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

[User] Generate student assessment data in CSV format.

[Assistant]
Approach:
1. Task: Create student assessment in CSV
2. Complexity: 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_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-879460,,CRS-8763,,2026-01-03,B,,,,,96.07,,"[{""question"": 1, ""points_earned"": 1, ""points_possible"": 10}, {""question"": 2, ""points_earned"": 4, ""po",STU-948921,,,83,quiz
,HVV256,CRS-5260,3,,,40,30,30,Nicole Miller,,"[{""week"": 1, ""topic"": ""late""}, {""week"": 2, ""topic"": ""magazine""}, {""week"": 3, ""topic"": ""environment""}",,,Spring 2024,Adaptive 24hour open architecture 101,,
,TLD443,CRS-8229,3,,,40,30,30,Elizabeth Jones,,"[{""week"": 1, ""topic"": ""on""}, {""week"": 2, ""topic"": ""travel""}, {""week"": 3, ""topic"": ""board""}, {""week"":",,,Spring 2024,Fundamental zero tolerance Internet solution 101,,
,ZWF427,CRS-5275,3,,,40,30,30,Mary Bell,,"[{""week"": 1, ""topic"": ""east""}, {""week"": 2, ""topic"": ""guy""}, {""week"": 3, ""topic"": ""teach""}, {""week"": ",,,Fall 2024,Profit-focused 6thgeneration help-desk 101,,


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<error_log>
<error_id>424897c8-d97d-4bfb-9c1a-7b6e63fd6096</error_id>
<timestamp>2026-01-07T13:51:27.529237</timestamp>
<level>ERROR</level>
<service>heartService</service>
<message>How these anyone stop indeed.</message>
<stack_trace>at manage.py:289</stack_trace>
<stack_trace>at thing.py:107</stack_trace>
<stack_trace>at guy.py:172</stack_trace>
<stack_trace>at seat.py:479</stack_trace>
<context>
<user_id>082cc3eb-3997-4d99-990c-f696ca4ee534</user_id>
<request_id>0f3326d0-3afd-48c1-9c4d-32cc8b0c5920</request_id>
</context>
</error_log>

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

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


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

[User] Create a XML representation of news article.

[Assistant]
Approach:
1. Task: Create news article in XML
2. Complexity: 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"?>
<news_article>
<views>92789</views>
<content>Couple and teacher radio compare consumer. Pass thing much rather light.
Foot four country subject first interview. Defense TV artist to of. Fund miss window scene.
Wish successful movement city door politics measure. Police media TV out word remain as. Report option appear station example role.</content>
<shares>213</shares>
<headline>Re-engineered composite Local Area Network</headline>
<tags>couple</tags>
<tags>this</tags>
<tags>themselves</tags>
<tags>whom</tags>
</news_article>


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

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

[Assistant]
Approach:
1. Task: Create social media post 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:
post_id = "POST-33796851"
platform = "instagram"
user_id = "aa32cdd3-72c6-4e38-bd5e-ff3918321d73"
username = "qtownsend"
content = "List floor whatever fly. Play represent five my. Stuff area push other begin team. Wind leg require represent."
timestamp = "2026-01-07T13:51:26.038556"
hashtags = [ "#study", "#able", "#week",]

[engagement]
likes = 3006
shares = 53
comments = 61


[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-948175</assessment_id>
<student_id>STU-160858</student_id>
<course_id>CRS-5368</course_id>
<type>assignment</type>
<date>2026-01-03</date>
<scores>
<question>1</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>3</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>5</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>3</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>9</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>89</total_score>
<percentage>96.29</percentage>
<grade>B</grade>
</student_assessment>

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

Output:
{
  "assessment_id": "ASMT-948175",
  "student_id": "STU-160858",
  "course_id": "CRS-5368",
  "type": "assignment",
  "date": "2026-01-03",
  "scores": [
    {
      "question": 1,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 5,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 3,
      "points_possible": 10
    },
    {
      "question": 9,
      "points_earned": 9,
      "points_possible": 10
    }
  ],
  "total_score": 89,
  "percentage": 96.29,
  "grade": "B"
}


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

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

[Assistant]
Approach:
1. Task: Create social media post 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:
{
  "post_id": "POST-78526123",
  "platform": "twitter",
  "user_id": "17596017-ad50-41af-8dc2-8746d15af00d",
  "username": "qsharp",
  "content": "Seven behavior less water pretty.\nRock key include. Kind than game agreement.\nPaper position reduce purpose I affect wait threat. Third effect newspaper before include decision recently million.",
  "timestamp": "2026-01-07T13:51:27.460227",
  "hashtags": [
    "#draw",
    "#five",
    "#culture",
    "#sport"
  ],
  "engagement": {
    "likes": 1826,
    "shares": 489,
    "comments": 393
  }
}


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

[User] Output error log as YAML.

[Assistant]
Approach:
1. Task: Create error log in YAML
2. Complexity: 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:
service: approachService
context:
  user_id: fe05329e-c851-4258-9b5b-a5822613303b
  request_id: 7878bb2d-6319-4d97-8924-bd0357b0788d
stack_trace:
- at level.py:451
- at science.py:176
- at art.py:498
- at success.py:287
level: WARNING
error_id: d3f1548e-3d70-475b-a25a-df504add1be1


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

[User]
Transform this JSON data into XML format:
{
  "article_id": "ART-3281345",
  "headline": "Streamlined object-oriented toolset",
  "author": "James Dunn",
  "published": "2026-01-03T08:23:33.060508",
  "section": "Politics",
  "content": "Win take among professor. Glass reflect black similar future. Risk than tree.\nEconomic sit plan. Available then already skill up reason back. Course his threat growth physical parent truth.\nLaugh article pull goal. Believe those few.",
  "tags": [
    "hit",
    "summer",
    "official",
    "rather"
  ],
  "views": 75669,
  "shares": 293
}

[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-3281345</article_id>
<headline>Streamlined object-oriented toolset</headline>
<author>James Dunn</author>
<published>2026-01-03T08:23:33.060508</published>

Politics

<content>Win take among professor. Glass reflect black similar future. Risk than tree.
Economic sit plan. Available then already skill up reason back. Course his threat growth physical parent truth.
Laugh article pull goal. Believe those few.</content>
<tags>hit</tags>
<tags>summer</tags>
<tags>official</tags>
<tags>rather</tags>
<views>75669</views>
<shares>293</shares>
</news_article>


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

[User] Create a JSON representation of error log.

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

Output:
{
  "error_id": "a016c8d2-6aba-435a-ab46-60ac8aacf0a5",
  "timestamp": "2026-01-07T13:51:26.006823",
  "level": "CRITICAL",
  "service": "currentService",
  "message": "Well nation stay number now but.",
  "stack_trace": [
    "at daughter.py:364",
    "at same.py:66"
  ],
  "context": {
    "user_id": "432ef3ee-7f2b-4bc8-a8a7-159d64a89fd5",
    "request_id": "4ed63374-fc09-4101-b987-4a8ee575fee3"
  }
}


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

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


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

[User]
Transform this JSON data into XML format:
{
  "post_id": "POST-90196326",
  "platform": "facebook",
  "user_id": "146c178d-e548-4357-8cd4-e8464cea2f9b",
  "username": "kevincunningham",
  "content": "Three would identify method across operation opportunity.\nWhat realize number. Country perform simple team player. Improve order east mother news magazine trade.\nCentral thus simple thousand morning.",
  "timestamp": "2026-01-07T13:51:26.698310",
  "hashtags": [
    "#pay",
    "#keep"
  ],
  "engagement": {
    "likes": 458,
    "shares": 383,
    "comments": 63
  }
}

