "panel": "Lipid",
  "results": [
    {
      "test": "Hemoglobin",
      "value": 74.9,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "Hemoglobin",
      "value": 68.3,
      "unit": "mg/dL",
      "flag": "low"
    },
    {
      "test": "WBC",
      "value": 121.2,
      "unit": "mg/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 142.6,
      "unit": "g/dL",
      "flag": "normal"
    }
  ]
}


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

Output:
{
  "paper_id": "arXiv:2024.31964",
  "title": "Optimized solution-oriented success",
  "authors": [
    {
      "name": "Meagan Sutton",
      "affiliation": "Williamson, Mitchell and Smith",
      "email": "davilabridget@example.com"
    },
    {
      "name": "William Gross",
      "affiliation": "Miller and Sons",
      "email": "linda03@example.net"
    }
  ],
  "abstract": "Price while never. Night great must well remain. Share less reveal often.",
  "keywords": [
    "less",
    "radio",
    "spend",
    "which"
  ],
  "publication": {
    "venue": "Science",
    "year": 2023,
    "doi": "10.4651/vEqE"
  },
  "citations": 155,
  "funding_source": null
}


[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"?>
<financial_report>
<company>Tucker and Sons</company>
<ticker>BPQE</ticker>
<quarter>Q4 2024</quarter>
<revenue>70279854</revenue>
<expenses>61737533</expenses>
<net_income>12235621</net_income>
<eps>3.52</eps>
<metrics>
<profit_margin>24.27</profit_margin>
<roe>16.15</roe>
</metrics>
</financial_report>

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

Output:
{
  "company": "Tucker and Sons",
  "ticker": "BPQE",
  "quarter": "Q4 2024",
  "revenue": 70279854,
  "expenses": 61737533,
  "net_income": 12235621,
  "eps": 3.52,
  "metrics": {
    "profit_margin": 24.27,
    "roe": 16.15
  }
}


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

[User]
Reformat the data below from TOML to XML:
period = "March 2022"
total_revenue = 7500818
units_sold = 73950
[[channels]]
name = "retail"
revenue = 528123
growth = 12.05

[[channels]]
name = "online"
revenue = 1160273
growth = 23.93

[[top_products]]
sku = "SKU-6153"
sales = 328911

[[top_products]]
sku = "SKU-4483"
sales = 21251

[[top_products]]
sku = "SKU-5114"
sales = 21486

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<sales_analytics>
<period>March 2022</period>
<total_revenue>7500818</total_revenue>
<units_sold>73950</units_sold>
<channels>
<name>retail</name>
<revenue>528123</revenue>
<growth>12.05</growth>
</channels>
<channels>
<name>online</name>
<revenue>1160273</revenue>
<growth>23.93</growth>
</channels>
<top_products>
<sku>SKU-6153</sku>
<sales>328911</sales>
</top_products>
<top_products>
<sku>SKU-4483</sku>
<sales>21251</sales>
</top_products>
<top_products>
<sku>SKU-5114</sku>
<sales>21486</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:
{
  "result_id": "LAB-6812810",
  "patient_mrn": "MRN-631747",
  "order_date": "2026-01-04",
  "panel": "Lipid",
  "results": [
    {
      "test": "WBC",
      "value": 54.3,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "WBC",
      "value": 70.8,
      "unit": "mg/dL",
      "flag": "low"
    },
    {
      "test": "Glucose",
      "value": 59.6,
      "unit": "mg/dL",
      "flag": "low"
    },
    {
      "test": "WBC",
      "value": 140.8,
      "unit": "mg/dL",
      "flag": "high"
    }
  ]
}

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

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


[System] You are an expert in 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"?>
<financial_report>
<company>Becker-Martinez</company>
<ticker>QZXR</ticker>
<quarter>Q4 2021</quarter>
<revenue>48919598</revenue>
<expenses>50274851</expenses>
<net_income>7284021</net_income>
<eps>2.39</eps>
<metrics>
<profit_margin>17.0</profit_margin>
<roe>10.6</roe>
</metrics>
</financial_report>

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

Output:
{
  "company": "Becker-Martinez",
  "ticker": "QZXR",
  "quarter": "Q4 2021",
  "revenue": 48919598,
  "expenses": 50274851,
  "net_income": 7284021,
  "eps": 2.39,
  "metrics": {
    "profit_margin": 17.0,
    "roe": 10.6
  }
}


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

[User] Output product listing as TOML.

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

Output:
product_id = "PROD-480886"
name = "Operative optimizing monitoring"
category = "books"
price = 967.35
currency = "USD"
stock = 887
is_available = true
rating = 2.99
reviews = 465

[specs]
weight_kg = 39.19
dimensions = "82x84x37cm"


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

[User] Output contract as CSV.

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

Output:
contract_id,effective_date,parties,status,term_months,value
CTR-457828,2026-01-01,,,32,
CTR-540672,2026-01-02,"[{""name"": ""Austin, Hicks and Hernandez"", ""role"": ""party_a""}, {""name"": ""Berry PLC"", ""role"": ""party_b""",active,35,532999
CTR-333953,2026-01-01,"[{""name"": ""Davidson-Mendez"", ""role"": ""party_a""}, {""name"": ""Sullivan, Roman and Owens"", ""role"": ""part",active,14,810125
CTR-693038,2026-01-03,"[{""name"": ""Taylor-Mejia"", ""role"": ""party_a""}, {""name"": ""Mack-Schneider"", ""role"": ""party_b""}]",executed,43,523686
CTR-603667,2026-01-05,"[{""name"": ""Richardson-Baker"", ""role"": ""party_a""}, {""name"": ""Jacobs-Macias"", ""role"": ""party_b""}]",executed,45,489773


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

[User]
Transform this XML data into YAML format:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<review_id>REV-7122533</review_id>
<content>Expert difficult hot radio mission. Throw southern he book way media particular.</content>
<rating>1</rating>
<date>2026-01-06</date>
<verified_purchase>False</verified_purchase>
</customer_review>

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

Output:
review_id: REV-7122533
content: Expert difficult hot radio mission. Throw southern he book way media particular.
rating: 1
date: '2026-01-06'
verified_purchase: false


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

[User] Output clinical note as TOML.

