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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<review_id>REV-9723622</review_id>
<product_id>PROD-853148</product_id>
<user_id>44919496-69de-498e-922c-5ea4230c00fa</user_id>
<rating>3</rating>
<title>Risk tell team series house.</title>
<content>Official police serve past already. Number down similar senior head amount. Focus reality really hold lose.</content>
<date>2026-01-03</date>
<verified_purchase>False</verified_purchase>
<helpful_votes>99</helpful_votes>
</customer_review>


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

[User]
Reformat the data below from JSON to XML:
{
  "rating": 5,
  "review_id": "REV-2205395",
  "content": "Respond order far story by area affect. Important also catch down choice office necessary political. Firm along bar.\nStuff create including star question traditional reflect. Share fast thought."
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<rating>5</rating>
<review_id>REV-2205395</review_id>
<content>Respond order far story by area affect. Important also catch down choice office necessary political. Firm along bar.
Stuff create including star question traditional reflect. Share fast thought.</content>
</customer_review>


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

Output:
post_id: POST-39289028
platform: instagram
user_id: a2301bd9-5c11-406a-b2a8-1c1f96bbd31c
username: rhodessharon
content: City window data describe address street. Environmental wall shoulder happy
  artist forget hospital. Chair their before reach picture serve.
timestamp: '2026-01-07T13:51:26.862472'
hashtags:
- '#yet'
- '#listen'
engagement:
  likes: 2391
  shares: 751
  comments: 108


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

[User]
Reformat the data below from YAML to JSON:
post_id: POST-19357850
platform: twitter
user_id: 664b960b-1331-492f-addd-e9b37d21656f
username: mbaldwin
content: Forward front agreement cover hour we remember ask. Read glass few word mother
  deep TV.
timestamp: '2026-01-07T13:51:27.605837'
hashtags:
- '#cost'
- '#he'
- '#relationship'
engagement:
  likes: 304
  shares: 796
  comments: 124

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

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


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

[User]
Convert the following JSON to XML:
{
  "result_id": "LAB-2983714",
  "patient_mrn": "MRN-369371",
  "order_date": "2026-01-04",
  "panel": "CMP",
  "results": [
    {
      "test": "Hemoglobin",
      "value": 97.6,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "WBC",
      "value": 60.0,
      "unit": "mg/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 172.2,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "WBC",
      "value": 145.9,
      "unit": "g/dL",
      "flag": "high"
    },
    {
      "test": "WBC",
      "value": 83.4,
      "unit": "mg/dL",
      "flag": "low"
    }
  ]
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<lab_result>
<result_id>LAB-2983714</result_id>
<patient_mrn>MRN-369371</patient_mrn>
<order_date>2026-01-04</order_date>
<panel>CMP</panel>
<results>
<test>Hemoglobin</test>
<value>97.6</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>WBC</test>
<value>60.0</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>172.2</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>WBC</test>
<value>145.9</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
<results>
<test>WBC</test>
<value>83.4</value>
<unit>mg/dL</unit>
<flag>low</flag>
</results>
</lab_result>


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

[User] Create a JSON representation of contract.

[Assistant]
Approach:
1. Task: Create contract 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:
{
  "contract_id": "CTR-123472",
  "parties": [
    {
      "name": "Palmer-White",
      "role": "party_a"
    },
    {
      "name": "Rodriguez-Moore",
      "role": "party_b"
    }
  ],
  "effective_date": "2026-01-06",
  "term_months": 59,
  "value": 388976,
  "status": "pending"
}


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

[User] Output financial report as CSV.

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

Output:
company,eps,expenses,metrics_profit_margin,metrics_roe,net_income,quarter,revenue,ticker
Harris Inc,2.68,36366080,18.37,11.92,6859279,Q2 2023,96096321,KXNS
Mullen and Sons,4.1,964025,6.08,6.89,16533345,Q2 2021,83340431,MVVB
Snyder Inc,3.79,33830279,11.9,5.98,1013080,Q3 2024,48566957,OFTZ


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<financial_report>
<company>Harris Inc</company>
<ticker>KXNS</ticker>
<quarter>Q2 2023</quarter>
<revenue>96096321</revenue>
<expenses>36366080</expenses>
<net_income>6859279</net_income>
<eps>2.68</eps>
<metrics>
<profit_margin>18.37</profit_margin>
<roe>11.92</roe>
</metrics>
</financial_report>

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

Output:
{
  "company": "Harris Inc",
  "ticker": "KXNS",
  "quarter": "Q2 2023",
  "revenue": 96096321,
  "expenses": 36366080,
  "net_income": 6859279,
  "eps": 2.68,
  "metrics": {
    "profit_margin": 18.37,
    "roe": 11.92
  }
}


[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:
{
  "views": 92789,
  "content": "Couple and teacher radio compare consumer. Pass thing much rather light.\nFoot four country subject first interview. Defense TV artist to of. Fund miss window scene.\nWish successful movement city door politics measure. Police media TV out word remain as. Report option appear station example role.",
  "shares": 213,
  "headline": "Re-engineered composite Local Area Network",
  "tags": [
    "couple",
    "this",
    "themselves",
    "whom"
  ]
}

[Assistant]
Approach:
1. Task: Convert news article 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"?>
<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 XML format. Think step-by-step, then generate syntactically perfect XML.

[User]
Transform this JSON 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 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-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 JSON format. Think step-by-step, then generate syntactically perfect JSON.

[User] Create a JSON representation of clinical note.

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

Output:
{
  "note_id": "CN-4315709",
  "patient": {
    "mrn": "MRN-534874",
    "age": 89,
    "gender": "M"
  },
  "encounter_date": "2026-01-02",
  "chief_complaint": "chest pain",
  "vitals": {
    "bp": "165/61",
    "hr": 112,
    "temp_f": 99.4
  },
  "assessment": [
    {
      "problem": "diabetes",
      "icd10": "I12"
    },
    {
      "problem": "diabetes",
      "icd10": "K62"
    }
  ]
}


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

[User]
Convert the following JSON to XML:
{
  "post_id": "POST-18209344",
  "platform": "facebook",
  "user_id": "8880ae5d-22ce-466e-ac5d-224201417b5e",
  "username": "xmcbride",
  "content": "Determine live compare center as direction. Eye experience low wear. If south level.\nWorry expect style camera. Scene majority pay voice television professor.",
  "timestamp": "2026-01-07T13:51:27.602464",
  "hashtags": [
    "#culture",
    "#whole",
    "#central"
  ],
  "engagement": {
    "likes": 2214,
    "shares": 878,
    "comments": 146
  }
}

[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-18209344</post_id>
<platform>facebook</platform>
<user_id>8880ae5d-22ce-466e-ac5d-224201417b5e</user_id>
<username>xmcbride</username>
<content>Determine live compare center as direction. Eye experience low wear. If south level.
Worry expect style camera. Scene majority pay voice television professor.</content>
<timestamp>2026-01-07T13:51:27.602464</timestamp>
<hashtags>#culture</hashtags>
<hashtags>#whole</hashtags>
<hashtags>#central</hashtags>
<engagement>
<likes>2214</likes>
<shares>878</shares>
<comments>146</comments>
</engagement>
</social_media_post>


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

[User]
Convert the following XML to YAML:
<?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>

[Assistant]
Approach:
1. Task: Convert news article 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:
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.

  Economic sit plan. Available then already skill up reason back. Course his threat
  growth physical parent truth.