[Assistant]
Approach:
1. Task: Convert social media post 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"?>
<social_media_post>
<post_id>POST-90196326</post_id>
<platform>facebook</platform>
<user_id>146c178d-e548-4357-8cd4-e8464cea2f9b</user_id>
<username>kevincunningham</username>
<content>Three would identify method across operation opportunity.
What realize number. Country perform simple team player. Improve order east mother news magazine trade.
Central thus simple thousand morning.</content>
<timestamp>2026-01-07T13:51:26.698310</timestamp>
<hashtags>#pay</hashtags>
<hashtags>#keep</hashtags>
<engagement>
<likes>458</likes>
<shares>383</shares>
<comments>63</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"?>
<social_media_post>
<post_id>POST-49469407</post_id>
<platform>instagram</platform>
<user_id>c776cd7c-2538-4c81-83c8-03afd724bed1</user_id>
<username>donald18</username>
<content>Knowledge between friend wife property kid out. Trouble recent member sort arrive foot space good.</content>
<timestamp>2026-01-07T13:51:26.031233</timestamp>
<hashtags>#daughter</hashtags>
<hashtags>#after</hashtags>
<hashtags>#affect</hashtags>
<hashtags>#goal</hashtags>
<engagement>
<likes>2564</likes>
<shares>187</shares>
<comments>95</comments>
</engagement>
</social_media_post>

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

Output:
{
  "post_id": "POST-49469407",
  "platform": "instagram",
  "user_id": "c776cd7c-2538-4c81-83c8-03afd724bed1",
  "username": "donald18",
  "content": "Knowledge between friend wife property kid out. Trouble recent member sort arrive foot space good.",
  "timestamp": "2026-01-07T13:51:26.031233",
  "hashtags": [
    "#daughter",
    "#after",
    "#affect",
    "#goal"
  ],
  "engagement": {
    "likes": 2564,
    "shares": 187,
    "comments": 95
  }
}


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

[Assistant]
Approach:
1. Task: Convert error log 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"?>
<error_log>
<service>approachService</service>
<context>
<user_id>fe05329e-c851-4258-9b5b-a5822613303b</user_id>
<request_id>7878bb2d-6319-4d97-8924-bd0357b0788d</request_id>
</context>
<stack_trace>at level.py:451</stack_trace>
<stack_trace>at science.py:176</stack_trace>
<stack_trace>at art.py:498</stack_trace>
<stack_trace>at success.py:287</stack_trace>
<level>WARNING</level>
<error_id>d3f1548e-3d70-475b-a25a-df504add1be1</error_id>
</error_log>


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<sales_analytics>
<period>April 2020</period>
<total_revenue>1914989</total_revenue>
<units_sold>47758</units_sold>
<channels>
<name>wholesale</name>
<revenue>3617590</revenue>
<growth>20.48</growth>
</channels>
<channels>
<name>online</name>
<revenue>654207</revenue>
<growth>24.4</growth>
</channels>
<top_products>
<sku>SKU-4328</sku>
<sales>466200</sales>
</top_products>
<top_products>
<sku>SKU-2589</sku>
<sales>244105</sales>
</top_products>
<top_products>
<sku>SKU-7725</sku>
<sales>25778</sales>
</top_products>
</sales_analytics>

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

Output:
{
  "period": "April 2020",
  "total_revenue": 1914989,
  "units_sold": 47758,
  "channels": [
    {
      "name": "wholesale",
      "revenue": 3617590,
      "growth": 20.48
    },
    {
      "name": "online",
      "revenue": 654207,
      "growth": 24.4
    }
  ],
  "top_products": [
    {
      "sku": "SKU-4328",
      "sales": 466200
    },
    {
      "sku": "SKU-2589",
      "sales": 244105
    },
    {
      "sku": "SKU-7725",
      "sales": 25778
    }
  ]
}


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

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

[Assistant]
Approach:
1. Task: Create lab result 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:
result_id = "LAB-5796495"
patient_mrn = "MRN-496025"
order_date = "2026-01-06"
panel = "Lipid"
[[results]]
test = "Hemoglobin"
value = 74.9
unit = "g/dL"
flag = "low"

[[results]]
test = "Hemoglobin"
value = 68.3
unit = "mg/dL"
flag = "low"

[[results]]
test = "WBC"
value = 121.2
unit = "mg/dL"
flag = "normal"

[[results]]
test = "Hemoglobin"
value = 142.6
unit = "g/dL"
flag = "normal"


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Synchronized holistic archive API</title>
<version>1.0.0</version>
</info>
<paths>
</policy>
<get>
<summary>Red reason present loss yeah run.</summary>
<parameters>
<name>param0</name>
<in>query</in>
<type>string</type>
</parameters>
<responses>
<200>
<description>Success</description>
</200>
<400>
<description>Bad Request</description>
</400>
</responses>
</get>
<//policy>
</paths>
</api_specification>


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

[User]
Convert the following XML to YAML:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<review_id>REV-1417017</review_id>
<product_id>PROD-561113</product_id>
<user_id>58368812-841f-4b65-a63f-bf59f81a4b62</user_id>
<rating>2</rating>
<title>Miss entire student source like impact.</title>
<content>Particularly myself court bring vote business boy lawyer. Economy name wonder thank a charge. Successful value site thus. Exist election about task reason.</content>
<date>2026-01-04</date>
<verified_purchase>False</verified_purchase>
<helpful_votes>17</helpful_votes>
</customer_review>

[Assistant]
Approach:
1. Task: Convert customer review 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:
review_id: REV-1417017
product_id: PROD-561113
user_id: 58368812-841f-4b65-a63f-bf59f81a4b62
rating: 2
title: Miss entire student source like impact.
content: Particularly myself court bring vote business boy lawyer. Economy name wonder
  thank a charge. Successful value site thus. Exist election about task reason.
date: '2026-01-04'
verified_purchase: false
helpful_votes: 17


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

[User] Generate research paper data in JSON format.

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

Output:
{
  "paper_id": "arXiv:2021.53732",
  "title": "De-engineered exuding monitoring",
  "authors": [
    {
      "name": "Joseph Johnson",
      "affiliation": "Mccann, Romero and Ortiz",
      "email": "wcook@example.org"
    },
    {
      "name": "Mr. Henry Thomas",
      "affiliation": "Clarke-Williams",
      "email": "mlittle@example.com"
    }
  ],
  "abstract": "Cut happen you after talk trial accept she. Country church development card. Learn support son service.",
  "keywords": [
    "positive",
    "American",
    "hand",
    "sure"
  ],
  "publication": {
    "venue": "Science",
    "year": 2024,
    "doi": "10.3815/gTFt"
  },
  "citations": 88,
  "funding_source": "Kim LLC"
}


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

[User] Generate research paper data in TOML format.

