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

[User]
Reformat the data below from JSON to TOML:
{
  "product_id": "PROD-361703",
  "name": "Grass-roots methodical neural-net",
  "category": "books",
  "price": 156.58,
  "currency": "USD",
  "stock": 3,
  "is_available": true,
  "rating": 3.73,
  "reviews": 915,
  "specs": {
    "weight_kg": 25.41,
    "dimensions": "90x40x81cm"
  }
}

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

Output:
product_id = "PROD-361703"
name = "Grass-roots methodical neural-net"
category = "books"
price = 156.58
currency = "USD"
stock = 3
is_available = true
rating = 3.73
reviews = 915

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


[System] You are an expert in 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"?>
<error_log>
<timestamp>2026-01-07T13:51:26.818902</timestamp>
<context>
<user_id>3a96bf92-d9b7-4f9e-91da-6a15b590d5cf</user_id>
<request_id>d8c0cfbc-2ae8-46b8-8db8-ee3a71153dc5</request_id>
</context>
<error_id>de32926d-7560-4176-8c16-f346784a78af</error_id>
</error_log>

[Assistant]
Approach:
1. Task: Convert error log 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:
{
  "timestamp": "2026-01-07T13:51:26.818902",
  "context": {
    "user_id": "3a96bf92-d9b7-4f9e-91da-6a15b590d5cf",
    "request_id": "d8c0cfbc-2ae8-46b8-8db8-ee3a71153dc5"
  },
  "error_id": "de32926d-7560-4176-8c16-f346784a78af"
}


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

[User] Output course syllabus as JSON.

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

Output:
{
  "course_id": "CRS-2063",
  "code": "FAH301",
  "title": "Ameliorated zero administration productivity 101",
  "instructor": "Aaron Bailey",
  "credits": 4,
  "term": "Fall 2023",
  "schedule": [
    {
      "week": 1,
      "topic": "health"
    },
    {
      "week": 2,
      "topic": "buy"
    },
    {
      "week": 3,
      "topic": "conference"
    },
    {
      "week": 4,
      "topic": "late"
    },
    {
      "week": 5,
      "topic": "fear"
    },
    {
      "week": 6,
      "topic": "ability"
    },
    {
      "week": 7,
      "topic": "control"
    },
    {
      "week": 8,
      "topic": "choose"
    },
    {
      "week": 9,
      "topic": "measure"
    },
    {
      "week": 10,
      "topic": "social"
    }
  ],
  "grading": {
    "homework": 30,
    "midterm": 30,
    "final": 40
  }
}


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<financial_report>
<net_income>16280737</net_income>
<revenue>93235840</revenue>
<metrics>
<profit_margin>9.67</profit_margin>
<roe>5.79</roe>
</metrics>
<expenses>6835352</expenses>
</financial_report>

[Assistant]
Approach:
1. Task: Convert financial report 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:
{
  "net_income": 16280737,
  "revenue": 93235840,
  "metrics": {
    "profit_margin": 9.67,
    "roe": 5.79
  },
  "expenses": 6835352
}


[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:
{
  "assessment_id": "ASMT-485879",
  "student_id": "STU-284737",
  "course_id": "CRS-1053",
  "type": "exam",
  "date": "2026-01-03",
  "scores": [
    {
      "question": 1,
      "points_earned": 0,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 6,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 5,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 2,
      "points_possible": 10
    }
  ],
  "total_score": 89,
  "percentage": 64.04,
  "grade": "A"
}

[Assistant]
Approach:
1. Task: Convert student assessment 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"?>
<student_assessment>
<assessment_id>ASMT-485879</assessment_id>
<student_id>STU-284737</student_id>
<course_id>CRS-1053</course_id>
<type>exam</type>
<date>2026-01-03</date>
<scores>
<question>1</question>
<points_earned>0</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>6</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>3</question>
<points_earned>7</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>5</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>89</total_score>
<percentage>64.04</percentage>
<grade>A</grade>
</student_assessment>


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

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

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

Output:
abstract,authors,channels,citations,funding_source,keywords,paper_id,period,publication_doi,publication_venue,publication_year,title,top_products,total_revenue,units_sold
,,"[{""name"": ""online"", ""revenue"": 235807, ""growth"": 46.03}, {""name"": ""wholesale"", ""revenue"": 4419318, """,,,,,February 2020,,,,,"[{""sku"": ""SKU-6554"", ""sales"": 258652}, {""sku"": ""SKU-8652"", ""sales"": 200091}, {""sku"": ""SKU-9581"", ""sa",2007174,24558
"Without assume market. Middle style sound professor.
Capital suddenly defense eight watch soon. Gard","[{""name"": ""Jessica Bishop"", ""affiliation"": ""Padilla PLC"", ""email"": ""johnperkins@example.net""}, {""nam",,122,"Brown, Edwards and Anderson","[""morning"", ""gas"", ""those""]",arXiv:2021.92662,,10.6655/mbuo,Science,2024,Configurable radical concept,,,
Trouble detail paper already social. Free word performance suffer really. Woman often laugh hear who,"[{""name"": ""Jennifer Bradley"", ""affiliation"": ""Tapia, Frost and Mitchell"", ""email"": ""ellisheidi@examp",,1,None,"[""behavior"", ""benefit"", ""realize""]",arXiv:2024.62231,,10.8481/ngag,Cell,2023,Diverse 24/7 moderator,,,


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

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

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


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<news_article>
<article_id>ART-6180455</article_id>
<headline>Grass-roots multi-tasking hub</headline>
<author>David Espinoza</author>
<published>2026-01-07T13:20:10.771283</published>

Politics

<content>Either large lot east. Show everybody away city election happy my. Believe left sure mother.
Whom game determine road little. Sing this character. Agent fill kitchen themselves agreement.
Woman draw budget stage. Star cultural old president where national success.</content>
<tags>size</tags>
<tags>commercial</tags>
<tags>president</tags>
<tags>city</tags>
<tags>expect</tags>
<views>43396</views>
<shares>2564</shares>
</news_article>

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

Output:
{
  "article_id": "ART-6180455",
  "headline": "Grass-roots multi-tasking hub",
  "author": "David Espinoza",
  "published": "2026-01-07T13:20:10.771283",
  "section": "Politics",
  "content": "Either large lot east. Show everybody away city election happy my. Believe left sure mother.\nWhom game determine road little. Sing this character. Agent fill kitchen themselves agreement.\nWoman draw budget stage. Star cultural old president where national success.",
  "tags": [
    "size",
    "commercial",
    "president",
    "city",
    "expect"
  ],
  "views": 43396,
  "shares": 2564
}


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

[User] Output student assessment as JSON.

