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

[User] Output api specification as CSV.

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

Output:
abstract,authors,citations,funding_source,info_title,info_version,keywords,openapi,paper_id,paths_/anything_get_parameters,paths_/anything_get_responses_200_description,paths_/anything_get_responses_400_description,paths_/anything_get_summary,publication_doi,publication_venue,publication_year,title
,,,,Sharable solution-oriented migration API,1.0.0,,3.0.0,,"[{""name"": ""param0"", ""in"": ""query"", ""type"": ""string""}, {""name"": ""param1"", ""in"": ""query"", ""type"": ""str",Success,Bad Request,Those all evidence respond she listen.,,,,
Challenge business necessary society result reality. He ago work than focus. Provide future knowledg,"[{""name"": ""Dawn Garcia"", ""affiliation"": ""Walter PLC"", ""email"": ""zramirez@example.com""}, {""name"": ""Jo",494,None,,,"[""strong"", ""administration"", ""big"", ""be"", ""change""]",,arXiv:2024.73589,,,,,10.8263/xHEH,Nature,2020,Stand-alone mission-critical circuit
Fact never recently sign late star case. Should real language. Growth which key industry piece last.,"[{""name"": ""Craig Lane"", ""affiliation"": ""Lynch LLC"", ""email"": ""jnorton@example.com""}, {""name"": ""Jane ",354,Jenkins-Smith,,,"[""full"", ""within"", ""here"", ""can"", ""fill""]",,arXiv:2024.66351,,,,,10.4021/aHrl,Cell,2024,Re-contextualized intermediate implementation
Foreign experience society best treatment sure. Place culture ability which. Popular voice most foll,"[{""name"": ""John Galloway"", ""affiliation"": ""Parks, Collins and Dean"", ""email"": ""christine09@example.n",188,None,,,"[""politics"", ""enter"", ""tax"", ""month""]",,arXiv:2024.97009,,,,,10.2498/Hgrd,Nature,2022,Focused 24hour migration


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

[User] Create a CSV representation of lab result.

[Assistant]
Approach:
1. Task: Create lab result in CSV
2. Complexity: 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:
order_date,panel,patient_mrn,result_id,results
2026-01-05,CBC,MRN-887521,LAB-5387789,"[{""test"": ""WBC"", ""value"": 66.6, ""unit"": ""mg/dL"", ""flag"": ""normal""}, {""test"": ""Glucose"", ""value"": 111"
2026-01-02,CBC,MRN-585936,LAB-4433305,"[{""test"": ""Hemoglobin"", ""value"": 61.7, ""unit"": ""mg/dL"", ""flag"": ""normal""}, {""test"": ""WBC"", ""value"": "
2026-01-05,CBC,MRN-405052,LAB-2396583,"[{""test"": ""WBC"", ""value"": 181.2, ""unit"": ""mg/dL"", ""flag"": ""low""}, {""test"": ""Hemoglobin"", ""value"": 18"


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

[User] Create a JSON representation of product listing.

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

Output:
{
  "product_id": "PROD-597223",
  "name": "Proactive tertiary database",
  "category": "books",
  "price": 435.77,
  "currency": "USD",
  "stock": 111,
  "is_available": true,
  "rating": 1.73,
  "reviews": 539,
  "specs": {
    "weight_kg": 19.61,
    "dimensions": "87x91x85cm"
  }
}


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

[User]
Convert the following YAML to XML:
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

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

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


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

[User]
Transform this JSON data into XML format:
{
  "openapi": "3.0.0",
  "info": {
    "title": "Business-focused zero administration encryption API",
    "version": "1.0.0"
  },
  "paths": {
    "/teach": {
      "get": {
        "summary": "Government trade direction personal reason hundred",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          },
          {
            "name": "param1",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  }
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Business-focused zero administration encryption API</title>
<version>1.0.0</version>
</info>
<paths>
</teach>
<get>
<summary>Government trade direction personal reason hundred</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>
<//teach>
</paths>
</api_specification>


[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:
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"

[Assistant]
Approach:
1. Task: Convert product listing 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"?>
<product_listing>
<product_id>PROD-480886</product_id>
<name>Operative optimizing monitoring</name>
<category>books</category>
<price>967.35</price>
<currency>USD</currency>
<stock>887</stock>
<is_available>True</is_available>
<rating>2.99</rating>
<reviews>465</reviews>
<specs>
<weight_kg>39.19</weight_kg>
<dimensions>82x84x37cm</dimensions>
</specs>
</product_listing>


[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-353280</assessment_id>
<student_id>STU-259399</student_id>
<course_id>CRS-9241</course_id>
<type>quiz</type>
<date>2026-01-05</date>
<scores>
<question>1</question>
<points_earned>4</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>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>4</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>7</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>4</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>9</question>
<points_earned>3</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>10</question>
<points_earned>7</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>11</question>
<points_earned>7</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>12</question>
<points_earned>0</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>13</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>68</total_score>
<percentage>88.23</percentage>
<grade>C</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-353280",
  "student_id": "STU-259399",
  "course_id": "CRS-9241",
  "type": "quiz",
  "date": "2026-01-05",
  "scores": [
    {
      "question": 1,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 6,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 0,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 9,
      "points_earned": 3,
      "points_possible": 10
    },
    {
      "question": 10,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 11,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 12,
      "points_earned": 0,
      "points_possible": 10
    },
    {
      "question": 13,
      "points_earned": 2,
      "points_possible": 10
    }
  ],
  "total_score": 68,
  "percentage": 88.23,
  "grade": "C"
}


[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: 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:
{
  "article_id": "ART-9801838",
  "headline": "Multi-lateral didactic encryption",
  "author": "Jeffrey Gordon",
  "published": "2026-01-04T05:36:27.140251",
  "section": "Business",
  "content": "Partner energy whose simply half because long. Pattern include thousand care four against.\nScene center certainly letter already rate among. Do amount account court term same.\nStep usually ground onto study myself.",
  "tags": [
    "word",
    "public",
    "near"
  ],
  "views": 26731,
  "shares": 4423
}


[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"?>
<prescription>
<rx_id>RX-7309915</rx_id>
<patient_mrn>MRN-389849</patient_mrn>
<prescriber>Briana Dickerson</prescriber>
<date>2026-01-03</date>
<medications>
<name>Metformin</name>
<dosage>20mg</dosage>
<frequency>daily</frequency>
<quantity>30</quantity>
</medications>
</prescription>

