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

[User] Create a TOML representation of sales analytics.

[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 = "January 2022"
total_revenue = 7456708
units_sold = 82349
[[channels]]
name = "wholesale"
revenue = 3622404
growth = -8.05

[[channels]]
name = "online"
revenue = 1893923
growth = 2.21

[[top_products]]
sku = "SKU-2073"
sales = 98550

[[top_products]]
sku = "SKU-3707"
sales = 233488

[[top_products]]
sku = "SKU-7843"
sales = 172526


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

[User] Create a YAML representation of customer review.

[Assistant]
Approach:
1. Task: Create customer review in YAML
2. Complexity: 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:
review_id: REV-8075236
product_id: PROD-326180
user_id: e70c9373-b1ad-41a5-8939-e3c28041d8f5
rating: 4
title: Most teacher Mrs system watch.
content: 'Address music major. Magazine three about. Security ready result improve.

  Hand other collection name wife remain. Speech perhaps newspaper. Talk place third
  about writer billion physical.'
date: '2026-01-03'
verified_purchase: false
helpful_votes: 50


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

[User] Create a JSON representation of experiment result.

[Assistant]
Approach:
1. Task: Create experiment result in JSON
2. Complexity: 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:
{
  "experiment_id": "EXP-318732",
  "title": "Effect of produce on stock",
  "methodology": {
    "design": "observational",
    "sample_size": 303,
    "duration_days": 155
  },
  "results": [
    {
      "metric": "safety",
      "baseline": 20.77,
      "endpoint": 67.03,
      "p_value": 0.1826
    },
    {
      "metric": "safety",
      "baseline": 69.69,
      "endpoint": 32.04,
      "p_value": 0.1176
    }
  ],
  "conclusion": "non-significant"
}


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

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

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

Output:
error_id: ff91c212-6cce-4ac2-978d-0740381882de
timestamp: '2026-01-07T13:51:27.679071'
level: WARNING
service: drawService
message: Support red list product forget cut speak.
stack_trace:
- at girl.py:186
- at hold.py:186
context:
  user_id: 473e683b-291e-461f-b848-d224b7dcbd8b
  request_id: 454a35ad-23ee-42a8-9d57-dbf5cedbef74


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

[User] Produce a TOML document for a prescription.

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

Output:
rx_id = "RX-2317847"
patient_mrn = "MRN-412331"
prescriber = "Tammy Adams"
date = "2026-01-01"
[[medications]]
name = "Lisinopril"
dosage = "10mg"
frequency = "BID"
quantity = 60

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

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


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

[User] Generate product listing data in XML format.

[Assistant]
Approach:
1. Task: Create product listing in XML
2. Complexity: 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"?>
<product_listing>
<reviews>730</reviews>
<category>books</category>
<stock>824</stock>
<is_available>True</is_available>
<specs>
<weight_kg>7.36</weight_kg>
<dimensions>46x21x76cm</dimensions>
</specs>
</product_listing>


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

[User] Create a XML representation of sales analytics.

[Assistant]
Approach:
1. Task: Create sales analytics 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"?>
<sales_analytics>
<period>June 2020</period>
<total_revenue>2603625</total_revenue>
<units_sold>51574</units_sold>
<channels>
<name>retail</name>
<revenue>1926384</revenue>
<growth>34.29</growth>
</channels>
<channels>
<name>online</name>
<revenue>1062444</revenue>
<growth>-1.99</growth>
</channels>
<top_products>
<sku>SKU-3818</sku>
<sales>48786</sales>
</top_products>
<top_products>
<sku>SKU-7605</sku>
<sales>408187</sales>
</top_products>
<top_products>
<sku>SKU-6728</sku>
<sales>223732</sales>
</top_products>
</sales_analytics>


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

[User] Output lab result as JSON.

[Assistant]
Approach:
1. Task: Create lab result in JSON
2. Complexity: 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:
{
  "result_id": "LAB-4303735",
  "patient_mrn": "MRN-230243",
  "order_date": "2026-01-02",
  "panel": "Lipid",
  "results": [
    {
      "test": "WBC",
      "value": 142.8,
      "unit": "g/dL",
      "flag": "high"
    },
    {
      "test": "Hemoglobin",
      "value": 100.6,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "WBC",
      "value": 148.7,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "Hemoglobin",
      "value": 95.1,
      "unit": "g/dL",
      "flag": "normal"
    }
  ]
}


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

[User] Create a XML representation of contract.

[Assistant]
Approach:
1. Task: Create contract 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"?>
<contract>
<contract_id>CTR-274282</contract_id>
<parties>
<name>Schroeder LLC</name>
<role>party_a</role>
</parties>
<parties>
<name>Kemp-Jones</name>
<role>party_b</role>
</parties>
<effective_date>2026-01-01</effective_date>
<term_months>28</term_months>
<value>285721</value>
<status>active</status>
</contract>


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

[User] Generate sales analytics data in YAML format.

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

Output:
period: November 2022
total_revenue: 9138741
units_sold: 89798
channels:
- name: wholesale
  revenue: 1234153
  growth: 40.64
- name: online
  revenue: 991509
  growth: -4.15
top_products:
- sku: SKU-9585
  sales: 30234
- sku: SKU-8072
  sales: 57362
- sku: SKU-4011
  sales: 249730


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

[User]
Convert the following YAML to XML:
title: Effect of main on stand
results:
- metric: efficacy
  baseline: 50.39
  endpoint: 61.09
  p_value: 0.3936
- metric: safety
  baseline: 99.02
  endpoint: 82.38
  p_value: 0.0752
- metric: efficacy
  baseline: 94.16
  endpoint: 58.56
  p_value: 0.1239
- metric: safety
  baseline: 41.74
  endpoint: 45.99
  p_value: 0.0661
experiment_id: EXP-681166
methodology:
  design: RCT
  sample_size: 875
  duration_days: 212
conclusion: non-significant

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<experiment_result>
<title>Effect of main on stand</title>
<results>
<metric>efficacy</metric>
<baseline>50.39</baseline>
<endpoint>61.09</endpoint>
<p_value>0.3936</p_value>
</results>
<results>
<metric>safety</metric>
<baseline>99.02</baseline>
<endpoint>82.38</endpoint>
<p_value>0.0752</p_value>
</results>
<results>
<metric>efficacy</metric>
<baseline>94.16</baseline>
<endpoint>58.56</endpoint>
<p_value>0.1239</p_value>
</results>
<results>
<metric>safety</metric>
<baseline>41.74</baseline>
<endpoint>45.99</endpoint>
<p_value>0.0661</p_value>
</results>
<experiment_id>EXP-681166</experiment_id>
<methodology>
<design>RCT</design>
<sample_size>875</sample_size>
<duration_days>212</duration_days>
</methodology>
<conclusion>non-significant</conclusion>
</experiment_result>


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

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

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

Output:
post_id = "POST-39452168"
platform = "twitter"
user_id = "ca270bc8-d443-4389-880a-6fc8dd3e9fa5"
username = "robertowens"
content = "With writer dinner any kitchen add well. Floor image speech charge rate manager vote. Worry involve benefit there nothing rock.\nFactor even apply how three box light."
timestamp = "2026-01-07T13:51:25.425211"
hashtags = [ "#training", "#Democrat", "#pattern", "#discover",]

[engagement]
likes = 5319
shares = 573
comments = 283


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

[User] Produce a YAML document for a contract.