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

Output:
{
  "assessment_id": "ASMT-549878",
  "student_id": "STU-264168",
  "course_id": "CRS-6692",
  "type": "assignment",
  "date": "2026-01-01",
  "scores": [
    {
      "question": 1,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 1,
      "points_possible": 10
    }
  ],
  "total_score": 70,
  "percentage": 54.38,
  "grade": "C"
}


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

[User] Create a TOML representation of api specification.

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

Output:
openapi = "3.0.0"

[info]
title = "Seamless disintermediate flexibility API"
version = "1.0.0"

[paths."/significant".get]
summary = "Box project skin day catch."
[[paths."/significant".get.parameters]]
name = "param0"
in = "query"
type = "string"

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

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


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

[User]
Convert the following JSON to XML:
{
  "contract_id": "CTR-640570",
  "parties": [
    {
      "name": "Mitchell-Clark",
      "role": "party_a"
    },
    {
      "name": "Simmons-Marquez",
      "role": "party_b"
    }
  ],
  "effective_date": "2026-01-06",
  "term_months": 52,
  "value": 450714,
  "status": "pending"
}

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


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

[User] Output news article as YAML.

[Assistant]
Approach:
1. Task: Create news article in YAML
2. Complexity: 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-2188860
headline: Advanced well-modulated service-desk
author: Michael Logan
published: '2026-01-03T08:09:52.608144'
section: Politics
content: 'Include start build no effort continue. Mention sister mention threat.

  Choose herself case writer question over. Hand quickly house send shoulder expert
  hour.

  All probably suffer law consider kitchen relationship. Data population personal
  past security but across.'
tags:
- hear
- civil
- might
- way
- win
views: 35184
shares: 1092


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

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

[Assistant]
Approach:
1. Task: Create student assessment in XML
2. Complexity: 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"?>
<student_assessment>
<total_score>96</total_score>
<percentage>61.11</percentage>
<student_id>STU-785727</student_id>
</student_assessment>


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

[User] Output prescription as XML.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<prescription>
<rx_id>RX-5336793</rx_id>
<patient_mrn>MRN-644295</patient_mrn>
<prescriber>Thomas Ponce</prescriber>
<date>2026-01-03</date>
<medications>
<name>Atorvastatin</name>
<dosage>5mg</dosage>
<frequency>BID</frequency>
<quantity>90</quantity>
</medications>
<medications>
<name>Atorvastatin</name>
<dosage>5mg</dosage>
<frequency>daily</frequency>
<quantity>30</quantity>
</medications>
<medications>
<name>Atorvastatin</name>
<dosage>10mg</dosage>
<frequency>BID</frequency>
<quantity>30</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:
{
  "assessment_id": "ASMT-996269",
  "student_id": "STU-878254",
  "course_id": "CRS-8988",
  "type": "exam",
  "date": "2026-01-03",
  "scores": [
    {
      "question": 1,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 0,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 3,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 9,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 10,
      "points_earned": 3,
      "points_possible": 10
    }
  ],
  "total_score": 71,
  "percentage": 94.86,
  "grade": "B"
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<student_assessment>
<assessment_id>ASMT-996269</assessment_id>
<student_id>STU-878254</student_id>
<course_id>CRS-8988</course_id>
<type>exam</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>0</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>3</question>
<points_earned>8</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>7</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>3</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>7</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>9</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>10</question>
<points_earned>3</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>71</total_score>
<percentage>94.86</percentage>
<grade>B</grade>
</student_assessment>


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

[User]
Reformat the data below from JSON to XML:
{
  "experiment_id": "EXP-318732",
  "title": "Effect of produce on stock",
  "methodology": {
    "design": "observational",
    "sample_size": 303,
    "duration_days": 155
  },
  "results": [
    {
      "metric": "safety",
      "baseline": 20.77,
      "endpoint": 67.03,
      "p_value": 0.1826
    },
    {
      "metric": "safety",
      "baseline": 69.69,
      "endpoint": 32.04,
      "p_value": 0.1176
    }
  ],
  "conclusion": "non-significant"
}

[Assistant]
Approach:
1. Task: Convert experiment 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"?>
<experiment_result>
<experiment_id>EXP-318732</experiment_id>
<title>Effect of produce on stock</title>
<methodology>
<design>observational</design>
<sample_size>303</sample_size>
<duration_days>155</duration_days>
</methodology>
<results>
<metric>safety</metric>
<baseline>20.77</baseline>
<endpoint>67.03</endpoint>
<p_value>0.1826</p_value>
</results>
<results>
<metric>safety</metric>
<baseline>69.69</baseline>
<endpoint>32.04</endpoint>
<p_value>0.1176</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] Create a XML representation of 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:2023.67497</paper_id>
<title>Open-architected logistical paradigm</title>
<authors>
<name>William Martin</name>
<affiliation>George, Nichols and Johnston</affiliation>
<email>crystal73@example.org</email>
</authors>
<authors>
<name>Thomas Boyer</name>
<affiliation>Powers, Miller and Johnston</affiliation>
<email>xhardin@example.com</email>
</authors>
<authors>
<name>Tanner Coffey</name>
<affiliation>Perez, Marks and Thomas</affiliation>
<email>tracywilliams@example.com</email>
</authors>
<abstract>Yes eat up himself consumer. Technology just debate bill live oil.</abstract>
<keywords>each</keywords>
<keywords>on</keywords>
<keywords>perhaps</keywords>
<publication>
<venue>Nature</venue>
<year>2022</year>
<doi>10.2923/Xnio</doi>
</publication>
<citations>265</citations>
<funding_source>Smith Ltd</funding_source>
</research_paper>


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

[User] Create a TOML representation of news article.

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

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


[System] You are an expert in 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>
<content>Range condition class leader wrong subject wait. Stop we prevent particular front method. Force item executive employee green large house nation. General doctor material rule head event.
One will dog chance. Order away music seem director put upon. Find boy again direction four.</content>
<article_id>ART-9628131</article_id>
<headline>Re-contextualized logistical paradigm</headline>
</news_article>

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

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


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<experiment_result>
<experiment_id>EXP-734376</experiment_id>
<title>Effect of probably on skin</title>
<methodology>
<design>cohort</design>
<sample_size>800</sample_size>
<duration_days>273</duration_days>
</methodology>
<results>
<metric>efficacy</metric>
<baseline>94.92</baseline>
<endpoint>99.12</endpoint>
<p_value>0.3163</p_value>
</results>
<results>
<metric>safety</metric>
<baseline>43.8</baseline>
<endpoint>81.58</endpoint>
<p_value>0.1627</p_value>
</results>
<results>
<metric>efficacy</metric>
<baseline>31.59</baseline>
<endpoint>36.02</endpoint>
<p_value>0.4619</p_value>
</results>
<results>
<metric>efficacy</metric>
<baseline>82.54</baseline>
<endpoint>59.85</endpoint>
<p_value>0.3654</p_value>
</results>
<conclusion>significant</conclusion>
</experiment_result>

[Assistant]
Approach:
1. Task: Convert experiment 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:
{
  "experiment_id": "EXP-734376",
  "title": "Effect of probably on skin",
  "methodology": {
    "design": "cohort",
    "sample_size": 800,
    "duration_days": 273
  },
  "results": [
    {
      "metric": "efficacy",
      "baseline": 94.92,
      "endpoint": 99.12,
      "p_value": 0.3163
    },
    {
      "metric": "safety",
      "baseline": 43.8,
      "endpoint": 81.58,
      "p_value": 0.1627
    },
    {
      "metric": "efficacy",
      "baseline": 31.59,
      "endpoint": 36.02,
      "p_value": 0.4619
    },
    {
      "metric": "efficacy",
      "baseline": 82.54,
      "endpoint": 59.85,
      "p_value": 0.3654
    }
  ],
  "conclusion": "significant"
}


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

[User] Create a TOML representation of error log.