  Laugh article pull goal. Believe those few.'
tags:
- hit
- summer
- official
- rather
views: 75669
shares: 293


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

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

[Assistant]
Approach:
1. Task: Create customer review in CSV
2. Complexity: 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:
category,content,currency,date,helpful_votes,is_available,name,price,product_id,rating,review_id,reviews,specs_dimensions,specs_weight_kg,stock,title,user_id,verified_purchase
,"I stay little Democrat money where stop. Than development activity.
Along ahead their standard early",,2026-01-05,94,,,,PROD-499626,1,REV-1384784,,,,,Respond out five.,4c396b1f-b1b7-4ef7-9587-0fda03a6f7f9,False
clothing,,USD,,,True,Diverse 24hour capacity,131.84,PROD-283364,1.32,,84,100x78x13cm,3.49,819,,,
clothing,,USD,,,True,Switchable zero-defect architecture,760.42,PROD-170009,1.05,,195,50x100x85cm,8.8,780,,,
books,,USD,,,True,Sharable mobile Graphic Interface,292.26,PROD-458849,3.2,,846,58x35x93cm,22.63,269,,,
clothing,,USD,,,True,Cross-group composite Internet solution,720.16,PROD-581074,2.97,,220,90x66x88cm,33.25,949,,,


[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"?>
<product_listing>
<product_id>PROD-986141</product_id>
<name>Focused neutral encoding</name>
<category>books</category>
<price>14.45</price>
<currency>USD</currency>
<stock>826</stock>
<is_available>True</is_available>
<rating>4.59</rating>
<reviews>564</reviews>
<specs>
<weight_kg>27.7</weight_kg>
<dimensions>42x99x90cm</dimensions>
</specs>
</product_listing>

[Assistant]
Approach:
1. Task: Convert product listing 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:
{
  "product_id": "PROD-986141",
  "name": "Focused neutral encoding",
  "category": "books",
  "price": 14.45,
  "currency": "USD",
  "stock": 826,
  "is_available": true,
  "rating": 4.59,
  "reviews": 564,
  "specs": {
    "weight_kg": 27.7,
    "dimensions": "42x99x90cm"
  }
}


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

[User] Generate api specification data in TOML format.

[Assistant]
Approach:
1. Task: Create api specification 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:
openapi = "3.0.0"

[info]
title = "Implemented leadingedge groupware API"
version = "1.0.0"

[paths."/reveal".get]
summary = "Parent dark five."
[[paths."/reveal".get.parameters]]
name = "param0"
in = "query"
type = "string"

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

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

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

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


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

[User]
Convert the following JSON to XML:
{
  "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"
}

[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-766800</assessment_id>
<student_id>STU-927295</student_id>
<course_id>CRS-8819</course_id>
<type>assignment</type>
<date>2026-01-03</date>
<scores>
<question>1</question>
<points_earned>8</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>3</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>3</question>
<points_earned>8</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>1</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>0</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>4</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>9</question>
<points_earned>3</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>99</total_score>
<percentage>71.71</percentage>
<grade>A</grade>
</student_assessment>


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<research_paper>
<title>Polarized methodical algorithm</title>
<authors>
<name>Caroline Barnes</name>
<affiliation>Parker Ltd</affiliation>
<email>angelajackson@example.net</email>
</authors>
<authors>
<name>Mario Boyd</name>
<affiliation>Johnson, Barber and Higgins</affiliation>
<email>lfuller@example.com</email>
</authors>
<funding_source />
</research_paper>

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

Output:
{
  "title": "Polarized methodical algorithm",
  "authors": [
    {
      "name": "Caroline Barnes",
      "affiliation": "Parker Ltd",
      "email": "angelajackson@example.net"
    },
    {
      "name": "Mario Boyd",
      "affiliation": "Johnson, Barber and Higgins",
      "email": "lfuller@example.com"
    }
  ],
  "funding_source": null
}


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

[User]
Transform this TOML data into JSON format:
period = "February 2022"
total_revenue = 6033804
units_sold = 27183
[[channels]]
name = "wholesale"
revenue = 4147239
growth = 40.37

[[channels]]
name = "online"
revenue = 2663137
growth = 9.96

[[top_products]]
sku = "SKU-2538"
sales = 420940

[[top_products]]
sku = "SKU-8680"
sales = 364206

[[top_products]]
sku = "SKU-2062"
sales = 350623

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

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

[User]
Reformat the data below from YAML to CSV:
schedule:
- week: 1
  topic: table
- week: 2
  topic: team
- week: 3
  topic: miss
- week: 4
  topic: face
- week: 5
  topic: sort
- week: 6
  topic: board
- week: 7
  topic: effect
- week: 8
  topic: still
- week: 9
  topic: training
- week: 10
  topic: different
code: GHC481
grading:
  homework: 30
  midterm: 30
  final: 40
term: Spring 2020
credits: 4

[Assistant]
Approach:
1. Task: Convert course syllabus from YAML 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:
abstract,authors,citations,code,credits,funding_source,grading_final,grading_homework,grading_midterm,keywords,paper_id,publication_doi,publication_venue,publication_year,schedule,term,title
,,,GHC481,4,,40,30,30,,,,,,"[{""week"": 1, ""topic"": ""table""}, {""week"": 2, ""topic"": ""team""}, {""week"": 3, ""topic"": ""miss""}, {""week"":",Spring 2020,
Law move western heart owner catch event. Ability with minute those attorney present meet. See start,"[{""name"": ""Dana Klein"", ""affiliation"": ""Flynn, Daniels and Humphrey"", ""email"": ""latoya73@example.net",190,,,Roberts-Bowen,,,,"[""back"", ""at"", ""body"", ""some"", ""especially""]",arXiv:2021.27593,10.1016/ZWJq,Nature,2020,,,Operative discrete Local Area Network
Event method half up. Offer movie direction president occur list.,"[{""name"": ""Ashley Webb"", ""affiliation"": ""Griffith, Stewart and Hernandez"", ""email"": ""lewisalejandra@",153,,,Bryant Ltd,,,,"[""ahead"", ""know"", ""truth""]",arXiv:2023.17476,10.8768/EaZG,Cell,2022,,,Profit-focused zero tolerance complexity
"Wait but most ten price life way.
Choose I discover alone government high important.","[{""name"": ""Jason Stephens"", ""affiliation"": ""Roberts and Sons"", ""email"": ""vincentyates@example.org""},",436,,,Fields-Stone,,,,"[""hand"", ""per"", ""idea"", ""also""]",arXiv:2023.26758,10.3984/WfES,Science,2024,,,Open-architected even-keeled attitude


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

[User] Create a TOML representation of clinical note.

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

Output:
note_id = "CN-2341842"
encounter_date = "2026-01-01"
chief_complaint = "fever"
[[assessment]]
problem = "diabetes"
icd10 = "I65"

[[assessment]]
problem = "diabetes"
icd10 = "J29"

[patient]
mrn = "MRN-739833"
age = 85
gender = "F"

[vitals]
bp = "174/60"
hr = 60
temp_f = 98.7


[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-9548003"
patient_mrn = "MRN-322322"
order_date = "2026-01-03"
panel = "CMP"
[[results]]
test = "Glucose"
value = 67.0
unit = "g/dL"
flag = "high"

[[results]]
test = "Hemoglobin"
value = 66.7
unit = "mg/dL"
flag = "low"

[[results]]
test = "Glucose"
value = 118.1
unit = "mg/dL"
flag = "normal"

[[results]]
test = "Hemoglobin"
value = 198.6
unit = "mg/dL"
flag = "normal"

[[results]]
test = "Glucose"
value = 167.9
unit = "mg/dL"
flag = "low"

[[results]]
test = "Hemoglobin"
value = 143.5
unit = "mg/dL"
flag = "normal"

[[results]]
test = "Glucose"
value = 150.3
unit = "g/dL"
flag = "low"


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

[User] Output financial report as YAML.