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

Output:
contract_id: CTR-274282
parties:
- name: Schroeder LLC
  role: party_a
- name: Kemp-Jones
  role: party_b
effective_date: '2026-01-01'
term_months: 28
value: 285721
status: active


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

[User]
Transform this JSON data into XML format:
{
  "openapi": "3.0.0",
  "info": {
    "title": "Secured well-modulated policy API",
    "version": "1.0.0"
  },
  "paths": {
    "/article": {
      "get": {
        "summary": "During certainly full.",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          },
          {
            "name": "param1",
            "in": "query",
            "type": "string"
          },
          {
            "name": "param2",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  }
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Secured well-modulated policy API</title>
<version>1.0.0</version>
</info>
<paths>
</article>
<get>
<summary>During certainly full.</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>
<//article>
</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 product listing.

[Assistant]
Approach:
1. Task: Create product listing 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,currency,is_available,name,price,product_id,rating,reviews,specs_dimensions,specs_weight_kg,stock
clothing,USD,True,Cross-platform scalable protocol,855.77,PROD-651261,3.23,830,84x20x91cm,21.29,343
books,USD,True,Decentralized clear-thinking system engine,763.23,PROD-386832,4.72,39,22x47x26cm,42.64,939
clothing,USD,True,Synchronized well-modulated circuit,415.95,PROD-411911,1.72,984,97x26x95cm,17.25,282
clothing,USD,True,Stand-alone zero administration adapter,51.0,PROD-569235,1.37,67,51x15x96cm,45.54,955


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

[User] Generate course syllabus data in JSON format.

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

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


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

[User] Create a TOML representation of course syllabus.

[Assistant]
Approach:
1. Task: Create course syllabus in TOML
2. Complexity: 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:
instructor = "Rachel Moreno DVM"
credits = 4
course_id = "CRS-8305"
title = "Open-architected even-keeled support 101"
term = "Spring 2023"


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

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

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

Output:
abstract,authors,citations,funding_source,keywords,paper_id,publication_doi,publication_venue,publication_year,title
Win both purpose hour professor table.,"[{""name"": ""Gary Johnson"", ""affiliation"": ""Wolf Group"", ""email"": ""jamie40@example.org""}, {""name"": ""Li",258,"Espinoza, Khan and Lowe","[""office"", ""during"", ""more"", ""apply"", ""program""]",arXiv:2022.79764,10.1780/NyHo,Nature,2023,Progressive exuding adapter
Several oil hotel structure Democrat. Evidence able majority group piece. Rate election probably man,"[{""name"": ""Johnny Perry"", ""affiliation"": ""Christensen, Frederick and Robinson"", ""email"": ""meghan41@e",369,"Randall, Williams and Mcfarland","[""price"", ""trip"", ""at""]",arXiv:2023.96163,10.3589/MUjC,Cell,2022,Cloned methodical encryption
Recognize region people million. Simple option edge responsibility share involve.,"[{""name"": ""Ann Juarez"", ""affiliation"": ""Anderson PLC"", ""email"": ""swilliams@example.com""}, {""name"": """,377,None,"[""stay"", ""tax"", ""surface""]",arXiv:2024.29086,10.9771/TUZf,Cell,2021,Progressive needs-based knowledgebase
Wish point network head put political less. Government say summer image.,"[{""name"": ""Jeremy Haynes"", ""affiliation"": ""Gibson-King"", ""email"": ""pkelly@example.net""}, {""name"": ""K",118,None,"[""there"", ""first"", ""deal"", ""spend""]",arXiv:2022.77669,10.4828/YrKq,Cell,2023,Progressive grid-enabled support


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<lab_result>
<result_id>LAB-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>

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

Output:
{
  "result_id": "LAB-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"
    }
  ]
}


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

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

[Assistant]
Approach:
1. Task: Create social media post 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:
content,engagement_comments,engagement_likes,engagement_shares,hashtags,platform,post_id,timestamp,user_id,username
Forward front agreement cover hour we remember ask. Read glass few word mother deep TV.,124,304,796,"[""#cost"", ""#he"", ""#relationship""]",twitter,POST-19357850,2026-01-07T13:51:27.605837,664b960b-1331-492f-addd-e9b37d21656f,mbaldwin
"Method next right do. Speak build along speech. Rise their will adult marriage few throughout.
Compa",329,6665,890,"[""#right"", ""#what"", ""#west"", ""#drive""]",instagram,POST-49554802,2026-01-07T13:51:27.607103,5b9ad0aa-0d8f-4f04-8066-bb32349f88de,arnoldamy
Behavior Congress value these however subject let. Artist one likely child support subject. Lot whol,355,6717,190,"[""#mention"", ""#executive""]",twitter,POST-45981103,2026-01-07T13:51:27.607385,d1daa942-5f60-47f9-aac9-8956689c6f46,adrian70


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

[User]
Transform this YAML data into XML format:
company: Snow, Shelton and Parsons
ticker: LYEH
quarter: Q3 2022
revenue: 49988929
expenses: 3428077
net_income: 8543670
eps: 3.41
metrics:
  profit_margin: 11.21
  roe: 5.99

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<financial_report>
<company>Snow, Shelton and Parsons</company>
<ticker>LYEH</ticker>
<quarter>Q3 2022</quarter>
<revenue>49988929</revenue>
<expenses>3428077</expenses>
<net_income>8543670</net_income>
<eps>3.41</eps>
<metrics>
<profit_margin>11.21</profit_margin>
<roe>5.99</roe>
</metrics>
</financial_report>


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

[User] Create a JSON representation of error log.

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

Output:
{
  "error_id": "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]
Transform this JSON data into XML format:
{
  "units_sold": 11543,
  "period": "June 2021",
  "channels": [
    {
      "name": "online",
      "revenue": 1417680,
      "growth": 41.94
    },
    {
      "name": "wholesale",
      "revenue": 3176166,
      "growth": 26.78
    }
  ],
  "total_revenue": 8223229,
  "top_products": [
    {
      "sku": "SKU-9002",
      "sales": 412560
    },
    {
      "sku": "SKU-3918",
      "sales": 426996
    },
    {
      "sku": "SKU-1618",
      "sales": 496165
    }
  ]
}

[Assistant]
Approach:
1. Task: Convert sales analytics 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"?>
<sales_analytics>
<units_sold>11543</units_sold>
<period>June 2021</period>
<channels>
<name>online</name>
<revenue>1417680</revenue>
<growth>41.94</growth>
</channels>
<channels>
<name>wholesale</name>
<revenue>3176166</revenue>
<growth>26.78</growth>
</channels>
<total_revenue>8223229</total_revenue>
<top_products>
<sku>SKU-9002</sku>
<sales>412560</sales>
</top_products>
<top_products>
<sku>SKU-3918</sku>
<sales>426996</sales>
</top_products>
<top_products>
<sku>SKU-1618</sku>
<sales>496165</sales>
</top_products>
</sales_analytics>


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

[User]
Convert the following YAML to XML:
result_id: LAB-6812810
patient_mrn: MRN-631747
order_date: '2026-01-04'
panel: Lipid
results:
- test: WBC
  value: 54.3
  unit: mg/dL
  flag: high
- test: WBC
  value: 70.8
  unit: mg/dL
  flag: low
- test: Glucose
  value: 59.6
  unit: mg/dL
  flag: low
- test: WBC
  value: 140.8
  unit: mg/dL
  flag: high

[Assistant]
Approach:
1. Task: Convert lab result from 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"?>
<lab_result>
<result_id>LAB-6812810</result_id>
<patient_mrn>MRN-631747</patient_mrn>
<order_date>2026-01-04</order_date>
<panel>Lipid</panel>
<results>
<test>WBC</test>
<value>54.3</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>WBC</test>
<value>70.8</value>
<unit>mg/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Glucose</test>
<value>59.6</value>
<unit>mg/dL</unit>
<flag>low</flag>
</results>
<results>
<test>WBC</test>
<value>140.8</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
</lab_result>


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

[User] Generate customer review data in YAML format.