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

Output:
level = "ERROR"
service = "writeService"
error_id = "85223c4c-4b76-4351-95ee-55a2460043f3"


[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:
{
  "company": "Scott-Campbell",
  "ticker": "SZQB",
  "quarter": "Q2 2021",
  "revenue": 15063505,
  "expenses": 40738667,
  "net_income": 16626814,
  "eps": 6.47,
  "metrics": {
    "profit_margin": 15.92,
    "roe": 8.35
  }
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<financial_report>
<company>Scott-Campbell</company>
<ticker>SZQB</ticker>
<quarter>Q2 2021</quarter>
<revenue>15063505</revenue>
<expenses>40738667</expenses>
<net_income>16626814</net_income>
<eps>6.47</eps>
<metrics>
<profit_margin>15.92</profit_margin>
<roe>8.35</roe>
</metrics>
</financial_report>


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

[User] Create a XML representation of api specification.

[Assistant]
Approach:
1. Task: Create api specification in XML
2. Complexity: 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"?>
<api_specification>
<openapi>3.0.0</openapi>
<paths>
</somebody>
<get>
<summary>Threat common organization project.</summary>
<parameters>
<name>param0</name>
<in>query</in>
<type>string</type>
</parameters>
<parameters>
<name>param1</name>
<in>query</in>
<type>string</type>
</parameters>
<responses>
<200>
<description>Success</description>
</200>
<400>
<description>Bad Request</description>
</400>
</responses>
</get>
<//somebody>
</paths>
<info>
<title>Networked system-worthy project API</title>
<version>1.0.0</version>
</info>
</api_specification>


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

[User] Create a JSON representation of clinical note.

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

Output:
{
  "note_id": "CN-3409162",
  "patient": {
    "mrn": "MRN-721241",
    "age": 35,
    "gender": "F"
  },
  "encounter_date": "2026-01-05",
  "chief_complaint": "fever",
  "vitals": {
    "bp": "173/107",
    "hr": 61,
    "temp_f": 99.6
  },
  "assessment": [
    {
      "problem": "diabetes",
      "icd10": "J46"
    }
  ]
}


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

[User]
Reformat the data below from XML to TOML:
<?xml version="1.0" encoding="UTF-8"?>
<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>

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

Output:
openapi = "3.0.0"

[info]
title = "Stand-alone dedicated complexity API"
version = "1.0.0"

[paths."/hear".get]
summary = "Chance cultural sort including high."
[[paths."/hear".get.parameters]]
name = "param0"
in = "query"
type = "string"

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

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

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

[paths."/hear".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 student assessment data in JSON format.

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

Output:
{
  "assessment_id": "ASMT-554535",
  "student_id": "STU-693793",
  "course_id": "CRS-9992",
  "type": "exam",
  "date": "2026-01-03",
  "scores": [
    {
      "question": 1,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 6,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 6,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 6,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 9,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 10,
      "points_earned": 3,
      "points_possible": 10
    }
  ],
  "total_score": 86,
  "percentage": 63.99,
  "grade": "B"
}


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

[User] Output prescription as TOML.

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

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


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<social_media_post>
<post_id>POST-19357850</post_id>
<platform>twitter</platform>
<user_id>664b960b-1331-492f-addd-e9b37d21656f</user_id>
<username>mbaldwin</username>
<content>Forward front agreement cover hour we remember ask. Read glass few word mother deep TV.</content>
<timestamp>2026-01-07T13:51:27.605837</timestamp>
<hashtags>#cost</hashtags>
<hashtags>#he</hashtags>
<hashtags>#relationship</hashtags>
<engagement>
<likes>304</likes>
<shares>796</shares>
<comments>124</comments>
</engagement>
</social_media_post>

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

Output:
{
  "post_id": "POST-19357850",
  "platform": "twitter",
  "user_id": "664b960b-1331-492f-addd-e9b37d21656f",
  "username": "mbaldwin",
  "content": "Forward front agreement cover hour we remember ask. Read glass few word mother deep TV.",
  "timestamp": "2026-01-07T13:51:27.605837",
  "hashtags": [
    "#cost",
    "#he",
    "#relationship"
  ],
  "engagement": {
    "likes": 304,
    "shares": 796,
    "comments": 124
  }
}


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

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

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

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


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

[User] Output error log as YAML.

[Assistant]
Approach:
1. Task: Create error log 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:
error_id: 042db0a1-c9b1-49a9-9d69-5247a8c47159
timestamp: '2026-01-07T13:51:27.377057'
level: ERROR
service: whomService
message: Each reality trip red enough tough common.
stack_trace:
- at note.py:398
- at purpose.py:452
- at onto.py:106
- at member.py:439
context:
  user_id: 70c0c786-0e43-42b2-8ec7-e975f39a71f7
  request_id: 95ca942a-a33a-413f-b1a1-a21e12fa0f30


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

[User] Create a CSV representation of news article.

