[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-19844803</post_id>
<platform>instagram</platform>
<user_id>eee48898-e428-4685-b6ea-d0074f4ffb8a</user_id>
<username>pinedaryan</username>
<content>Between past agree writer forget big. Simple glass protect job answer thank.
Government prepare rather agency hard. Fear director room future hospital.</content>
<timestamp>2026-01-07T13:51:25.753060</timestamp>
<hashtags>#fast</hashtags>
<hashtags>#imagine</hashtags>
<hashtags>#carry</hashtags>
<engagement>
<likes>1299</likes>
<shares>900</shares>
<comments>90</comments>
</engagement>
</social_media_post>

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

Output:
{
  "post_id": "POST-19844803",
  "platform": "instagram",
  "user_id": "eee48898-e428-4685-b6ea-d0074f4ffb8a",
  "username": "pinedaryan",
  "content": "Between past agree writer forget big. Simple glass protect job answer thank.\nGovernment prepare rather agency hard. Fear director room future hospital.",
  "timestamp": "2026-01-07T13:51:25.753060",
  "hashtags": [
    "#fast",
    "#imagine",
    "#carry"
  ],
  "engagement": {
    "likes": 1299,
    "shares": 900,
    "comments": 90
  }
}


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<financial_report>
<company>Thompson, Yang and Roberts</company>
<ticker>ATOM</ticker>
<quarter>Q1 2022</quarter>
<revenue>59725729</revenue>
<expenses>36274579</expenses>
<net_income>7802792</net_income>
<eps>8.84</eps>
<metrics>
<profit_margin>17.46</profit_margin>
<roe>22.69</roe>
</metrics>
</financial_report>

[Assistant]
Approach:
1. Task: Convert financial report 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:
{
  "company": "Thompson, Yang and Roberts",
  "ticker": "ATOM",
  "quarter": "Q1 2022",
  "revenue": 59725729,
  "expenses": 36274579,
  "net_income": 7802792,
  "eps": 8.84,
  "metrics": {
    "profit_margin": 17.46,
    "roe": 22.69
  }
}


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

[User]
Convert the following JSON to XML:
{
  "product_id": "PROD-986141",
  "name": "Focused neutral encoding",
  "category": "books",
  "price": 14.45,
  "currency": "USD",
  "stock": 826,
  "is_available": true,
  "rating": 4.59,
  "reviews": 564,
  "specs": {
    "weight_kg": 27.7,
    "dimensions": "42x99x90cm"
  }
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<product_listing>
<product_id>PROD-986141</product_id>
<name>Focused neutral encoding</name>
<category>books</category>
<price>14.45</price>
<currency>USD</currency>
<stock>826</stock>
<is_available>True</is_available>
<rating>4.59</rating>
<reviews>564</reviews>
<specs>
<weight_kg>27.7</weight_kg>
<dimensions>42x99x90cm</dimensions>
</specs>
</product_listing>


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

[User] Produce a TOML document for a transaction record.

[Assistant]
Approach:
1. Task: Create transaction record 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:
txn_id = "TXN-95106885"
customer_id = "9090a0a6-3421-4a93-9d6e-78b6a1f8fed7"
timestamp = "2026-01-07T13:51:27.692524"
subtotal = 793.41
tax = 85.16
total = 1645.24
payment_method = "apple_pay"
[[items]]
sku = "SKU-33525"
qty = 3
price = 130.6


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

[User] Create a CSV representation of error log.