[Assistant]
Approach:
1. Task: Create customer review 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:
review_id: REV-5008217
product_id: PROD-173271
user_id: 11121b86-b60c-4ea2-b83a-cbb727cd7a24
rating: 2
title: Lay lead it politics brother.
content: Camera left hope prevent inside real. Whether trouble their always manager
  cultural majority popular. Song condition entire security concern science. Run number
  firm listen serious.
date: '2026-01-01'
verified_purchase: true
helpful_votes: 23


[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-2575466",
  "product_id": "PROD-346187",
  "user_id": "320eb87e-12bd-44ab-bb47-6fec45bd5144",
  "rating": 1,
  "title": "Possible modern last rate memory fight conference ",
  "content": "Character walk loss rock me social gun.\nCenter choice either push. Push stop yourself.",
  "date": "2026-01-01",
  "verified_purchase": false,
  "helpful_votes": 26
}

[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-2575466</review_id>
<product_id>PROD-346187</product_id>
<user_id>320eb87e-12bd-44ab-bb47-6fec45bd5144</user_id>
<rating>1</rating>
<title>Possible modern last rate memory fight conference </title>
<content>Character walk loss rock me social gun.
Center choice either push. Push stop yourself.</content>
<date>2026-01-01</date>
<verified_purchase>False</verified_purchase>
<helpful_votes>26</helpful_votes>
</customer_review>


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

[User] Generate student assessment data in YAML format.

[Assistant]
Approach:
1. Task: Create student assessment 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:
assessment_id: ASMT-893180
student_id: STU-881633
course_id: CRS-6394
type: quiz
date: '2026-01-03'
scores:
- question: 1
  points_earned: 10
  points_possible: 10
- question: 2
  points_earned: 8
  points_possible: 10
- question: 3
  points_earned: 10
  points_possible: 10
- question: 4
  points_earned: 6
  points_possible: 10
- question: 5
  points_earned: 4
  points_possible: 10
- question: 6
  points_earned: 6
  points_possible: 10
- question: 7
  points_earned: 0
  points_possible: 10
- question: 8
  points_earned: 10
  points_possible: 10
- question: 9
  points_earned: 5
  points_possible: 10
total_score: 98
percentage: 73.06
grade: A


[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-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
  }
}

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


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

[User]
Reformat the data below from TOML to XML:
contract_id = "CTR-291572"
effective_date = "2026-01-03"
term_months = 47
value = 297446
status = "pending"
[[parties]]
name = "Smith and Sons"
role = "party_a"

[[parties]]
name = "Avila-Campbell"
role = "party_b"

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<contract>
<contract_id>CTR-291572</contract_id>
<parties>
<name>Smith and Sons</name>
<role>party_a</role>
</parties>
<parties>
<name>Avila-Campbell</name>
<role>party_b</role>
</parties>
<effective_date>2026-01-03</effective_date>
<term_months>47</term_months>
<value>297446</value>
<status>pending</status>
</contract>


[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-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


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

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

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

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


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

[User] Generate product listing data in XML format.

[Assistant]
Approach:
1. Task: Create product listing in XML
2. Complexity: 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"?>
<product_listing>
<rating>4.54</rating>
<stock>843</stock>
<specs>
<weight_kg>34.7</weight_kg>
<dimensions>61x86x65cm</dimensions>
</specs>
<currency>USD</currency>
</product_listing>


[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:
{
  "txn_id": "TXN-95106885",
  "customer_id": "9090a0a6-3421-4a93-9d6e-78b6a1f8fed7",
  "timestamp": "2026-01-07T13:51:27.692524",
  "items": [
    {
      "sku": "SKU-33525",
      "qty": 3,
      "price": 130.6
    }
  ],
  "subtotal": 793.41,
  "tax": 85.16,
  "total": 1645.24,
  "payment_method": "apple_pay"
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<transaction_record>
<txn_id>TXN-95106885</txn_id>
<customer_id>9090a0a6-3421-4a93-9d6e-78b6a1f8fed7</customer_id>
<timestamp>2026-01-07T13:51:27.692524</timestamp>
<items>
<sku>SKU-33525</sku>
<qty>3</qty>
<price>130.6</price>
</items>
<subtotal>793.41</subtotal>
<tax>85.16</tax>
<total>1645.24</total>
<payment_method>apple_pay</payment_method>
</transaction_record>


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

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

[Assistant]
Approach:
1. Task: Create social media post in CSV
2. Complexity: 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:
content,engagement_comments,engagement_likes,engagement_shares,hashtags,platform,post_id,timestamp,user_id,username
"See personal couple road president most next. Laugh teach lawyer character work present.
Page give e",62,1911,761,"[""#PM"", ""#stage"", ""#government""]",twitter,POST-69367106,2026-01-07T13:51:25.991400,7643b70d-1c60-436f-974e-7bc6cee5e032,gordonalexander
Boy whose edge avoid force together example. Sense leave major example.,170,1418,558,"[""#alone"", ""#fire"", ""#such"", ""#rate""]",instagram,POST-25052128,2026-01-07T13:51:25.992859,329689c8-d515-4b74-aac8-680281f98730,garzasteven
"Nor mouth wind movement action. Now sense method until.
Design south defense say key his professiona",167,953,375,"[""#police"", ""#remain"", ""#kid""]",instagram,POST-32026983,2026-01-07T13:51:25.993258,7453d5f5-c3a0-432d-9ada-bb6b48cdd445,jonessarah
Institution produce enjoy space. City draw girl right. Walk and affect natural almost democratic.,191,8329,401,"[""#dinner"", ""#campaign""]",instagram,POST-20598937,2026-01-07T13:51:25.993532,ae2ebd48-0287-40ab-acef-1024261e5ade,robert88


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

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

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

Output:
assessment,chief_complaint,encounter_date,note_id,patient_age,patient_gender,patient_mrn,vitals_bp,vitals_hr,vitals_temp_f
"[{""problem"": ""diabetes"", ""icd10"": ""J60""}, {""problem"": ""hypertension"", ""icd10"": ""I21""}, {""problem"": """,headache,2026-01-02,CN-4441974,60,F,MRN-925906,154/95,108,97.8
"[{""problem"": ""hypertension"", ""icd10"": ""I88""}]",chest pain,2026-01-06,CN-7868117,57,M,MRN-127397,101/68,113,99.7
"[{""problem"": ""hypertension"", ""icd10"": ""K40""}, {""problem"": ""hypertension"", ""icd10"": ""I63""}]",headache,2026-01-03,CN-2244265,19,F,MRN-771354,134/94,64,101.9
"[{""problem"": ""diabetes"", ""icd10"": ""J35""}]",chest pain,2026-01-04,CN-4758078,63,M,MRN-858083,172/103,70,100.4


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

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


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

[User] Generate contract data in JSON format.

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

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

[User] Output api specification as YAML.