[Assistant]
Approach:
1. Task: Create news article 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:
article_id,author,content,headline,published,section,shares,tags,views
ART-7317178,Judy Garner,"Cover whole myself late last month authority. Make away choose difficult.
Shoulder so support like l",Sharable 5thgeneration framework,2026-01-07T07:35:28.380949,Politics,2480,"[""cover"", ""people"", ""available"", ""above"", ""service""]",84087
ART-4025776,Marissa Kennedy,"Board standard any blue gun service majority. Why join young significant event trouble.
Us between d",Sharable dedicated concept,2026-01-05T18:08:58.149402,Business,850,"[""summer"", ""wait"", ""very""]",86681
ART-6766984,Miranda Reyes,"Then receive audience very begin plant the. At like age coach discuss modern than.
Example all want ",Advanced zero-defect parallelism,2026-01-04T13:00:56.531845,Sports,622,"[""major"", ""mission"", ""beyond""]",55380
ART-1099587,Nancy Ochoa,Executive kitchen hundred box music deal development public. Perhaps after game option. A decide Rep,Total user-facing info-mediaries,2026-01-05T10:42:32.416088,Sports,4540,"[""true"", ""remain"", ""less"", ""meet""]",81698
ART-1183727,Stephanie Cross MD,"Near city especially. Open eat kitchen meet act. Trial six too remain.
Enough those this never forwa",Focused logistical emulation,2026-01-06T11:34:26.139234,Politics,2118,"[""total"", ""myself"", ""very"", ""little"", ""check""]",83589


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

[User] Output customer review as XML.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<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 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"?>
<prescription>
<rx_id>RX-5305677</rx_id>
<patient_mrn>MRN-215469</patient_mrn>
<prescriber>Jeremy Hatfield</prescriber>
<date>2026-01-03</date>
<medications>
<name>Metformin</name>
<dosage>10mg</dosage>
<frequency>daily</frequency>
<quantity>90</quantity>
</medications>
<medications>
<name>Metformin</name>
<dosage>5mg</dosage>
<frequency>daily</frequency>
<quantity>30</quantity>
</medications>
<medications>
<name>Atorvastatin</name>
<dosage>10mg</dosage>
<frequency>BID</frequency>
<quantity>90</quantity>
</medications>
</prescription>

[Assistant]
Approach:
1. Task: Convert prescription 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:
rx_id: RX-5305677
patient_mrn: MRN-215469
prescriber: Jeremy Hatfield
date: '2026-01-03'
medications:
- name: Metformin
  dosage: 10mg
  frequency: daily
  quantity: 90
- name: Metformin
  dosage: 5mg
  frequency: daily
  quantity: 30
- name: Atorvastatin
  dosage: 10mg
  frequency: BID
  quantity: 90


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<student_assessment>
<assessment_id>ASMT-817642</assessment_id>
<student_id>STU-222420</student_id>
<course_id>CRS-8326</course_id>
<type>assignment</type>
<date>2026-01-03</date>
<scores>
<question>1</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>10</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>3</question>
<points_earned>0</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>7</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>4</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>10</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>7</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>60</total_score>
<percentage>56.31</percentage>
<grade>A</grade>
</student_assessment>

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


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

[User] Create a JSON representation of financial report.

[Assistant]
Approach:
1. Task: Create financial report 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:
{
  "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 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: 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": "October 2022",
  "total_revenue": 4790876,
  "units_sold": 72609,
  "channels": [
    {
      "name": "retail",
      "revenue": 1112533,
      "growth": 2.85
    },
    {
      "name": "wholesale",
      "revenue": 3150615,
      "growth": -3.34
    }
  ],
  "top_products": [
    {
      "sku": "SKU-7795",
      "sales": 492045
    },
    {
      "sku": "SKU-5231",
      "sales": 195976
    },
    {
      "sku": "SKU-5539",
      "sales": 335045
    }
  ]
}


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

[User]
Reformat the data below from JSON to XML:
{
  "review_id": "REV-5008217",
  "product_id": "PROD-173271",
  "user_id": "11121b86-b60c-4ea2-b83a-cbb727cd7a24",
  "rating": 2,
  "title": "Lay lead it politics brother.",
  "content": "Camera left hope prevent inside real. Whether trouble their always manager cultural majority popular. Song condition entire security concern science. Run number firm listen serious.",
  "date": "2026-01-01",
  "verified_purchase": true,
  "helpful_votes": 23
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<review_id>REV-5008217</review_id>
<product_id>PROD-173271</product_id>
<user_id>11121b86-b60c-4ea2-b83a-cbb727cd7a24</user_id>
<rating>2</rating>
<title>Lay lead it politics brother.</title>
<content>Camera left hope prevent inside real. Whether trouble their always manager cultural majority popular. Song condition entire security concern science. Run number firm listen serious.</content>
<date>2026-01-01</date>
<verified_purchase>True</verified_purchase>
<helpful_votes>23</helpful_votes>
</customer_review>


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

[User] Output product listing as CSV.

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

Output:
category,currency,is_available,name,price,product_id,rating,reviews,specs_dimensions,specs_weight_kg,stock
books,USD,True,Proactive tertiary database,435.77,PROD-597223,1.73,539,87x91x85cm,19.61,111
electronics,USD,True,Up-sized discrete matrices,901.15,PROD-517587,1.1,967,87x27x37cm,35.01,34
electronics,USD,True,Right-sized bottom-line model,41.89,PROD-228718,2.12,46,98x73x60cm,10.49,301


[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:
{
  "items": [
    {
      "sku": "SKU-71565",
      "qty": 1,
      "price": 387.38
    },
    {
      "sku": "SKU-23891",
      "qty": 1,
      "price": 432.74
    },
    {
      "sku": "SKU-77840",
      "qty": 1,
      "price": 463.12
    },
    {
      "sku": "SKU-27496",
      "qty": 3,
      "price": 295.3
    }
  ],
  "tax": 39.55,
  "total": 1865.58,
  "customer_id": "bf96f80b-072c-4f04-82b0-c235c01681a8"
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<transaction_record>
<items>
<sku>SKU-71565</sku>
<qty>1</qty>
<price>387.38</price>
</items>
<items>
<sku>SKU-23891</sku>
<qty>1</qty>
<price>432.74</price>
</items>
<items>
<sku>SKU-77840</sku>
<qty>1</qty>
<price>463.12</price>
</items>
<items>
<sku>SKU-27496</sku>
<qty>3</qty>
<price>295.3</price>
</items>
<tax>39.55</tax>
<total>1865.58</total>
<customer_id>bf96f80b-072c-4f04-82b0-c235c01681a8</customer_id>
</transaction_record>


[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"?>
<contract>
<contract_id>CTR-449984</contract_id>
<parties>
<name>Garcia-Henson</name>
<role>party_a</role>
</parties>
<parties>
<name>Moore LLC</name>
<role>party_b</role>
</parties>
<effective_date>2026-01-04</effective_date>
<term_months>49</term_months>
<value>694475</value>
<status>pending</status>
</contract>

[Assistant]
Approach:
1. Task: Convert contract 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:
{
  "contract_id": "CTR-449984",
  "parties": [
    {
      "name": "Garcia-Henson",
      "role": "party_a"
    },
    {
      "name": "Moore LLC",
      "role": "party_b"
    }
  ],
  "effective_date": "2026-01-04",
  "term_months": 49,
  "value": 694475,
  "status": "pending"
}


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

[User]
Reformat the data below from XML to TOML:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<review_id>REV-3637179</review_id>
<product_id>PROD-905516</product_id>
<user_id>cbc145e7-7f32-438c-ba90-61711bf65a15</user_id>
<rating>1</rating>
<title>Hand ok join you population.</title>
<content>Develop particularly receive thing process sister source. Ago short fact start meeting note need. However music factor my million scene use.</content>
<date>2026-01-03</date>
<verified_purchase>False</verified_purchase>
<helpful_votes>42</helpful_votes>
</customer_review>

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

Output:
review_id = "REV-3637179"
product_id = "PROD-905516"
user_id = "cbc145e7-7f32-438c-ba90-61711bf65a15"
rating = 1
title = "Hand ok join you population."
content = "Develop particularly receive thing process sister source. Ago short fact start meeting note need. However music factor my million scene use."
date = "2026-01-03"
verified_purchase = false
helpful_votes = 42


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

[User] Create a YAML representation of clinical note.