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

Output:
abstract,authors,citations,context_request_id,context_user_id,funding_source,keywords,message,paper_id,publication_doi,publication_venue,publication_year,stack_trace,timestamp,title
,,,0aea7b7e-f431-4209-a4db-008320d27043,b89e754b-fd03-47c7-9600-09a7cb6d3517,,,Baby inside high our should character study quickly.,,,,,"[""at standard.py:486"", ""at memory.py:53"", ""at team.py:342""]",2026-01-07T13:51:25.507604,
"Because mean yard protect sit relate.
Education campaign force right contain choose. Special pick ed","[{""name"": ""Michael Thompson"", ""affiliation"": ""Farmer LLC"", ""email"": ""vlee@example.org""}, {""name"": ""C",397,,,None,"[""parent"", ""challenge"", ""either""]",,arXiv:2023.13141,10.6960/Mnur,Cell,2022,,,Phased well-modulated infrastructure
Entire stock use name. Really authority rather heavy. Skill travel month focus thus see shoulder.,"[{""name"": ""Jeanne Parker"", ""affiliation"": ""Woods-Brown"", ""email"": ""bjones@example.org""}, {""name"": ""K",430,,,Ortiz PLC,"[""option"", ""though"", ""teacher""]",,arXiv:2022.94041,10.6127/xrZD,Cell,2021,,,Automated holistic Local Area Network
Eight increase smile often law challenge citizen. Along door season international report.,"[{""name"": ""David Aguilar"", ""affiliation"": ""Crawford and Sons"", ""email"": ""jfrye@example.com""}, {""name",447,,,None,"[""it"", ""wear"", ""perhaps"", ""enjoy""]",,arXiv:2021.67731,10.6543/nZAn,Nature,2022,,,Sharable object-oriented leverage


[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"?>
<clinical_note>
<note_id>CN-6709459</note_id>
<patient>
<mrn>MRN-104418</mrn>
<age>50</age>
<gender>M</gender>
</patient>
<encounter_date>2026-01-03</encounter_date>
<chief_complaint>fever</chief_complaint>
<vitals>
<bp>143/96</bp>

69

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

[Assistant]
Approach:
1. Task: Convert clinical note 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:
{
  "note_id": "CN-6709459",
  "patient": {
    "mrn": "MRN-104418",
    "age": 50,
    "gender": "M"
  },
  "encounter_date": "2026-01-03",
  "chief_complaint": "fever",
  "vitals": {
    "bp": "143/96",
    "hr": 69,
    "temp_f": 101.3
  },
  "assessment": [
    {
      "problem": "diabetes",
      "icd10": "J90"
    },
    {
      "problem": "hypertension",
      "icd10": "I22"
    },
    {
      "problem": "hypertension",
      "icd10": "K97"
    }
  ]
}


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

[User] Output prescription as TOML.

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

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


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

[User] Create a YAML representation of research paper.

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

Output:
paper_id: arXiv:2024.49729
title: Optimized fault-tolerant monitoring
authors:
- name: Ashley Hubbard
  affiliation: Mcdonald-White
  email: jenniferlong@example.net
- name: Erica Marshall
  affiliation: Calderon-Dalton
  email: adouglas@example.org
- name: Mercedes Campbell
  affiliation: Davis-Lynch
  email: yharris@example.org
abstract: 'Relate make read game soldier new. Agree south attorney one century drive
  draw.

  Reduce head tax certainly offer deal. Sister station adult seat wear.'
keywords:
- gas
- understand
- everything
- miss
publication:
  venue: Cell
  year: 2024
  doi: 10.3465/hMKF
citations: 65
funding_source: Parsons Inc


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

[User] Create a XML representation of transaction record.

[Assistant]
Approach:
1. Task: Create transaction record 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"?>
<transaction_record>
<txn_id>TXN-13058367</txn_id>
<customer_id>852e4544-1bd4-44f1-abf0-2ff01b4a4792</customer_id>
<timestamp>2026-01-07T13:51:26.835091</timestamp>
<items>
<sku>SKU-47822</sku>
<qty>3</qty>
<price>237.72</price>
</items>
<items>
<sku>SKU-38430</sku>
<qty>4</qty>
<price>285.9</price>
</items>
<items>
<sku>SKU-22327</sku>
<qty>1</qty>
<price>141.71</price>
</items>
<subtotal>408.33</subtotal>
<tax>11.32</tax>
<total>1142.29</total>
<payment_method>paypal</payment_method>
</transaction_record>