[Assistant]
Approach:
1. Task: Create research paper 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:
paper_id = "arXiv:2023.87771"
title = "User-centric stable ability"
abstract = "Behavior skin nation pay behind remain. Then put again. Process participant current all."
keywords = [ "design", "him", "blue", "less", "fine",]
citations = 194
[[authors]]
name = "Todd Hall MD"
affiliation = "Nunez-Nguyen"
email = "grhodes@example.net"

[[authors]]
name = "Makayla Long"
affiliation = "Stanley, Sellers and Jones"
email = "johnsontammy@example.net"

[publication]
venue = "Nature"
year = 2020
doi = "10.6248/yEgY"


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

[User]
Convert the following TOML to YAML:
paper_id = "arXiv:2020.57295"
title = "Persevering global groupware"
abstract = "Stand season mind indicate either. Buy gas keep skin."
keywords = [ "stock", "member", "laugh", "language", "right",]
citations = 204
[[authors]]
name = "Edwin Moore"
affiliation = "Smith-Jones"
email = "bowenzachary@example.net"

[[authors]]
name = "Anna Collins"
affiliation = "Thomas, Rogers and Baldwin"
email = "thill@example.com"

[[authors]]
name = "Mrs. Mary Delacruz MD"
affiliation = "French, Rodriguez and Johnson"
email = "amywest@example.org"

[publication]
venue = "Cell"
year = 2022
doi = "10.9461/HDZk"

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

Output:
paper_id: arXiv:2020.57295
title: Persevering global groupware
authors:
- name: Edwin Moore
  affiliation: Smith-Jones
  email: bowenzachary@example.net
- name: Anna Collins
  affiliation: Thomas, Rogers and Baldwin
  email: thill@example.com
- name: Mrs. Mary Delacruz MD
  affiliation: French, Rodriguez and Johnson
  email: amywest@example.org
abstract: Stand season mind indicate either. Buy gas keep skin.
keywords:
- stock
- member
- laugh
- language
- right
publication:
  venue: Cell
  year: 2022
  doi: 10.9461/HDZk
citations: 204
funding_source: null


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

[User]
Convert the following CSV to XML:
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
,,,a05e806a-f592-4611-8d80-dbe2773bec40,162209b9-e3ae-4c7a-af39-f96af44cdcaa,8ef553f5-74fa-47eb-bfcb-571b6fa73c35,,,WARNING,Professional pull soon.,,,,,radioService,"[""at eye.py:220"", ""at short.py:148"", ""at the.py:448""]",2026-01-07T13:51:27.105544,
Training another stuff audience lot. Area throw spring house provide dog themselves. Understand that,"[{""name"": ""Amanda Nelson"", ""affiliation"": ""Mcdonald, Evans and Harmon"", ""email"": ""leeandrew@example.",339,,,,Knapp-Graham,"[""fish"", ""particularly"", ""brother"", ""sit""]",,,arXiv:2021.90885,10.1009/VVyo,Cell,2022,,,,Visionary interactive time-frame
"Drive eight government drive rich your.
Economic seem despite case avoid. Manage thus policy continu","[{""name"": ""Zachary Anderson Jr."", ""affiliation"": ""Watson-James"", ""email"": ""laurasmith@example.net""},",315,,,,Ramos Group,"[""relationship"", ""develop"", ""question""]",,,arXiv:2021.84172,10.2976/QDxs,Nature,2021,,,,Customizable motivating moderator

[Assistant]
Approach:
1. Task: Convert error log from CSV 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"?>
<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 JSON format. Think step-by-step, then generate syntactically perfect JSON.

[User] Output course syllabus as JSON.

[Assistant]
Approach:
1. Task: Create course syllabus in JSON
2. Complexity: 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:
{
  "instructor": "Tamara Stark",
  "term": "Spring 2022",
  "code": "VMA483",
  "grading": {
    "homework": 30,
    "midterm": 30,
    "final": 40
  }
}


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

[User]
Transform this TOML data into YAML format:
date = "2026-01-04"
patient_mrn = "MRN-588828"
[[medications]]
name = "Atorvastatin"
dosage = "20mg"
frequency = "TID"
quantity = 60

[[medications]]
name = "Metformin"
dosage = "20mg"
frequency = "daily"
quantity = 60

[[medications]]
name = "Atorvastatin"
dosage = "5mg"
frequency = "TID"
quantity = 60

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

Output:
date: '2026-01-04'
medications:
- name: Atorvastatin
  dosage: 20mg
  frequency: TID
  quantity: 60
- name: Metformin
  dosage: 20mg
  frequency: daily
  quantity: 60
- name: Atorvastatin
  dosage: 5mg
  frequency: TID
  quantity: 60
patient_mrn: MRN-588828


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

[User]
Convert the following XML to YAML:
<?xml version="1.0" encoding="UTF-8"?>
<sales_analytics>
<period>September 2024</period>
<total_revenue>6726526</total_revenue>
<units_sold>45392</units_sold>
<channels>
<name>retail</name>
<revenue>2051641</revenue>
<growth>15.93</growth>
</channels>
<channels>
<name>wholesale</name>
<revenue>4340607</revenue>
<growth>-6.59</growth>
</channels>
<top_products>
<sku>SKU-7798</sku>
<sales>367269</sales>
</top_products>
<top_products>
<sku>SKU-2105</sku>
<sales>291023</sales>
</top_products>
<top_products>
<sku>SKU-5730</sku>
<sales>275348</sales>
</top_products>
</sales_analytics>

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

Output:
period: September 2024
total_revenue: 6726526
units_sold: 45392
channels:
- name: retail
  revenue: 2051641
  growth: 15.93
- name: wholesale
  revenue: 4340607
  growth: -6.59
top_products:
- sku: SKU-7798
  sales: 367269
- sku: SKU-2105
  sales: 291023
- sku: SKU-5730
  sales: 275348


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<student_assessment>
<total_score>97</total_score>
<scores>
<question>1</question>
<points_earned>0</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>4</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>3</question>
<points_earned>10</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>5</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>2</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>5</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>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>11</question>
<points_earned>5</points_earned>
<points_possible>10</points_possible>
</scores>
<percentage>78.32</percentage>
<course_id>CRS-4089</course_id>
</student_assessment>


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

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

[Assistant]
Approach:
1. Task: Convert social media post from YAML 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"?>
<social_media_post>
<post_id>POST-29576154</post_id>
<platform>instagram</platform>
<user_id>b3774d2a-dced-4164-bd7b-7d043d7ec920</user_id>
<username>boydkaren</username>
<content>Responsibility this statement area thing imagine free. Under quickly treatment ever end social military. Majority before treatment decide.</content>
<timestamp>2026-01-07T13:51:27.160344</timestamp>
<hashtags>#involve</hashtags>
<hashtags>#fact</hashtags>
<hashtags>#rest</hashtags>
<engagement>
<likes>923</likes>
<shares>56</shares>
<comments>396</comments>
</engagement>
</social_media_post>


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

[User] Create a XML representation of lab result.

[Assistant]
Approach:
1. Task: Create lab 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"?>
<lab_result>
<result_id>LAB-9047593</result_id>
<patient_mrn>MRN-478989</patient_mrn>
<order_date>2026-01-06</order_date>
<panel>CMP</panel>
<results>
<test>Hemoglobin</test>
<value>171.8</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>WBC</test>
<value>58.0</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>WBC</test>
<value>78.7</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Glucose</test>
<value>138.7</value>
<unit>mg/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>51.5</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>141.9</value>
<unit>mg/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>191.7</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
</lab_result>


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

[User]
Transform this JSON data into CSV format:
{
  "grading": {
    "homework": 30,
    "midterm": 30,
    "final": 40
  },
  "credits": 4,
  "course_id": "CRS-7759",
  "schedule": [
    {
      "week": 1,
      "topic": "meet"
    },
    {
      "week": 2,
      "topic": "around"
    },
    {
      "week": 3,
      "topic": "college"
    },
    {
      "week": 4,
      "topic": "fly"
    },
    {
      "week": 5,
      "topic": "summer"
    },
    {
      "week": 6,
      "topic": "painting"
    },
    {
      "week": 7,
      "topic": "size"
    },
    {
      "week": 8,
      "topic": "off"
    },
    {
      "week": 9,
      "topic": "point"
    },
    {
      "week": 10,
      "topic": "light"
    },
    {
      "week": 11,
      "topic": "nothing"
    }
  ],
  "instructor": "Matthew Johnson"
}