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

Output:
note_id: CN-6224145
patient:
  mrn: MRN-560569
  age: 88
  gender: F
encounter_date: '2026-01-04'
chief_complaint: headache
vitals:
  bp: 119/73
  hr: 63
  temp_f: 100.0
assessment:
- problem: hypertension
  icd10: I32


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

[User]
Reformat the data below from JSON to CSV:
{
  "company": "Hill-Marsh",
  "ticker": "ZFVR",
  "quarter": "Q3 2024",
  "revenue": 46703834,
  "expenses": 77071880,
  "net_income": 4141173,
  "eps": 8.71,
  "metrics": {
    "profit_margin": 28.84,
    "roe": 14.06
  }
}

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

Output:
company,eps,expenses,metrics_profit_margin,metrics_roe,net_income,quarter,revenue,ticker
Hill-Marsh,8.71,77071880,28.84,14.06,4141173,Q3 2024,46703834,ZFVR
"Gray, Baldwin and Bradley",7.96,16998062,10.31,9.3,16393625,Q3 2021,9591147,AUBW
"Olson, Green and Bradley",4.71,71722749,5.91,13.17,5485814,Q3 2024,14743710,AVIR
"Rodriguez, Kirby and Anderson",2.17,43143419,12.58,11.11,3610898,Q3 2024,11484247,XUXZ
"Gardner, Baker and Obrien",3.02,20063335,21.21,11.64,3240977,Q3 2023,50601728,DUFP


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

[User] Output financial report as XML.

[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>Harris Inc</company>
<ticker>KXNS</ticker>
<quarter>Q2 2023</quarter>
<revenue>96096321</revenue>
<expenses>36366080</expenses>
<net_income>6859279</net_income>
<eps>2.68</eps>
<metrics>
<profit_margin>18.37</profit_margin>
<roe>11.92</roe>
</metrics>
</financial_report>


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

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

[Assistant]
Approach:
1. Task: Create clinical note 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"?>
<clinical_note>
<patient>
<mrn>MRN-802088</mrn>
<age>30</age>
<gender>M</gender>
</patient>
<note_id>CN-3759937</note_id>
<vitals>
<bp>119/74</bp>

67

<temp_f>100.9</temp_f>
</vitals>
</clinical_note>


[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: 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:
contract_id: CTR-464030
parties:
- name: Morales, Williams and Williams
  role: party_a
- name: Ward-Miller
  role: party_b
effective_date: '2026-01-06'
term_months: 35
value: 994957
status: active


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<news_article>
<article_id>ART-8846154</article_id>
<headline>Phased bifurcated instruction set</headline>
<author>Melanie Kennedy</author>
<published>2026-01-02T14:27:49.190328</published>

Sports

<content>Edge wear coach whether dog sell respond. Claim feeling meeting somebody four real.
Indeed use send represent leader require. Cup attack instead discuss. Plan with character rule.
Information mind company even serve. Experience pattern but certain she design speech.</content>
<tags>memory</tags>
<tags>score</tags>
<tags>game</tags>
<tags>join</tags>
<views>47684</views>
<shares>4081</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-8846154",
  "headline": "Phased bifurcated instruction set",
  "author": "Melanie Kennedy",
  "published": "2026-01-02T14:27:49.190328",
  "section": "Sports",
  "content": "Edge wear coach whether dog sell respond. Claim feeling meeting somebody four real.\nIndeed use send represent leader require. Cup attack instead discuss. Plan with character rule.\nInformation mind company even serve. Experience pattern but certain she design speech.",
  "tags": [
    "memory",
    "score",
    "game",
    "join"
  ],
  "views": 47684,
  "shares": 4081
}


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<social_media_post>
<post_id>POST-52722833</post_id>
<platform>facebook</platform>
<user_id>d42576ea-a78d-4261-852d-cbcc2fd55da5</user_id>
<username>justin96</username>
<content>Southern write three operation throw interest whether.
Decade quality training employee. Financial out position catch finish author. Past over in create.
Nice reduce try contain future back customer.</content>
<timestamp>2026-01-07T13:51:26.716888</timestamp>
<hashtags>#report</hashtags>
<hashtags>#newspaper</hashtags>
<engagement>
<likes>8106</likes>
<shares>850</shares>
<comments>244</comments>
</engagement>
</social_media_post>

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

Output:
{
  "post_id": "POST-52722833",
  "platform": "facebook",
  "user_id": "d42576ea-a78d-4261-852d-cbcc2fd55da5",
  "username": "justin96",
  "content": "Southern write three operation throw interest whether.\nDecade quality training employee. Financial out position catch finish author. Past over in create.\nNice reduce try contain future back customer.",
  "timestamp": "2026-01-07T13:51:26.716888",
  "hashtags": [
    "#report",
    "#newspaper"
  ],
  "engagement": {
    "likes": 8106,
    "shares": 850,
    "comments": 244
  }
}


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

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

[Assistant]
Approach:
1. Task: Create social media post 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:
content,engagement_comments,engagement_likes,engagement_shares,hashtags,platform,post_id,timestamp,user_id,username
"Three would identify method across operation opportunity.
What realize number. Country perform simpl",63,458,383,"[""#pay"", ""#keep""]",facebook,POST-90196326,2026-01-07T13:51:26.698310,146c178d-e548-4357-8cd4-e8464cea2f9b,kevincunningham
Education wife spring billion week. Image attorney whole fight artist. Improve message election rate,408,2103,232,"[""#tonight"", ""#fly""]",instagram,POST-75733660,2026-01-07T13:51:26.699739,545ab2f6-d76f-41ef-9816-fb6089e98282,donnacastro
Responsibility drug individual hit expert almost finally couple. Wait save stay money administration,62,7801,670,"[""#quality"", ""#camera""]",twitter,POST-89046668,2026-01-07T13:51:26.700163,ba15477b-6686-49f4-90e3-c993976aad86,greenedavid


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

[User]
Reformat the data below from JSON to YAML:
{
  "service": "findService",
  "stack_trace": [
    "at watch.py:197",
    "at body.py:298",
    "at girl.py:392",
    "at red.py:350"
  ],
  "level": "ERROR",
  "message": "Head then too threat drive."
}

[Assistant]
Approach:
1. Task: Convert error log from JSON to 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:
service: findService
stack_trace:
- at watch.py:197
- at body.py:298
- at girl.py:392
- at red.py:350
level: ERROR
message: Head then too threat drive.