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<transaction_record>
<txn_id>TXN-98000345</txn_id>
<customer_id>681a59bc-1151-4d49-8e75-1af0878315cb</customer_id>
<timestamp>2026-01-07T13:51:26.087659</timestamp>
<items>
<sku>SKU-50616</sku>
<qty>3</qty>
<price>180.94</price>
</items>
<items>
<sku>SKU-82812</sku>
<qty>5</qty>
<price>490.31</price>
</items>
<subtotal>948.16</subtotal>
<tax>93.65</tax>
<total>1389.7</total>
<payment_method>credit_card</payment_method>
</transaction_record>

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

Output:
{
  "txn_id": "TXN-98000345",
  "customer_id": "681a59bc-1151-4d49-8e75-1af0878315cb",
  "timestamp": "2026-01-07T13:51:26.087659",
  "items": [
    {
      "sku": "SKU-50616",
      "qty": 3,
      "price": 180.94
    },
    {
      "sku": "SKU-82812",
      "qty": 5,
      "price": 490.31
    }
  ],
  "subtotal": 948.16,
  "tax": 93.65,
  "total": 1389.7,
  "payment_method": "credit_card"
}


[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"?>
<course_syllabus>
<instructor>Rachel Moreno DVM</instructor>
<credits>4</credits>
<course_id>CRS-8305</course_id>
<title>Open-architected even-keeled support 101</title>
<term>Spring 2023</term>
</course_syllabus>

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

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

[User] Create a TOML representation of research paper.

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

Output:
paper_id = "arXiv:2024.66116"
title = "Quality-focused grid-enabled service-desk"
abstract = "Body exactly last operation trouble. Financial whole check management chance eat us. Likely wrong explain by would born only."
keywords = [ "rather", "hair", "attorney", "chance", "bring",]
citations = 174
[[authors]]
name = "David Cohen"
affiliation = "Lopez and Sons"
email = "mark98@example.com"

[[authors]]
name = "Ashley Spencer"
affiliation = "Hood Ltd"
email = "pbailey@example.org"

[[authors]]
name = "Robin Lynch"
affiliation = "Camacho, Nelson and Perez"
email = "samantha44@example.net"

[publication]
venue = "Cell"
year = 2020
doi = "10.7468/EeJM"


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

[User]
Reformat the data below from JSON to XML:
{
  "rx_id": "RX-5973418",
  "patient_mrn": "MRN-615844",
  "prescriber": "Brian Erickson",
  "date": "2026-01-01",
  "medications": [
    {
      "name": "Lisinopril",
      "dosage": "20mg",
      "frequency": "TID",
      "quantity": 60
    },
    {
      "name": "Metformin",
      "dosage": "20mg",
      "frequency": "daily",
      "quantity": 60
    }
  ]
}

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


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<error_log>
<error_id>92d36993-19b1-4c19-9b64-8b4669c6636f</error_id>
<timestamp>2026-01-07T13:51:27.222487</timestamp>
<level>WARNING</level>
<service>voiceService</service>
<message>Analysis beautiful attack blue eye.</message>
<stack_trace>at well.py:163</stack_trace>
<stack_trace>at will.py:421</stack_trace>
<stack_trace>at run.py:384</stack_trace>
<stack_trace>at TV.py:103</stack_trace>
<context>
<user_id>c92bcb8f-c109-47f8-aa13-b43737a1fc38</user_id>
<request_id>f4cb6737-30c9-41ef-814b-34c3ec971deb</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 product listing.

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

Output:
product_id = "PROD-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"


[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: 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: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 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:
{
  "contract_id": "CTR-457828",
  "effective_date": "2026-01-01",
  "term_months": 32
}


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

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

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


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

[User]
Reformat the data below from JSON to XML:
{
  "contract_id": "CTR-926700",
  "parties": [
    {
      "name": "Kelly-Jackson",
      "role": "party_a"
    },
    {
      "name": "Ramos, Hampton and Hartman",
      "role": "party_b"
    }
  ],
  "effective_date": "2026-01-04",
  "term_months": 36,
  "value": 178791,
  "status": "pending"
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<contract>
<contract_id>CTR-926700</contract_id>
<parties>
<name>Kelly-Jackson</name>
<role>party_a</role>
</parties>
<parties>
<name>Ramos, Hampton and Hartman</name>
<role>party_b</role>
</parties>
<effective_date>2026-01-04</effective_date>
<term_months>36</term_months>
<value>178791</value>
<status>pending</status>
</contract>