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

Output:
note_id = "CN-4036732"
encounter_date = "2026-01-06"
chief_complaint = "headache"
[[assessment]]
problem = "hypertension"
icd10 = "K52"

[patient]
mrn = "MRN-366942"
age = 79
gender = "M"

[vitals]
bp = "102/96"
hr = 61
temp_f = 97.1


[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:
{
  "expenses": 54498119,
  "ticker": "OKCY",
  "company": "Clark-Pearson"
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<financial_report>
<expenses>54498119</expenses>
<ticker>OKCY</ticker>
<company>Clark-Pearson</company>
</financial_report>


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

[User] Generate news article data in YAML format.

[Assistant]
Approach:
1. Task: Create news article 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:
article_id: ART-2388619
headline: Switchable tertiary collaboration
author: Paula Martinez
published: '2026-01-07T02:15:35.006278'
section: Politics
content: 'Choice list strong let reason. Education class ok front impact successful.
  Huge professor happen data image stop. Notice movie reduce everyone among ask already
  company.

  Door president he always capital.

  Black democratic heart read name. Professional billion prepare executive meeting
  sport.'
tags:
- hair
- democratic
- financial
- huge
- available
views: 74003
shares: 1794


[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:
{
  "result_id": "LAB-4303735",
  "patient_mrn": "MRN-230243",
  "order_date": "2026-01-02",
  "panel": "Lipid",
  "results": [
    {
      "test": "WBC",
      "value": 142.8,
      "unit": "g/dL",
      "flag": "high"
    },
    {
      "test": "Hemoglobin",
      "value": 100.6,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "WBC",
      "value": 148.7,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "Hemoglobin",
      "value": 95.1,
      "unit": "g/dL",
      "flag": "normal"
    }
  ]
}

[Assistant]
Approach:
1. Task: Convert lab result 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"?>
<lab_result>
<result_id>LAB-4303735</result_id>
<patient_mrn>MRN-230243</patient_mrn>
<order_date>2026-01-02</order_date>
<panel>Lipid</panel>
<results>
<test>WBC</test>
<value>142.8</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>100.6</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>WBC</test>
<value>148.7</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>95.1</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
</lab_result>


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

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

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

Output:
{
  "review_id": "REV-9723622",
  "product_id": "PROD-853148",
  "user_id": "44919496-69de-498e-922c-5ea4230c00fa",
  "rating": 3,
  "title": "Risk tell team series house.",
  "content": "Official police serve past already. Number down similar senior head amount. Focus reality really hold lose.",
  "date": "2026-01-03",
  "verified_purchase": false,
  "helpful_votes": 99
}


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

[User] Create a YAML representation of prescription.

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

Output:
rx_id: RX-1795504
patient_mrn: MRN-355763
prescriber: Henry Padilla
date: '2026-01-01'
medications:
- name: Metformin
  dosage: 20mg
  frequency: daily
  quantity: 90


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<product_listing>
<product_id>PROD-325945</product_id>
<name>Universal bottom-line system engine</name>
<category>electronics</category>
<price>225.75</price>
<currency>USD</currency>
<stock>955</stock>
<is_available>True</is_available>
<rating>3.31</rating>
<reviews>802</reviews>
<specs>
<weight_kg>22.25</weight_kg>
<dimensions>77x29x32cm</dimensions>
</specs>
</product_listing>


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

[User] Generate product listing data in YAML format.

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

Output:
product_id: PROD-891981
name: Focused background info-mediaries
category: books
price: 16.4
currency: USD
stock: 192
is_available: true
rating: 3.23
reviews: 117
specs:
  weight_kg: 31.51
  dimensions: 65x39x62cm


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

[User] Output sales analytics as XML.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<sales_analytics>
<period>February 2024</period>
<total_revenue>3108970</total_revenue>
<units_sold>70292</units_sold>
<channels>
<name>online</name>
<revenue>1867975</revenue>
<growth>-2.95</growth>
</channels>
<channels>
<name>retail</name>
<revenue>1947932</revenue>
<growth>22.54</growth>
</channels>
<top_products>
<sku>SKU-5409</sku>
<sales>492017</sales>
</top_products>
<top_products>
<sku>SKU-4816</sku>
<sales>486050</sales>
</top_products>
<top_products>
<sku>SKU-9957</sku>
<sales>44038</sales>
</top_products>
</sales_analytics>


[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"?>
<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>

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

Output:
{
  "experiment_id": "EXP-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]
Convert the following CSV to TOML:
assessment_id,code,course_id,credits,date,grade,grading_final,grading_homework,grading_midterm,instructor,percentage,schedule,scores,student_id,term,title,total_score,type
ASMT-549878,,CRS-6692,,2026-01-01,C,,,,,54.38,,"[{""question"": 1, ""points_earned"": 7, ""points_possible"": 10}, {""question"": 2, ""points_earned"": 1, ""po",STU-264168,,,70,assignment
,IFZ117,CRS-2273,4,,,40,30,30,Regina Williamson,,"[{""week"": 1, ""topic"": ""player""}, {""week"": 2, ""topic"": ""prove""}, {""week"": 3, ""topic"": ""contain""}, {""w",,,Fall 2020,Fundamental asymmetric focus group 101,,
,CCS271,CRS-6000,3,,,40,30,30,Craig Ruiz,,"[{""week"": 1, ""topic"": ""young""}, {""week"": 2, ""topic"": ""successful""}, {""week"": 3, ""topic"": ""word""}, {""",,,Fall 2024,Front-line foreground protocol 101,,

[Assistant]
Approach:
1. Task: Convert student assessment from CSV 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:
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 TOML format. Think step-by-step, then generate syntactically perfect TOML.

[User] Create a TOML representation of customer review.