[Assistant]
Approach:
1. Task: Create financial report 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:
company: Leon-Lewis
ticker: FGCI
quarter: Q4 2022
revenue: 56885685
expenses: 46362888
net_income: 14538939
eps: 7.9
metrics:
  profit_margin: 25.04
  roe: 5.27


[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:
{
  "experiment_id": "EXP-574681",
  "title": "Effect of anyone on society",
  "methodology": {
    "design": "cohort",
    "sample_size": 560,
    "duration_days": 320
  },
  "results": [
    {
      "metric": "efficacy",
      "baseline": 50.77,
      "endpoint": 70.83,
      "p_value": 0.3046
    },
    {
      "metric": "efficacy",
      "baseline": 96.52,
      "endpoint": 82.25,
      "p_value": 0.0326
    },
    {
      "metric": "safety",
      "baseline": 43.38,
      "endpoint": 72.88,
      "p_value": 0.2787
    },
    {
      "metric": "safety",
      "baseline": 17.71,
      "endpoint": 95.37,
      "p_value": 0.4542
    }
  ],
  "conclusion": "non-significant"
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<experiment_result>
<experiment_id>EXP-574681</experiment_id>
<title>Effect of anyone on society</title>
<methodology>
<design>cohort</design>
<sample_size>560</sample_size>
<duration_days>320</duration_days>
</methodology>
<results>
<metric>efficacy</metric>
<baseline>50.77</baseline>
<endpoint>70.83</endpoint>
<p_value>0.3046</p_value>
</results>
<results>
<metric>efficacy</metric>
<baseline>96.52</baseline>
<endpoint>82.25</endpoint>
<p_value>0.0326</p_value>
</results>
<results>
<metric>safety</metric>
<baseline>43.38</baseline>
<endpoint>72.88</endpoint>
<p_value>0.2787</p_value>
</results>
<results>
<metric>safety</metric>
<baseline>17.71</baseline>
<endpoint>95.37</endpoint>
<p_value>0.4542</p_value>
</results>
<conclusion>non-significant</conclusion>
</experiment_result>


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

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

[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-66277640",
  "platform": "instagram",
  "user_id": "7e83a029-16e2-49ad-a855-906c882abe46",
  "username": "reynoldstaylor",
  "content": "Thousand book animal myself wear beautiful. Room rock couple reality her.\nJoin town travel agency value improve way. Heavy late science mind develop consider ability.",
  "timestamp": "2026-01-07T13:51:26.676406",
  "hashtags": [
    "#case",
    "#along",
    "#only",
    "#have"
  ],
  "engagement": {
    "likes": 9942,
    "shares": 119,
    "comments": 368
  }
}


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

[User] Create a TOML representation of api specification.

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

Output:
openapi = "3.0.0"

[info]
title = "Assimilated neutral archive API"
version = "1.0.0"

[paths."/sea".get]
summary = "Team happen challenge address expert manage beyond"
[[paths."/sea".get.parameters]]
name = "param0"
in = "query"
type = "string"

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

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

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

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


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

[User]
Convert the following JSON to XML:
{
  "article_id": "ART-4067367",
  "headline": "Polarized human-resource adapter",
  "author": "Kristin Larson",
  "published": "2026-01-07T00:05:34.405255",
  "section": "Business",
  "content": "Ahead effort author use. Unit together series provide arrive country off. Whether let thought down.\nEight audience power analysis. Age hope leader yeah without. Experience kitchen heart city.",
  "tags": [
    "program",
    "final",
    "computer",
    "live"
  ],
  "views": 74807,
  "shares": 3986
}

[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-4067367</article_id>
<headline>Polarized human-resource adapter</headline>
<author>Kristin Larson</author>
<published>2026-01-07T00:05:34.405255</published>

Business

<content>Ahead effort author use. Unit together series provide arrive country off. Whether let thought down.
Eight audience power analysis. Age hope leader yeah without. Experience kitchen heart city.</content>
<tags>program</tags>
<tags>final</tags>
<tags>computer</tags>
<tags>live</tags>
<views>74807</views>
<shares>3986</shares>
</news_article>


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

[User] Output api specification as TOML.

[Assistant]
Approach:
1. Task: Create api specification 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:
openapi = "3.0.0"

[info]
title = "Multi-tiered directional knowledge user API"
version = "1.0.0"

[paths."/require".get]
summary = "Suffer kid pull bed decision rest."
[[paths."/require".get.parameters]]
name = "param0"
in = "query"
type = "string"

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

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

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

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


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

[User] Create a XML representation of api specification.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<api_specification>
<info>
<title>Multi-tiered directional knowledge user API</title>
<version>1.0.0</version>
</info>
<openapi>3.0.0</openapi>
<paths>
</require>
<get>
<summary>Suffer kid pull bed decision rest.</summary>
<parameters>
<name>param0</name>
<in>query</in>
<type>string</type>
</parameters>
<parameters>
<name>param1</name>
<in>query</in>
<type>string</type>
</parameters>
<parameters>
<name>param2</name>
<in>query</in>
<type>string</type>
</parameters>
<responses>
<200>
<description>Success</description>
</200>
<400>
<description>Bad Request</description>
</400>
</responses>
</get>
<//require>
</paths>
</api_specification>


[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: 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,effective_date,funding_source,keywords,paper_id,publication_doi,publication_venue,publication_year,status,term_months,title
,,,2026-01-02,,,,,,,pending,54,
They pattern adult plant tell contain point. Special none man by same party magazine.,"[{""name"": ""Stephanie Kline"", ""affiliation"": ""Davis, Doyle and Smith"", ""email"": ""dawn74@example.net""}",240,,Hernandez Inc,"[""office"", ""father"", ""prepare"", ""low""]",arXiv:2023.61366,10.5021/PALz,Science,2023,,,Organized disintermediate superstructure
Couple oil executive. Business low send than. Treat worry move pull forget begin few boy.,"[{""name"": ""Benjamin Williams"", ""affiliation"": ""Lynch and Sons"", ""email"": ""smitherin@example.org""}, {",94,,None,"[""computer"", ""smile"", ""save"", ""hot"", ""wide""]",arXiv:2023.69035,10.7541/TTLX,Cell,2023,,,Upgradable clear-thinking infrastructure
"Face financial crime tell life determine. Unit present can expect discuss.
Actually spend him when p","[{""name"": ""Mary Thomas"", ""affiliation"": ""Martinez, Reynolds and Erickson"", ""email"": ""kmiller@example",217,,None,"[""activity"", ""street"", ""will""]",arXiv:2020.74346,10.9206/HUYW,Science,2024,,,Reactive reciprocal database
None appear generation foreign commercial follow. Strategy run coach few. Success reach money.,"[{""name"": ""Cassandra Mayer"", ""affiliation"": ""Welch, Lopez and Tucker"", ""email"": ""ctanner@example.net",152,,"Smith, Hays and Lewis","[""commercial"", ""drop"", ""age"", ""across""]",arXiv:2022.43774,10.7575/BUIi,Cell,2023,,,Function-based attitude-oriented moderator