[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"?>
<experiment_result>
<experiment_id>EXP-393268</experiment_id>
<title>Effect of themselves on time</title>
<methodology>
<design>RCT</design>
<sample_size>237</sample_size>
<duration_days>116</duration_days>
</methodology>
<results>
<metric>efficacy</metric>
<baseline>34.76</baseline>
<endpoint>73.98</endpoint>
<p_value>0.4055</p_value>
</results>
<results>
<metric>safety</metric>
<baseline>70.26</baseline>
<endpoint>84.17</endpoint>
<p_value>0.253</p_value>
</results>
<results>
<metric>safety</metric>
<baseline>22.1</baseline>
<endpoint>56.91</endpoint>
<p_value>0.1172</p_value>
</results>
<conclusion>significant</conclusion>
</experiment_result>

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

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


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

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

[Assistant]
Approach:
1. Task: Create social media post 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:
{
  "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 XML format. Think step-by-step, then generate syntactically perfect XML.

[User] Create a XML representation of financial report.

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

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


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

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

[Assistant]
Approach:
1. Task: Create customer review in YAML
2. Complexity: 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-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.

  List catch candidate west research. Meeting many imagine.'
date: '2026-01-01'
verified_purchase: false
helpful_votes: 23


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

[User] Create a YAML representation of 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-143990
parties:
- name: Brady Inc
  role: party_a
- name: Gonzalez, Coleman and Sanchez
  role: party_b
effective_date: '2026-01-02'
term_months: 32
value: 452000
status: active


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

[User] Output transaction record as JSON.

[Assistant]
Approach:
1. Task: Create transaction record in JSON
2. Complexity: 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:
{
  "subtotal": 205.31,
  "payment_method": "apple_pay",
  "total": 1732.06
}


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

[User] Create a XML representation of financial report.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<financial_report>
<company>Mcintyre, French and Sherman</company>
<ticker>GRIC</ticker>
<quarter>Q4 2021</quarter>
<revenue>78125638</revenue>
<expenses>13448897</expenses>
<net_income>14876002</net_income>
<eps>9.04</eps>
<metrics>
<profit_margin>9.81</profit_margin>
<roe>23.34</roe>
</metrics>
</financial_report>


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

[User]
Reformat the data below from CSV to JSON:
company,eps,expenses,metrics_profit_margin,metrics_roe,net_income,quarter,revenue,ticker
Becker-Martinez,2.39,50274851,17.0,10.6,7284021,Q4 2021,48919598,QZXR
Johnson-Steele,1.11,69430773,19.0,9.65,7959822,Q1 2020,62654443,BQLE
Anderson-Graham,5.89,68379328,14.38,15.83,12240911,Q3 2023,67416606,QXVQ
"Fry, Larsen and Taylor",4.82,24798058,15.39,6.77,5018725,Q4 2021,62010556,BFEK
"Smith, Cabrera and Carney",5.08,32876364,25.73,16.81,228293,Q1 2023,73439746,BOIP

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

Output:
{
  "company": "Becker-Martinez",
  "ticker": "QZXR",
  "quarter": "Q4 2021",
  "revenue": 48919598,
  "expenses": 50274851,
  "net_income": 7284021,
  "eps": 2.39,
  "metrics": {
    "profit_margin": 17.0,
    "roe": 10.6
  }
}


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

[User] Output financial report as CSV.

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

Output:
company,eps,expenses,metrics_profit_margin,metrics_roe,net_income,quarter,revenue,ticker
Moore-Thompson,9.88,43130054,22.03,10.54,18329728,Q2 2022,73324772,XFVE
"Mitchell, Hill and Snyder",2.11,62228330,27.98,6.91,15794806,Q1 2023,33373636,ZJPQ
Black-Lee,4.6,6806668,28.92,9.57,15521739,Q3 2022,4159375,POVF
"Moore, Jackson and Clark",5.4,19651312,27.9,7.54,15441171,Q3 2022,72468776,EYIF
Daniels Group,3.98,45295567,10.11,14.31,15253374,Q2 2022,27807708,DVIK


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

[User] Create a JSON representation of news article.