[Assistant]
Approach:
1. Task: Create api specification 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:
openapi: 3.0.0
info:
  title: Implemented leadingedge groupware API
  version: 1.0.0
paths:
  /reveal:
    get:
      summary: Parent dark five.
      parameters:
      - name: param0
        in: query
        type: string
      - name: param1
        in: query
        type: string
      - name: param2
        in: query
        type: string
      responses:
        '200':
          description: Success
        '400':
          description: Bad Request


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

[User] Output experiment result as YAML.

[Assistant]
Approach:
1. Task: Create experiment result 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:
experiment_id: EXP-956799
title: Effect of town on start
methodology:
  design: RCT
  sample_size: 962
  duration_days: 355
results:
- metric: efficacy
  baseline: 84.98
  endpoint: 18.54
  p_value: 0.3765
- metric: safety
  baseline: 50.71
  endpoint: 79.49
  p_value: 0.1783
- metric: safety
  baseline: 22.25
  endpoint: 81.5
  p_value: 0.0959
- metric: efficacy
  baseline: 53.32
  endpoint: 58.41
  p_value: 0.1807
conclusion: significant


[System] You are an expert in 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-3440</course_id>
KLD251
<title>Reverse-engineered foreground infrastructure 101</title>
<instructor>Courtney Escobar</instructor>
<credits>4</credits>
<term>Spring 2022</term>
<schedule>
<week>1</week>
<topic>despite</topic>
</schedule>
<schedule>
<week>2</week>
<topic>choose</topic>
</schedule>
<schedule>
<week>3</week>
<topic>action</topic>
</schedule>
<schedule>
<week>4</week>
<topic>couple</topic>
</schedule>
<schedule>
<week>5</week>
<topic>big</topic>
</schedule>
<schedule>
<week>6</week>
<topic>trade</topic>
</schedule>
<schedule>
<week>7</week>
<topic>measure</topic>
</schedule>
<schedule>
<week>8</week>
<topic>music</topic>
</schedule>
<grading>
<homework>30</homework>
<midterm>30</midterm>
<final>40</final>
</grading>
</course_syllabus>

[Assistant]
Approach:
1. Task: Convert course syllabus 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:
{
  "course_id": "CRS-3440",
  "code": "KLD251",
  "title": "Reverse-engineered foreground infrastructure 101",
  "instructor": "Courtney Escobar",
  "credits": 4,
  "term": "Spring 2022",
  "schedule": [
    {
      "week": 1,
      "topic": "despite"
    },
    {
      "week": 2,
      "topic": "choose"
    },
    {
      "week": 3,
      "topic": "action"
    },
    {
      "week": 4,
      "topic": "couple"
    },
    {
      "week": 5,
      "topic": "big"
    },
    {
      "week": 6,
      "topic": "trade"
    },
    {
      "week": 7,
      "topic": "measure"
    },
    {
      "week": 8,
      "topic": "music"
    }
  ],
  "grading": {
    "homework": 30,
    "midterm": 30,
    "final": 40
  }
}


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

[User]
Reformat the data below from CSV to XML:
category,currency,is_available,name,price,product_id,rating,reviews,specs_dimensions,specs_weight_kg,stock
clothing,USD,True,Streamlined full-range ability,959.9,PROD-723394,3.7,332,53x67x45cm,9.93,28
electronics,USD,True,Synchronized heuristic standardization,880.8,PROD-606091,3.65,516,67x86x14cm,29.97,683
electronics,USD,True,Assimilated human-resource matrices,427.66,PROD-549544,3.47,970,62x82x94cm,30.97,140

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<product_listing>
<product_id>PROD-723394</product_id>
<name>Streamlined full-range ability</name>
<category>clothing</category>
<price>959.9</price>
<currency>USD</currency>
<stock>28</stock>
<is_available>True</is_available>
<rating>3.7</rating>
<reviews>332</reviews>
<specs>
<weight_kg>9.93</weight_kg>
<dimensions>53x67x45cm</dimensions>
</specs>
</product_listing>


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

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

[Assistant]
Approach:
1. Task: Create sales analytics 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"?>
<sales_analytics>
<period>June 2022</period>
<total_revenue>7287772</total_revenue>
<units_sold>8566</units_sold>
<channels>
<name>retail</name>
<revenue>931216</revenue>
<growth>10.96</growth>
</channels>
<channels>
<name>wholesale</name>
<revenue>1224016</revenue>
<growth>31.92</growth>
</channels>
<top_products>
<sku>SKU-1474</sku>
<sales>19268</sales>
</top_products>
<top_products>
<sku>SKU-3289</sku>
<sales>31397</sales>
</top_products>
<top_products>
<sku>SKU-4950</sku>
<sales>322920</sales>
</top_products>
</sales_analytics>


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

[User] Create a YAML representation of product listing.

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

Output:
product_id: PROD-524008
name: Implemented multimedia focus group
category: electronics
price: 524.9
currency: USD
stock: 714
is_available: true
rating: 2.56
reviews: 633
specs:
  weight_kg: 40.1
  dimensions: 80x44x77cm


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

[User] Produce a XML document for a prescription.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<prescription>
<rx_id>RX-7665793</rx_id>
<patient_mrn>MRN-934255</patient_mrn>
<prescriber>Danielle Brown</prescriber>
<date>2026-01-06</date>
<medications>
<name>Atorvastatin</name>
<dosage>20mg</dosage>
<frequency>daily</frequency>
<quantity>90</quantity>
</medications>
<medications>
<name>Atorvastatin</name>
<dosage>5mg</dosage>
<frequency>BID</frequency>
<quantity>90</quantity>
</medications>
<medications>
<name>Metformin</name>
<dosage>5mg</dosage>
<frequency>BID</frequency>
<quantity>60</quantity>
</medications>
</prescription>


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

[User] Output clinical note as XML.

[Assistant]
Approach:
1. Task: Create clinical note 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"?>
<clinical_note>
<note_id>CN-4315709</note_id>
<patient>
<mrn>MRN-534874</mrn>
<age>89</age>
<gender>M</gender>
</patient>
<encounter_date>2026-01-02</encounter_date>
<chief_complaint>chest pain</chief_complaint>
<vitals>
<bp>165/61</bp>

112

<temp_f>99.4</temp_f>
</vitals>
<assessment>
<problem>diabetes</problem>
<icd10>I12</icd10>
</assessment>
<assessment>
<problem>diabetes</problem>
<icd10>K62</icd10>
</assessment>
</clinical_note>


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

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

[Assistant]
Approach:
1. Task: Create experiment 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:
experiment_id = "EXP-883806"
title = "Effect of there on wife"
conclusion = "significant"
[[results]]
metric = "efficacy"
baseline = 15.64
endpoint = 83.3
p_value = 0.4248

[[results]]
metric = "efficacy"
baseline = 36.36
endpoint = 63.05
p_value = 0.0775

[methodology]
design = "observational"
sample_size = 200
duration_days = 32


[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"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Cross-group bottom-line algorithm API</title>
<version>1.0.0</version>
</info>
<paths>
</rule>
<get>
<summary>Center available level environment per away author</summary>
<parameters>
<name>param0</name>
<in>query</in>
<type>string</type>
</parameters>
<parameters>
<name>param1</name>
<in>query</in>
<type>string</type>
</parameters>
<responses>
<200>
<description>Success</description>
</200>
<400>
<description>Bad Request</description>
</400>
</responses>
</get>
<//rule>
</paths>
</api_specification>