[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"?>
<course_syllabus>
<course_id>CRS-6496</course_id>
TMG245
<instructor>Maria Bowers</instructor>
<schedule>
<week>1</week>
<topic>situation</topic>
</schedule>
<schedule>
<week>2</week>
<topic>firm</topic>
</schedule>
<schedule>
<week>3</week>
<topic>involve</topic>
</schedule>
<schedule>
<week>4</week>
<topic>change</topic>
</schedule>
<schedule>
<week>5</week>
<topic>yard</topic>
</schedule>
<schedule>
<week>6</week>
<topic>morning</topic>
</schedule>
<schedule>
<week>7</week>
<topic>other</topic>
</schedule>
<schedule>
<week>8</week>
<topic>left</topic>
</schedule>
</course_syllabus>

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

Output:
{
  "course_id": "CRS-6496",
  "code": "TMG245",
  "instructor": "Maria Bowers",
  "schedule": [
    {
      "week": 1,
      "topic": "situation"
    },
    {
      "week": 2,
      "topic": "firm"
    },
    {
      "week": 3,
      "topic": "involve"
    },
    {
      "week": 4,
      "topic": "change"
    },
    {
      "week": 5,
      "topic": "yard"
    },
    {
      "week": 6,
      "topic": "morning"
    },
    {
      "week": 7,
      "topic": "other"
    },
    {
      "week": 8,
      "topic": "left"
    }
  ]
}


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

[User]
Reformat the data below from JSON to XML:
{
  "openapi": "3.0.0",
  "info": {
    "title": "Grass-roots 6thgeneration ability API",
    "version": "1.0.0"
  },
  "paths": {
    "/million": {
      "get": {
        "summary": "About little above investment already magazine.",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  }
}

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

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


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

[User] Output sales analytics as CSV.

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

Output:
abstract,authors,channels,citations,funding_source,keywords,paper_id,period,publication_doi,publication_venue,publication_year,title,top_products,total_revenue,units_sold
,,"[{""name"": ""wholesale"", ""revenue"": 2316482, ""growth"": -1.07}, {""name"": ""online"", ""revenue"": 3744469, ",,,,,December 2023,,,,,"[{""sku"": ""SKU-4601"", ""sales"": 454934}, {""sku"": ""SKU-9892"", ""sales"": 55264}, {""sku"": ""SKU-8319"", ""sal",5338205,90572
Necessary ground him entire behind thing spend. Decide there against general newspaper popular. Soci,"[{""name"": ""Michael Schmidt"", ""affiliation"": ""Saunders, Lopez and Todd"", ""email"": ""wthompson@example.",,248,Powers-Bird,"[""drive"", ""stand"", ""white""]",arXiv:2023.61228,,10.6053/oPeS,Nature,2023,Enhanced 24/7 knowledgebase,,,
"Result several give will court.
Season today level its. Window soon already myself.","[{""name"": ""Bridget Fisher"", ""affiliation"": ""Cole-Gibson"", ""email"": ""jessica24@example.com""}, {""name""",,276,"Chapman, Smith and Sanchez","[""move"", ""full"", ""game"", ""challenge""]",arXiv:2020.27018,,10.1331/ipgf,Cell,2022,Reactive bandwidth-monitored software,,,


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

[User] Generate error log data in JSON format.

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

Output:
{
  "error_id": "c6e14566-270a-4a5f-a250-5239ca9174ac",
  "timestamp": "2026-01-07T13:51:26.338486",
  "level": "ERROR",
  "service": "humanService",
  "message": "Fear she east talk better central.",
  "stack_trace": [
    "at college.py:218",
    "at economy.py:209",
    "at let.py:252",
    "at whole.py:18"
  ],
  "context": {
    "user_id": "bda2bdb3-cc4e-4711-8927-aa42dc72d462",
    "request_id": "c7d51186-07ee-4743-a193-c5688ac0d6c5"
  }
}


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

[User]
Transform this JSON data into XML format:
{
  "paper_id": "arXiv:2022.87629",
  "title": "Decentralized zero tolerance knowledgebase",
  "authors": [
    {
      "name": "Jonathan Murphy",
      "affiliation": "Long and Sons",
      "email": "loconnell@example.org"
    },
    {
      "name": "Patrick Skinner",
      "affiliation": "Williams and Sons",
      "email": "chentimothy@example.org"
    },
    {
      "name": "Todd Smith",
      "affiliation": "Lewis LLC",
      "email": "nedwards@example.org"
    }
  ],
  "abstract": "System many view vote. Into challenge wind result new good.",
  "keywords": [
    "modern",
    "over",
    "during",
    "affect",
    "sport"
  ],
  "publication": {
    "venue": "Cell",
    "year": 2022,
    "doi": "10.5354/mlMa"
  },
  "citations": 187,
  "funding_source": "Fischer and Sons"
}

[Assistant]
Approach:
1. Task: Convert research paper 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"?>
<research_paper>
<paper_id>arXiv:2022.87629</paper_id>
<title>Decentralized zero tolerance knowledgebase</title>
<authors>
<name>Jonathan Murphy</name>
<affiliation>Long and Sons</affiliation>
<email>loconnell@example.org</email>
</authors>
<authors>
<name>Patrick Skinner</name>
<affiliation>Williams and Sons</affiliation>
<email>chentimothy@example.org</email>
</authors>
<authors>
<name>Todd Smith</name>
<affiliation>Lewis LLC</affiliation>
<email>nedwards@example.org</email>
</authors>
<abstract>System many view vote. Into challenge wind result new good.</abstract>
<keywords>modern</keywords>
<keywords>over</keywords>
<keywords>during</keywords>
<keywords>affect</keywords>
<keywords>sport</keywords>
<publication>
<venue>Cell</venue>
<year>2022</year>
<doi>10.5354/mlMa</doi>
</publication>
<citations>187</citations>
<funding_source>Fischer and Sons</funding_source>
</research_paper>


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

[User] Generate contract data in TOML format.

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

[[parties]]
name = "Roberts Ltd"
role = "party_b"


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

[User] Output customer review as YAML.

[Assistant]
Approach:
1. Task: Create customer review in YAML
2. Complexity: 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:
helpful_votes: 39
date: '2026-01-04'
rating: 5
review_id: REV-1864702
title: State standard bad message use.


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

[User] Generate experiment result data in CSV format.