[Assistant]
Approach:
1. Task: Create customer review 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:
review_id = "REV-5832770"
product_id = "PROD-688379"
user_id = "d5e035fb-55b8-4fae-85aa-504fb2b837bd"
rating = 3
title = "Investment great beat fear step Democrat treat."
content = "Near season take foot decade hold some meet.\nPretty season exist old turn consumer particularly star. Step receive unit different."
date = "2026-01-02"
verified_purchase = false
helpful_votes = 62


[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"?>
<clinical_note>
<vitals>
<bp>97/107</bp>

107

<temp_f>99.6</temp_f>
</vitals>
<patient>
<mrn>MRN-705297</mrn>
<age>67</age>
<gender>F</gender>
</patient>
<chief_complaint>chest pain</chief_complaint>
<assessment>
<problem>hypertension</problem>
<icd10>K41</icd10>
</assessment>
<assessment>
<problem>hypertension</problem>
<icd10>J91</icd10>
</assessment>
<assessment>
<problem>hypertension</problem>
<icd10>J64</icd10>
</assessment>
<note_id>CN-6154695</note_id>
</clinical_note>

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

Output:
{
  "vitals": {
    "bp": "97/107",
    "hr": 107,
    "temp_f": 99.6
  },
  "patient": {
    "mrn": "MRN-705297",
    "age": 67,
    "gender": "F"
  },
  "chief_complaint": "chest pain",
  "assessment": [
    {
      "problem": "hypertension",
      "icd10": "K41"
    },
    {
      "problem": "hypertension",
      "icd10": "J91"
    },
    {
      "problem": "hypertension",
      "icd10": "J64"
    }
  ],
  "note_id": "CN-6154695"
}


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

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

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

Output:
note_id = "CN-3041313"
encounter_date = "2026-01-04"
chief_complaint = "fever"
[[assessment]]
problem = "hypertension"
icd10 = "I84"

[[assessment]]
problem = "hypertension"
icd10 = "J93"

[patient]
mrn = "MRN-164256"
age = 45
gender = "F"

[vitals]
bp = "153/76"
hr = 98
temp_f = 102.6


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

[User] Generate research paper data in YAML format.

[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:2023.57642
title: Organized clear-thinking projection
authors:
- name: Thomas Harrison
  affiliation: Benjamin, Peterson and James
  email: martinjoseph@example.com
- name: Samantha Phillips
  affiliation: Carpenter Ltd
  email: hawkinssarah@example.com
abstract: 'Leg third those over. Almost state money hear condition little.

  Manager minute writer manager. Walk hand situation similar media back fill huge.'
keywords:
- decade
- kitchen
- discover
- wide
publication:
  venue: Cell
  year: 2023
  doi: 10.5371/HWME
citations: 306
funding_source: null


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

[User] Generate clinical note data in CSV format.

[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"": ""hypertension"", ""icd10"": ""I32""}]",headache,2026-01-04,CN-6224145,88,F,MRN-560569,119/73,63,100.0
"[{""problem"": ""hypertension"", ""icd10"": ""J55""}, {""problem"": ""hypertension"", ""icd10"": ""J65""}, {""problem",chest pain,2026-01-06,CN-8316209,48,F,MRN-849962,107/82,96,97.8
"[{""problem"": ""diabetes"", ""icd10"": ""J66""}, {""problem"": ""hypertension"", ""icd10"": ""J57""}, {""problem"": """,fever,2026-01-02,CN-2758349,68,F,MRN-160095,164/81,115,100.7


[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-8246470</rx_id>
<patient_mrn>MRN-256913</patient_mrn>
<prescriber>Victor Valentine</prescriber>
<date>2026-01-01</date>
<medications>
<name>Lisinopril</name>
<dosage>20mg</dosage>
<frequency>daily</frequency>
<quantity>30</quantity>
</medications>
<medications>
<name>Lisinopril</name>
<dosage>10mg</dosage>
<frequency>BID</frequency>
<quantity>60</quantity>
</medications>
<medications>
<name>Lisinopril</name>
<dosage>5mg</dosage>
<frequency>TID</frequency>
<quantity>30</quantity>
</medications>
</prescription>

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

Output:
{
  "rx_id": "RX-8246470",
  "patient_mrn": "MRN-256913",
  "prescriber": "Victor Valentine",
  "date": "2026-01-01",
  "medications": [
    {
      "name": "Lisinopril",
      "dosage": "20mg",
      "frequency": "daily",
      "quantity": 30
    },
    {
      "name": "Lisinopril",
      "dosage": "10mg",
      "frequency": "BID",
      "quantity": 60
    },
    {
      "name": "Lisinopril",
      "dosage": "5mg",
      "frequency": "TID",
      "quantity": 30
    }
  ]
}


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

[User] Produce a TOML document for a prescription.

[Assistant]
Approach:
1. Task: Create prescription 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:
rx_id = "RX-6036951"
patient_mrn = "MRN-440463"
prescriber = "Lisa Mathews"
date = "2026-01-05"
[[medications]]
name = "Metformin"
dosage = "20mg"
frequency = "TID"
quantity = 90


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<news_article>
<article_id>ART-9178511</article_id>
<headline>Fully-configurable secondary access</headline>
<author>Gabrielle Daugherty</author>
<published>2026-01-05T07:34:40.744934</published>

Tech

<content>Lawyer might home mouth end so science. Hope attention strong public teach person beautiful though. Really decision land evening year.
Just role ground discover. Five stand writer floor.</content>
<tags>maybe</tags>
<tags>glass</tags>
<tags>election</tags>
<tags>moment</tags>
<views>24250</views>
<shares>778</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-9178511",
  "headline": "Fully-configurable secondary access",
  "author": "Gabrielle Daugherty",
  "published": "2026-01-05T07:34:40.744934",
  "section": "Tech",
  "content": "Lawyer might home mouth end so science. Hope attention strong public teach person beautiful though. Really decision land evening year.\nJust role ground discover. Five stand writer floor.",
  "tags": [
    "maybe",
    "glass",
    "election",
    "moment"
  ],
  "views": 24250,
  "shares": 778
}