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

Output:
{
  "rx_id": "RX-7309915",
  "patient_mrn": "MRN-389849",
  "prescriber": "Briana Dickerson",
  "date": "2026-01-03",
  "medications": [
    {
      "name": "Metformin",
      "dosage": "20mg",
      "frequency": "daily",
      "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"?>
<product_listing>
<product_id>PROD-210763</product_id>
<name>Team-oriented grid-enabled support</name>
<category>clothing</category>
<price>360.14</price>
<currency>USD</currency>
<stock>657</stock>
<is_available>True</is_available>
<rating>3.34</rating>
<reviews>923</reviews>
<specs>
<weight_kg>14.15</weight_kg>
<dimensions>28x80x26cm</dimensions>
</specs>
</product_listing>

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

Output:
{
  "product_id": "PROD-210763",
  "name": "Team-oriented grid-enabled support",
  "category": "clothing",
  "price": 360.14,
  "currency": "USD",
  "stock": 657,
  "is_available": true,
  "rating": 3.34,
  "reviews": 923,
  "specs": {
    "weight_kg": 14.15,
    "dimensions": "28x80x26cm"
  }
}


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

[User] Output social media post as XML.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<social_media_post>
<post_id>POST-33796851</post_id>
<platform>instagram</platform>
<user_id>aa32cdd3-72c6-4e38-bd5e-ff3918321d73</user_id>
<username>qtownsend</username>
<content>List floor whatever fly. Play represent five my. Stuff area push other begin team. Wind leg require represent.</content>
<timestamp>2026-01-07T13:51:26.038556</timestamp>
<hashtags>#study</hashtags>
<hashtags>#able</hashtags>
<hashtags>#week</hashtags>
<engagement>
<likes>3006</likes>
<shares>53</shares>
<comments>61</comments>
</engagement>
</social_media_post>


[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"?>
<experiment_result>
<experiment_id>EXP-883806</experiment_id>
<title>Effect of there on wife</title>
<methodology>
<design>observational</design>
<sample_size>200</sample_size>
<duration_days>32</duration_days>
</methodology>
<results>
<metric>efficacy</metric>
<baseline>15.64</baseline>
<endpoint>83.3</endpoint>
<p_value>0.4248</p_value>
</results>
<results>
<metric>efficacy</metric>
<baseline>36.36</baseline>
<endpoint>63.05</endpoint>
<p_value>0.0775</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-883806",
  "title": "Effect of there on wife",
  "methodology": {
    "design": "observational",
    "sample_size": 200,
    "duration_days": 32
  },
  "results": [
    {
      "metric": "efficacy",
      "baseline": 15.64,
      "endpoint": 83.3,
      "p_value": 0.4248
    },
    {
      "metric": "efficacy",
      "baseline": 36.36,
      "endpoint": 63.05,
      "p_value": 0.0775
    }
  ],
  "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: 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 = "234c0781-6e40-4e46-8b0d-ad1b39309eb0"
timestamp = "2026-01-07T13:51:25.659911"
level = "WARNING"
service = "beyondService"
message = "Section material entire top community."
stack_trace = [ "at reason.py:320", "at always.py:365", "at red.py:27",]

[context]
user_id = "6765bd92-f82e-426f-a383-fa0a088a0752"
request_id = "4ccfb0b5-8185-4d26-902a-0379b3534400"


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

[User]
Transform this JSON data into XML format:
{
  "review_id": "REV-8549692",
  "product_id": "PROD-108019",
  "user_id": "a4c4fbe3-7a0e-49f5-b14b-2ab1ca2d6ed5",
  "rating": 4,
  "title": "Development know write believe teacher ability.",
  "content": "Guy generation provide economy test bit. Page cost and.\nArm test ok green. Likely card reality school stop something those.\nYour spend discuss yeah hear. Same language box us magazine simple.",
  "date": "2026-01-06",
  "verified_purchase": true,
  "helpful_votes": 22
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<review_id>REV-8549692</review_id>
<product_id>PROD-108019</product_id>
<user_id>a4c4fbe3-7a0e-49f5-b14b-2ab1ca2d6ed5</user_id>
<rating>4</rating>
<title>Development know write believe teacher ability.</title>
<content>Guy generation provide economy test bit. Page cost and.
Arm test ok green. Likely card reality school stop something those.
Your spend discuss yeah hear. Same language box us magazine simple.</content>
<date>2026-01-06</date>
<verified_purchase>True</verified_purchase>
<helpful_votes>22</helpful_votes>
</customer_review>


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

[User] Generate student assessment data in XML format.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<student_assessment>
<assessment_id>ASMT-577861</assessment_id>
<student_id>STU-664280</student_id>
<course_id>CRS-8099</course_id>
<type>exam</type>
<date>2026-01-06</date>
<scores>
<question>1</question>
<points_earned>7</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>5</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>6</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>3</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>0</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>52</total_score>
<percentage>81.98</percentage>
<grade>B</grade>
</student_assessment>


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

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

[Assistant]
Approach:
1. Task: Create research paper in YAML
2. Complexity: 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:
publication:
  venue: Cell
  year: 2021
  doi: 10.3653/hXNF
funding_source: Kramer Ltd
title: Configurable bandwidth-monitored strategy
authors:
- name: James Brown
  affiliation: Ward-Davidson
  email: wilsonkristin@example.org
- name: Luke Liu
  affiliation: Obrien-Huynh
  email: jason08@example.org
- name: Paula Gonzalez
  affiliation: Jones-Howell
  email: brent41@example.org


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

[User] Output customer review as TOML.

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

Output:
review_id = "REV-3982215"
product_id = "PROD-143836"
user_id = "0dd51960-e54b-4127-90d4-b32b17839969"
rating = 2
title = "Fight and building toward office."
content = "Hear media safe I visit language. Difference part thousand. Society inside describe decision."
date = "2026-01-06"
verified_purchase = true
helpful_votes = 16


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

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

[Assistant]
Approach:
1. Task: Create social media post 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"?>
<social_media_post>
<post_id>POST-66277640</post_id>
<platform>instagram</platform>
<user_id>7e83a029-16e2-49ad-a855-906c882abe46</user_id>
<username>reynoldstaylor</username>
<content>Thousand book animal myself wear beautiful. Room rock couple reality her.
Join town travel agency value improve way. Heavy late science mind develop consider ability.</content>
<timestamp>2026-01-07T13:51:26.676406</timestamp>
<hashtags>#case</hashtags>
<hashtags>#along</hashtags>
<hashtags>#only</hashtags>
<hashtags>#have</hashtags>
<engagement>
<likes>9942</likes>
<shares>119</shares>
<comments>368</comments>
</engagement>
</social_media_post>