[Assistant]
Approach:
1. Task: Convert api specification 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:
{
  "openapi": "3.0.0",
  "info": {
    "title": "Cross-group bottom-line algorithm API",
    "version": "1.0.0"
  },
  "paths": {
    "/rule": {
      "get": {
        "summary": "Center available level environment per away author",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          },
          {
            "name": "param1",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  }
}


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<error_log>
<error_id>bcec7cd1-70fc-42ba-97dd-2c6e2159fc7d</error_id>
<timestamp>2026-01-07T13:51:27.288021</timestamp>
<level>CRITICAL</level>
<service>reasonService</service>
<message>Recent security meet three Congress find seat.</message>
<stack_trace>at current.py:236</stack_trace>
<stack_trace>at your.py:146</stack_trace>
<stack_trace>at without.py:194</stack_trace>
<context>
<user_id>fc408ea4-9df4-4d81-87da-9d63d4bc8744</user_id>
<request_id>d8c95012-b6bb-42d7-8cb4-e57e77353a5b</request_id>
</context>
</error_log>


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

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

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

Output:
expenses = 54498119
ticker = "OKCY"
company = "Clark-Pearson"


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

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

[Assistant]
Approach:
1. Task: Create error log in XML
2. Complexity: 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"?>
<error_log>
<message>Computer so cold feeling huge reason reach.</message>
<error_id>ddf52566-8f32-4c90-8477-d7f45504f7db</error_id>
<stack_trace>at their.py:436</stack_trace>
<stack_trace>at activity.py:81</stack_trace>
<stack_trace>at test.py:46</stack_trace>
<timestamp>2026-01-07T13:51:26.578554</timestamp>
<context>
<user_id>97fc14e5-867d-4c23-9d2e-00b538b50acf</user_id>
<request_id>ab94fb1e-d258-4626-9686-12f860249c41</request_id>
</context>
</error_log>


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

[User] Create a YAML representation of error log.

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

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


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

[User] Create a JSON representation of research paper.

[Assistant]
Approach:
1. Task: Create research paper 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:
{
  "paper_id": "arXiv:2024.67669",
  "title": "Triple-buffered dedicated knowledgebase",
  "authors": [
    {
      "name": "Julie Mclaughlin",
      "affiliation": "Andrews Group",
      "email": "brianna81@example.org"
    },
    {
      "name": "Peggy Kramer",
      "affiliation": "Beasley, Edwards and Webb",
      "email": "susan35@example.com"
    }
  ],
  "abstract": "Account fish possible democratic ok no. Accept short mention guy.\nPlace finish religious mean end success. Travel into music they.",
  "keywords": [
    "thank",
    "far",
    "fund",
    "get",
    "role"
  ],
  "publication": {
    "venue": "Nature",
    "year": 2023,
    "doi": "10.1349/JgWc"
  },
  "citations": 60,
  "funding_source": "Diaz-Salinas"
}


[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:
{
  "product_id": "PROD-421885",
  "name": "Diverse 6thgeneration solution",
  "category": "books",
  "price": 48.12,
  "currency": "USD",
  "stock": 460,
  "is_available": true,
  "rating": 3.7,
  "reviews": 717,
  "specs": {
    "weight_kg": 20.82,
    "dimensions": "87x57x81cm"
  }
}

[Assistant]
Approach:
1. Task: Convert product listing 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"?>
<product_listing>
<product_id>PROD-421885</product_id>
<name>Diverse 6thgeneration solution</name>
<category>books</category>
<price>48.12</price>
<currency>USD</currency>
<stock>460</stock>
<is_available>True</is_available>
<rating>3.7</rating>
<reviews>717</reviews>
<specs>
<weight_kg>20.82</weight_kg>
<dimensions>87x57x81cm</dimensions>
</specs>
</product_listing>


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

[User]
Reformat the data below from JSON to TOML:
{
  "error_id": "e78ff1cc-d984-499d-9fcf-126ccada9355",
  "timestamp": "2026-01-07T13:51:26.607679",
  "level": "WARNING",
  "service": "generationService",
  "message": "Bag difference growth have leader yeah him.",
  "stack_trace": [
    "at teach.py:30",
    "at poor.py:409"
  ],
  "context": {
    "user_id": "e8daac99-0bad-4fb0-ae26-78525528db85",
    "request_id": "a6fe9e0f-a1a6-42b2-ab77-98b8bb662a52"
  }
}

[Assistant]
Approach:
1. Task: Convert error log from JSON 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:
error_id = "e78ff1cc-d984-499d-9fcf-126ccada9355"
timestamp = "2026-01-07T13:51:26.607679"
level = "WARNING"
service = "generationService"
message = "Bag difference growth have leader yeah him."
stack_trace = [ "at teach.py:30", "at poor.py:409",]

[context]
user_id = "e8daac99-0bad-4fb0-ae26-78525528db85"
request_id = "a6fe9e0f-a1a6-42b2-ab77-98b8bb662a52"


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

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

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

Output:
{
  "paper_id": "arXiv: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"
}


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

[User] Output social media post as XML.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<social_media_post>
<post_id>POST-93814090</post_id>
<platform>facebook</platform>
<user_id>6a4446e9-5537-4ba1-bf03-5db2d36e07b9</user_id>
<username>tonyaguzman</username>
<content>Subject watch side owner new. Quality million clear hand clearly environmental. Forget face machine little check.</content>
<timestamp>2026-01-07T13:51:26.454281</timestamp>
<hashtags>#plan</hashtags>
<hashtags>#area</hashtags>
<hashtags>#foreign</hashtags>
<engagement>
<likes>5322</likes>
<shares>327</shares>
<comments>152</comments>
</engagement>
</social_media_post>


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

[User] Output product listing as YAML.

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

Output:
product_id: PROD-319304
name: Self-enabling clear-thinking help-desk
category: clothing
price: 510.64
currency: USD
stock: 595
is_available: true
rating: 2.22
reviews: 791
specs:
  weight_kg: 30.42
  dimensions: 12x58x39cm


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

[User] Output sales analytics as JSON.

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

Output:
{
  "period": "March 2022",
  "total_revenue": 7500818,
  "units_sold": 73950,
  "channels": [
    {
      "name": "retail",
      "revenue": 528123,
      "growth": 12.05
    },
    {
      "name": "online",
      "revenue": 1160273,
      "growth": 23.93
    }
  ],
  "top_products": [
    {
      "sku": "SKU-6153",
      "sales": 328911
    },
    {
      "sku": "SKU-4483",
      "sales": 21251
    },
    {
      "sku": "SKU-5114",
      "sales": 21486
    }
  ]
}


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

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

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

Output:
{
  "post_id": "POST-33796851",
  "platform": "instagram",
  "user_id": "aa32cdd3-72c6-4e38-bd5e-ff3918321d73",
  "username": "qtownsend",
  "content": "List floor whatever fly. Play represent five my. Stuff area push other begin team. Wind leg require represent.",
  "timestamp": "2026-01-07T13:51:26.038556",
  "hashtags": [
    "#study",
    "#able",
    "#week"
  ],
  "engagement": {
    "likes": 3006,
    "shares": 53,
    "comments": 61
  }
}


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

[User]
Reformat the data below from JSON to CSV:
{
  "post_id": "POST-78635818",
  "platform": "facebook",
  "user_id": "a739269a-9642-463c-9c88-cb97c795c8d8",
  "username": "kevin10",
  "content": "Specific other kind choice. Condition main resource finish north reach with break. Area strategy huge edge.",
  "timestamp": "2026-01-07T13:51:25.965362",
  "hashtags": [
    "#model",
    "#firm"
  ],
  "engagement": {
    "likes": 3831,
    "shares": 379,
    "comments": 204
  }
}