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

[User]
Convert the following CSV to JSON:
customer_id,items,payment_method,subtotal,tax,timestamp,total,txn_id
3fe35528-f72a-4e45-bcf8-f7cb059fe7e5,"[{""sku"": ""SKU-59380"", ""qty"": 2, ""price"": 447.63}, {""sku"": ""SKU-56357"", ""qty"": 4, ""price"": 130.56}, {",apple_pay,1853.52,74.51,2026-01-07T13:51:27.778783,1419.49,TXN-20904368
00822dd3-c280-484d-b039-1cbeacb2cb03,"[{""sku"": ""SKU-52545"", ""qty"": 4, ""price"": 49.0}, {""sku"": ""SKU-11180"", ""qty"": 2, ""price"": 467.11}, {""s",apple_pay,361.04,14.16,2026-01-07T13:51:27.780604,176.31,TXN-70393053
1838abf7-7fab-46af-bf06-186bdc7171f0,"[{""sku"": ""SKU-42034"", ""qty"": 1, ""price"": 491.97}, {""sku"": ""SKU-76502"", ""qty"": 4, ""price"": 107.66}]",paypal,728.1,53.89,2026-01-07T13:51:27.780657,1886.58,TXN-94221286

[Assistant]
Approach:
1. Task: Convert transaction record from CSV 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:
{
  "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 YAML format. Think step-by-step, then generate syntactically perfect YAML.

[User] Output transaction record as YAML.

[Assistant]
Approach:
1. Task: Create transaction record in YAML
2. Complexity: 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:
txn_id: TXN-15638187
customer_id: 242fd3fb-d1fb-4e06-b998-4ca6fd25c6b7
timestamp: '2026-01-07T13:51:27.047573'
items:
- sku: SKU-16950
  qty: 3
  price: 120.22
- sku: SKU-76122
  qty: 1
  price: 377.76
- sku: SKU-41194
  qty: 3
  price: 254.19
- sku: SKU-75246
  qty: 2
  price: 418.85
subtotal: 1338.06
tax: 172.92
total: 2048.81
payment_method: apple_pay


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

[User] Generate error log data in XML format.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<error_log>
<error_id>249c5a8d-effc-4f5a-9a18-79860cd86eba</error_id>
<timestamp>2026-01-07T13:51:25.844189</timestamp>
<level>CRITICAL</level>
<service>createService</service>
<message>Capital carry as agree member lead one.</message>
<stack_trace>at sign.py:359</stack_trace>
<stack_trace>at college.py:115</stack_trace>
<stack_trace>at try.py:133</stack_trace>
<context>
<user_id>e110a198-5d8a-4242-b2e4-6ec6ae49ca80</user_id>
<request_id>939e8b37-2ce6-4ba0-bde6-ca285c8d396c</request_id>
</context>
</error_log>


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<lab_result>
<result_id>LAB-2441646</result_id>
<patient_mrn>MRN-228148</patient_mrn>
<order_date>2026-01-01</order_date>
<panel>Lipid</panel>
<results>
<test>Glucose</test>
<value>81.9</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
<results>
<test>WBC</test>
<value>107.7</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>101.6</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>197.9</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
</lab_result>

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

Output:
{
  "result_id": "LAB-2441646",
  "patient_mrn": "MRN-228148",
  "order_date": "2026-01-01",
  "panel": "Lipid",
  "results": [
    {
      "test": "Glucose",
      "value": 81.9,
      "unit": "g/dL",
      "flag": "high"
    },
    {
      "test": "WBC",
      "value": 107.7,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "Hemoglobin",
      "value": 101.6,
      "unit": "mg/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 197.9,
      "unit": "g/dL",
      "flag": "low"
    }
  ]
}


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

[User] Create a JSON representation of sales analytics.

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

Output:
{
  "period": "February 2020",
  "total_revenue": 5010605,
  "units_sold": 4486,
  "channels": [
    {
      "name": "online",
      "revenue": 4865933,
      "growth": 41.22
    },
    {
      "name": "wholesale",
      "revenue": 4636446,
      "growth": 21.68
    }
  ],
  "top_products": [
    {
      "sku": "SKU-3361",
      "sales": 360256
    },
    {
      "sku": "SKU-1576",
      "sales": 355717
    },
    {
      "sku": "SKU-8891",
      "sales": 396344
    }
  ]
}


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

[User] Generate experiment result data in CSV format.

[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-330074,RCT,247,328,"[{""metric"": ""efficacy"", ""baseline"": 34.54, ""endpoint"": 53.32, ""p_value"": 0.0487}, {""metric"": ""safety",Effect of politics on stop
non-significant,EXP-260755,cohort,113,628,"[{""metric"": ""safety"", ""baseline"": 74.48, ""endpoint"": 63.81, ""p_value"": 0.3973}, {""metric"": ""efficacy",Effect of structure on deep
significant,EXP-236883,cohort,349,828,"[{""metric"": ""safety"", ""baseline"": 95.69, ""endpoint"": 88.84, ""p_value"": 0.0656}, {""metric"": ""safety"",",Effect of two on former
non-significant,EXP-851071,cohort,318,576,"[{""metric"": ""safety"", ""baseline"": 37.45, ""endpoint"": 97.83, ""p_value"": 0.0116}, {""metric"": ""efficacy",Effect of everyone on experience
non-significant,EXP-385875,cohort,204,726,"[{""metric"": ""efficacy"", ""baseline"": 19.28, ""endpoint"": 81.05, ""p_value"": 0.4331}, {""metric"": ""effica",Effect of modern on allow


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

[User] Produce a XML document for a 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>Stand-alone dedicated complexity API</title>
<version>1.0.0</version>
</info>
<paths>
</hear>
<get>
<summary>Chance cultural sort including high.</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>
<//hear>
</paths>
</api_specification>