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

[User]
Convert the following CSV to YAML:
category,currency,is_available,name,price,product_id,rating,reviews,specs_dimensions,specs_weight_kg,stock
books,USD,True,Decentralized heuristic migration,124.58,PROD-791864,3.59,538,30x16x25cm,9.83,601
books,USD,True,Multi-lateral needs-based data-warehouse,947.53,PROD-386548,3.69,587,63x53x28cm,43.49,619
clothing,USD,True,Business-focused asymmetric methodology,467.54,PROD-845071,3.78,904,74x85x88cm,33.97,927

[Assistant]
Approach:
1. Task: Convert product listing 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:
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]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<lab_result>
<patient_mrn>MRN-135092</patient_mrn>
<order_date>2026-01-02</order_date>
<panel>CBC</panel>
<results>
<test>Hemoglobin</test>
<value>129.6</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>120.7</value>
<unit>mg/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>141.8</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>131.3</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Glucose</test>
<value>147.1</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<result_id>LAB-9224780</result_id>
</lab_result>

[Assistant]
Approach:
1. Task: Convert lab result 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:
{
  "patient_mrn": "MRN-135092",
  "order_date": "2026-01-02",
  "panel": "CBC",
  "results": [
    {
      "test": "Hemoglobin",
      "value": 129.6,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "Hemoglobin",
      "value": 120.7,
      "unit": "mg/dL",
      "flag": "low"
    },
    {
      "test": "Hemoglobin",
      "value": 141.8,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "Hemoglobin",
      "value": 131.3,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "Glucose",
      "value": 147.1,
      "unit": "mg/dL",
      "flag": "high"
    }
  ],
  "result_id": "LAB-9224780"
}


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

[User] Create a JSON representation of customer review.

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

Output:
{
  "review_id": "REV-2971879",
  "product_id": "PROD-601177",
  "user_id": "49ec79ac-cc63-409f-8812-a70c492b6835",
  "rating": 3,
  "title": "Safe everything country understand subject.",
  "content": "Explain among above role speech. Hear law enjoy. Lose building fall everything million.\nEast choose however class dark test good contain. Indicate worker mean hot.",
  "date": "2026-01-06",
  "verified_purchase": true,
  "helpful_votes": 67
}


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

[User] Output product listing as XML.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<product_listing>
<product_id>PROD-308726</product_id>
<name>Cross-platform client-server attitude</name>
<category>electronics</category>
<price>875.12</price>
<currency>USD</currency>
<stock>161</stock>
<is_available>True</is_available>
<rating>1.18</rating>
<reviews>705</reviews>
<specs>
<weight_kg>37.34</weight_kg>
<dimensions>78x81x41cm</dimensions>
</specs>
</product_listing>


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<student_assessment>
<assessment_id>ASMT-350362</assessment_id>
<student_id>STU-421536</student_id>
<course_id>CRS-1231</course_id>
<type>exam</type>
<date>2026-01-01</date>
<scores>
<question>1</question>
<points_earned>2</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>8</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>8</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>8</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>6</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>5</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>9</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>10</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>11</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>51</total_score>
<percentage>80.6</percentage>
<grade>A</grade>
</student_assessment>

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

Output:
{
  "assessment_id": "ASMT-350362",
  "student_id": "STU-421536",
  "course_id": "CRS-1231",
  "type": "exam",
  "date": "2026-01-01",
  "scores": [
    {
      "question": 1,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 6,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 5,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 9,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 10,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 11,
      "points_earned": 9,
      "points_possible": 10
    }
  ],
  "total_score": 51,
  "percentage": 80.6,
  "grade": "A"
}


[System] You are an expert in 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"?>
<news_article>
<content>Capital way what customer unit skill. Arm bar occur article mouth enjoy. Exactly approach mention single.
Strong who against entire.
Kid television artist dream back agency. Need main ago investment job behavior.</content>
<published>2026-01-03T04:54:27.964292</published>
<views>73181</views>
<headline>Vision-oriented analyzing groupware</headline>

Business

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


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

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

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

Output:
period: February 2020
total_revenue: 2337421
units_sold: 23839
channels:
- name: retail
  revenue: 3840938
  growth: 18.52
- name: wholesale
  revenue: 1512471
  growth: 13.02
top_products:
- sku: SKU-1744
  sales: 276633
- sku: SKU-5145
  sales: 26445
- sku: SKU-9218
  sales: 412054


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

[User]
Reformat the data below from CSV to JSON:
assessment,chief_complaint,encounter_date,note_id,patient_age,patient_gender,patient_mrn,vitals_bp,vitals_hr,vitals_temp_f
"[{""problem"": ""diabetes"", ""icd10"": ""I93""}]",headache,2026-01-05,CN-5751204,47,M,MRN-566004,160/96,75,102.4
"[{""problem"": ""hypertension"", ""icd10"": ""I43""}, {""problem"": ""hypertension"", ""icd10"": ""K19""}]",chest pain,2026-01-03,CN-5247630,18,M,MRN-928754,101/99,65,97.9
"[{""problem"": ""hypertension"", ""icd10"": ""J13""}, {""problem"": ""hypertension"", ""icd10"": ""I47""}]",chest pain,2026-01-06,CN-3352178,66,F,MRN-233461,151/80,99,97.7
"[{""problem"": ""hypertension"", ""icd10"": ""I62""}, {""problem"": ""diabetes"", ""icd10"": ""I20""}, {""problem"": """,headache,2026-01-03,CN-3393992,87,F,MRN-401400,125/88,110,102.5

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

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

[User] Generate sales analytics data in JSON format.

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

Output:
{
  "period": "June 2021",
  "total_revenue": 4317671,
  "units_sold": 11582,
  "channels": [
    {
      "name": "wholesale",
      "revenue": 2780960,
      "growth": 22.76
    },
    {
      "name": "retail",
      "revenue": 4140341,
      "growth": -9.84
    }
  ],
  "top_products": [
    {
      "sku": "SKU-8636",
      "sales": 261407
    },
    {
      "sku": "SKU-9950",
      "sales": 107242
    },
    {
      "sku": "SKU-8311",
      "sales": 494004
    }
  ]
}


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

[User] Create a XML representation of customer review.

[Assistant]
Approach:
1. Task: Create customer review in XML
2. Complexity: 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"?>
<customer_review>
<review_id>REV-9982202</review_id>
<product_id>PROD-452864</product_id>
<user_id>015289de-7f3e-45e2-b1d0-7fe22aff92a9</user_id>
<rating>3</rating>
<title>Example center fill free.</title>
<content>North describe old attention usually third. Important wish security ago somebody remain everyone modern. Significant chair place throughout study administration American.</content>
<date>2026-01-04</date>
<verified_purchase>False</verified_purchase>
<helpful_votes>34</helpful_votes>
</customer_review>


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

[User] Generate course syllabus data in XML format.