[Assistant]
Approach:
1. Task: Convert social media post 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:
content,engagement_comments,engagement_likes,engagement_shares,hashtags,platform,post_id,timestamp,user_id,username
Specific other kind choice. Condition main resource finish north reach with break. Area strategy hug,204,3831,379,"[""#model"", ""#firm""]",facebook,POST-78635818,2026-01-07T13:51:25.965362,a739269a-9642-463c-9c88-cb97c795c8d8,kevin10
"Happen hold place decision eight yeah another performance. Mother same teacher step receive.
Answer ",460,1163,231,"[""#fill"", ""#blood""]",twitter,POST-41903911,2026-01-07T13:51:25.967869,eb3a0a35-2686-4085-a1ef-8e4471021524,jessica37
"Issue wonder fight blood. Have nearly protect.
Debate response kid claim up. And either view ball.
T",352,9232,1,"[""#consider"", ""#old"", ""#window""]",facebook,POST-34325917,2026-01-07T13:51:25.968216,01d66a28-f522-413f-abe9-ca75980d44b7,cassidy60
Entire call want man so political work. His new each western time each. Thing part political who mov,357,5433,191,"[""#spring"", ""#part""]",twitter,POST-18455284,2026-01-07T13:51:25.968594,0c574abb-ce5d-47a9-9962-6df013221b3e,phillipsbecky
"Door during company factor he key.
Early movement summer along will ok. Ok show thought. Cell score ",295,920,845,"[""#politics"", ""#represent""]",instagram,POST-18820580,2026-01-07T13:51:25.968959,46efbc86-2800-4e13-a7d9-9de97b0bc5ee,qhunter


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

[User] Produce a XML document for a experiment result.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<experiment_result>
<experiment_id>EXP-160417</experiment_id>
<title>Effect of agree on both</title>
<methodology>
<design>cohort</design>
<sample_size>663</sample_size>
<duration_days>354</duration_days>
</methodology>
<results>
<metric>safety</metric>
<baseline>13.92</baseline>
<endpoint>49.07</endpoint>
<p_value>0.4102</p_value>
</results>
<results>
<metric>safety</metric>
<baseline>15.99</baseline>
<endpoint>65.81</endpoint>
<p_value>0.3043</p_value>
</results>
<results>
<metric>efficacy</metric>
<baseline>46.51</baseline>
<endpoint>82.23</endpoint>
<p_value>0.4775</p_value>
</results>
<conclusion>non-significant</conclusion>
</experiment_result>


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<news_article>
<content>Range condition class leader wrong subject wait. Stop we prevent particular front method. Force item executive employee green large house nation. General doctor material rule head event.
One will dog chance. Order away music seem director put upon. Find boy again direction four.</content>
<article_id>ART-9628131</article_id>
<headline>Re-contextualized logistical paradigm</headline>
</news_article>


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

[Assistant]
Approach:
1. Task: Convert research paper from JSON to 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:2020.10600</paper_id>
<title>Reactive bi-directional middleware</title>
<authors>
<name>Sarah Rose</name>
<affiliation>Martin, Taylor and Mills</affiliation>
<email>adrianporter@example.com</email>
</authors>
<authors>
<name>Samantha Garcia</name>
<affiliation>Santiago LLC</affiliation>
<email>cbrewer@example.net</email>
</authors>
<abstract>Carry prove certain tell event break. Thus not actually teacher girl perhaps.</abstract>
<keywords>public</keywords>
<keywords>stock</keywords>
<keywords>student</keywords>
<keywords>hair</keywords>
<keywords>hard</keywords>
<publication>
<venue>Cell</venue>
<year>2022</year>
<doi>10.6112/KodW</doi>
</publication>
<citations>273</citations>
<funding_source>Salazar, Mullen and Johnson</funding_source>
</research_paper>


[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: complex - 8-10 fields, 3-4 levels
3. Format rules: header row, comma-separated, quoted fields with commas
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
abstract,authors,channels,citations,funding_source,keywords,paper_id,period,publication_doi,publication_venue,publication_year,title,top_products,total_revenue,units_sold
,,"[{""name"": ""online"", ""revenue"": 1867975, ""growth"": -2.95}, {""name"": ""retail"", ""revenue"": 1947932, ""gr",,,,,February 2024,,,,,"[{""sku"": ""SKU-5409"", ""sales"": 492017}, {""sku"": ""SKU-4816"", ""sales"": 486050}, {""sku"": ""SKU-9957"", ""sa",3108970,70292
Deal future person mouth. Conference teacher right century road miss investment.,"[{""name"": ""Shannon Huffman"", ""affiliation"": ""Robbins Ltd"", ""email"": ""heidibecker@example.org""}, {""na",,263,None,"[""grow"", ""ever"", ""government"", ""decide"", ""others""]",arXiv:2022.88134,,10.6936/DOHE,Science,2024,Phased explicit productivity,,,
Painting decade property act. Recently generation church perform.,"[{""name"": ""Theresa Marshall"", ""affiliation"": ""Nguyen-Bowers"", ""email"": ""timothy82@example.org""}, {""n",,40,Perez Group,"[""drug"", ""run"", ""child""]",arXiv:2020.10489,,10.7625/OKbW,Nature,2022,Adaptive real-time frame,,,
Pattern certain bring although central truth. It reality father. Draw could see door Democrat.,"[{""name"": ""Natalie Lane"", ""affiliation"": ""Stephenson-Chavez"", ""email"": ""zmurray@example.net""}, {""nam",,390,"Adams, Norris and Mcdonald","[""remember"", ""significant"", ""plan"", ""know"", ""list""]",arXiv:2023.54771,,10.3213/HEIC,Science,2023,Vision-oriented cohesive migration,,,


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

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

[Assistant]
Approach:
1. Task: Create social media post 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:
content,engagement_comments,engagement_likes,engagement_shares,hashtags,platform,post_id,timestamp,user_id,username
"Speech can sea play. Season near story animal remain.
Off present vote wall. Society know family bui",161,248,32,"[""#once"", ""#it"", ""#rich"", ""#keep""]",instagram,POST-58559815,2026-01-07T13:51:26.463560,0fae79ab-dabb-47f5-823b-f22743181c7c,ortizkristina
Technology subject market. This and left hair hour important whatever outside. Hear evidence parent ,97,1028,267,"[""#station"", ""#key""]",facebook,POST-56873412,2026-01-07T13:51:26.464950,6ae9ae62-20d4-40e8-b046-c02de1e12018,april62
"Them per ground quite common. Determine rest imagine less. Throughout back give.
Risk church treatme",276,4105,359,"[""#consumer"", ""#dinner"", ""#national"", ""#amount""]",twitter,POST-66004552,2026-01-07T13:51:26.465520,e0b5b01d-c32c-441f-9bce-4fbc6c6db3e8,kathyanderson
"Least should break he look door establish. Indeed later again.
Rule economic old anything line term.",209,1083,187,"[""#set"", ""#apply"", ""#control""]",twitter,POST-73257797,2026-01-07T13:51:26.466224,5c140188-df51-432a-9479-7339507a516a,randallbailey
"Matter on word suddenly myself lead admit. Network half program home someone financial within.
Expla",280,645,355,"[""#break"", ""#nor"", ""#almost"", ""#mind""]",instagram,POST-28207122,2026-01-07T13:51:26.466901,d7bc5771-d243-4900-8d43-f914044b162b,martinezjill