[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:
{
  "article_id": "ART-8221745",
  "headline": "Polarized zero administration support",
  "author": "Maria Johnson",
  "published": "2026-01-03T08:37:58.870132",
  "section": "Business",
  "content": "Would movement white military what them cup. Available remember control staff. None mean hundred PM.\nImprove wear produce price according. He method market computer TV strategy.\nBody into language. Which other hear they look some option.",
  "tags": [
    "environment",
    "name",
    "receive",
    "happen",
    "join"
  ],
  "views": 46852,
  "shares": 763
}

[Assistant]
Approach:
1. Task: Convert news article 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"?>
<news_article>
<article_id>ART-8221745</article_id>
<headline>Polarized zero administration support</headline>
<author>Maria Johnson</author>
<published>2026-01-03T08:37:58.870132</published>

Business

<content>Would movement white military what them cup. Available remember control staff. None mean hundred PM.
Improve wear produce price according. He method market computer TV strategy.
Body into language. Which other hear they look some option.</content>
<tags>environment</tags>
<tags>name</tags>
<tags>receive</tags>
<tags>happen</tags>
<tags>join</tags>
<views>46852</views>
<shares>763</shares>
</news_article>


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

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

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

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


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<social_media_post>
<post_id>POST-64636774</post_id>
<platform>instagram</platform>
<user_id>180a1898-015f-483f-94a7-e771a6fb148e</user_id>
<username>melissa16</username>
<content>Use Mr only week. Crime form attention. Right world stand surface rate three.</content>
<timestamp>2026-01-07T13:51:26.942814</timestamp>
<hashtags>#economic</hashtags>
<hashtags>#speak</hashtags>
<engagement>
<likes>9998</likes>
<shares>653</shares>
<comments>4</comments>
</engagement>
</social_media_post>

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

Output:
{
  "post_id": "POST-64636774",
  "platform": "instagram",
  "user_id": "180a1898-015f-483f-94a7-e771a6fb148e",
  "username": "melissa16",
  "content": "Use Mr only week. Crime form attention. Right world stand surface rate three.",
  "timestamp": "2026-01-07T13:51:26.942814",
  "hashtags": [
    "#economic",
    "#speak"
  ],
  "engagement": {
    "likes": 9998,
    "shares": 653,
    "comments": 4
  }
}


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

[User] Output customer review as CSV.

[Assistant]
Approach:
1. Task: Create customer review 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:
category,content,currency,date,is_available,name,price,product_id,rating,reviews,specs_dimensions,specs_weight_kg,stock,title
,"Arrive much low will teach. By possible nature learn could. Act hot whole guy experience.
Identify w",,2026-01-02,,,,PROD-922306,,,,,,Exactly almost full new record save.
clothing,,USD,,True,Multi-layered multi-state website,296.23,PROD-588177,3.98,223,43x94x88cm,15.03,95,
clothing,,USD,,True,Realigned leadingedge frame,301.77,PROD-401757,2.55,650,71x35x17cm,31.66,815,


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

[User]
Reformat the data below from TOML to YAML:
company = "Nichols, Ferguson and Butler"
ticker = "NDVN"
quarter = "Q1 2022"
revenue = 39470251
expenses = 26562838
net_income = 16784469
eps = 3.2

[metrics]
profit_margin = 27.93
roe = 5.96

[Assistant]
Approach:
1. Task: Convert financial report 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:
company: Nichols, Ferguson and Butler
ticker: NDVN
quarter: Q1 2022
revenue: 39470251
expenses: 26562838
net_income: 16784469
eps: 3.2
metrics:
  profit_margin: 27.93
  roe: 5.96


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

[User] Create a JSON representation of transaction record.

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

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


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

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

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

Output:
{
  "note_id": "CN-5751204",
  "patient": {
    "mrn": "MRN-566004",
    "age": 47,
    "gender": "M"
  },
  "encounter_date": "2026-01-05",
  "chief_complaint": "headache",
  "vitals": {
    "bp": "160/96",
    "hr": 75,
    "temp_f": 102.4
  },
  "assessment": [
    {
      "problem": "diabetes",
      "icd10": "I93"
    }
  ]
}


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

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

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

Output:
paper_id: arXiv:2020.10600
title: Reactive bi-directional middleware
authors:
- name: Sarah Rose
  affiliation: Martin, Taylor and Mills
  email: adrianporter@example.com
- name: Samantha Garcia
  affiliation: Santiago LLC
  email: cbrewer@example.net
abstract: Carry prove certain tell event break. Thus not actually teacher girl perhaps.
keywords:
- public
- stock
- student
- hair
- hard
publication:
  venue: Cell
  year: 2022
  doi: 10.6112/KodW
citations: 273
funding_source: Salazar, Mullen and Johnson


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

[User]
Convert the following TOML to XML:
result_id = "LAB-5387789"
patient_mrn = "MRN-887521"
order_date = "2026-01-05"
panel = "CBC"
[[results]]
test = "WBC"
value = 66.6
unit = "mg/dL"
flag = "normal"

[[results]]
test = "Glucose"
value = 111.4
unit = "mg/dL"
flag = "high"

[[results]]
test = "Hemoglobin"
value = 168.1
unit = "g/dL"
flag = "high"

[[results]]
test = "Hemoglobin"
value = 136.7
unit = "g/dL"
flag = "low"

[[results]]
test = "WBC"
value = 148.7
unit = "g/dL"
flag = "low"

[[results]]
test = "Glucose"
value = 86.9
unit = "mg/dL"
flag = "normal"

[Assistant]
Approach:
1. Task: Convert lab result from TOML 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-5387789</result_id>
<patient_mrn>MRN-887521</patient_mrn>
<order_date>2026-01-05</order_date>
<panel>CBC</panel>
<results>
<test>WBC</test>
<value>66.6</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Glucose</test>
<value>111.4</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>168.1</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>136.7</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>WBC</test>
<value>148.7</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Glucose</test>
<value>86.9</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
</lab_result>


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<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>

[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-31892506",
  "customer_id": "6c5d6d8e-2901-438d-be6d-be57a13ea5ab",
  "timestamp": "2026-01-07T13:51:25.485684",
  "items": [
    {
      "sku": "SKU-80058",
      "qty": 4,
      "price": 142.37
    },
    {
      "sku": "SKU-53232",
      "qty": 1,
      "price": 151.54
    }
  ],
  "subtotal": 692.94,
  "tax": 100.91,
  "total": 1647.14,
  "payment_method": "credit_card"
}


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

[User]
Convert the following JSON to XML:
{
  "specs": {
    "weight_kg": 41.33,
    "dimensions": "19x24x69cm"
  },
  "price": 743.81,
  "is_available": true,
  "rating": 2.69,
  "stock": 485
}

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

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


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

[User] Create a JSON representation of error log.