[Assistant]
Approach:
1. Task: Create news article in JSON
2. Complexity: 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:
{
  "author": "Jenna Bryant",
  "tags": [
    "most",
    "off",
    "shoulder"
  ],
  "headline": "Secured composite leverage",
  "published": "2026-01-04T22:19:16.750289"
}


[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>
<category>electronics</category>
<specs>
<weight_kg>38.59</weight_kg>
<dimensions>23x92x45cm</dimensions>
</specs>
<stock>596</stock>
<price>218.58</price>
</product_listing>


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

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

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


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

[User] Generate lab result data in JSON format.

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

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


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

[User]
Transform this JSON data into TOML format:
{
  "results": [
    {
      "metric": "efficacy",
      "baseline": 40.85,
      "endpoint": 40.08,
      "p_value": 0.4196
    },
    {
      "metric": "efficacy",
      "baseline": 82.87,
      "endpoint": 28.4,
      "p_value": 0.208
    },
    {
      "metric": "efficacy",
      "baseline": 74.0,
      "endpoint": 18.43,
      "p_value": 0.3638
    },
    {
      "metric": "efficacy",
      "baseline": 50.48,
      "endpoint": 15.59,
      "p_value": 0.1146
    }
  ],
  "methodology": {
    "design": "observational",
    "sample_size": 351,
    "duration_days": 339
  },
  "conclusion": "non-significant"
}

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

Output:
conclusion = "non-significant"
[[results]]
metric = "efficacy"
baseline = 40.85
endpoint = 40.08
p_value = 0.4196

[[results]]
metric = "efficacy"
baseline = 82.87
endpoint = 28.4
p_value = 0.208

[[results]]
metric = "efficacy"
baseline = 74.0
endpoint = 18.43
p_value = 0.3638

[[results]]
metric = "efficacy"
baseline = 50.48
endpoint = 15.59
p_value = 0.1146

[methodology]
design = "observational"
sample_size = 351
duration_days = 339


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

[User]
Reformat the data below from JSON to XML:
{
  "error_id": "2d978d26-6fd7-4641-b202-43ebc0760711",
  "timestamp": "2026-01-07T13:51:26.663970",
  "level": "WARNING",
  "service": "someoneService",
  "message": "Inside live none value unit Republican black.",
  "stack_trace": [
    "at role.py:276",
    "at loss.py:371"
  ],
  "context": {
    "user_id": "26f1b94c-c76e-47ab-9121-a3f8ec11053f",
    "request_id": "ce096dca-f53f-40bf-822d-ed29d8ca8dd9"
  }
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<error_log>
<error_id>2d978d26-6fd7-4641-b202-43ebc0760711</error_id>
<timestamp>2026-01-07T13:51:26.663970</timestamp>
<level>WARNING</level>
<service>someoneService</service>
<message>Inside live none value unit Republican black.</message>
<stack_trace>at role.py:276</stack_trace>
<stack_trace>at loss.py:371</stack_trace>
<context>
<user_id>26f1b94c-c76e-47ab-9121-a3f8ec11053f</user_id>
<request_id>ce096dca-f53f-40bf-822d-ed29d8ca8dd9</request_id>
</context>
</error_log>


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

[User] Create a TOML representation of product listing.

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

Output:
product_id = "PROD-107958"
name = "Adaptive asynchronous synergy"
category = "electronics"
price = 349.45
currency = "USD"
stock = 717
is_available = true
rating = 1.62
reviews = 33

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


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

[User] Output error log as TOML.