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

Output:
conclusion,experiment_id,methodology_design,methodology_duration_days,methodology_sample_size,results,title
non-significant,EXP-160417,cohort,354,663,"[{""metric"": ""safety"", ""baseline"": 13.92, ""endpoint"": 49.07, ""p_value"": 0.4102}, {""metric"": ""safety"",",Effect of agree on both
significant,EXP-890740,observational,157,229,"[{""metric"": ""efficacy"", ""baseline"": 57.73, ""endpoint"": 75.47, ""p_value"": 0.495}, {""metric"": ""efficac",Effect of Democrat on success
non-significant,EXP-254862,RCT,86,504,"[{""metric"": ""safety"", ""baseline"": 30.68, ""endpoint"": 65.63, ""p_value"": 0.226}, {""metric"": ""safety"", ",Effect of floor on great


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

Output:
{
  "note_id": "CN-4441974",
  "patient": {
    "mrn": "MRN-925906",
    "age": 60,
    "gender": "F"
  },
  "encounter_date": "2026-01-02",
  "chief_complaint": "headache",
  "vitals": {
    "bp": "154/95",
    "hr": 108,
    "temp_f": 97.8
  },
  "assessment": [
    {
      "problem": "diabetes",
      "icd10": "J60"
    },
    {
      "problem": "hypertension",
      "icd10": "I21"
    },
    {
      "problem": "diabetes",
      "icd10": "K16"
    }
  ]
}


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

[User]
Transform this JSON data into XML format:
{
  "result_id": "LAB-2309770",
  "patient_mrn": "MRN-380513",
  "order_date": "2026-01-02",
  "panel": "CMP",
  "results": [
    {
      "test": "Glucose",
      "value": 62.8,
      "unit": "mg/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 141.2,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "WBC",
      "value": 75.4,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "Glucose",
      "value": 174.6,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "Glucose",
      "value": 170.1,
      "unit": "g/dL",
      "flag": "low"
    }
  ]
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<lab_result>
<result_id>LAB-2309770</result_id>
<patient_mrn>MRN-380513</patient_mrn>
<order_date>2026-01-02</order_date>
<panel>CMP</panel>
<results>
<test>Glucose</test>
<value>62.8</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>141.2</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>WBC</test>
<value>75.4</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Glucose</test>
<value>174.6</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Glucose</test>
<value>170.1</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
</lab_result>


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<product_listing>
<product_id>PROD-942707</product_id>
<name>Organic demand-driven installation</name>
<category>books</category>
<price>698.66</price>
<currency>USD</currency>
<stock>819</stock>
<is_available>True</is_available>
<rating>4.45</rating>
<reviews>103</reviews>
<specs>
<weight_kg>32.63</weight_kg>
<dimensions>66x30x83cm</dimensions>
</specs>
</product_listing>

[Assistant]
Approach:
1. Task: Convert product listing 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:
{
  "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 TOML format. Think step-by-step, then generate syntactically perfect TOML.

[User]
Reformat the data below from YAML to TOML:
rx_id: RX-3472120
patient_mrn: MRN-972429
prescriber: Matthew Bennett
date: '2026-01-06'
medications:
- name: Atorvastatin
  dosage: 10mg
  frequency: daily
  quantity: 60

[Assistant]
Approach:
1. Task: Convert prescription from YAML 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-3472120"
patient_mrn = "MRN-972429"
prescriber = "Matthew Bennett"
date = "2026-01-06"
[[medications]]
name = "Atorvastatin"
dosage = "10mg"
frequency = "daily"
quantity = 60


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

[User] Output student assessment as TOML.

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

Output:
assessment_id = "ASMT-530397"
student_id = "STU-509684"
course_id = "CRS-8191"
type = "quiz"
date = "2026-01-01"
total_score = 91
percentage = 61.03
grade = "A"
[[scores]]
question = 1
points_earned = 3
points_possible = 10

[[scores]]
question = 2
points_earned = 5
points_possible = 10

[[scores]]
question = 3
points_earned = 4
points_possible = 10

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

[[scores]]
question = 5
points_earned = 0
points_possible = 10

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

[[scores]]
question = 7
points_earned = 3
points_possible = 10

[[scores]]
question = 8
points_earned = 6
points_possible = 10

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

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

[[scores]]
question = 11
points_earned = 7
points_possible = 10

[[scores]]
question = 12
points_earned = 9
points_possible = 10

[[scores]]
question = 13
points_earned = 2
points_possible = 10

[[scores]]
question = 14
points_earned = 7
points_possible = 10


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

[User] Output lab result as CSV.

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

Output:
order_date,panel,patient_mrn,result_id,results
2026-01-06,CMP,MRN-755137,LAB-1812594,"[{""test"": ""Glucose"", ""value"": 131.9, ""unit"": ""mg/dL"", ""flag"": ""normal""}, {""test"": ""Glucose"", ""value"""
2026-01-02,CBC,MRN-692743,LAB-7038079,"[{""test"": ""WBC"", ""value"": 67.2, ""unit"": ""mg/dL"", ""flag"": ""normal""}, {""test"": ""Glucose"", ""value"": 138"
2026-01-06,CMP,MRN-547924,LAB-8394339,"[{""test"": ""Hemoglobin"", ""value"": 87.2, ""unit"": ""g/dL"", ""flag"": ""high""}, {""test"": ""Hemoglobin"", ""valu"


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

[User] Output prescription as XML.

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


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

[User] Generate prescription data in TOML format.

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

Output:
rx_id = "RX-9442688"
patient_mrn = "MRN-277514"
prescriber = "Timothy Goodman"
date = "2026-01-04"
[[medications]]
name = "Metformin"
dosage = "20mg"
frequency = "TID"
quantity = 30

[[medications]]
name = "Metformin"
dosage = "5mg"
frequency = "BID"
quantity = 30

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


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<review_id>REV-2971879</review_id>
<product_id>PROD-601177</product_id>
<user_id>49ec79ac-cc63-409f-8812-a70c492b6835</user_id>
<rating>3</rating>
<title>Safe everything country understand subject.</title>
<content>Explain among above role speech. Hear law enjoy. Lose building fall everything million.
East choose however class dark test good contain. Indicate worker mean hot.</content>
<date>2026-01-06</date>
<verified_purchase>True</verified_purchase>
<helpful_votes>67</helpful_votes>
</customer_review>

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


[System] You are an expert in 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"?>
<product_listing>
<product_id>PROD-738287</product_id>
<name>Function-based dedicated installation</name>
<category>electronics</category>
<price>364.53</price>
<currency>USD</currency>
<stock>956</stock>
<is_available>True</is_available>
<rating>1.64</rating>
<reviews>854</reviews>
<specs>
<weight_kg>19.72</weight_kg>
<dimensions>48x33x88cm</dimensions>
</specs>
</product_listing>

[Assistant]
Approach:
1. Task: Convert product listing 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:
{
  "product_id": "PROD-738287",
  "name": "Function-based dedicated installation",
  "category": "electronics",
  "price": 364.53,
  "currency": "USD",
  "stock": 956,
  "is_available": true,
  "rating": 1.64,
  "reviews": 854,
  "specs": {
    "weight_kg": 19.72,
    "dimensions": "48x33x88cm"
  }
}


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

[User] Create a XML representation of news article.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<news_article>
<article_id>ART-2188860</article_id>
<headline>Advanced well-modulated service-desk</headline>
<author>Michael Logan</author>
<published>2026-01-03T08:09:52.608144</published>

Politics

<content>Include start build no effort continue. Mention sister mention threat.
Choose herself case writer question over. Hand quickly house send shoulder expert hour.
All probably suffer law consider kitchen relationship. Data population personal past security but across.</content>
<tags>hear</tags>
<tags>civil</tags>
<tags>might</tags>
<tags>way</tags>
<tags>win</tags>
<views>35184</views>
<shares>1092</shares>
</news_article>


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

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

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

Output:
{
  "error_id": "fd278ff8-fdfc-4b1d-81ec-31cf5ce70502",
  "timestamp": "2026-01-07T13:51:26.554266",
  "level": "ERROR",
  "service": "heartService",
  "message": "Attack candidate in give wish tree.",
  "stack_trace": [
    "at thousand.py:354",
    "at forget.py:20",
    "at consider.py:392"
  ],
  "context": {
    "user_id": "d753ac0c-8931-4c37-8bd5-01413aaaba41",
    "request_id": "b35b2bd7-dc59-4d80-ba5d-dc21fa7f0bf7"
  }
}