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

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

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

Output:
post_id = "POST-25055870"
platform = "twitter"
user_id = "28837af0-4898-41b2-8a38-faf0e2d7f431"
username = "khahn"
content = "Serve student science today general. Tell risk ball quickly technology.\nDrive because generation support gun message majority. Though do old."
timestamp = "2026-01-07T13:51:27.403909"
hashtags = [ "#conference", "#body",]

[engagement]
likes = 9394
shares = 444
comments = 203


[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 = "c6e14566-270a-4a5f-a250-5239ca9174ac"
timestamp = "2026-01-07T13:51:26.338486"
level = "ERROR"
service = "humanService"
message = "Fear she east talk better central."
stack_trace = [ "at college.py:218", "at economy.py:209", "at let.py:252", "at whole.py:18",]

[context]
user_id = "bda2bdb3-cc4e-4711-8927-aa42dc72d462"
request_id = "c7d51186-07ee-4743-a193-c5688ac0d6c5"


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

[Assistant]
Approach:
1. Task: Convert transaction record 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:
{
  "txn_id": "TXN-48552675",
  "customer_id": "19d3d880-f410-4b85-a35d-9c5777705d1f",
  "timestamp": "2026-01-07T13:51:26.837603",
  "items": [
    {
      "sku": "SKU-30306",
      "qty": 4,
      "price": 206.74
    }
  ],
  "subtotal": 1354.26,
  "tax": 33.08,
  "total": 766.28,
  "payment_method": "paypal"
}


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

[User]
Reformat the data below from CSV to XML:
date,medications,patient_mrn,prescriber,rx_id
2026-01-04,"[{""name"": ""Lisinopril"", ""dosage"": ""20mg"", ""frequency"": ""TID"", ""quantity"": 30}, {""name"": ""Metformin"",",MRN-740510,William Hebert,RX-7328466
2026-01-04,"[{""name"": ""Lisinopril"", ""dosage"": ""5mg"", ""frequency"": ""BID"", ""quantity"": 60}, {""name"": ""Atorvastatin",MRN-142901,Brian Chan,RX-8471203
2026-01-06,"[{""name"": ""Metformin"", ""dosage"": ""20mg"", ""frequency"": ""BID"", ""quantity"": 60}]",MRN-443940,Mary Jordan,RX-5172927
2026-01-05,"[{""name"": ""Lisinopril"", ""dosage"": ""10mg"", ""frequency"": ""daily"", ""quantity"": 90}, {""name"": ""Metformin",MRN-575818,James Jacobs,RX-7236451
2026-01-02,"[{""name"": ""Metformin"", ""dosage"": ""20mg"", ""frequency"": ""BID"", ""quantity"": 60}, {""name"": ""Atorvastatin",MRN-671786,Jesse Carr,RX-6487072

[Assistant]
Approach:
1. Task: Convert prescription from CSV 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"?>
<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>


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

[User]
Convert the following JSON to XML:
{
  "period": "June 2024",
  "total_revenue": 5319249,
  "units_sold": 96009,
  "channels": [
    {
      "name": "wholesale",
      "revenue": 941227,
      "growth": 26.4
    },
    {
      "name": "retail",
      "revenue": 937409,
      "growth": 30.07
    }
  ],
  "top_products": [
    {
      "sku": "SKU-2900",
      "sales": 81858
    },
    {
      "sku": "SKU-8266",
      "sales": 123988
    },
    {
      "sku": "SKU-9969",
      "sales": 32400
    }
  ]
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<sales_analytics>
<period>June 2024</period>
<total_revenue>5319249</total_revenue>
<units_sold>96009</units_sold>
<channels>
<name>wholesale</name>
<revenue>941227</revenue>
<growth>26.4</growth>
</channels>
<channels>
<name>retail</name>
<revenue>937409</revenue>
<growth>30.07</growth>
</channels>
<top_products>
<sku>SKU-2900</sku>
<sales>81858</sales>
</top_products>
<top_products>
<sku>SKU-8266</sku>
<sales>123988</sales>
</top_products>
<top_products>
<sku>SKU-9969</sku>
<sales>32400</sales>
</top_products>
</sales_analytics>


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<sales_analytics>
<period>May 2020</period>
<total_revenue>534039</total_revenue>
<units_sold>34851</units_sold>
<channels>
<name>retail</name>
<revenue>707158</revenue>
<growth>43.16</growth>
</channels>
<channels>
<name>wholesale</name>
<revenue>2548868</revenue>
<growth>26.24</growth>
</channels>
<top_products>
<sku>SKU-6020</sku>
<sales>18280</sales>
</top_products>
<top_products>
<sku>SKU-3349</sku>
<sales>458703</sales>
</top_products>
<top_products>
<sku>SKU-8781</sku>
<sales>265385</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": "May 2020",
  "total_revenue": 534039,
  "units_sold": 34851,
  "channels": [
    {
      "name": "retail",
      "revenue": 707158,
      "growth": 43.16
    },
    {
      "name": "wholesale",
      "revenue": 2548868,
      "growth": 26.24
    }
  ],
  "top_products": [
    {
      "sku": "SKU-6020",
      "sales": 18280
    },
    {
      "sku": "SKU-3349",
      "sales": 458703
    },
    {
      "sku": "SKU-8781",
      "sales": 265385
    }
  ]
}


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

[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-9546377</review_id>
<product_id>PROD-108034</product_id>
<user_id>d01ac4e1-ccd9-4273-9fe0-9ca6afc6af77</user_id>
<rating>4</rating>
<title>Appear speak sure list.</title>
<content>Today offer none role certain reach. Second Mr official enjoy movement turn city. Name employee early much first sit.</content>
<date>2026-01-01</date>
<verified_purchase>True</verified_purchase>
<helpful_votes>43</helpful_votes>
</customer_review>


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<financial_report>
<company>Williams Ltd</company>
<ticker>IHFM</ticker>
<quarter>Q3 2022</quarter>
<revenue>93368790</revenue>
<expenses>48847964</expenses>
<net_income>12028281</net_income>
<eps>9.18</eps>
<metrics>
<profit_margin>7.56</profit_margin>
<roe>13.89</roe>
</metrics>
</financial_report>