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

Output:
{
  "service": "approachService",
  "context": {
    "user_id": "fe05329e-c851-4258-9b5b-a5822613303b",
    "request_id": "7878bb2d-6319-4d97-8924-bd0357b0788d"
  },
  "stack_trace": [
    "at level.py:451",
    "at science.py:176",
    "at art.py:498",
    "at success.py:287"
  ],
  "level": "WARNING",
  "error_id": "d3f1548e-3d70-475b-a25a-df504add1be1"
}


[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: medium - 5-8 fields, 2-3 levels
3. Format rules: consistent indentation, colon-space syntax, hyphen lists
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

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


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

[User] Produce a JSON document for a contract.

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

Output:
{
  "contract_id": "CTR-299234",
  "parties": [
    {
      "name": "Murphy, Hawkins and Mckenzie",
      "role": "party_a"
    },
    {
      "name": "Collins-Miller",
      "role": "party_b"
    }
  ],
  "effective_date": "2026-01-06",
  "term_months": 46,
  "value": 506357,
  "status": "pending"
}


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

[User] Create a YAML representation of error log.

[Assistant]
Approach:
1. Task: Create error log 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:
timestamp: '2026-01-07T13:51:26.818902'
context:
  user_id: 3a96bf92-d9b7-4f9e-91da-6a15b590d5cf
  request_id: d8c0cfbc-2ae8-46b8-8db8-ee3a71153dc5
error_id: de32926d-7560-4176-8c16-f346784a78af


[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 = "0ea30289-ce13-425f-910d-da970e03d0fa"
timestamp = "2026-01-07T13:51:25.772316"
level = "WARNING"
service = "theService"
message = "Country specific information follow daughter dark."
stack_trace = [ "at enjoy.py:340", "at current.py:45", "at hand.py:478",]

[context]
user_id = "91a6b883-2593-4790-8a1e-5acd27aad31b"
request_id = "1b22b6e6-0879-45de-9655-0fac03142f9b"


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

[User]
Transform this YAML data into TOML format:
effective_date: '2026-01-03'
value: 837359
term_months: 24
status: executed

[Assistant]
Approach:
1. Task: Convert contract from YAML 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:
effective_date = "2026-01-03"
value = 837359
term_months = 24
status = "executed"


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

[User]
Convert the following JSON to XML:
{
  "patient_mrn": "MRN-119365",
  "order_date": "2026-01-05",
  "results": [
    {
      "test": "Glucose",
      "value": 134.6,
      "unit": "g/dL",
      "flag": "high"
    },
    {
      "test": "Hemoglobin",
      "value": 69.4,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "Glucose",
      "value": 85.6,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "WBC",
      "value": 69.6,
      "unit": "mg/dL",
      "flag": "low"
    },
    {
      "test": "Hemoglobin",
      "value": 79.1,
      "unit": "g/dL",
      "flag": "high"
    }
  ]
}

[Assistant]
Approach:
1. Task: Convert lab 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"?>
<lab_result>
<patient_mrn>MRN-119365</patient_mrn>
<order_date>2026-01-05</order_date>
<results>
<test>Glucose</test>
<value>134.6</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>69.4</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Glucose</test>
<value>85.6</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>WBC</test>
<value>69.6</value>
<unit>mg/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>79.1</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
</lab_result>


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

[User] Generate financial report data in TOML format.

[Assistant]
Approach:
1. Task: Create financial report in TOML
2. Complexity: 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:
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]
Convert the following JSON to XML:
{
  "txn_id": "TXN-38439045",
  "customer_id": "39de4165-2950-403a-b7cf-252ec7bafdcc",
  "timestamp": "2026-01-07T13:51:25.757679",
  "items": [
    {
      "sku": "SKU-68017",
      "qty": 5,
      "price": 287.63
    },
    {
      "sku": "SKU-13598",
      "qty": 1,
      "price": 397.9
    },
    {
      "sku": "SKU-25253",
      "qty": 4,
      "price": 226.78
    },
    {
      "sku": "SKU-92380",
      "qty": 1,
      "price": 318.47
    }
  ],
  "subtotal": 964.6,
  "tax": 142.48,
  "total": 1270.74,
  "payment_method": "credit_card"
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<transaction_record>
<txn_id>TXN-38439045</txn_id>
<customer_id>39de4165-2950-403a-b7cf-252ec7bafdcc</customer_id>
<timestamp>2026-01-07T13:51:25.757679</timestamp>
<items>
<sku>SKU-68017</sku>
<qty>5</qty>
<price>287.63</price>
</items>
<items>
<sku>SKU-13598</sku>
<qty>1</qty>
<price>397.9</price>
</items>
<items>
<sku>SKU-25253</sku>
<qty>4</qty>
<price>226.78</price>
</items>
<items>
<sku>SKU-92380</sku>
<qty>1</qty>
<price>318.47</price>
</items>
<subtotal>964.6</subtotal>
<tax>142.48</tax>
<total>1270.74</total>
<payment_method>credit_card</payment_method>
</transaction_record>


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

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

[Assistant]
Approach:
1. Task: Create student assessment in XML
2. Complexity: 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"?>
<student_assessment>
<assessment_id>ASMT-549878</assessment_id>
<student_id>STU-264168</student_id>
<course_id>CRS-6692</course_id>
<type>assignment</type>
<date>2026-01-01</date>
<scores>
<question>1</question>
<points_earned>7</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>3</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>4</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>70</total_score>
<percentage>54.38</percentage>
<grade>C</grade>
</student_assessment>


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

[User]
Reformat the data below from TOML to XML:
openapi = "3.0.0"

[info]
title = "Networked system-worthy project API"
version = "1.0.0"

[paths."/somebody".get]
summary = "Threat common organization project."
[[paths."/somebody".get.parameters]]
name = "param0"
in = "query"
type = "string"

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

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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<api_specification>
<openapi>3.0.0</openapi>
<paths>
</somebody>
<get>
<summary>Threat common organization project.</summary>
<parameters>
<name>param0</name>
<in>query</in>
<type>string</type>
</parameters>
<parameters>
<name>param1</name>
<in>query</in>
<type>string</type>
</parameters>
<responses>
<200>
<description>Success</description>
</200>
<400>
<description>Bad Request</description>
</400>
</responses>
</get>
<//somebody>
</paths>
<info>
<title>Networked system-worthy project API</title>
<version>1.0.0</version>
</info>
</api_specification>


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

[User] Produce a CSV document for a contract.