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

Output:
error_id = "2d978d26-6fd7-4641-b202-43ebc0760711"
timestamp = "2026-01-07T13:51:26.663970"
level = "WARNING"
service = "someoneService"
message = "Inside live none value unit Republican black."
stack_trace = [ "at role.py:276", "at loss.py:371",]

[context]
user_id = "26f1b94c-c76e-47ab-9121-a3f8ec11053f"
request_id = "ce096dca-f53f-40bf-822d-ed29d8ca8dd9"


[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"?>
<clinical_note>
<note_id>CN-4441974</note_id>
<patient>
<mrn>MRN-925906</mrn>
<age>60</age>
<gender>F</gender>
</patient>
<encounter_date>2026-01-02</encounter_date>
<chief_complaint>headache</chief_complaint>
<vitals>
<bp>154/95</bp>

108

<temp_f>97.8</temp_f>
</vitals>
<assessment>
<problem>diabetes</problem>
<icd10>J60</icd10>
</assessment>
<assessment>
<problem>hypertension</problem>
<icd10>I21</icd10>
</assessment>
<assessment>
<problem>diabetes</problem>
<icd10>K16</icd10>
</assessment>
</clinical_note>

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


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

[User] Generate prescription data in XML format.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<prescription>
<rx_id>RX-7328466</rx_id>
<patient_mrn>MRN-740510</patient_mrn>
<prescriber>William Hebert</prescriber>
<date>2026-01-04</date>
<medications>
<name>Lisinopril</name>
<dosage>20mg</dosage>
<frequency>TID</frequency>
<quantity>30</quantity>
</medications>
<medications>
<name>Metformin</name>
<dosage>20mg</dosage>
<frequency>BID</frequency>
<quantity>60</quantity>
</medications>
</prescription>


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

[User] Create a JSON representation of financial report.

[Assistant]
Approach:
1. Task: Create financial report in JSON
2. Complexity: 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:
{
  "company": "Ortega-Owens",
  "ticker": "YLLB",
  "quarter": "Q3 2022",
  "revenue": 37598920,
  "expenses": 44591506,
  "net_income": 3197580,
  "eps": 1.51,
  "metrics": {
    "profit_margin": 5.54,
    "roe": 6.32
  }
}


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

[User] Create a YAML representation of prescription.

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

Output:
rx_id: RX-5160762
patient_mrn: MRN-568012
prescriber: Linda Gonzalez
date: '2026-01-06'
medications:
- name: Lisinopril
  dosage: 20mg
  frequency: TID
  quantity: 30
- name: Atorvastatin
  dosage: 5mg
  frequency: daily
  quantity: 60


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

[User]
Transform this YAML data into JSON format:
course_id: CRS-8422
code: OMY437
title: Optimized upward-trending conglomeration 101
instructor: Rodney Anderson
credits: 3
term: Spring 2023
schedule:
- week: 1
  topic: answer
- week: 2
  topic: best
- week: 3
  topic: meet
- week: 4
  topic: simple
- week: 5
  topic: peace
- week: 6
  topic: upon
- week: 7
  topic: power
grading:
  homework: 30
  midterm: 30
  final: 40

[Assistant]
Approach:
1. Task: Convert course syllabus from YAML 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-8422",
  "code": "OMY437",
  "title": "Optimized upward-trending conglomeration 101",
  "instructor": "Rodney Anderson",
  "credits": 3,
  "term": "Spring 2023",
  "schedule": [
    {
      "week": 1,
      "topic": "answer"
    },
    {
      "week": 2,
      "topic": "best"
    },
    {
      "week": 3,
      "topic": "meet"
    },
    {
      "week": 4,
      "topic": "simple"
    },
    {
      "week": 5,
      "topic": "peace"
    },
    {
      "week": 6,
      "topic": "upon"
    },
    {
      "week": 7,
      "topic": "power"
    }
  ],
  "grading": {
    "homework": 30,
    "midterm": 30,
    "final": 40
  }
}


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

[User]
Reformat the data below from TOML to JSON:
review_id = "REV-2971879"
product_id = "PROD-601177"
user_id = "49ec79ac-cc63-409f-8812-a70c492b6835"
rating = 3
title = "Safe everything country understand subject."
content = "Explain among above role speech. Hear law enjoy. Lose building fall everything million.\nEast choose however class dark test good contain. Indicate worker mean hot."
date = "2026-01-06"
verified_purchase = true
helpful_votes = 67

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


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

[User] Generate customer review data in JSON format.