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

[User]
Convert the following JSON to XML:
{
  "review_id": "REV-1369973",
  "product_id": "PROD-861575",
  "user_id": "a55bb48c-5dcb-464a-b952-9d377a4cb9c4",
  "rating": 1,
  "title": "Relationship job find one allow law through.",
  "content": "Now decide senior fact big window yourself. Difference appear seat coach rather once politics. Modern always able physical Republican best draw land.",
  "date": "2026-01-02",
  "verified_purchase": true,
  "helpful_votes": 8
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<review_id>REV-1369973</review_id>
<product_id>PROD-861575</product_id>
<user_id>a55bb48c-5dcb-464a-b952-9d377a4cb9c4</user_id>
<rating>1</rating>
<title>Relationship job find one allow law through.</title>
<content>Now decide senior fact big window yourself. Difference appear seat coach rather once politics. Modern always able physical Republican best draw land.</content>
<date>2026-01-02</date>
<verified_purchase>True</verified_purchase>
<helpful_votes>8</helpful_votes>
</customer_review>


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

[User]
Transform this JSON data into CSV format:
{
  "product_id": "PROD-308726",
  "name": "Cross-platform client-server attitude",
  "category": "electronics",
  "price": 875.12,
  "currency": "USD",
  "stock": 161,
  "is_available": true,
  "rating": 1.18,
  "reviews": 705,
  "specs": {
    "weight_kg": 37.34,
    "dimensions": "78x81x41cm"
  }
}

[Assistant]
Approach:
1. Task: Convert product listing from JSON to 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. Transform values to match the target format specifications.

Output:
category,currency,is_available,name,price,product_id,rating,reviews,specs_dimensions,specs_weight_kg,stock
electronics,USD,True,Cross-platform client-server attitude,875.12,PROD-308726,1.18,705,78x81x41cm,37.34,161
clothing,USD,True,Front-line responsive access,180.26,PROD-328602,4.6,235,26x49x54cm,22.71,166
electronics,USD,True,Upgradable methodical framework,715.27,PROD-742433,3.77,956,67x98x22cm,2.65,380
clothing,USD,True,Focused object-oriented monitoring,284.93,PROD-399576,4.3,858,63x31x39cm,24.02,950
electronics,USD,True,Devolved 24/7 circuit,803.8,PROD-188320,3.15,515,51x38x55cm,41.73,998


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

[User]
Transform this JSON data into YAML format:
{
  "term_months": 34,
  "parties": [
    {
      "name": "Garza-Henson",
      "role": "party_a"
    },
    {
      "name": "Griffin-Weaver",
      "role": "party_b"
    }
  ],
  "status": "executed",
  "effective_date": "2026-01-01"
}

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

Output:
term_months: 34
parties:
- name: Garza-Henson
  role: party_a
- name: Griffin-Weaver
  role: party_b
status: executed
effective_date: '2026-01-01'


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

[User] Generate customer review data in CSV format.

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

Output:
category,content,currency,date,helpful_votes,is_available,name,price,product_id,rating,review_id,reviews,specs_dimensions,specs_weight_kg,stock,title,user_id,verified_purchase
,Candidate stuff mission end nature hundred. Recently game stage agreement. Seem central blood add en,,2026-01-01,8,,,,PROD-542599,3,REV-9529513,,,,,Money face statement talk day.,67bb80c4-7c72-4c1b-886f-8186f18f45e3,True
books,,USD,,,True,Synergized object-oriented data-warehouse,270.97,PROD-646408,3.59,,582,89x91x51cm,47.2,728,,,
clothing,,USD,,,True,Customizable multi-tasking parallelism,863.93,PROD-630531,4.12,,745,56x31x27cm,37.68,837,,,
electronics,,USD,,,True,Grass-roots systematic frame,61.72,PROD-395121,2.85,,38,20x99x57cm,48.82,910,,,
electronics,,USD,,,True,Fundamental logistical success,756.33,PROD-973596,2.97,,766,36x57x61cm,43.96,230,,,


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

[User] Create a TOML representation of error log.

[Assistant]
Approach:
1. Task: Create error log in TOML
2. Complexity: 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:
error_id = "042db0a1-c9b1-49a9-9d69-5247a8c47159"
timestamp = "2026-01-07T13:51:27.377057"
level = "ERROR"
service = "whomService"
message = "Each reality trip red enough tough common."
stack_trace = [ "at note.py:398", "at purpose.py:452", "at onto.py:106", "at member.py:439",]

[context]
user_id = "70c0c786-0e43-42b2-8ec7-e975f39a71f7"
request_id = "95ca942a-a33a-413f-b1a1-a21e12fa0f30"


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

[User] Output customer review as XML.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<review_id>REV-5650887</review_id>
<product_id>PROD-601157</product_id>
<user_id>ac7725ae-2567-44d1-8d40-a64432b9801b</user_id>
<rating>3</rating>
<title>Personal order single check off but my.</title>
<content>Key Mrs say because walk old certainly. Product figure event choice.
Skill cut plan per side same. Between common join partner kid enter page discover.</content>
<date>2026-01-06</date>
<verified_purchase>True</verified_purchase>
<helpful_votes>66</helpful_votes>
</customer_review>


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

[User] Generate prescription data in TOML format.

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

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

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


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

[User] Create a XML representation of financial report.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<financial_report>
<company>Thompson LLC</company>
<ticker>QQLN</ticker>
<quarter>Q2 2020</quarter>
<revenue>63838743</revenue>
<expenses>967762</expenses>
<net_income>16633381</net_income>
<eps>0.69</eps>
<metrics>
<profit_margin>22.56</profit_margin>
<roe>23.58</roe>
</metrics>
</financial_report>


[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:
{
  "error_id": "3ee04eb7-6a96-4708-8070-7816402d081f",
  "timestamp": "2026-01-07T13:51:26.236854",
  "level": "ERROR",
  "service": "checkService",
  "message": "Base information cell production decade back.",
  "stack_trace": [
    "at quality.py:463",
    "at but.py:317"
  ],
  "context": {
    "user_id": "9d5113f2-65b2-4f61-b9b2-2b011fc1bc1b",
    "request_id": "f5a78ca9-3dcc-4c14-bcea-f5b7936cdde5"
  }
}

[Assistant]
Approach:
1. Task: Convert error log 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"?>
<error_log>
<error_id>3ee04eb7-6a96-4708-8070-7816402d081f</error_id>
<timestamp>2026-01-07T13:51:26.236854</timestamp>
<level>ERROR</level>
<service>checkService</service>
<message>Base information cell production decade back.</message>
<stack_trace>at quality.py:463</stack_trace>
<stack_trace>at but.py:317</stack_trace>
<context>
<user_id>9d5113f2-65b2-4f61-b9b2-2b011fc1bc1b</user_id>
<request_id>f5a78ca9-3dcc-4c14-bcea-f5b7936cdde5</request_id>
</context>
</error_log>


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

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

[Assistant]
Approach:
1. Task: Create social media post in XML
2. Complexity: 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"?>
<social_media_post>
<post_id>POST-58883169</post_id>
<user_id>9fc1586a-703b-4459-a18b-2f5e0582ab64</user_id>
<username>alexandra57</username>
</social_media_post>


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

[User] Generate lab result data in TOML format.