[Assistant]
Approach:
1. Task: Create contract 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:
contract_id,effective_date,parties,status,term_months,value
CTR-370819,2026-01-01,"[{""name"": ""Stewart, Thompson and Rogers"", ""role"": ""party_a""}, {""name"": ""Jackson, Griffin and Flowers",active,13,109351
CTR-778899,2026-01-01,"[{""name"": ""Davis-Chavez"", ""role"": ""party_a""}, {""name"": ""Johnson Group"", ""role"": ""party_b""}]",pending,19,372198
CTR-784768,2026-01-01,"[{""name"": ""Davis-Huynh"", ""role"": ""party_a""}, {""name"": ""Swanson, Brown and Fry"", ""role"": ""party_b""}]",active,44,94687
CTR-637250,2026-01-05,"[{""name"": ""Gilbert-Sutton"", ""role"": ""party_a""}, {""name"": ""Mcmahon, Wilson and Gill"", ""role"": ""party_",active,53,948767
CTR-372607,2026-01-06,"[{""name"": ""Stewart Ltd"", ""role"": ""party_a""}, {""name"": ""King Group"", ""role"": ""party_b""}]",active,58,20065


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

[User]
Convert the following CSV to YAML:
company,eps,expenses,metrics_profit_margin,metrics_roe,net_income,quarter,revenue,ticker
"Mcintyre, French and Sherman",9.04,13448897,9.81,23.34,14876002,Q4 2021,78125638,GRIC
Reid-Becker,4.92,36172810,21.94,12.02,18464317,Q4 2020,4105232,UTHL
"Patel, Webb and Erickson",6.47,14114733,12.06,11.9,8481942,Q4 2021,38608650,ZGNN
West Inc,8.83,31089765,18.47,8.17,13547925,Q4 2023,41163290,ETSU
Long-Jones,9.42,47270220,12.67,14.44,11156249,Q4 2023,96271641,SBRJ

[Assistant]
Approach:
1. Task: Convert financial report from CSV 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:
company: Mcintyre, French and Sherman
ticker: GRIC
quarter: Q4 2021
revenue: 78125638
expenses: 13448897
net_income: 14876002
eps: 9.04
metrics:
  profit_margin: 9.81
  roe: 23.34


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

[User] Create a JSON representation of news article.

[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-8846154",
  "headline": "Phased bifurcated instruction set",
  "author": "Melanie Kennedy",
  "published": "2026-01-02T14:27:49.190328",
  "section": "Sports",
  "content": "Edge wear coach whether dog sell respond. Claim feeling meeting somebody four real.\nIndeed use send represent leader require. Cup attack instead discuss. Plan with character rule.\nInformation mind company even serve. Experience pattern but certain she design speech.",
  "tags": [
    "memory",
    "score",
    "game",
    "join"
  ],
  "views": 47684,
  "shares": 4081
}


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

[User] Generate financial report data in CSV format.

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

Output:
company,eps,expenses,metrics_profit_margin,metrics_roe,net_income,quarter,revenue,ticker
"Mcintyre, French and Sherman",9.04,13448897,9.81,23.34,14876002,Q4 2021,78125638,GRIC
Jordan Inc,2.2,15183757,19.41,9.53,18628732,Q4 2021,5531913,JRVD
Andrews and Sons,3.73,49610028,12.69,14.66,818990,Q2 2020,9288010,JTTG


[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-4278484</rx_id>
<patient_mrn>MRN-990980</patient_mrn>
<prescriber>Andrew Kelly</prescriber>
<date>2026-01-06</date>
<medications>
<name>Metformin</name>
<dosage>10mg</dosage>
<frequency>BID</frequency>
<quantity>30</quantity>
</medications>
<medications>
<name>Atorvastatin</name>
<dosage>10mg</dosage>
<frequency>BID</frequency>
<quantity>90</quantity>
</medications>
</prescription>

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

Output:
{
  "rx_id": "RX-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 TOML format. Think step-by-step, then generate syntactically perfect TOML.

[User] Produce a TOML document for a contract.

[Assistant]
Approach:
1. Task: Create contract 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:
contract_id = "CTR-544771"
effective_date = "2026-01-02"
term_months = 52
value = 394049
status = "active"
[[parties]]
name = "Prince-Finley"
role = "party_a"

[[parties]]
name = "Stone LLC"
role = "party_b"


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

[User] Output experiment result as CSV.

[Assistant]
Approach:
1. Task: Create experiment result 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:
conclusion,experiment_id,methodology_design,methodology_duration_days,methodology_sample_size,results,title
non-significant,EXP-690622,RCT,247,718,"[{""metric"": ""efficacy"", ""baseline"": 65.65, ""endpoint"": 47.19, ""p_value"": 0.4009}, {""metric"": ""effica",Effect of drug on effect
significant,EXP-691414,observational,126,197,"[{""metric"": ""safety"", ""baseline"": 25.53, ""endpoint"": 54.96, ""p_value"": 0.394}, {""metric"": ""efficacy""",Effect of wonder on attack
non-significant,EXP-698371,observational,228,345,"[{""metric"": ""efficacy"", ""baseline"": 94.15, ""endpoint"": 43.76, ""p_value"": 0.1696}, {""metric"": ""effica",Effect of remain on among


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

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

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

Output:
{
  "course_id": "CRS-9368",
  "percentage": 68.59,
  "assessment_id": "ASMT-453812",
  "scores": [
    {
      "question": 1,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 3,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 0,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 6,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 9,
      "points_earned": 5,
      "points_possible": 10
    },
    {
      "question": 10,
      "points_earned": 0,
      "points_possible": 10
    },
    {
      "question": 11,
      "points_earned": 2,
      "points_possible": 10
    }
  ]
}


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

[User] Produce a JSON document for a prescription.

[Assistant]
Approach:
1. Task: Create prescription 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:
{
  "rx_id": "RX-5160762",
  "patient_mrn": "MRN-568012",
  "prescriber": "Linda Gonzalez",
  "date": "2026-01-06",
  "medications": [
    {
      "name": "Lisinopril",
      "dosage": "20mg",
      "frequency": "TID",
      "quantity": 30
    },
    {
      "name": "Atorvastatin",
      "dosage": "5mg",
      "frequency": "daily",
      "quantity": 60
    }
  ]
}


[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>July 2021</period>
<total_revenue>5979422</total_revenue>
<units_sold>82076</units_sold>
<channels>
<name>retail</name>
<revenue>3460112</revenue>
<growth>36.85</growth>
</channels>
<channels>
<name>online</name>
<revenue>3983364</revenue>
<growth>5.55</growth>
</channels>
<top_products>
<sku>SKU-1065</sku>
<sales>105510</sales>
</top_products>
<top_products>
<sku>SKU-4043</sku>
<sales>281142</sales>
</top_products>
<top_products>
<sku>SKU-1338</sku>
<sales>43006</sales>
</top_products>
</sales_analytics>

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

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