[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"?>
<research_paper>
<paper_id>arXiv:2023.67735</paper_id>
<title>Optimized even-keeled conglomeration</title>
<authors>
<name>Garrett Contreras</name>
<affiliation>Drake-Dunn</affiliation>
<email>sandrapineda@example.net</email>
</authors>
<authors>
<name>Ryan Bell</name>
<affiliation>Ramos, Gates and Reed</affiliation>
<email>kdavis@example.net</email>
</authors>
<authors>
<name>Cindy Silva</name>
<affiliation>Bryant, Pratt and Henderson</affiliation>
<email>fmiller@example.net</email>
</authors>
<abstract>Sort suffer stand purpose six resource. Forward hard officer film the word human first.</abstract>
<keywords>attack</keywords>
<keywords>not</keywords>
<keywords>describe</keywords>
<publication>
<venue>Nature</venue>
<year>2024</year>
<doi>10.7544/lKSL</doi>
</publication>
<citations>172</citations>
<funding_source>Wood, Baldwin and Cain</funding_source>
</research_paper>

[Assistant]
Approach:
1. Task: Convert research paper 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:
{
  "paper_id": "arXiv:2023.67735",
  "title": "Optimized even-keeled conglomeration",
  "authors": [
    {
      "name": "Garrett Contreras",
      "affiliation": "Drake-Dunn",
      "email": "sandrapineda@example.net"
    },
    {
      "name": "Ryan Bell",
      "affiliation": "Ramos, Gates and Reed",
      "email": "kdavis@example.net"
    },
    {
      "name": "Cindy Silva",
      "affiliation": "Bryant, Pratt and Henderson",
      "email": "fmiller@example.net"
    }
  ],
  "abstract": "Sort suffer stand purpose six resource. Forward hard officer film the word human first.",
  "keywords": [
    "attack",
    "not",
    "describe"
  ],
  "publication": {
    "venue": "Nature",
    "year": 2024,
    "doi": "10.7544/lKSL"
  },
  "citations": 172,
  "funding_source": "Wood, Baldwin and Cain"
}


[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-1369973</review_id>
<product_id>PROD-861575</product_id>
<user_id>a55bb48c-5dcb-464a-b952-9d377a4cb9c4</user_id>
<rating>1</rating>
<title>Relationship job find one allow law through.</title>
<content>Now decide senior fact big window yourself. Difference appear seat coach rather once politics. Modern always able physical Republican best draw land.</content>
<date>2026-01-02</date>
<verified_purchase>True</verified_purchase>
<helpful_votes>8</helpful_votes>
</customer_review>


[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:
{
  "title": "Exactly almost full new record save.",
  "date": "2026-01-02",
  "product_id": "PROD-922306",
  "content": "Arrive much low will teach. By possible nature learn could. Act hot whole guy experience.\nIdentify world fight stock. Force fear soon. Author night think."
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<title>Exactly almost full new record save.</title>
<date>2026-01-02</date>
<product_id>PROD-922306</product_id>
<content>Arrive much low will teach. By possible nature learn could. Act hot whole guy experience.
Identify world fight stock. Force fear soon. Author night think.</content>
</customer_review>


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

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

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


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

[User]
Transform this TOML data into YAML format:
rx_id = "RX-4278484"
patient_mrn = "MRN-990980"
prescriber = "Andrew Kelly"
date = "2026-01-06"
[[medications]]
name = "Metformin"
dosage = "10mg"
frequency = "BID"
quantity = 30

[[medications]]
name = "Atorvastatin"
dosage = "10mg"
frequency = "BID"
quantity = 90

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

Output:
rx_id: RX-4278484
patient_mrn: MRN-990980
prescriber: Andrew Kelly
date: '2026-01-06'
medications:
- name: Metformin
  dosage: 10mg
  frequency: BID
  quantity: 30
- name: Atorvastatin
  dosage: 10mg
  frequency: BID
  quantity: 90


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

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

[Assistant]
Approach:
1. Task: Convert sales analytics from XML 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:
period: November 2021
total_revenue: 8992427
units_sold: 30636
channels:
- name: wholesale
  revenue: 3169564
  growth: 42.35
- name: retail
  revenue: 2683860
  growth: 36.55
top_products:
- sku: SKU-9614
  sales: 412171
- sku: SKU-7573
  sales: 203488
- sku: SKU-4372
  sales: 55896


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

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

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

Output:
credits = 4
course_id = "CRS-7759"
instructor = "Matthew Johnson"
[[schedule]]
week = 1
topic = "meet"

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

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

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

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

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

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

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

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

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

[[schedule]]
week = 11
topic = "nothing"

[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] Create a XML representation of transaction record.

[Assistant]
Approach:
1. Task: Create transaction record 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"?>
<transaction_record>
<txn_id>TXN-31892506</txn_id>
<customer_id>6c5d6d8e-2901-438d-be6d-be57a13ea5ab</customer_id>
<timestamp>2026-01-07T13:51:25.485684</timestamp>
<items>
<sku>SKU-80058</sku>
<qty>4</qty>
<price>142.37</price>
</items>
<items>
<sku>SKU-53232</sku>
<qty>1</qty>
<price>151.54</price>
</items>
<subtotal>692.94</subtotal>
<tax>100.91</tax>
<total>1647.14</total>
<payment_method>credit_card</payment_method>
</transaction_record>


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

[User] Generate course syllabus data in CSV format.

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

Output:
code,course_id,credits,grading_final,grading_homework,grading_midterm,instructor,schedule,term,title
CSZ142,CRS-3948,4,40,30,30,Robert Carter,"[{""week"": 1, ""topic"": ""manage""}, {""week"": 2, ""topic"": ""catch""}, {""week"": 3, ""topic"": ""people""}, {""we",Fall 2022,Intuitive foreground functionalities 101
MZW327,CRS-6722,4,40,30,30,Anna Williams,"[{""week"": 1, ""topic"": ""chance""}, {""week"": 2, ""topic"": ""PM""}, {""week"": 3, ""topic"": ""value""}, {""week"":",Spring 2024,Adaptive even-keeled pricing structure 101
CBD152,CRS-7496,4,40,30,30,Timothy Rodriguez,"[{""week"": 1, ""topic"": ""science""}, {""week"": 2, ""topic"": ""maybe""}, {""week"": 3, ""topic"": ""discuss""}, {""",Spring 2020,Cross-group 4thgeneration model 101


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

[User] Produce a YAML document for a contract.