[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:2020.86983",
  "title": "Reverse-engineered national Graphical User Interface",
  "authors": [
    {
      "name": "Wesley Murphy",
      "affiliation": "Nunez, Meyer and Snow",
      "email": "nina74@example.net"
    },
    {
      "name": "Richard Morgan",
      "affiliation": "Hall-Jones",
      "email": "justin85@example.org"
    },
    {
      "name": "Anthony Johnson",
      "affiliation": "Kelley-Murphy",
      "email": "srichmond@example.com"
    }
  ],
  "abstract": "Sure finally site who truth. Close stop when low. Check news mother democratic.",
  "keywords": [
    "old",
    "indeed",
    "general",
    "claim",
    "every"
  ],
  "publication": {
    "venue": "Nature",
    "year": 2024,
    "doi": "10.2539/QMDE"
  },
  "citations": 221,
  "funding_source": null
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<research_paper>
<paper_id>arXiv:2020.86983</paper_id>
<title>Reverse-engineered national Graphical User Interface</title>
<authors>
<name>Wesley Murphy</name>
<affiliation>Nunez, Meyer and Snow</affiliation>
<email>nina74@example.net</email>
</authors>
<authors>
<name>Richard Morgan</name>
<affiliation>Hall-Jones</affiliation>
<email>justin85@example.org</email>
</authors>
<authors>
<name>Anthony Johnson</name>
<affiliation>Kelley-Murphy</affiliation>
<email>srichmond@example.com</email>
</authors>
<abstract>Sure finally site who truth. Close stop when low. Check news mother democratic.</abstract>
<keywords>old</keywords>
<keywords>indeed</keywords>
<keywords>general</keywords>
<keywords>claim</keywords>
<keywords>every</keywords>
<publication>
<venue>Nature</venue>
<year>2024</year>
<doi>10.2539/QMDE</doi>
</publication>
<citations>221</citations>
<funding_source />
</research_paper>


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

[User] Create a XML representation of customer review.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<review_id>REV-1132090</review_id>
<product_id>PROD-380257</product_id>
<user_id>251dc214-da1e-4fb5-8ea5-d107ad43f82c</user_id>
<rating>4</rating>
<title>Young race true property less government.</title>
<content>Brother agent radio might own development. Too strong minute building why. Cell so amount imagine simple.
Court every deal change allow last practice. Western far thus.</content>
<date>2026-01-03</date>
<verified_purchase>False</verified_purchase>
<helpful_votes>14</helpful_votes>
</customer_review>


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

[User]
Convert the following TOML to JSON:
review_id = "REV-3836429"
product_id = "PROD-852988"
user_id = "39a3d2bd-fb84-4dfc-9cb6-45bd3ebddca0"
rating = 2
title = "Report thus get describe identify."
content = "Or dog never any center population. Program it they Republican over step. Who television finish true game.\nList catch candidate west research. Meeting many imagine."
date = "2026-01-01"
verified_purchase = false
helpful_votes = 23

[Assistant]
Approach:
1. Task: Convert customer review from TOML 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-3836429",
  "product_id": "PROD-852988",
  "user_id": "39a3d2bd-fb84-4dfc-9cb6-45bd3ebddca0",
  "rating": 2,
  "title": "Report thus get describe identify.",
  "content": "Or dog never any center population. Program it they Republican over step. Who television finish true game.\nList catch candidate west research. Meeting many imagine.",
  "date": "2026-01-01",
  "verified_purchase": false,
  "helpful_votes": 23
}


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

[User] Output student assessment as XML.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<student_assessment>
<total_score>65</total_score>
<percentage>51.02</percentage>
<assessment_id>ASMT-810488</assessment_id>
</student_assessment>


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

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

[Assistant]
Approach:
1. Task: Create course syllabus in TOML
2. Complexity: 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:
course_id = "CRS-3440"
code = "KLD251"
title = "Reverse-engineered foreground infrastructure 101"
instructor = "Courtney Escobar"
credits = 4
term = "Spring 2022"
[[schedule]]
week = 1
topic = "despite"

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

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

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

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

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

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

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

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


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

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

[Assistant]
Approach:
1. Task: Create course syllabus 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:
code,course_id,credits,grading_final,grading_homework,grading_midterm,instructor,schedule,term,title
DBP130,CRS-8855,3,40,30,30,Carl Davis,"[{""week"": 1, ""topic"": ""manage""}, {""week"": 2, ""topic"": ""someone""}, {""week"": 3, ""topic"": ""bring""}, {""w",Fall 2024,Team-oriented 3rdgeneration implementation 101
DEN254,CRS-9176,4,40,30,30,Barry Atkinson,"[{""week"": 1, ""topic"": ""present""}, {""week"": 2, ""topic"": ""wait""}, {""week"": 3, ""topic"": ""fact""}, {""week",Spring 2022,Distributed next generation contingency 101
MTT479,CRS-8159,3,40,30,30,Thomas Reyes,"[{""week"": 1, ""topic"": ""set""}, {""week"": 2, ""topic"": ""bit""}, {""week"": 3, ""topic"": ""husband""}, {""week"":",Spring 2021,Expanded intangible pricing structure 101
TIJ329,CRS-4277,3,40,30,30,Kelly Rush,"[{""week"": 1, ""topic"": ""after""}, {""week"": 2, ""topic"": ""visit""}, {""week"": 3, ""topic"": ""easy""}, {""week""",Fall 2020,Implemented methodical installation 101
VLH270,CRS-7106,3,40,30,30,Darryl Ferguson IV,"[{""week"": 1, ""topic"": ""team""}, {""week"": 2, ""topic"": ""rest""}, {""week"": 3, ""topic"": ""decade""}, {""week""",Fall 2023,Grass-roots tangible complexity 101


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

[User] Output research paper as XML.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<research_paper>
<paper_id>arXiv:2020.57295</paper_id>
<title>Persevering global groupware</title>
<authors>
<name>Edwin Moore</name>
<affiliation>Smith-Jones</affiliation>
<email>bowenzachary@example.net</email>
</authors>
<authors>
<name>Anna Collins</name>
<affiliation>Thomas, Rogers and Baldwin</affiliation>
<email>thill@example.com</email>
</authors>
<authors>
<name>Mrs. Mary Delacruz MD</name>
<affiliation>French, Rodriguez and Johnson</affiliation>
<email>amywest@example.org</email>
</authors>
<abstract>Stand season mind indicate either. Buy gas keep skin.</abstract>
<keywords>stock</keywords>
<keywords>member</keywords>
<keywords>laugh</keywords>
<keywords>language</keywords>
<keywords>right</keywords>
<publication>
<venue>Cell</venue>
<year>2022</year>
<doi>10.9461/HDZk</doi>
</publication>
<citations>204</citations>
<funding_source />
</research_paper>


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

[User] Output financial report as XML.

[Assistant]
Approach:
1. Task: Create financial report in XML
2. Complexity: 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"?>
<financial_report>
<revenue>81140617</revenue>
<metrics>
<profit_margin>25.46</profit_margin>
<roe>20.6</roe>
</metrics>
<quarter>Q1 2021</quarter>
</financial_report>


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<financial_report>
<company>Leon-Lewis</company>
<ticker>FGCI</ticker>
<quarter>Q4 2022</quarter>
<revenue>56885685</revenue>
<expenses>46362888</expenses>
<net_income>14538939</net_income>
<eps>7.9</eps>
<metrics>
<profit_margin>25.04</profit_margin>
<roe>5.27</roe>
</metrics>
</financial_report>


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

[User] Create a YAML representation of error log.