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

Output:
code,course_id,credits,grading_final,grading_homework,grading_midterm,instructor,schedule,term,title
,CRS-7759,4,40,30,30,Matthew Johnson,"[{""week"": 1, ""topic"": ""meet""}, {""week"": 2, ""topic"": ""around""}, {""week"": 3, ""topic"": ""college""}, {""we",,
URJ468,CRS-8587,4,40,30,30,Sarah Brown,"[{""week"": 1, ""topic"": ""green""}, {""week"": 2, ""topic"": ""room""}, {""week"": 3, ""topic"": ""others""}, {""week",Spring 2024,Networked homogeneous installation 101
HRO409,CRS-5288,4,40,30,30,Anthony Bryan,"[{""week"": 1, ""topic"": ""range""}, {""week"": 2, ""topic"": ""believe""}, {""week"": 3, ""topic"": ""little""}, {""w",Spring 2021,Quality-focused 24/7 artificial intelligence 101


[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:2020.59386
title: Self-enabling demand-driven application
authors:
- name: Keith Wilcox
  affiliation: Ruiz-Torres
  email: martinstephanie@example.org
- name: Jennifer Mccoy
  affiliation: Thompson-Marshall
  email: brianvelasquez@example.org
abstract: Before today call network oil future. Admit itself catch song various rest.
  Personal worry quality director.
keywords:
- song
- TV
- southern
publication:
  venue: Nature
  year: 2020
  doi: 10.1369/MikD
citations: 274
funding_source: null


[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>
<result_id>LAB-9017474</result_id>
<patient_mrn>MRN-783803</patient_mrn>
<order_date>2026-01-04</order_date>
<panel>Lipid</panel>
<results>
<test>Glucose</test>
<value>65.6</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Glucose</test>
<value>160.2</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>WBC</test>
<value>142.4</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Glucose</test>
<value>179.9</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>97.3</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>148.5</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>174.6</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
</lab_result>

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

Output:
{
  "result_id": "LAB-9017474",
  "patient_mrn": "MRN-783803",
  "order_date": "2026-01-04",
  "panel": "Lipid",
  "results": [
    {
      "test": "Glucose",
      "value": 65.6,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "Glucose",
      "value": 160.2,
      "unit": "mg/dL",
      "flag": "normal"
    },
    {
      "test": "WBC",
      "value": 142.4,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "Glucose",
      "value": 179.9,
      "unit": "mg/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 97.3,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 148.5,
      "unit": "g/dL",
      "flag": "high"
    },
    {
      "test": "Hemoglobin",
      "value": 174.6,
      "unit": "g/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 TOML to XML:
product_id = "PROD-107958"
name = "Adaptive asynchronous synergy"
category = "electronics"
price = 349.45
currency = "USD"
stock = 717
is_available = true
rating = 1.62
reviews = 33

[specs]
weight_kg = 15.32
dimensions = "74x31x68cm"

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<product_listing>
<product_id>PROD-107958</product_id>
<name>Adaptive asynchronous synergy</name>
<category>electronics</category>
<price>349.45</price>
<currency>USD</currency>
<stock>717</stock>
<is_available>True</is_available>
<rating>1.62</rating>
<reviews>33</reviews>
<specs>
<weight_kg>15.32</weight_kg>
<dimensions>74x31x68cm</dimensions>
</specs>
</product_listing>


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

[User] Create a CSV representation of clinical note.

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

Output:
assessment,chief_complaint,encounter_date,note_id,patient_age,patient_gender,patient_mrn,vitals_bp,vitals_hr,vitals_temp_f
"[{""problem"": ""hypertension"", ""icd10"": ""K52""}]",headache,2026-01-06,CN-4036732,79,M,MRN-366942,102/96,61,97.1
"[{""problem"": ""hypertension"", ""icd10"": ""J96""}, {""problem"": ""diabetes"", ""icd10"": ""K89""}, {""problem"": """,chest pain,2026-01-06,CN-6906831,19,F,MRN-340156,92/79,98,98.5
"[{""problem"": ""hypertension"", ""icd10"": ""J92""}, {""problem"": ""diabetes"", ""icd10"": ""J26""}]",headache,2026-01-06,CN-5464803,61,M,MRN-684195,115/108,86,99.8
"[{""problem"": ""hypertension"", ""icd10"": ""J83""}, {""problem"": ""hypertension"", ""icd10"": ""K46""}, {""problem",fever,2026-01-03,CN-5582516,65,M,MRN-203756,133/68,64,102.1
"[{""problem"": ""hypertension"", ""icd10"": ""I60""}, {""problem"": ""diabetes"", ""icd10"": ""K79""}]",headache,2026-01-02,CN-5304711,18,F,MRN-484429,146/88,97,100.2


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Visionary eco-centric methodology API</title>
<version>1.0.0</version>
</info>
<paths>
</edge>
<get>
<summary>Simple really social range.</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>
<//edge>
</paths>
</api_specification>


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

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

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

Output:
code,course_id,credits,grading_final,grading_homework,grading_midterm,instructor,schedule,term,title
NLW161,CRS-4864,,,,,Ryan Griffin,,,
MNO475,CRS-1155,4,40,30,30,Gary Anderson,"[{""week"": 1, ""topic"": ""chance""}, {""week"": 2, ""topic"": ""six""}, {""week"": 3, ""topic"": ""they""}, {""week"":",Spring 2021,Advanced bandwidth-monitored pricing structure 101
PNK422,CRS-6967,4,40,30,30,Belinda Gilbert,"[{""week"": 1, ""topic"": ""real""}, {""week"": 2, ""topic"": ""rate""}, {""week"": 3, ""topic"": ""road""}, {""week"": ",Spring 2020,Multi-lateral national circuit 101
IMZ299,CRS-2472,4,40,30,30,Alexander Wallace,"[{""week"": 1, ""topic"": ""begin""}, {""week"": 2, ""topic"": ""against""}, {""week"": 3, ""topic"": ""seat""}, {""wee",Spring 2024,Re-engineered user-facing array 101


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

[User] Generate clinical note data in JSON format.

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

Output:
{
  "note_id": "CN-7937835",
  "patient": {
    "mrn": "MRN-749785",
    "age": 66,
    "gender": "M"
  },
  "encounter_date": "2026-01-06",
  "chief_complaint": "chest pain",
  "vitals": {
    "bp": "179/85",
    "hr": 81,
    "temp_f": 101.7
  },
  "assessment": [
    {
      "problem": "hypertension",
      "icd10": "I52"
    },
    {
      "problem": "diabetes",
      "icd10": "J76"
    }
  ]
}


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

[User] Output prescription as JSON.

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


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

[User] Output research paper as CSV.

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

Output:
abstract,authors,citations,funding_source,keywords,paper_id,publication_doi,publication_venue,publication_year,title
Price while never. Night great must well remain. Share less reveal often.,"[{""name"": ""Meagan Sutton"", ""affiliation"": ""Williamson, Mitchell and Smith"", ""email"": ""davilabridget@",155,None,"[""less"", ""radio"", ""spend"", ""which""]",arXiv:2024.31964,10.4651/vEqE,Science,2023,Optimized solution-oriented success
Back after own. Church go before group wife. Can else along election.,"[{""name"": ""Stephanie Mcdaniel"", ""affiliation"": ""Allen PLC"", ""email"": ""carpenterbrittany@example.net""",412,None,"[""focus"", ""name"", ""beautiful""]",arXiv:2023.87185,10.2442/PvlY,Science,2023,De-engineered object-oriented algorithm
Kid grow drive system arrive reflect. Usually cost early suddenly box. Air crime bring.,"[{""name"": ""Karen Mcgee DDS"", ""affiliation"": ""Leblanc, Thompson and Sanchez"", ""email"": ""kingderrick@e",79,"Williams, Hodge and Simmons","[""among"", ""them"", ""stand""]",arXiv:2020.49913,10.1185/DvlS,Nature,2020,Inverse systemic emulation
Meeting effect memory environmental three buy life. Participant foreign best citizen base top. Last ,"[{""name"": ""William Foster"", ""affiliation"": ""Baker, Clark and Henderson"", ""email"": ""christopher55@exa",89,Rodriguez-Murphy,"[""itself"", ""choose"", ""front""]",arXiv:2021.69166,10.6861/LyFY,Cell,2022,Face-to-face even-keeled Graphical User Interface


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

[User] Output clinical note as CSV.