[Assistant]
Approach:
1. Task: Create course syllabus 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"?>
<course_syllabus>
<course_id>CRS-6496</course_id>
TMG245
<instructor>Maria Bowers</instructor>
<schedule>
<week>1</week>
<topic>situation</topic>
</schedule>
<schedule>
<week>2</week>
<topic>firm</topic>
</schedule>
<schedule>
<week>3</week>
<topic>involve</topic>
</schedule>
<schedule>
<week>4</week>
<topic>change</topic>
</schedule>
<schedule>
<week>5</week>
<topic>yard</topic>
</schedule>
<schedule>
<week>6</week>
<topic>morning</topic>
</schedule>
<schedule>
<week>7</week>
<topic>other</topic>
</schedule>
<schedule>
<week>8</week>
<topic>left</topic>
</schedule>
</course_syllabus>


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

[User] Output sales analytics as TOML.

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

Output:
period = "June 2021"
total_revenue = 4317671
units_sold = 11582
[[channels]]
name = "wholesale"
revenue = 2780960
growth = 22.76

[[channels]]
name = "retail"
revenue = 4140341
growth = -9.84

[[top_products]]
sku = "SKU-8636"
sales = 261407

[[top_products]]
sku = "SKU-9950"
sales = 107242

[[top_products]]
sku = "SKU-8311"
sales = 494004


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

[User] Output course syllabus as XML.

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


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

[User]
Convert the following JSON to XML:
{
  "product_id": "PROD-524008",
  "name": "Implemented multimedia focus group",
  "category": "electronics",
  "price": 524.9,
  "currency": "USD",
  "stock": 714,
  "is_available": true,
  "rating": 2.56,
  "reviews": 633,
  "specs": {
    "weight_kg": 40.1,
    "dimensions": "80x44x77cm"
  }
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<product_listing>
<product_id>PROD-524008</product_id>
<name>Implemented multimedia focus group</name>
<category>electronics</category>
<price>524.9</price>
<currency>USD</currency>
<stock>714</stock>
<is_available>True</is_available>
<rating>2.56</rating>
<reviews>633</reviews>
<specs>
<weight_kg>40.1</weight_kg>
<dimensions>80x44x77cm</dimensions>
</specs>
</product_listing>


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

[User]
Convert the following CSV to TOML:
date,medications,patient_mrn,prescriber,rx_id
2026-01-03,"[{""name"": ""Lisinopril"", ""dosage"": ""10mg"", ""frequency"": ""daily"", ""quantity"": 90}, {""name"": ""Metformin",MRN-446802,James Bryant,RX-8350891
2026-01-01,"[{""name"": ""Metformin"", ""dosage"": ""5mg"", ""frequency"": ""BID"", ""quantity"": 90}]",MRN-449837,Billy Ford,RX-1000213
2026-01-05,"[{""name"": ""Metformin"", ""dosage"": ""20mg"", ""frequency"": ""BID"", ""quantity"": 90}, {""name"": ""Atorvastatin",MRN-278651,Tyler Reed,RX-6346758
2026-01-02,"[{""name"": ""Metformin"", ""dosage"": ""20mg"", ""frequency"": ""TID"", ""quantity"": 60}]",MRN-973582,Dr. Jennifer Castillo MD,RX-6195384

[Assistant]
Approach:
1. Task: Convert prescription from CSV 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:
rx_id = "RX-8350891"
patient_mrn = "MRN-446802"
prescriber = "James Bryant"
date = "2026-01-03"
[[medications]]
name = "Lisinopril"
dosage = "10mg"
frequency = "daily"
quantity = 90

[[medications]]
name = "Metformin"
dosage = "20mg"
frequency = "TID"
quantity = 30


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

[User] Output clinical note as JSON.

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


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

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

[Assistant]
Approach:
1. Task: Create social media post 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"?>
<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>


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

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

[Assistant]
Approach:
1. Task: Create student assessment in TOML
2. Complexity: 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:
course_id = "CRS-9368"
percentage = 68.59
assessment_id = "ASMT-453812"
[[scores]]
question = 1
points_earned = 2
points_possible = 10

[[scores]]
question = 2
points_earned = 3
points_possible = 10

[[scores]]
question = 3
points_earned = 0
points_possible = 10

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

[[scores]]
question = 5
points_earned = 6
points_possible = 10

[[scores]]
question = 6
points_earned = 9
points_possible = 10

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

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

[[scores]]
question = 9
points_earned = 5
points_possible = 10

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

[[scores]]
question = 11
points_earned = 2
points_possible = 10


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

[User] Generate prescription data in TOML format.

[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-9036427"
patient_mrn = "MRN-461250"
prescriber = "Zachary Berry"
date = "2026-01-01"
[[medications]]
name = "Atorvastatin"
dosage = "5mg"
frequency = "daily"
quantity = 30


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

[User] Generate student assessment data in TOML format.

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

Output:
assessment_id = "ASMT-996269"
student_id = "STU-878254"
course_id = "CRS-8988"
type = "exam"
date = "2026-01-03"
total_score = 71
percentage = 94.86
grade = "B"
[[scores]]
question = 1
points_earned = 8
points_possible = 10

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

[[scores]]
question = 3
points_earned = 8
points_possible = 10

[[scores]]
question = 4
points_earned = 2
points_possible = 10

[[scores]]
question = 5
points_earned = 7
points_possible = 10

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

[[scores]]
question = 7
points_earned = 9
points_possible = 10

[[scores]]
question = 8
points_earned = 7
points_possible = 10

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

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


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

[User] Generate course syllabus data in YAML format.

[Assistant]
Approach:
1. Task: Create course syllabus 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:
course_id: CRS-3440
code: KLD251
title: Reverse-engineered foreground infrastructure 101
instructor: Courtney Escobar
credits: 4
term: Spring 2022
schedule:
- week: 1
  topic: despite
- week: 2
  topic: choose
- week: 3
  topic: action
- week: 4
  topic: couple
- week: 5
  topic: big
- week: 6
  topic: trade
- week: 7
  topic: measure
- week: 8
  topic: music
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]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<student_assessment>
<assessment_id>ASMT-852879</assessment_id>
<student_id>STU-517758</student_id>
<course_id>CRS-9070</course_id>
<type>exam</type>
<date>2026-01-04</date>
<scores>
<question>1</question>
<points_earned>4</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>1</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>3</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>10</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>9</question>
<points_earned>7</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>10</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>11</question>
<points_earned>6</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>12</question>
<points_earned>8</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>58</total_score>
<percentage>53.23</percentage>
<grade>C</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-852879",
  "student_id": "STU-517758",
  "course_id": "CRS-9070",
  "type": "exam",
  "date": "2026-01-04",
  "scores": [
    {
      "question": 1,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 10,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 3,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 10,
      "points_possible": 10
    },
    {
      "question": 9,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 10,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 11,
      "points_earned": 6,
      "points_possible": 10
    },
    {
      "question": 12,
      "points_earned": 8,
      "points_possible": 10
    }
  ],
  "total_score": 58,
  "percentage": 53.23,
  "grade": "C"
}


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

[User] Create a YAML representation of customer review.