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

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


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

[User]
Convert the following CSV to TOML:
abstract,authors,citations,funding_source,keywords,paper_id,publication_doi,publication_venue,publication_year,title
Yes eat up himself consumer. Technology just debate bill live oil.,"[{""name"": ""William Martin"", ""affiliation"": ""George, Nichols and Johnston"", ""email"": ""crystal73@examp",265,Smith Ltd,"[""each"", ""on"", ""perhaps""]",arXiv:2023.67497,10.2923/Xnio,Nature,2022,Open-architected logistical paradigm
"Recent you low standard case. War set happen business both.
Interest white another begin bit. Hotel ","[{""name"": ""Tony Johnson"", ""affiliation"": ""Velasquez-Mcgee"", ""email"": ""powellbeth@example.net""}, {""na",39,Alexander-Williams,"[""including"", ""image"", ""same"", ""front""]",arXiv:2024.55127,10.1618/CRnt,Nature,2022,Distributed real-time encoding
Role attention attention. Director population and view theory vote.,"[{""name"": ""Amy Atkinson"", ""affiliation"": ""Drake Inc"", ""email"": ""kirk52@example.net""}, {""name"": ""Andr",258,Davis-Adams,"[""lot"", ""later"", ""sell""]",arXiv:2021.67897,10.2296/JGbp,Nature,2023,Re-engineered exuding firmware
"Wonder he ball American page commercial able. Agree international positive meet travel.
Blood summer","[{""name"": ""Mrs. Traci Brown"", ""affiliation"": ""Shields, Howell and Rodriguez"", ""email"": ""barbernatash",194,Moore Ltd,"[""any"", ""talk"", ""under"", ""speech"", ""laugh""]",arXiv:2023.80940,10.3189/iPdm,Science,2021,Profit-focused attitude-oriented ability

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

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

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

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

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


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

[User] Generate course syllabus data in XML format.

[Assistant]
Approach:
1. Task: Create course syllabus in XML
2. Complexity: 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-2281</course_id>
NHA456
<title>Profit-focused mission-critical hardware 101</title>
<instructor>Natalie Middleton</instructor>
<credits>3</credits>
<term>Spring 2024</term>
<schedule>
<week>1</week>
<topic>its</topic>
</schedule>
<schedule>
<week>2</week>
<topic>attorney</topic>
</schedule>
<schedule>
<week>3</week>
<topic>decision</topic>
</schedule>
<schedule>
<week>4</week>
<topic>every</topic>
</schedule>
<schedule>
<week>5</week>
<topic>direction</topic>
</schedule>
<schedule>
<week>6</week>
<topic>player</topic>
</schedule>
<schedule>
<week>7</week>
<topic>city</topic>
</schedule>
<schedule>
<week>8</week>
<topic>everybody</topic>
</schedule>
<schedule>
<week>9</week>
<topic>throw</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 research paper data in JSON format.

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

Output:
{
  "publication": {
    "venue": "Cell",
    "year": 2021,
    "doi": "10.3653/hXNF"
  },
  "funding_source": "Kramer Ltd",
  "title": "Configurable bandwidth-monitored strategy",
  "authors": [
    {
      "name": "James Brown",
      "affiliation": "Ward-Davidson",
      "email": "wilsonkristin@example.org"
    },
    {
      "name": "Luke Liu",
      "affiliation": "Obrien-Huynh",
      "email": "jason08@example.org"
    },
    {
      "name": "Paula Gonzalez",
      "affiliation": "Jones-Howell",
      "email": "brent41@example.org"
    }
  ]
}


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

[User]
Convert the following CSV to TOML:
assessment,chief_complaint,encounter_date,note_id,patient_age,patient_gender,patient_mrn,vitals_bp,vitals_hr,vitals_temp_f
"[{""problem"": ""diabetes"", ""icd10"": ""I65""}, {""problem"": ""diabetes"", ""icd10"": ""J29""}]",fever,2026-01-01,CN-2341842,85,F,MRN-739833,174/60,60,98.7
"[{""problem"": ""hypertension"", ""icd10"": ""J12""}, {""problem"": ""diabetes"", ""icd10"": ""I41""}, {""problem"": """,chest pain,2026-01-01,CN-7426022,39,F,MRN-407740,177/64,95,100.1
"[{""problem"": ""hypertension"", ""icd10"": ""J61""}, {""problem"": ""hypertension"", ""icd10"": ""K55""}, {""problem",chest pain,2026-01-02,CN-4241326,58,M,MRN-538287,104/103,117,98.2

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

Output:
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]
Convert the following XML to TOML:
<?xml version="1.0" encoding="UTF-8"?>
<financial_report>
<company>Richard Ltd</company>
<ticker>XHCL</ticker>
<quarter>Q4 2020</quarter>
<revenue>71255223</revenue>
<expenses>54916122</expenses>
<net_income>1190834</net_income>
<eps>4.63</eps>
<metrics>
<profit_margin>14.39</profit_margin>
<roe>19.33</roe>
</metrics>
</financial_report>

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

Output:
company = "Richard Ltd"
ticker = "XHCL"
quarter = "Q4 2020"
revenue = 71255223
expenses = 54916122
net_income = 1190834
eps = 4.63

[metrics]
profit_margin = 14.39
roe = 19.33


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

[User] Generate customer review data in YAML format.

[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:
date: '2026-01-04'
user_id: d6e6e646-61a4-4af9-a9a1-d03d234244eb
content: 'It herself scene five side support onto. Shake fear western believe. Say
  fact shoulder investment television pretty suffer.

  Ground listen official hand at indeed. Effort thus wife control.'


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

[User] Generate research paper data in CSV format.

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

Output:
abstract,authors,citations,funding_source,keywords,paper_id,publication_doi,publication_venue,publication_year,title
Cut happen you after talk trial accept she. Country church development card. Learn support son servi,"[{""name"": ""Joseph Johnson"", ""affiliation"": ""Mccann, Romero and Ortiz"", ""email"": ""wcook@example.org""}",88,Kim LLC,"[""positive"", ""American"", ""hand"", ""sure""]",arXiv:2021.53732,10.3815/gTFt,Science,2024,De-engineered exuding monitoring
Unit change own. Soldier produce political. Learn product data million write.,"[{""name"": ""Tim Mason"", ""affiliation"": ""Taylor, Reed and Robinson"", ""email"": ""douglashood@example.org",313,None,"[""up"", ""message"", ""any"", ""free""]",arXiv:2023.83242,10.1869/XBoV,Cell,2020,Compatible 3rdgeneration framework
"Sort reduce watch dark manage base.
Big dog with kid truth various. Possible media including informa","[{""name"": ""Kristin Waters"", ""affiliation"": ""Taylor, Taylor and Little"", ""email"": ""carrillomatthew@ex",8,None,"[""number"", ""music"", ""sign"", ""hundred""]",arXiv:2020.24597,10.3170/KwZQ,Cell,2022,Cross-group eco-centric intranet
Congress wear attorney home civil still. Support lose key. Loss player front themselves until suffer,"[{""name"": ""David Griffin"", ""affiliation"": ""Parker-Page"", ""email"": ""donna51@example.net""}, {""name"": """,258,Hood Ltd,"[""Mr"", ""smile"", ""throw"", ""find""]",arXiv:2021.47100,10.3704/OpCW,Nature,2020,Focused tertiary workforce