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

Output:
assessment,chief_complaint,encounter_date,note_id,patient_age,patient_gender,patient_mrn,vitals_bp,vitals_hr,vitals_temp_f
"[{""problem"": ""hypertension"", ""icd10"": ""K96""}, {""problem"": ""diabetes"", ""icd10"": ""K86""}]",chest pain,2026-01-06,CN-3508494,51,F,MRN-721804,130/109,78,100.6
"[{""problem"": ""diabetes"", ""icd10"": ""J36""}, {""problem"": ""diabetes"", ""icd10"": ""J36""}]",chest pain,2026-01-04,CN-9035071,18,M,MRN-491263,101/72,90,100.2
"[{""problem"": ""hypertension"", ""icd10"": ""I74""}, {""problem"": ""hypertension"", ""icd10"": ""K86""}]",headache,2026-01-01,CN-9917027,75,M,MRN-127789,140/62,92,99.8
"[{""problem"": ""diabetes"", ""icd10"": ""I13""}, {""problem"": ""hypertension"", ""icd10"": ""J44""}, {""problem"": """,fever,2026-01-06,CN-6959076,38,M,MRN-145025,129/80,98,100.4
"[{""problem"": ""diabetes"", ""icd10"": ""I81""}, {""problem"": ""hypertension"", ""icd10"": ""K27""}]",chest pain,2026-01-06,CN-8756681,64,M,MRN-299511,116/102,108,98.2


[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-891981"
name = "Focused background info-mediaries"
category = "books"
price = 16.4
currency = "USD"
stock = 192
is_available = true
rating = 3.23
reviews = 117

[specs]
weight_kg = 31.51
dimensions = "65x39x62cm"


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

[User] Generate research paper data in CSV format.

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

Output:
abstract,authors,citations,funding_source,keywords,paper_id,publication_doi,publication_venue,publication_year,title
,"[{""name"": ""Caroline Barnes"", ""affiliation"": ""Parker Ltd"", ""email"": ""angelajackson@example.net""}, {""n",,None,,,,,,Polarized methodical algorithm
White society church break ready address thought hour. Agent national low win despite staff. Foreign,"[{""name"": ""Melanie Combs"", ""affiliation"": ""Boone-Patel"", ""email"": ""hannah03@example.com""}, {""name"": ",177,"Parker, White and Dunlap","[""again"", ""study"", ""impact""]",arXiv:2024.46227,10.2940/McCw,Cell,2023,Versatile multi-state workforce
Information find establish note these tough so. Brother big first. Cell government section contain b,"[{""name"": ""Jennifer Williams"", ""affiliation"": ""Williams and Sons"", ""email"": ""wtucker@example.com""}, ",372,Stewart-Martin,"[""movement"", ""red"", ""also"", ""phone"", ""international""]",arXiv:2020.72457,10.4229/qult,Cell,2024,Inverse reciprocal hub
Action good could campaign. Keep similar office beyond late. Truth similar life well down condition ,"[{""name"": ""Barbara Johnson"", ""affiliation"": ""Fuller-Davies"", ""email"": ""grayjoanna@example.net""}, {""n",382,None,"[""growth"", ""small"", ""indicate"", ""rate"", ""since""]",arXiv:2021.34255,10.5216/HFKy,Science,2024,Enterprise-wide dedicated groupware


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

[User] Generate transaction record data in CSV format.

[Assistant]
Approach:
1. Task: Create transaction record 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:
customer_id,items,payment_method,subtotal,tax,timestamp,total,txn_id
3fe35528-f72a-4e45-bcf8-f7cb059fe7e5,"[{""sku"": ""SKU-59380"", ""qty"": 2, ""price"": 447.63}, {""sku"": ""SKU-56357"", ""qty"": 4, ""price"": 130.56}, {",apple_pay,1853.52,74.51,2026-01-07T13:51:27.778783,1419.49,TXN-20904368
65034345-49ed-4e0e-8cf0-cc2fa07c4c41,"[{""sku"": ""SKU-66926"", ""qty"": 2, ""price"": 412.29}]",apple_pay,768.96,92.62,2026-01-07T13:51:27.780122,1096.76,TXN-55193557
1e89a59b-9c19-42d5-b832-f7ac1cca0fcf,"[{""sku"": ""SKU-29338"", ""qty"": 4, ""price"": 383.29}, {""sku"": ""SKU-27248"", ""qty"": 2, ""price"": 131.29}, {",credit_card,1304.11,110.73,2026-01-07T13:51:27.780173,920.45,TXN-88368033
d1b31124-8de7-4cbe-a484-f72a8f6cc8ad,"[{""sku"": ""SKU-26613"", ""qty"": 4, ""price"": 239.51}, {""sku"": ""SKU-14570"", ""qty"": 3, ""price"": 302.82}, {",credit_card,103.98,134.59,2026-01-07T13:51:27.780221,1930.99,TXN-99668834
35b6929e-ea36-43b0-ae68-6d85fc0ce801,"[{""sku"": ""SKU-49018"", ""qty"": 2, ""price"": 143.28}, {""sku"": ""SKU-71933"", ""qty"": 1, ""price"": 29.07}]",paypal,1559.34,131.04,2026-01-07T13:51:27.780260,2007.98,TXN-86934436


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

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

[Assistant]
Approach:
1. Task: Create clinical note in JSON
2. Complexity: 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:
{
  "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 YAML format. Think step-by-step, then generate syntactically perfect YAML.

[User]
Transform this TOML data into YAML format:
company = "Ortega-Owens"
ticker = "YLLB"
quarter = "Q3 2022"
revenue = 37598920
expenses = 44591506
net_income = 3197580
eps = 1.51

[metrics]
profit_margin = 5.54
roe = 6.32

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

Output:
company: Ortega-Owens
ticker: YLLB
quarter: Q3 2022
revenue: 37598920
expenses: 44591506
net_income: 3197580
eps: 1.51
metrics:
  profit_margin: 5.54
  roe: 6.32


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

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

[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-15490463</post_id>
<platform>instagram</platform>
<user_id>dcf0c28f-6ad6-4153-873b-0cd39fa73a46</user_id>
<username>allenjames</username>
<content>Eight television free focus window leave. Education Democrat past music mother able. Fund season represent when analysis movement.
Everything over rich serious forget. Fire particular western.</content>
<timestamp>2026-01-07T13:51:27.338072</timestamp>
<hashtags>#left</hashtags>
<hashtags>#long</hashtags>
<hashtags>#instead</hashtags>
<hashtags>#budget</hashtags>
<engagement>
<likes>85</likes>
<shares>112</shares>
<comments>292</comments>
</engagement>
</social_media_post>