[Assistant]
Approach:
1. Task: Create contract 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:
term_months: 33
parties:
- name: Hart-Villanueva
  role: party_a
- name: Roberts Ltd
  role: party_b
effective_date: '2026-01-05'
value: 95653


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

[User] Create a YAML representation of product listing.

[Assistant]
Approach:
1. Task: Create product listing in YAML
2. Complexity: 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:
specs:
  weight_kg: 8.02
  dimensions: 62x22x22cm
name: Universal fault-tolerant service-desk
price: 907.33
reviews: 493


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

[User] Output sales analytics as JSON.

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

Output:
{
  "period": "February 2022",
  "total_revenue": 6033804,
  "units_sold": 27183,
  "channels": [
    {
      "name": "wholesale",
      "revenue": 4147239,
      "growth": 40.37
    },
    {
      "name": "online",
      "revenue": 2663137,
      "growth": 9.96
    }
  ],
  "top_products": [
    {
      "sku": "SKU-2538",
      "sales": 420940
    },
    {
      "sku": "SKU-8680",
      "sales": 364206
    },
    {
      "sku": "SKU-2062",
      "sales": 350623
    }
  ]
}


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

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

[Assistant]
Approach:
1. Task: Convert api specification 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"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Robust demand-driven hub API</title>
<version>1.0.0</version>
</info>
<paths>
</finally>
<get>
<summary>Describe experience pick treatment up remain withi</summary>
<parameters>
<name>param0</name>
<in>query</in>
<type>string</type>
</parameters>
<parameters>
<name>param1</name>
<in>query</in>
<type>string</type>
</parameters>
<parameters>
<name>param2</name>
<in>query</in>
<type>string</type>
</parameters>
<responses>
<200>
<description>Success</description>
</200>
<400>
<description>Bad Request</description>
</400>
</responses>
</get>
<//finally>
</paths>
</api_specification>


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

[User] Output course syllabus as TOML.

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

Output:
course_id = "CRS-9456"
code = "KDS432"
title = "Multi-channeled local complexity 101"
instructor = "Kenneth Rogers"
credits = 3
term = "Fall 2020"
[[schedule]]
week = 1
topic = "activity"

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

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

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

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

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

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

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

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

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

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


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

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

[Assistant]
Approach:
1. Task: Create error log 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,level,message,paper_id,publication_doi,publication_venue,publication_year,service,stack_trace,title
,,,,,ERROR,Head then too threat drive.,,,,,findService,"[""at watch.py:197"", ""at body.py:298"", ""at girl.py:392"", ""at red.py:350""]",
Allow morning green year daughter. Officer upon rich along. Occur executive authority speak itself t,"[{""name"": ""Timothy Morton"", ""affiliation"": ""Hunt, Johnson and Watson"", ""email"": ""qriley@example.net""",93,"Williams, Whitehead and Harmon","[""together"", ""development"", ""memory"", ""true"", ""produce""]",,,arXiv:2021.23197,10.7001/XfaU,Science,2022,,,Stand-alone coherent migration
"Also factor four issue. Behind western while bit behavior. Prove those pick behind the.
Clear law re","[{""name"": ""Jordan Cook"", ""affiliation"": ""Thomas, Rollins and Alvarez"", ""email"": ""rossjoe@example.com",175,None,"[""large"", ""child"", ""choose"", ""such"", ""year""]",,,arXiv:2020.97123,10.3187/cgfu,Nature,2021,,,Fully-configurable user-facing flexibility


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

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

[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
"Leg third those over. Almost state money hear condition little.
Manager minute writer manager. Walk ","[{""name"": ""Thomas Harrison"", ""affiliation"": ""Benjamin, Peterson and James"", ""email"": ""martinjoseph@e",306,None,"[""decade"", ""kitchen"", ""discover"", ""wide""]",arXiv:2023.57642,10.5371/HWME,Cell,2023,Organized clear-thinking projection
Though million until technology material street. Little mind order practice early recognize cut.,"[{""name"": ""Julian Robbins"", ""affiliation"": ""Beck and Sons"", ""email"": ""rebecca07@example.net""}, {""nam",467,Ford-Williamson,"[""dark"", ""hot"", ""prepare"", ""establish"", ""fall""]",arXiv:2022.96500,10.7502/ZIBn,Science,2020,Grass-roots uniform superstructure
Better factor such trip make. Population way result film player. Never expect this activity full of.,"[{""name"": ""Kathy Bullock"", ""affiliation"": ""Coleman and Sons"", ""email"": ""sheenadillon@example.com""}, ",320,"Davis, Jones and Davis","[""better"", ""key"", ""word"", ""them""]",arXiv:2023.75053,10.5800/dmja,Nature,2020,Public-key 24hour application
Ball party certain child hard environmental box there. Buy course seven down soldier near staff.,"[{""name"": ""Cody Wilkins"", ""affiliation"": ""Parker-Brown"", ""email"": ""tamaramueller@example.com""}, {""na",458,None,"[""bag"", ""actually"", ""walk"", ""woman"", ""high""]",arXiv:2022.75176,10.2392/ISUm,Nature,2021,Sharable composite collaboration


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

[User] Generate product listing data in XML format.

[Assistant]
Approach:
1. Task: Create product listing 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"?>
<product_listing>
<product_id>PROD-210763</product_id>
<name>Team-oriented grid-enabled support</name>
<category>clothing</category>
<price>360.14</price>
<currency>USD</currency>
<stock>657</stock>
<is_available>True</is_available>
<rating>3.34</rating>
<reviews>923</reviews>
<specs>
<weight_kg>14.15</weight_kg>
<dimensions>28x80x26cm</dimensions>
</specs>
</product_listing>


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

[User] Generate customer review data in JSON format.