[Assistant]
Approach:
1. Task: Create lab result in TOML
2. Complexity: 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:
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"

[[results]]
test = "Glucose"
value = 160.2
unit = "mg/dL"
flag = "normal"

[[results]]
test = "WBC"
value = 142.4
unit = "g/dL"
flag = "normal"

[[results]]
test = "Glucose"
value = 179.9
unit = "mg/dL"
flag = "normal"

[[results]]
test = "Hemoglobin"
value = 97.3
unit = "g/dL"
flag = "normal"

[[results]]
test = "Hemoglobin"
value = 148.5
unit = "g/dL"
flag = "high"

[[results]]
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 YAML to XML:
error_id: 385c5830-2f90-42e3-ae2f-53faace4448a
timestamp: '2026-01-07T13:51:26.292009'
level: CRITICAL
service: almostService
message: People party agreement mother that investment approach.
stack_trace:
- at fight.py:491
- at city.py:369
- at statement.py:378
context:
  user_id: 264dfcb4-39aa-45b1-999f-d115795470f4
  request_id: 4c579c9e-314d-44f6-9e5a-9c3c95ea5e82

[Assistant]
Approach:
1. Task: Convert error log 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"?>
<error_log>
<error_id>385c5830-2f90-42e3-ae2f-53faace4448a</error_id>
<timestamp>2026-01-07T13:51:26.292009</timestamp>
<level>CRITICAL</level>
<service>almostService</service>
<message>People party agreement mother that investment approach.</message>
<stack_trace>at fight.py:491</stack_trace>
<stack_trace>at city.py:369</stack_trace>
<stack_trace>at statement.py:378</stack_trace>
<context>
<user_id>264dfcb4-39aa-45b1-999f-d115795470f4</user_id>
<request_id>4c579c9e-314d-44f6-9e5a-9c3c95ea5e82</request_id>
</context>
</error_log>


[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:
{
  "verified_purchase": true,
  "title": "Country especially hand.",
  "review_id": "REV-4835597",
  "product_id": "PROD-713270"
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<verified_purchase>True</verified_purchase>
<title>Country especially hand.</title>
<review_id>REV-4835597</review_id>
<product_id>PROD-713270</product_id>
</customer_review>


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

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

[Assistant]
Approach:
1. Task: Create error log in CSV
2. Complexity: 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,context_request_id,context_user_id,error_id,funding_source,keywords,paper_id,publication_doi,publication_venue,publication_year,timestamp,title
,,,d8c0cfbc-2ae8-46b8-8db8-ee3a71153dc5,3a96bf92-d9b7-4f9e-91da-6a15b590d5cf,de32926d-7560-4176-8c16-f346784a78af,,,,,,,2026-01-07T13:51:26.818902,
Situation hand chance ahead citizen special thank another. Your political lawyer small artist determ,"[{""name"": ""Christopher Stevens"", ""affiliation"": ""Klein Inc"", ""email"": ""obrown@example.net""}, {""name""",59,,,,None,"[""appear"", ""director"", ""class""]",arXiv:2024.12574,10.9859/Gyae,Science,2023,,Fully-configurable bandwidth-monitored installation
Institution rock traditional drug. Particular find just him task. Pick short partner prove group agr,"[{""name"": ""Scott Brown"", ""affiliation"": ""Gibson PLC"", ""email"": ""raymondbradford@example.org""}, {""nam",442,,,,None,"[""phone"", ""like"", ""nor"", ""bag""]",arXiv:2022.52146,10.8667/tNnH,Cell,2024,,Compatible secondary orchestration


[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"?>
<api_specification>
<paths>
</population>
<get>
<summary>Lead room develop man according street century.</summary>
<parameters>
<name>param0</name>
<in>query</in>
<type>string</type>
</parameters>
<parameters>
<name>param1</name>
<in>query</in>
<type>string</type>
</parameters>
<parameters>
<name>param2</name>
<in>query</in>
<type>string</type>
</parameters>
<responses>
<200>
<description>Success</description>
</200>
<400>
<description>Bad Request</description>
</400>
</responses>
</get>
<//population>
</paths>
<info>
<title>Ameliorated radical initiative API</title>
<version>1.0.0</version>
</info>
<openapi>3.0.0</openapi>
</api_specification>

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

Output:
{
  "paths": {
    "/population": {
      "get": {
        "summary": "Lead room develop man according street century.",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          },
          {
            "name": "param1",
            "in": "query",
            "type": "string"
          },
          {
            "name": "param2",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  },
  "info": {
    "title": "Ameliorated radical initiative API",
    "version": "1.0.0"
  },
  "openapi": "3.0.0"
}


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<financial_report>
<quarter>Q3 2022</quarter>
<company>Dunn-Byrd</company>
<expenses>58548919</expenses>
<eps>9.56</eps>
<ticker>ATGQ</ticker>
</financial_report>

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

Output:
{
  "quarter": "Q3 2022",
  "company": "Dunn-Byrd",
  "expenses": 58548919,
  "eps": 9.56,
  "ticker": "ATGQ"
}


[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 = "April 2020"
total_revenue = 1914989
units_sold = 47758
[[channels]]
name = "wholesale"
revenue = 3617590
growth = 20.48

[[channels]]
name = "online"
revenue = 654207
growth = 24.4

[[top_products]]
sku = "SKU-4328"
sales = 466200

[[top_products]]
sku = "SKU-2589"
sales = 244105

[[top_products]]
sku = "SKU-7725"
sales = 25778


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

[User] Output course syllabus as XML.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<course_syllabus>
<course_id>CRS-4513</course_id>
NEE477
<title>Exclusive bottom-line artificial intelligence 101</title>
<instructor>Jaime Roman</instructor>
<credits>3</credits>
<term>Spring 2022</term>
<schedule>
<week>1</week>
<topic>marriage</topic>
</schedule>
<schedule>
<week>2</week>
<topic>wonder</topic>
</schedule>
<schedule>
<week>3</week>
<topic>system</topic>
</schedule>
<schedule>
<week>4</week>
<topic>order</topic>
</schedule>
<schedule>
<week>5</week>
<topic>very</topic>
</schedule>
<schedule>
<week>6</week>
<topic>laugh</topic>
</schedule>
<schedule>
<week>7</week>
<topic>practice</topic>
</schedule>
<schedule>
<week>8</week>
<topic>sister</topic>
</schedule>
<schedule>
<week>9</week>
<topic>join</topic>
</schedule>
<schedule>
<week>10</week>
<topic>expect</topic>
</schedule>
<grading>
<homework>30</homework>
<midterm>30</midterm>
<final>40</final>
</grading>
</course_syllabus>


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

[User] Generate api specification data in JSON format.

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

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


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

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

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


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

[User] Output transaction record as JSON.

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

Output:
{
  "txn_id": "TXN-72432123",
  "customer_id": "d14101dd-b47b-4916-b7e5-0ad54eefbb55",
  "timestamp": "2026-01-07T13:51:26.808008",
  "items": [
    {
      "sku": "SKU-29323",
      "qty": 2,
      "price": 70.49
    },
    {
      "sku": "SKU-65460",
      "qty": 3,
      "price": 466.32
    },
    {
      "sku": "SKU-59283",
      "qty": 1,
      "price": 149.96
    },
    {
      "sku": "SKU-68579",
      "qty": 2,
      "price": 13.04
    }
  ],
  "subtotal": 1301.16,
  "tax": 124.54,
  "total": 239.49,
  "payment_method": "apple_pay"
}


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

[User] Output sales analytics as YAML.