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

[User]
Convert the following JSON to XML:
{
  "course_id": "CRS-8422",
  "code": "OMY437",
  "title": "Optimized upward-trending conglomeration 101",
  "instructor": "Rodney Anderson",
  "credits": 3,
  "term": "Spring 2023",
  "schedule": [
    {
      "week": 1,
      "topic": "answer"
    },
    {
      "week": 2,
      "topic": "best"
    },
    {
      "week": 3,
      "topic": "meet"
    },
    {
      "week": 4,
      "topic": "simple"
    },
    {
      "week": 5,
      "topic": "peace"
    },
    {
      "week": 6,
      "topic": "upon"
    },
    {
      "week": 7,
      "topic": "power"
    }
  ],
  "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-8422</course_id>
OMY437
<title>Optimized upward-trending conglomeration 101</title>
<instructor>Rodney Anderson</instructor>
<credits>3</credits>
<term>Spring 2023</term>
<schedule>
<week>1</week>
<topic>answer</topic>
</schedule>
<schedule>
<week>2</week>
<topic>best</topic>
</schedule>
<schedule>
<week>3</week>
<topic>meet</topic>
</schedule>
<schedule>
<week>4</week>
<topic>simple</topic>
</schedule>
<schedule>
<week>5</week>
<topic>peace</topic>
</schedule>
<schedule>
<week>6</week>
<topic>upon</topic>
</schedule>
<schedule>
<week>7</week>
<topic>power</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:
{
  "error_id": "8ef553f5-74fa-47eb-bfcb-571b6fa73c35",
  "timestamp": "2026-01-07T13:51:27.105544",
  "level": "WARNING",
  "service": "radioService",
  "message": "Professional pull soon.",
  "stack_trace": [
    "at eye.py:220",
    "at short.py:148",
    "at the.py:448"
  ],
  "context": {
    "user_id": "162209b9-e3ae-4c7a-af39-f96af44cdcaa",
    "request_id": "a05e806a-f592-4611-8d80-dbe2773bec40"
  }
}

[Assistant]
Approach:
1. Task: Convert error log 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"?>
<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 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 2024",
  "total_revenue": 5319249,
  "units_sold": 96009,
  "channels": [
    {
      "name": "wholesale",
      "revenue": 941227,
      "growth": 26.4
    },
    {
      "name": "retail",
      "revenue": 937409,
      "growth": 30.07
    }
  ],
  "top_products": [
    {
      "sku": "SKU-2900",
      "sales": 81858
    },
    {
      "sku": "SKU-8266",
      "sales": 123988
    },
    {
      "sku": "SKU-9969",
      "sales": 32400
    }
  ]
}


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

[User]
Transform this JSON data into XML format:
{
  "company": "Richard Ltd",
  "ticker": "XHCL",
  "quarter": "Q4 2020",
  "revenue": 71255223,
  "expenses": 54916122,
  "net_income": 1190834,
  "eps": 4.63,
  "metrics": {
    "profit_margin": 14.39,
    "roe": 19.33
  }
}

[Assistant]
Approach:
1. Task: Convert financial report 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"?>
<financial_report>
<company>Richard Ltd</company>
<ticker>XHCL</ticker>
<quarter>Q4 2020</quarter>
<revenue>71255223</revenue>
<expenses>54916122</expenses>
<net_income>1190834</net_income>
<eps>4.63</eps>
<metrics>
<profit_margin>14.39</profit_margin>
<roe>19.33</roe>
</metrics>
</financial_report>


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

[User] Output research paper as TOML.

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

Output:
paper_id = "arXiv:2023.67497"
title = "Open-architected logistical paradigm"
abstract = "Yes eat up himself consumer. Technology just debate bill live oil."
keywords = [ "each", "on", "perhaps",]
citations = 265
funding_source = "Smith Ltd"
[[authors]]
name = "William Martin"
affiliation = "George, Nichols and Johnston"
email = "crystal73@example.org"

[[authors]]
name = "Thomas Boyer"
affiliation = "Powers, Miller and Johnston"
email = "xhardin@example.com"

[[authors]]
name = "Tanner Coffey"
affiliation = "Perez, Marks and Thomas"
email = "tracywilliams@example.com"

[publication]
venue = "Nature"
year = 2022
doi = "10.2923/Xnio"


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

[User] Create a TOML representation of financial report.

[Assistant]
Approach:
1. Task: Create financial report 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:
net_income = 4233102
company = "Blackwell, Simpson and Pace"
eps = 0.79
expenses = 41343491

[metrics]
profit_margin = 14.29
roe = 18.28


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

[User]
Convert the following XML to YAML:
<?xml version="1.0" encoding="UTF-8"?>
<lab_result>
<result_id>LAB-3941350</result_id>
<patient_mrn>MRN-739958</patient_mrn>
<order_date>2026-01-01</order_date>
<panel>CBC</panel>
<results>
<test>Glucose</test>
<value>134.1</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>WBC</test>
<value>188.7</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>142.9</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>117.3</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Glucose</test>
<value>159.8</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>WBC</test>
<value>131.5</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
</lab_result>

[Assistant]
Approach:
1. Task: Convert lab result from XML 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:
result_id: LAB-3941350
patient_mrn: MRN-739958
order_date: '2026-01-01'
panel: CBC
results:
- test: Glucose
  value: 134.1
  unit: mg/dL
  flag: high
- test: WBC
  value: 188.7
  unit: g/dL
  flag: low
- test: Hemoglobin
  value: 142.9
  unit: mg/dL
  flag: high
- test: Hemoglobin
  value: 117.3
  unit: g/dL
  flag: normal
- test: Glucose
  value: 159.8
  unit: g/dL
  flag: normal
- test: WBC
  value: 131.5
  unit: g/dL
  flag: normal


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

[User] Generate sales analytics data in TOML format.

[Assistant]
Approach:
1. Task: Create sales analytics in TOML
2. Complexity: 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 2022"
total_revenue = 7287772
units_sold = 8566
[[channels]]
name = "retail"
revenue = 931216
growth = 10.96

[[channels]]
name = "wholesale"
revenue = 1224016
growth = 31.92

[[top_products]]
sku = "SKU-1474"
sales = 19268

[[top_products]]
sku = "SKU-3289"
sales = 31397

[[top_products]]
sku = "SKU-4950"
sales = 322920


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

[User] Create a YAML representation of news article.

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

Output:
article_id: ART-2650245
headline: Enhanced multimedia hub
author: Jennifer Davis
published: '2026-01-02T17:44:08.333575'
section: Tech
content: 'Late situation both data share market. These foot health box.

  Pay me together western ever story cup. Game production million happy reveal. Attorney
  bill shake crime eat finally drive.

  Choice four concern cold test. Road executive policy official season increase.'
tags:
- future
- here
- new
views: 46115
shares: 2819


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

[User] Create a TOML representation of customer review.

[Assistant]
Approach:
1. Task: Create customer review in TOML
2. Complexity: 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-9529513"
product_id = "PROD-542599"
user_id = "67bb80c4-7c72-4c1b-886f-8186f18f45e3"
rating = 3
title = "Money face statement talk day."
content = "Candidate stuff mission end nature hundred. Recently game stage agreement. Seem central blood add environment several.\nSet less job reveal protect. Similar second staff owner international major."
date = "2026-01-01"
verified_purchase = true
helpful_votes = 8


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

[User] Create a XML representation of prescription.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<prescription>
<rx_id>RX-4278484</rx_id>
<patient_mrn>MRN-990980</patient_mrn>
<prescriber>Andrew Kelly</prescriber>
<date>2026-01-06</date>
<medications>
<name>Metformin</name>
<dosage>10mg</dosage>
<frequency>BID</frequency>
<quantity>30</quantity>
</medications>
<medications>
<name>Atorvastatin</name>
<dosage>10mg</dosage>
<frequency>BID</frequency>
<quantity>90</quantity>
</medications>
</prescription>


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<sales_analytics>
<period>June 2022</period>
<total_revenue>7287772</total_revenue>
<units_sold>8566</units_sold>
<channels>
<name>retail</name>
<revenue>931216</revenue>
<growth>10.96</growth>
</channels>
<channels>
<name>wholesale</name>
<revenue>1224016</revenue>
<growth>31.92</growth>
</channels>
<top_products>
<sku>SKU-1474</sku>
<sales>19268</sales>
</top_products>
<top_products>
<sku>SKU-3289</sku>
<sales>31397</sales>
</top_products>
<top_products>
<sku>SKU-4950</sku>
<sales>322920</sales>
</top_products>
</sales_analytics>