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

Output:
review_id: REV-5650887
product_id: PROD-601157
user_id: ac7725ae-2567-44d1-8d40-a64432b9801b
rating: 3
title: Personal order single check off but my.
content: 'Key Mrs say because walk old certainly. Product figure event choice.

  Skill cut plan per side same. Between common join partner kid enter page discover.'
date: '2026-01-06'
verified_purchase: true
helpful_votes: 66


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

[User] Generate financial report data in JSON format.

[Assistant]
Approach:
1. Task: Create financial report in JSON
2. Complexity: 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": "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 TOML format. Think step-by-step, then generate syntactically perfect TOML.

[User] Create a TOML representation of course syllabus.

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

Output:
course_id = "CRS-4765"
code = "VMZ479"
title = "Exclusive grid-enabled software 101"
instructor = "Amy Baker"
credits = 4
term = "Fall 2022"
[[schedule]]
week = 1
topic = "show"

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

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

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

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

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

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

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


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<news_article>
<article_id>ART-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>


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<error_log>
<error_id>8ef553f5-74fa-47eb-bfcb-571b6fa73c35</error_id>
<timestamp>2026-01-07T13:51:27.105544</timestamp>
<level>WARNING</level>
<service>radioService</service>
<message>Professional pull soon.</message>
<stack_trace>at eye.py:220</stack_trace>
<stack_trace>at short.py:148</stack_trace>
<stack_trace>at the.py:448</stack_trace>
<context>
<user_id>162209b9-e3ae-4c7a-af39-f96af44cdcaa</user_id>
<request_id>a05e806a-f592-4611-8d80-dbe2773bec40</request_id>
</context>
</error_log>


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

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

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

Output:
review_id: REV-1132090
product_id: PROD-380257
user_id: 251dc214-da1e-4fb5-8ea5-d107ad43f82c
rating: 4
title: Young race true property less government.
content: 'Brother agent radio might own development. Too strong minute building why.
  Cell so amount imagine simple.

  Court every deal change allow last practice. Western far thus.'
date: '2026-01-03'
verified_purchase: false
helpful_votes: 14


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

[User] Create a YAML representation of transaction record.

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

Output:
txn_id: TXN-23430167
customer_id: 7fb2e914-3f0f-4c3f-abb9-ef22ed2c1064
timestamp: '2026-01-07T13:51:26.046328'
items:
- sku: SKU-63492
  qty: 1
  price: 90.17
- sku: SKU-56350
  qty: 5
  price: 336.79
subtotal: 152.9
tax: 14.6
total: 796.85
payment_method: apple_pay


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

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

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

Output:
post_id: POST-86945311
platform: facebook
user_id: b9da037c-f6cd-4ced-8c95-ca7562cf6118
username: martinsteven
content: Forget late prevent year cold able arrive. Few possible himself sing community.
  Activity campaign sure south. Chance on none line best magazine education.
timestamp: '2026-01-07T13:51:26.810240'
hashtags:
- '#drop'
- '#consider'
- '#nature'
- '#all'
engagement:
  likes: 3344
  shares: 900
  comments: 482


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

[User]
Reformat the data below from JSON to XML:
{
  "openapi": "3.0.0",
  "info": {
    "title": "Stand-alone dedicated complexity API",
    "version": "1.0.0"
  },
  "paths": {
    "/hear": {
      "get": {
        "summary": "Chance cultural sort including high.",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          },
          {
            "name": "param1",
            "in": "query",
            "type": "string"
          },
          {
            "name": "param2",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  }
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Stand-alone dedicated complexity API</title>
<version>1.0.0</version>
</info>
<paths>
</hear>
<get>
<summary>Chance cultural sort including high.</summary>
<parameters>
<name>param0</name>
<in>query</in>
<type>string</type>
</parameters>
<parameters>
<name>param1</name>
<in>query</in>
<type>string</type>
</parameters>
<parameters>
<name>param2</name>
<in>query</in>
<type>string</type>
</parameters>
<responses>
<200>
<description>Success</description>
</200>
<400>
<description>Bad Request</description>
</400>
</responses>
</get>
<//hear>
</paths>
</api_specification>


[System] You are an expert in 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: 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:
{
  "grade": "A",
  "course_id": "CRS-4519",
  "total_score": 75
}


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

[User] Generate api specification data in YAML format.

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

Output:
openapi: 3.0.0
info:
  title: Seamless disintermediate flexibility API
  version: 1.0.0
paths:
  /significant:
    get:
      summary: Box project skin day catch.
      parameters:
      - name: param0
        in: query
        type: string
      responses:
        '200':
          description: Success
        '400':
          description: Bad Request


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

[User]
Convert the following JSON to TOML:
{
  "result_id": "LAB-1056021",
  "patient_mrn": "MRN-977601",
  "order_date": "2026-01-02",
  "panel": "CMP",
  "results": [
    {
      "test": "WBC",
      "value": 124.0,
      "unit": "g/dL",
      "flag": "high"
    },
    {
      "test": "Hemoglobin",
      "value": 114.5,
      "unit": "g/dL",
      "flag": "high"
    },
    {
      "test": "WBC",
      "value": 70.6,
      "unit": "g/dL",
      "flag": "high"
    },
    {
      "test": "Glucose",
      "value": 119.6,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "Hemoglobin",
      "value": 171.0,
      "unit": "mg/dL",
      "flag": "normal"
    }
  ]
}

[Assistant]
Approach:
1. Task: Convert lab result 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:
result_id = "LAB-1056021"
patient_mrn = "MRN-977601"
order_date = "2026-01-02"
panel = "CMP"
[[results]]
test = "WBC"
value = 124.0
unit = "g/dL"
flag = "high"

[[results]]
test = "Hemoglobin"
value = 114.5
unit = "g/dL"
flag = "high"

[[results]]
test = "WBC"
value = 70.6
unit = "g/dL"
flag = "high"

[[results]]
test = "Glucose"
value = 119.6
unit = "mg/dL"
flag = "high"

[[results]]
test = "Hemoglobin"
value = 171.0
unit = "mg/dL"
flag = "normal"


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Implemented leadingedge groupware API</title>
<version>1.0.0</version>
</info>
<paths>
</reveal>
<get>
<summary>Parent dark five.</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>
<//reveal>
</paths>
</api_specification>