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

Output:
{
  "rating": 2,
  "verified_purchase": true,
  "helpful_votes": 29,
  "date": "2026-01-01",
  "user_id": "ed843147-0604-46c9-98b2-def8aa0c8a20"
}


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

[User] Generate news article data in JSON format.

[Assistant]
Approach:
1. Task: Create news article in JSON
2. Complexity: 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:
{
  "article_id": "ART-5646798",
  "headline": "Switchable hybrid groupware",
  "author": "Joshua Bell",
  "published": "2026-01-05T05:31:42.088007",
  "section": "Business",
  "content": "List road lay not year. Congress gas full particular according. Prevent hear century game friend civil live.\nPossible option especially woman. Ahead down suffer doctor six traditional. Prove ready American star impact operation just. Difficult yourself difficult base of four letter.",
  "tags": [
    "author",
    "son",
    "food"
  ],
  "views": 74484,
  "shares": 596
}


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

[User] Generate student assessment data in TOML format.

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

Output:
assessment_id = "ASMT-577861"
student_id = "STU-664280"
course_id = "CRS-8099"
type = "exam"
date = "2026-01-06"
total_score = 52
percentage = 81.98
grade = "B"
[[scores]]
question = 1
points_earned = 7
points_possible = 10

[[scores]]
question = 2
points_earned = 0
points_possible = 10

[[scores]]
question = 3
points_earned = 5
points_possible = 10

[[scores]]
question = 4
points_earned = 6
points_possible = 10

[[scores]]
question = 5
points_earned = 3
points_possible = 10

[[scores]]
question = 6
points_earned = 0
points_possible = 10

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


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

[User] Output error log as XML.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<error_log>
<error_id>7af25ba6-3e63-43d5-89e6-c5a6b377b923</error_id>
<timestamp>2026-01-07T13:51:26.975438</timestamp>
<level>CRITICAL</level>
<service>downService</service>
<message>Prevent true movie stop.</message>
<stack_trace>at hand.py:436</stack_trace>
<stack_trace>at whose.py:275</stack_trace>
<stack_trace>at information.py:57</stack_trace>
<stack_trace>at central.py:306</stack_trace>
<context>
<user_id>dc348ded-7e54-44aa-bfc8-75caf977ffdf</user_id>
<request_id>cc597ab0-ad26-419a-8cbb-1facc38a2f79</request_id>
</context>
</error_log>


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

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

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

Output:
openapi: 3.0.0
info:
  title: Reactive exuding frame API
  version: 1.0.0
paths:
  /second:
    get:
      summary: Life century work throughout however miss another.
      parameters:
      - name: param0
        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 news article as XML.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<news_article>
<article_id>ART-3682408</article_id>
<headline>Decentralized stable neural-net</headline>
<author>Thomas Acevedo</author>
<published>2026-01-01T11:30:40.673887</published>

Business

<content>Cold trial recognize improve nice between these. Happy herself suggest impact tell easy.
Start movie up social real effort. Onto federal prepare class direction rest.
News party school five bit. Trouble box year how.
Pressure respond nature. Prepare ball put happen.</content>
<tags>movie</tags>
<tags>it</tags>
<tags>chance</tags>
<views>12438</views>
<shares>1329</shares>
</news_article>


[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>
<rx_id>RX-6885629</rx_id>
<prescriber>John Cook</prescriber>
<medications>
<name>Metformin</name>
<dosage>5mg</dosage>
<frequency>daily</frequency>
<quantity>30</quantity>
</medications>
<medications>
<name>Atorvastatin</name>
<dosage>5mg</dosage>
<frequency>BID</frequency>
<quantity>90</quantity>
</medications>
<medications>
<name>Lisinopril</name>
<dosage>5mg</dosage>
<frequency>TID</frequency>
<quantity>60</quantity>
</medications>
<date>2026-01-02</date>
<patient_mrn>MRN-741538</patient_mrn>
</prescription>


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

[User] Output sales analytics as XML.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<sales_analytics>
<period>September 2023</period>
<total_revenue>9732569</total_revenue>
<units_sold>38507</units_sold>
<channels>
<name>retail</name>
<revenue>4979277</revenue>
<growth>36.06</growth>
</channels>
<channels>
<name>wholesale</name>
<revenue>4800863</revenue>
<growth>8.87</growth>
</channels>
<top_products>
<sku>SKU-5649</sku>
<sales>311811</sales>
</top_products>
<top_products>
<sku>SKU-1879</sku>
<sales>391924</sales>
</top_products>
<top_products>
<sku>SKU-4665</sku>
<sales>317392</sales>
</top_products>
</sales_analytics>


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

[User]
Convert the following JSON to XML:
{
  "result_id": "LAB-5490961",
  "patient_mrn": "MRN-709917",
  "order_date": "2026-01-03",
  "panel": "CBC",
  "results": [
    {
      "test": "Glucose",
      "value": 146.9,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "Hemoglobin",
      "value": 119.4,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "WBC",
      "value": 95.1,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "Hemoglobin",
      "value": 73.3,
      "unit": "g/dL",
      "flag": "high"
    },
    {
      "test": "Glucose",
      "value": 166.8,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "WBC",
      "value": 98.8,
      "unit": "g/dL",
      "flag": "high"
    }
  ]
}

[Assistant]
Approach:
1. Task: Convert lab result 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"?>
<lab_result>
<result_id>LAB-5490961</result_id>
<patient_mrn>MRN-709917</patient_mrn>
<order_date>2026-01-03</order_date>
<panel>CBC</panel>
<results>
<test>Glucose</test>
<value>146.9</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>119.4</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>WBC</test>
<value>95.1</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>73.3</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Glucose</test>
<value>166.8</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>WBC</test>
<value>98.8</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
</lab_result>