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

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


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<error_log>
<error_id>a016c8d2-6aba-435a-ab46-60ac8aacf0a5</error_id>
<timestamp>2026-01-07T13:51:26.006823</timestamp>
<level>CRITICAL</level>
<service>currentService</service>
<message>Well nation stay number now but.</message>
<stack_trace>at daughter.py:364</stack_trace>
<stack_trace>at same.py:66</stack_trace>
<context>
<user_id>432ef3ee-7f2b-4bc8-a8a7-159d64a89fd5</user_id>
<request_id>4ed63374-fc09-4101-b987-4a8ee575fee3</request_id>
</context>
</error_log>

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

Output:
{
  "error_id": "a016c8d2-6aba-435a-ab46-60ac8aacf0a5",
  "timestamp": "2026-01-07T13:51:26.006823",
  "level": "CRITICAL",
  "service": "currentService",
  "message": "Well nation stay number now but.",
  "stack_trace": [
    "at daughter.py:364",
    "at same.py:66"
  ],
  "context": {
    "user_id": "432ef3ee-7f2b-4bc8-a8a7-159d64a89fd5",
    "request_id": "4ed63374-fc09-4101-b987-4a8ee575fee3"
  }
}


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

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

[Assistant]
Approach:
1. Task: Create social media post 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:
post_id: POST-78526123
platform: twitter
user_id: 17596017-ad50-41af-8dc2-8746d15af00d
username: qsharp
content: 'Seven behavior less water pretty.

  Rock key include. Kind than game agreement.

  Paper position reduce purpose I affect wait threat. Third effect newspaper before
  include decision recently million.'
timestamp: '2026-01-07T13:51:27.460227'
hashtags:
- '#draw'
- '#five'
- '#culture'
- '#sport'
engagement:
  likes: 1826
  shares: 489
  comments: 393


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

[User] Output news article as JSON.

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

Output:
{
  "article_id": "ART-1823437",
  "headline": "Integrated content-based throughput",
  "author": "Anna Ortiz",
  "published": "2026-01-05T06:32:59.977242",
  "section": "Politics",
  "content": "Success off activity him process hot whose pay. Most probably including at arm avoid media finally.\nFilm traditional together still member. Culture let serve home.\nChoose free minute in rich after image. Family meet health offer total leave media. Education enter against foreign.",
  "tags": [
    "base",
    "fight",
    "test"
  ],
  "views": 75522,
  "shares": 3070
}


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

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

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

Output:
{
  "article_id": "ART-2188860",
  "headline": "Advanced well-modulated service-desk",
  "author": "Michael Logan",
  "published": "2026-01-03T08:09:52.608144",
  "section": "Politics",
  "content": "Include start build no effort continue. Mention sister mention threat.\nChoose herself case writer question over. Hand quickly house send shoulder expert hour.\nAll probably suffer law consider kitchen relationship. Data population personal past security but across.",
  "tags": [
    "hear",
    "civil",
    "might",
    "way",
    "win"
  ],
  "views": 35184,
  "shares": 1092
}


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

[User] Output product listing as YAML.

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

Output:
specs:
  weight_kg: 41.33
  dimensions: 19x24x69cm
price: 743.81
is_available: true
rating: 2.69
stock: 485


[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-125540"
name = "Universal eco-centric approach"
category = "books"
price = 208.68
currency = "USD"
stock = 879
is_available = true
rating = 4.53
reviews = 925

[specs]
weight_kg = 20.35
dimensions = "45x91x83cm"


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

[User]
Reformat the data below from XML to TOML:
<?xml version="1.0" encoding="UTF-8"?>
<prescription>
<rx_id>RX-7665793</rx_id>
<patient_mrn>MRN-934255</patient_mrn>
<prescriber>Danielle Brown</prescriber>
<date>2026-01-06</date>
<medications>
<name>Atorvastatin</name>
<dosage>20mg</dosage>
<frequency>daily</frequency>
<quantity>90</quantity>
</medications>
<medications>
<name>Atorvastatin</name>
<dosage>5mg</dosage>
<frequency>BID</frequency>
<quantity>90</quantity>
</medications>
<medications>
<name>Metformin</name>
<dosage>5mg</dosage>
<frequency>BID</frequency>
<quantity>60</quantity>
</medications>
</prescription>

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

Output:
rx_id = "RX-7665793"
patient_mrn = "MRN-934255"
prescriber = "Danielle Brown"
date = "2026-01-06"
[[medications]]
name = "Atorvastatin"
dosage = "20mg"
frequency = "daily"
quantity = 90

[[medications]]
name = "Atorvastatin"
dosage = "5mg"
frequency = "BID"
quantity = 90

[[medications]]
name = "Metformin"
dosage = "5mg"
frequency = "BID"
quantity = 60


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

[User]
Transform this TOML data into YAML format:
product_id = "PROD-942707"
name = "Organic demand-driven installation"
category = "books"
price = 698.66
currency = "USD"
stock = 819
is_available = true
rating = 4.45
reviews = 103

[specs]
weight_kg = 32.63
dimensions = "66x30x83cm"

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

Output:
product_id: PROD-942707
name: Organic demand-driven installation
category: books
price: 698.66
currency: USD
stock: 819
is_available: true
rating: 4.45
reviews: 103
specs:
  weight_kg: 32.63
  dimensions: 66x30x83cm


[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"?>
<contract>
<contract_id>CTR-504304</contract_id>
<parties>
<name>Waters-Vega</name>
<role>party_a</role>
</parties>
<parties>
<name>Petty, Thompson and Dillon</name>
<role>party_b</role>
</parties>
<effective_date>2026-01-01</effective_date>
<term_months>50</term_months>
<value>407863</value>
<status>executed</status>
</contract>

[Assistant]
Approach:
1. Task: Convert contract 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:
{
  "contract_id": "CTR-504304",
  "parties": [
    {
      "name": "Waters-Vega",
      "role": "party_a"
    },
    {
      "name": "Petty, Thompson and Dillon",
      "role": "party_b"
    }
  ],
  "effective_date": "2026-01-01",
  "term_months": 50,
  "value": 407863,
  "status": "executed"
}


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

[User] Output financial report as TOML.

[Assistant]
Approach:
1. Task: Create financial report 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:
revenue = 81140617
quarter = "Q1 2021"

[metrics]
profit_margin = 25.46
roe = 20.6


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

[User] Generate transaction record data in XML format.

[Assistant]
Approach:
1. Task: Create transaction record 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"?>
<transaction_record>
<payment_method>paypal</payment_method>
<customer_id>fe237049-a4a1-4a5c-af14-940bbb31d0e7</customer_id>
<total>1227.54</total>
</transaction_record>


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

[User] Generate student assessment data in JSON format.

[Assistant]
Approach:
1. Task: Create student assessment in JSON
2. Complexity: 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-766800",
  "student_id": "STU-927295",
  "course_id": "CRS-8819",
  "type": "assignment",
  "date": "2026-01-03",
  "scores": [
    {
      "question": 1,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 3,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 5,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 0,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 9,
      "points_earned": 3,
      "points_possible": 10
    }
  ],
  "total_score": 99,
  "percentage": 71.71,
  "grade": "A"
}


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

[User] Create a CSV representation of contract.

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

Output:
contract_id,effective_date,parties,status,term_months,value
CTR-313579,2026-01-01,"[{""name"": ""Roberts, Newton and Ortiz"", ""role"": ""party_a""}, {""name"": ""Garcia PLC"", ""role"": ""party_b""}",active,55,108642
CTR-876127,2026-01-05,"[{""name"": ""Nicholson-Blair"", ""role"": ""party_a""}, {""name"": ""Johnson, Allen and Wright"", ""role"": ""part",pending,58,88306
CTR-535561,2026-01-02,"[{""name"": ""Ruiz Group"", ""role"": ""party_a""}, {""name"": ""Pham, Alvarez and Lee"", ""role"": ""party_b""}]",pending,58,713251
CTR-551639,2026-01-04,"[{""name"": ""Taylor-Taylor"", ""role"": ""party_a""}, {""name"": ""Russell Ltd"", ""role"": ""party_b""}]",executed,31,93830


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

[User] Produce a TOML document for a prescription.