[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:
{
  "medications": [
    {
      "name": "Atorvastatin",
      "dosage": "5mg",
      "frequency": "BID",
      "quantity": 30
    }
  ],
  "prescriber": "Isaac Howard",
  "date": "2026-01-03"
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<prescription>
<medications>
<name>Atorvastatin</name>
<dosage>5mg</dosage>
<frequency>BID</frequency>
<quantity>30</quantity>
</medications>
<prescriber>Isaac Howard</prescriber>
<date>2026-01-03</date>
</prescription>


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

[User] Create a XML representation of experiment result.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<experiment_result>
<experiment_id>EXP-818679</experiment_id>
<title>Effect of begin on task</title>
<methodology>
<design>RCT</design>
<sample_size>180</sample_size>
<duration_days>157</duration_days>
</methodology>
<results>
<metric>safety</metric>
<baseline>17.77</baseline>
<endpoint>32.37</endpoint>
<p_value>0.477</p_value>
</results>
<results>
<metric>safety</metric>
<baseline>20.98</baseline>
<endpoint>13.84</endpoint>
<p_value>0.2984</p_value>
</results>
<conclusion>non-significant</conclusion>
</experiment_result>


[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"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Re-engineered mobile superstructure API</title>
<version>1.0.0</version>
</info>
<paths>
</benefit>
<get>
<summary>Chair media space recognize doctor would second me</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>
<//benefit>
</paths>
</api_specification>

[Assistant]
Approach:
1. Task: Convert api specification 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:
{
  "openapi": "3.0.0",
  "info": {
    "title": "Re-engineered mobile superstructure API",
    "version": "1.0.0"
  },
  "paths": {
    "/benefit": {
      "get": {
        "summary": "Chair media space recognize doctor would second me",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          },
          {
            "name": "param1",
            "in": "query",
            "type": "string"
          },
          {
            "name": "param2",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  }
}


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

[User] Create a JSON representation of experiment result.

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

Output:
{
  "experiment_id": "EXP-393268",
  "title": "Effect of themselves on time",
  "methodology": {
    "design": "RCT",
    "sample_size": 237,
    "duration_days": 116
  },
  "results": [
    {
      "metric": "efficacy",
      "baseline": 34.76,
      "endpoint": 73.98,
      "p_value": 0.4055
    },
    {
      "metric": "safety",
      "baseline": 70.26,
      "endpoint": 84.17,
      "p_value": 0.253
    },
    {
      "metric": "safety",
      "baseline": 22.1,
      "endpoint": 56.91,
      "p_value": 0.1172
    }
  ],
  "conclusion": "significant"
}


[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"?>
<prescription>
<rx_id>RX-5973418</rx_id>
<patient_mrn>MRN-615844</patient_mrn>
<prescriber>Brian Erickson</prescriber>
<date>2026-01-01</date>
<medications>
<name>Lisinopril</name>
<dosage>20mg</dosage>
<frequency>TID</frequency>
<quantity>60</quantity>
</medications>
<medications>
<name>Metformin</name>
<dosage>20mg</dosage>
<frequency>daily</frequency>
<quantity>60</quantity>
</medications>
</prescription>

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

Output:
{
  "rx_id": "RX-5973418",
  "patient_mrn": "MRN-615844",
  "prescriber": "Brian Erickson",
  "date": "2026-01-01",
  "medications": [
    {
      "name": "Lisinopril",
      "dosage": "20mg",
      "frequency": "TID",
      "quantity": 60
    },
    {
      "name": "Metformin",
      "dosage": "20mg",
      "frequency": "daily",
      "quantity": 60
    }
  ]
}


[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>
<company>Martinez, Patterson and Hunter</company>
<ticker>PPOB</ticker>
<quarter>Q1 2023</quarter>
<revenue>66694743</revenue>
<expenses>21448775</expenses>
<net_income>421192</net_income>
<eps>2.32</eps>
<metrics>
<profit_margin>7.89</profit_margin>
<roe>9.32</roe>
</metrics>
</financial_report>

[Assistant]
Approach:
1. Task: Convert financial report 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:
{
  "company": "Martinez, Patterson and Hunter",
  "ticker": "PPOB",
  "quarter": "Q1 2023",
  "revenue": 66694743,
  "expenses": 21448775,
  "net_income": 421192,
  "eps": 2.32,
  "metrics": {
    "profit_margin": 7.89,
    "roe": 9.32
  }
}


[System] You are an expert in 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
"Seven behavior less water pretty.
Rock key include. Kind than game agreement.
Paper position reduce ",393,1826,489,"[""#draw"", ""#five"", ""#culture"", ""#sport""]",twitter,POST-78526123,2026-01-07T13:51:27.460227,17596017-ad50-41af-8dc2-8746d15af00d,qsharp
Decide size enough. Third song authority name seven edge scene. Impact million owner result this eye,440,9818,50,"[""#career"", ""#throw"", ""#hard""]",instagram,POST-25740818,2026-01-07T13:51:27.461650,cda65398-b2f1-4c14-8c04-374518a3ba20,lambertevan
"Hotel on black lead. Interview purpose one early.
Century final drop left put line drive. Own car le",136,894,493,"[""#successful"", ""#reduce"", ""#stock"", ""#reveal""]",instagram,POST-14479605,2026-01-07T13:51:27.462051,1a769d3a-0b1e-45a6-a719-2b55db5204dc,figueroakevin
Wife debate agreement create score. Positive option remain strong interesting key. Food return menti,394,5576,127,"[""#forget"", ""#agreement"", ""#play"", ""#career""]",instagram,POST-89677781,2026-01-07T13:51:27.462363,e253954f-7fef-4401-abfe-544599172fea,bailey39


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

[User] Create a TOML representation of product listing.

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

Output:
product_id = "PROD-842353"
name = "Synergistic bottom-line conglomeration"
category = "books"
price = 609.49
currency = "USD"
stock = 399
is_available = true
rating = 1.05
reviews = 570

[specs]
weight_kg = 25.04
dimensions = "30x19x82cm"


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

[User]
Convert the following CSV to YAML:
assessment_id,code,course_id,credits,date,grade,grading_final,grading_homework,grading_midterm,instructor,percentage,schedule,scores,student_id,term,title,total_score,type
ASMT-996269,,CRS-8988,,2026-01-03,B,,,,,94.86,,"[{""question"": 1, ""points_earned"": 8, ""points_possible"": 10}, {""question"": 2, ""points_earned"": 0, ""po",STU-878254,,,71,exam
,GFN193,CRS-3494,4,,,40,30,30,Kelsey Gonzales,,"[{""week"": 1, ""topic"": ""class""}, {""week"": 2, ""topic"": ""eat""}, {""week"": 3, ""topic"": ""thought""}, {""week",,,Fall 2021,Secured motivating framework 101,,
,RSA346,CRS-3718,4,,,40,30,30,Jacob Hodges,,"[{""week"": 1, ""topic"": ""of""}, {""week"": 2, ""topic"": ""national""}, {""week"": 3, ""topic"": ""debate""}, {""wee",,,Fall 2020,Virtual composite conglomeration 101,,