[Assistant]
Approach:
1. Task: Create sales analytics 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:
total_revenue: 6798538
channels:
- name: online
  revenue: 2139770
  growth: -9.99
- name: retail
  revenue: 1809716
  growth: 7.01
top_products:
- sku: SKU-3049
  sales: 22854
- sku: SKU-5505
  sales: 203281
- sku: SKU-9853
  sales: 260538


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

[User]
Transform this YAML data into JSON format:
course_id: CRS-4765
code: VMZ479
title: Exclusive grid-enabled software 101
instructor: Amy Baker
credits: 4
term: Fall 2022
schedule:
- week: 1
  topic: show
- week: 2
  topic: cut
- week: 3
  topic: next
- week: 4
  topic: everything
- week: 5
  topic: people
- week: 6
  topic: international
- week: 7
  topic: since
grading:
  homework: 30
  midterm: 30
  final: 40

[Assistant]
Approach:
1. Task: Convert course syllabus from YAML 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:
{
  "course_id": "CRS-4765",
  "code": "VMZ479",
  "title": "Exclusive grid-enabled software 101",
  "instructor": "Amy Baker",
  "credits": 4,
  "term": "Fall 2022",
  "schedule": [
    {
      "week": 1,
      "topic": "show"
    },
    {
      "week": 2,
      "topic": "cut"
    },
    {
      "week": 3,
      "topic": "next"
    },
    {
      "week": 4,
      "topic": "everything"
    },
    {
      "week": 5,
      "topic": "people"
    },
    {
      "week": 6,
      "topic": "international"
    },
    {
      "week": 7,
      "topic": "since"
    }
  ],
  "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]
Convert the following JSON to YAML:
{
  "product_id": "PROD-239354",
  "name": "User-centric tertiary contingency",
  "category": "electronics",
  "price": 998.51,
  "currency": "USD",
  "stock": 842,
  "is_available": true,
  "rating": 2.36,
  "reviews": 630,
  "specs": {
    "weight_kg": 0.61,
    "dimensions": "88x23x10cm"
  }
}

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

Output:
product_id: PROD-239354
name: User-centric tertiary contingency
category: electronics
price: 998.51
currency: USD
stock: 842
is_available: true
rating: 2.36
reviews: 630
specs:
  weight_kg: 0.61
  dimensions: 88x23x10cm


[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: medium - 5-8 fields, 2-3 levels
3. Format rules: well-formed tags, proper nesting, escaped special chars
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
<?xml version="1.0" encoding="UTF-8"?>
<social_media_post>
<post_id>POST-78635818</post_id>
<platform>facebook</platform>
<user_id>a739269a-9642-463c-9c88-cb97c795c8d8</user_id>
<username>kevin10</username>
<content>Specific other kind choice. Condition main resource finish north reach with break. Area strategy huge edge.</content>
<timestamp>2026-01-07T13:51:25.965362</timestamp>
<hashtags>#model</hashtags>
<hashtags>#firm</hashtags>
<engagement>
<likes>3831</likes>
<shares>379</shares>
<comments>204</comments>
</engagement>
</social_media_post>


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

[User] Create a CSV representation of experiment result.

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

Output:
conclusion,experiment_id,methodology_design,methodology_duration_days,methodology_sample_size,results,title
significant,EXP-506156,observational,87,884,"[{""metric"": ""safety"", ""baseline"": 32.86, ""endpoint"": 81.82, ""p_value"": 0.3265}, {""metric"": ""efficacy",Effect of window on soldier
significant,EXP-770920,cohort,50,829,"[{""metric"": ""efficacy"", ""baseline"": 26.74, ""endpoint"": 34.66, ""p_value"": 0.3504}, {""metric"": ""effica",Effect of important on responsibility
significant,EXP-507814,observational,193,187,"[{""metric"": ""efficacy"", ""baseline"": 20.79, ""endpoint"": 87.66, ""p_value"": 0.0658}, {""metric"": ""effica",Effect of success on memory


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

[User] Output customer review as CSV.

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

Output:
category,content,currency,date,helpful_votes,is_available,name,price,product_id,rating,review_id,reviews,specs_dimensions,specs_weight_kg,stock,title,user_id,verified_purchase
,Admit large politics decide might Mr their. Hundred play I deal but player leader old. Then similar ,,2026-01-03,36,,,,PROD-683988,5,REV-9701957,,,,,Teach look history according want manager perform.,4d7f9754-e296-4a29-967f-5c8de166a17c,False
clothing,,USD,,,True,Exclusive zero-defect knowledgebase,184.53,PROD-985402,3.14,,295,50x84x76cm,38.71,736,,,
electronics,,USD,,,True,Visionary tangible Graphic Interface,375.72,PROD-782099,2.63,,746,12x99x93cm,25.67,959,,,
electronics,,USD,,,True,Re-contextualized bottom-line approach,411.91,PROD-167625,1.83,,182,27x94x87cm,46.26,837,,,


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

[User] Create a XML representation of course syllabus.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<course_syllabus>
<course_id>CRS-3741</course_id>
XMJ312
<title>Managed incremental focus group 101</title>
<instructor>Rachel Diaz</instructor>
<credits>4</credits>
<term>Fall 2021</term>
<schedule>
<week>1</week>
<topic>body</topic>
</schedule>
<schedule>
<week>2</week>
<topic>rather</topic>
</schedule>
<schedule>
<week>3</week>
<topic>song</topic>
</schedule>
<schedule>
<week>4</week>
<topic>child</topic>
</schedule>
<schedule>
<week>5</week>
<topic>born</topic>
</schedule>
<schedule>
<week>6</week>
<topic>beyond</topic>
</schedule>
<schedule>
<week>7</week>
<topic>there</topic>
</schedule>
<grading>
<homework>30</homework>
<midterm>30</midterm>
<final>40</final>
</grading>
</course_syllabus>


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

[User] Create a YAML representation of lab result.

[Assistant]
Approach:
1. Task: Create lab result 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:
result_id: LAB-8547948
patient_mrn: MRN-375584
order_date: '2026-01-05'
panel: Lipid
results:
- test: WBC
  value: 136.4
  unit: mg/dL
  flag: low
- test: Glucose
  value: 110.1
  unit: mg/dL
  flag: normal
- test: Glucose
  value: 77.6
  unit: mg/dL
  flag: high
- test: Glucose
  value: 164.2
  unit: g/dL
  flag: normal
- test: Hemoglobin
  value: 53.3
  unit: g/dL
  flag: high


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

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

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

Output:
note_id: CN-1129442
patient:
  mrn: MRN-895859
  age: 79
  gender: M
encounter_date: '2026-01-03'
chief_complaint: headache
vitals:
  bp: 127/81
  hr: 117
  temp_f: 102.4
assessment:
- problem: hypertension
  icd10: J46


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

[User] Output financial report as CSV.

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

Output:
company,eps,expenses,metrics_profit_margin,metrics_roe,net_income,quarter,revenue,ticker
Hill-Marsh,8.71,77071880,28.84,14.06,4141173,Q3 2024,46703834,ZFVR
"Wheeler, Christensen and Stewart",1.31,79135038,21.97,24.44,8165689,Q4 2020,4587381,OZHP
Bailey and Sons,0.5,10457405,21.15,15.2,3578521,Q1 2022,78381258,HKTN
Smith LLC,6.94,11963849,26.51,18.87,4704703,Q4 2023,12325641,DWGJ
Wilson-Hughes,2.72,55363307,8.7,6.29,13925539,Q2 2020,37000853,FAPR