[Assistant]
Approach:
1. Task: Create prescription in TOML
2. Complexity: 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-9001624"
patient_mrn = "MRN-695608"
prescriber = "Stephen Davis"
date = "2026-01-05"
[[medications]]
name = "Lisinopril"
dosage = "20mg"
frequency = "daily"
quantity = 90


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

[User] Generate customer review data in TOML format.

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

Output:
review_id = "REV-1417017"
product_id = "PROD-561113"
user_id = "58368812-841f-4b65-a63f-bf59f81a4b62"
rating = 2
title = "Miss entire student source like impact."
content = "Particularly myself court bring vote business boy lawyer. Economy name wonder thank a charge. Successful value site thus. Exist election about task reason."
date = "2026-01-04"
verified_purchase = false
helpful_votes = 17


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

[User] Create a CSV representation of student assessment.

[Assistant]
Approach:
1. Task: Create student assessment 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_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-503362,,CRS-9952,,2026-01-01,C,,,,,94.35,,"[{""question"": 1, ""points_earned"": 1, ""points_possible"": 10}, {""question"": 2, ""points_earned"": 0, ""po",STU-235214,,,52,assignment
,JLD273,CRS-6723,4,,,40,30,30,John Holt,,"[{""week"": 1, ""topic"": ""carry""}, {""week"": 2, ""topic"": ""when""}, {""week"": 3, ""topic"": ""ask""}, {""week"": ",,,Spring 2022,Devolved holistic product 101,,
,ANZ278,CRS-1576,4,,,40,30,30,Kaitlyn Brown,,"[{""week"": 1, ""topic"": ""cover""}, {""week"": 2, ""topic"": ""success""}, {""week"": 3, ""topic"": ""compare""}, {""",,,Fall 2021,Organic even-keeled hub 101,,


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

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

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

Output:
{
  "course_id": "CRS-6204",
  "code": "WOR378",
  "title": "Multi-channeled bi-directional implementation 101",
  "instructor": "Charlene Houston",
  "credits": 4,
  "term": "Spring 2023",
  "schedule": [
    {
      "week": 1,
      "topic": "under"
    },
    {
      "week": 2,
      "topic": "trade"
    },
    {
      "week": 3,
      "topic": "good"
    },
    {
      "week": 4,
      "topic": "grow"
    },
    {
      "week": 5,
      "topic": "ability"
    },
    {
      "week": 6,
      "topic": "experience"
    },
    {
      "week": 7,
      "topic": "offer"
    },
    {
      "week": 8,
      "topic": "account"
    }
  ],
  "grading": {
    "homework": 30,
    "midterm": 30,
    "final": 40
  }
}


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

[User] 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 = 1467254
units_sold = 63744
[[channels]]
name = "wholesale"
revenue = 2975287
growth = -1.88

[[channels]]
name = "online"
revenue = 2665464
growth = 14.77

[[top_products]]
sku = "SKU-1172"
sales = 348860

[[top_products]]
sku = "SKU-4431"
sales = 479568

[[top_products]]
sku = "SKU-6244"
sales = 245719


[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:
{
  "note_id": "CN-6952117",
  "patient": {
    "mrn": "MRN-227055",
    "age": 50,
    "gender": "F"
  },
  "encounter_date": "2026-01-03",
  "chief_complaint": "headache",
  "vitals": {
    "bp": "146/78",
    "hr": 63,
    "temp_f": 97.9
  },
  "assessment": [
    {
      "problem": "hypertension",
      "icd10": "J35"
    },
    {
      "problem": "hypertension",
      "icd10": "K44"
    },
    {
      "problem": "hypertension",
      "icd10": "I58"
    }
  ]
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<clinical_note>
<note_id>CN-6952117</note_id>
<patient>
<mrn>MRN-227055</mrn>
<age>50</age>
<gender>F</gender>
</patient>
<encounter_date>2026-01-03</encounter_date>
<chief_complaint>headache</chief_complaint>
<vitals>
<bp>146/78</bp>

63

<temp_f>97.9</temp_f>
</vitals>
<assessment>
<problem>hypertension</problem>
<icd10>J35</icd10>
</assessment>
<assessment>
<problem>hypertension</problem>
<icd10>K44</icd10>
</assessment>
<assessment>
<problem>hypertension</problem>
<icd10>I58</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 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 2022
total_revenue: 6033804
units_sold: 27183
channels:
- name: wholesale
  revenue: 4147239
  growth: 40.37
- name: online
  revenue: 2663137
  growth: 9.96
top_products:
- sku: SKU-2538
  sales: 420940
- sku: SKU-8680
  sales: 364206
- sku: SKU-2062
  sales: 350623


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

[User]
Reformat the data below from JSON to XML:
{
  "assessment_id": "ASMT-879460",
  "student_id": "STU-948921",
  "course_id": "CRS-8763",
  "type": "quiz",
  "date": "2026-01-03",
  "scores": [
    {
      "question": 1,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 3,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 5,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 6,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 9,
      "points_possible": 10
    }
  ],
  "total_score": 83,
  "percentage": 96.07,
  "grade": "B"
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<student_assessment>
<assessment_id>ASMT-879460</assessment_id>
<student_id>STU-948921</student_id>
<course_id>CRS-8763</course_id>
<type>quiz</type>
<date>2026-01-03</date>
<scores>
<question>1</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>4</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>3</question>
<points_earned>7</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>3</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>5</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>6</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>83</total_score>
<percentage>96.07</percentage>
<grade>B</grade>
</student_assessment>


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

[User] Generate prescription data in YAML format.

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

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


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

[User]
Reformat the data below from JSON to XML:
{
  "course_id": "CRS-9279",
  "code": "WQT213",
  "title": "Ameliorated 3rdgeneration groupware 101",
  "instructor": "Mariah Wilson",
  "credits": 3,
  "term": "Fall 2020",
  "schedule": [
    {
      "week": 1,
      "topic": "together"
    },
    {
      "week": 2,
      "topic": "statement"
    },
    {
      "week": 3,
      "topic": "these"
    },
    {
      "week": 4,
      "topic": "American"
    },
    {
      "week": 5,
      "topic": "read"
    },
    {
      "week": 6,
      "topic": "age"
    },
    {
      "week": 7,
      "topic": "course"
    }
  ],
  "grading": {
    "homework": 30,
    "midterm": 30,
    "final": 40
  }
}

[Assistant]
Approach:
1. Task: Convert course syllabus from 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-9279</course_id>
WQT213
<title>Ameliorated 3rdgeneration groupware 101</title>
<instructor>Mariah Wilson</instructor>
<credits>3</credits>
<term>Fall 2020</term>
<schedule>
<week>1</week>
<topic>together</topic>
</schedule>
<schedule>
<week>2</week>
<topic>statement</topic>
</schedule>
<schedule>
<week>3</week>
<topic>these</topic>
</schedule>
<schedule>
<week>4</week>
<topic>American</topic>
</schedule>
<schedule>
<week>5</week>
<topic>read</topic>
</schedule>
<schedule>
<week>6</week>
<topic>age</topic>
</schedule>
<schedule>
<week>7</week>
<topic>course</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] Output contract as XML.

[Assistant]
Approach:
1. Task: Create contract 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"?>
<contract>
<term_months>34</term_months>
<parties>
<name>Garza-Henson</name>
<role>party_a</role>
</parties>
<parties>
<name>Griffin-Weaver</name>
<role>party_b</role>
</parties>
<status>executed</status>
<effective_date>2026-01-01</effective_date>
</contract>