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

Output:
assessment_id: ASMT-996269
student_id: STU-878254
course_id: CRS-8988
type: exam
date: '2026-01-03'
scores:
- question: 1
  points_earned: 8
  points_possible: 10
- question: 2
  points_earned: 0
  points_possible: 10
- question: 3
  points_earned: 8
  points_possible: 10
- question: 4
  points_earned: 2
  points_possible: 10
- question: 5
  points_earned: 7
  points_possible: 10
- question: 6
  points_earned: 3
  points_possible: 10
- question: 7
  points_earned: 9
  points_possible: 10
- question: 8
  points_earned: 7
  points_possible: 10
- question: 9
  points_earned: 2
  points_possible: 10
- question: 10
  points_earned: 3
  points_possible: 10
total_score: 71
percentage: 94.86
grade: B


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

[User] Generate customer review data in XML format.

[Assistant]
Approach:
1. Task: Create customer review in XML
2. Complexity: 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"?>
<customer_review>
<review_id>REV-9701957</review_id>
<product_id>PROD-683988</product_id>
<user_id>4d7f9754-e296-4a29-967f-5c8de166a17c</user_id>
<rating>5</rating>
<title>Teach look history according want manager perform.</title>
<content>Admit large politics decide might Mr their. Hundred play I deal but player leader old. Then similar drug coach.</content>
<date>2026-01-03</date>
<verified_purchase>False</verified_purchase>
<helpful_votes>36</helpful_votes>
</customer_review>


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

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

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

Output:
abstract,authors,citations,context_request_id,context_user_id,error_id,funding_source,keywords,level,message,paper_id,publication_doi,publication_venue,publication_year,service,stack_trace,timestamp,title
,,,454a35ad-23ee-42a8-9d57-dbf5cedbef74,473e683b-291e-461f-b848-d224b7dcbd8b,ff91c212-6cce-4ac2-978d-0740381882de,,,WARNING,Support red list product forget cut speak.,,,,,drawService,"[""at girl.py:186"", ""at hold.py:186""]",2026-01-07T13:51:27.679071,
"Training factor money enjoy either music. Heart four down finish. Individual dinner current west.
Ha","[{""name"": ""Kimberly Simpson"", ""affiliation"": ""Johnson-Valdez"", ""email"": ""mitchell94@example.com""}, {",319,,,,Roberts and Sons,"[""create"", ""industry"", ""will""]",,,arXiv:2020.96901,10.6701/IoSo,Nature,2022,,,,Robust executive paradigm
Produce everybody sit. Response several start star quality serious begin.,"[{""name"": ""Wendy Reed"", ""affiliation"": ""Adams-Butler"", ""email"": ""thomasbaxter@example.org""}, {""name""",172,,,,"Sutton, Anderson and Stuart","[""gas"", ""forward"", ""hear"", ""because""]",,,arXiv:2023.11247,10.1760/Fggq,Cell,2020,,,,Synergized solution-oriented hierarchy
Miss glass yes improve often central. Use career record country.,"[{""name"": ""Mary Spencer"", ""affiliation"": ""Ramirez and Sons"", ""email"": ""benjamin03@example.net""}, {""n",231,,,,None,"[""rock"", ""rise"", ""majority""]",,,arXiv:2022.97620,10.9693/VYcW,Cell,2020,,,,Optimized discrete software


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

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

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

Output:
assessment_id: ASMT-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


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

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

[Assistant]
Approach:
1. Task: Create customer review 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,content,currency,date,helpful_votes,is_available,name,price,product_id,rating,review_id,reviews,specs_dimensions,specs_weight_kg,stock,title,user_id,verified_purchase
,Suddenly plant stay thank project hand me. Commercial his road carry training trip.,,2026-01-02,3,,,,PROD-746934,4,REV-4787173,,,,,Rock company surface either million.,a1638e54-91af-4e5f-be10-465327f3fbf6,True
clothing,,USD,,,True,Multi-channeled systematic migration,990.03,PROD-696024,1.28,,996,23x32x55cm,25.57,658,,,
electronics,,USD,,,True,Persistent national hierarchy,572.53,PROD-233788,4.0,,442,40x22x12cm,32.32,164,,,
clothing,,USD,,,True,Horizontal uniform infrastructure,510.92,PROD-507888,4.95,,965,91x96x58cm,44.46,668,,,


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

[User] Create a YAML representation of sales analytics.

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

Output:
period: 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]
Transform this CSV data into XML format:
assessment,chief_complaint,encounter_date,note_id,patient_age,patient_gender,patient_mrn,vitals_bp,vitals_hr,vitals_temp_f
"[{""problem"": ""diabetes"", ""icd10"": ""J90""}, {""problem"": ""hypertension"", ""icd10"": ""I22""}, {""problem"": """,fever,2026-01-03,CN-6709459,50,M,MRN-104418,143/96,69,101.3
"[{""problem"": ""diabetes"", ""icd10"": ""K93""}, {""problem"": ""hypertension"", ""icd10"": ""K39""}, {""problem"": """,chest pain,2026-01-05,CN-2038769,19,F,MRN-764011,145/96,65,97.7
"[{""problem"": ""hypertension"", ""icd10"": ""K47""}, {""problem"": ""hypertension"", ""icd10"": ""I91""}]",chest pain,2026-01-03,CN-4758083,56,F,MRN-215899,101/72,60,101.8
"[{""problem"": ""hypertension"", ""icd10"": ""J64""}, {""problem"": ""hypertension"", ""icd10"": ""K58""}]",fever,2026-01-03,CN-9357487,38,M,MRN-728682,120/62,98,101.6
"[{""problem"": ""hypertension"", ""icd10"": ""J84""}]",chest pain,2026-01-01,CN-7990128,32,F,MRN-556057,177/76,120,97.5

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<clinical_note>
<note_id>CN-6709459</note_id>
<patient>
<mrn>MRN-104418</mrn>
<age>50</age>
<gender>M</gender>
</patient>
<encounter_date>2026-01-03</encounter_date>
<chief_complaint>fever</chief_complaint>
<vitals>
<bp>143/96</bp>

69

<temp_f>101.3</temp_f>
</vitals>
<assessment>
<problem>diabetes</problem>
<icd10>J90</icd10>
</assessment>
<assessment>
<problem>hypertension</problem>
<icd10>I22</icd10>
</assessment>
<assessment>
<problem>hypertension</problem>
<icd10>K97</icd10>
</assessment>
</clinical_note>


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

[User] Create a YAML representation of research paper.

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

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


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

Output:
{
  "assessment_id": "ASMT-350362",
  "student_id": "STU-421536",
  "course_id": "CRS-1231",
  "type": "exam",
  "date": "2026-01-01",
  "scores": [
    {
      "question": 1,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 6,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 5,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 9,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 10,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 11,
      "points_earned": 9,
      "points_possible": 10
    }
  ],
  "total_score": 51,
  "percentage": 80.6,
  "grade": "A"
}


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

[User]
Transform this CSV data into XML format:
code,course_id,credits,grading_final,grading_homework,grading_midterm,instructor,schedule,term,title
,CRS-8305,4,,,,Rachel Moreno DVM,,Spring 2023,Open-architected even-keeled support 101
SVL220,CRS-2673,4,40,30,30,Michael Fernandez,"[{""week"": 1, ""topic"": ""return""}, {""week"": 2, ""topic"": ""report""}, {""week"": 3, ""topic"": ""and""}, {""week",Spring 2022,Virtual foreground implementation 101
XYK360,CRS-8748,4,40,30,30,William Roberts,"[{""week"": 1, ""topic"": ""effect""}, {""week"": 2, ""topic"": ""sense""}, {""week"": 3, ""topic"": ""million""}, {""w",Spring 2020,Integrated dedicated middleware 101

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<course_syllabus>
<instructor>Rachel Moreno DVM</instructor>
<credits>4</credits>
<course_id>CRS-8305</course_id>
<title>Open-architected even-keeled support 101</title>
<term>Spring 2023</term>
</course_syllabus>


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

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

[Assistant]
Approach:
1. Task: Convert course syllabus from JSON to 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"?>
<course_syllabus>
<course_id>CRS-1797</course_id>
QAA477
<title>User-friendly composite interface 101</title>
<instructor>Selena Walker</instructor>
<credits>4</credits>
<term>Fall 2024</term>
<schedule>
<week>1</week>
<topic>all</topic>
</schedule>
<schedule>
<week>2</week>
<topic>education</topic>
</schedule>
<schedule>
<week>3</week>
<topic>will</topic>
</schedule>
<schedule>
<week>4</week>
<topic>operation</topic>
</schedule>
<schedule>
<week>5</week>
<topic>western</topic>
</schedule>
<schedule>
<week>6</week>
<topic>plan</topic>
</schedule>
<schedule>
<week>7</week>
<topic>allow</topic>
</schedule>
<grading>
<homework>30</homework>
<midterm>30</midterm>
<final>40</final>
</grading>
</course_syllabus>


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

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

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

Output:
assessment,chief_complaint,encounter_date,note_id,patient_age,patient_gender,patient_mrn,vitals_bp,vitals_hr,vitals_temp_f
"[{""problem"": ""hypertension"", ""icd10"": ""J46""}]",headache,2026-01-03,CN-1129442,79,M,MRN-895859,127/81,117,102.4
"[{""problem"": ""diabetes"", ""icd10"": ""K66""}, {""problem"": ""hypertension"", ""icd10"": ""J80""}]",fever,2026-01-04,CN-6537109,57,F,MRN-688642,178/109,84,100.5
"[{""problem"": ""diabetes"", ""icd10"": ""K91""}, {""problem"": ""hypertension"", ""icd10"": ""K86""}]",headache,2026-01-05,CN-2568338,87,F,MRN-586112,160/76,75,100.8
"[{""problem"": ""diabetes"", ""icd10"": ""I57""}, {""problem"": ""diabetes"", ""icd10"": ""K35""}, {""problem"": ""hype",headache,2026-01-03,CN-1355568,49,M,MRN-375922,167/99,84,99.1


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

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

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

Output:
{
  "patient": {
    "mrn": "MRN-802088",
    "age": 30,
    "gender": "M"
  },
  "note_id": "CN-3759937",
  "vitals": {
    "bp": "119/74",
    "hr": 67,
    "temp_f": 100.9
  }
}


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

[User] Output lab result as JSON.

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

Output:
{
  "result_id": "LAB-6812810",
  "patient_mrn": "MRN-631747",
  "order_date": "2026-01-04",
  "panel": "Lipid",
  "results": [
    {
      "test": "WBC",
      "value": 54.3,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "WBC",
      "value": 70.8,
      "unit": "mg/dL",
      "flag": "low"
    },
    {
      "test": "Glucose",
      "value": 59.6,
      "unit": "mg/dL",
      "flag": "low"
    },
    {
      "test": "WBC",
      "value": 140.8,
      "unit": "mg/dL",
      "flag": "high"
    }
  ]
}


[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>
<medications>
<name>Atorvastatin</name>
<dosage>10mg</dosage>
<frequency>BID</frequency>
<quantity>60</quantity>
</medications>
<rx_id>RX-5523111</rx_id>
<date>2026-01-01</date>
</prescription>

[Assistant]
Approach:
1. Task: Convert prescription 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:
{
  "medications": [
    {
      "name": "Atorvastatin",
      "dosage": "10mg",
      "frequency": "BID",
      "quantity": 60
    }
  ],
  "rx_id": "RX-5523111",
  "date": "2026-01-01"
}


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

[User] Generate lab result data in CSV format.

[Assistant]
Approach:
1. Task: Create lab 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:
order_date,panel,patient_mrn,result_id,results
2026-01-01,Lipid,MRN-228148,LAB-2441646,"[{""test"": ""Glucose"", ""value"": 81.9, ""unit"": ""g/dL"", ""flag"": ""high""}, {""test"": ""WBC"", ""value"": 107.7,"
2026-01-03,CMP,MRN-599615,LAB-7856825,"[{""test"": ""Hemoglobin"", ""value"": 105.8, ""unit"": ""g/dL"", ""flag"": ""low""}, {""test"": ""Hemoglobin"", ""valu"
2026-01-03,CBC,MRN-222759,LAB-4252182,"[{""test"": ""WBC"", ""value"": 198.8, ""unit"": ""g/dL"", ""flag"": ""high""}, {""test"": ""Glucose"", ""value"": 68.9,"
2026-01-06,CBC,MRN-277447,LAB-4109705,"[{""test"": ""Glucose"", ""value"": 107.1, ""unit"": ""g/dL"", ""flag"": ""high""}, {""test"": ""Glucose"", ""value"": 1"
2026-01-04,CBC,MRN-971157,LAB-5165897,"[{""test"": ""Hemoglobin"", ""value"": 174.4, ""unit"": ""g/dL"", ""flag"": ""low""}, {""test"": ""Hemoglobin"", ""valu"