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

Output:
{
  "review_id": "REV-4235678",
  "product_id": "PROD-754494",
  "user_id": "29638f7d-f697-4ae7-8fde-a1a70bcd6476",
  "rating": 5,
  "title": "Help program law water necessary return clearly.",
  "content": "Team hold course throw center open enjoy old. Huge candidate still act decade civil. Safe middle indeed.",
  "date": "2026-01-03",
  "verified_purchase": false,
  "helpful_votes": 98
}


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

[User] Output student assessment as CSV.

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

Output:
assessment_id,code,course_id,credits,date,grade,grading_final,grading_homework,grading_midterm,instructor,percentage,schedule,scores,student_id,term,title,total_score,type
ASMT-871992,,CRS-5865,,2026-01-05,B,,,,,70.57,,"[{""question"": 1, ""points_earned"": 1, ""points_possible"": 10}, {""question"": 2, ""points_earned"": 6, ""po",STU-916232,,,83,quiz
,KKE147,CRS-2056,4,,,40,30,30,Mary Blanchard,,"[{""week"": 1, ""topic"": ""particular""}, {""week"": 2, ""topic"": ""him""}, {""week"": 3, ""topic"": ""war""}, {""wee",,,Fall 2020,Right-sized interactive workforce 101,,
,VJM346,CRS-9407,4,,,40,30,30,Tony Johnson,,"[{""week"": 1, ""topic"": ""but""}, {""week"": 2, ""topic"": ""difference""}, {""week"": 3, ""topic"": ""final""}, {""w",,,Fall 2020,Operative empowering moderator 101,,
,ZVR422,CRS-7767,3,,,40,30,30,Andrea Lynch,,"[{""week"": 1, ""topic"": ""tough""}, {""week"": 2, ""topic"": ""attention""}, {""week"": 3, ""topic"": ""provide""}, ",,,Fall 2021,Reactive zero-defect instruction set 101,,
,PNM488,CRS-9779,3,,,40,30,30,Cynthia Chapman,,"[{""week"": 1, ""topic"": ""development""}, {""week"": 2, ""topic"": ""space""}, {""week"": 3, ""topic"": ""customer""",,,Spring 2020,Balanced content-based software 101,,


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

[User] Create a XML representation of research paper.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<research_paper>
<paper_id>arXiv:2022.87629</paper_id>
<title>Decentralized zero tolerance knowledgebase</title>
<authors>
<name>Jonathan Murphy</name>
<affiliation>Long and Sons</affiliation>
<email>loconnell@example.org</email>
</authors>
<authors>
<name>Patrick Skinner</name>
<affiliation>Williams and Sons</affiliation>
<email>chentimothy@example.org</email>
</authors>
<authors>
<name>Todd Smith</name>
<affiliation>Lewis LLC</affiliation>
<email>nedwards@example.org</email>
</authors>
<abstract>System many view vote. Into challenge wind result new good.</abstract>
<keywords>modern</keywords>
<keywords>over</keywords>
<keywords>during</keywords>
<keywords>affect</keywords>
<keywords>sport</keywords>
<publication>
<venue>Cell</venue>
<year>2022</year>
<doi>10.5354/mlMa</doi>
</publication>
<citations>187</citations>
<funding_source>Fischer and Sons</funding_source>
</research_paper>


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

[User]
Transform this TOML data into JSON format:
error_id = "2d978d26-6fd7-4641-b202-43ebc0760711"
timestamp = "2026-01-07T13:51:26.663970"
level = "WARNING"
service = "someoneService"
message = "Inside live none value unit Republican black."
stack_trace = [ "at role.py:276", "at loss.py:371",]

[context]
user_id = "26f1b94c-c76e-47ab-9121-a3f8ec11053f"
request_id = "ce096dca-f53f-40bf-822d-ed29d8ca8dd9"

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

Output:
{
  "error_id": "2d978d26-6fd7-4641-b202-43ebc0760711",
  "timestamp": "2026-01-07T13:51:26.663970",
  "level": "WARNING",
  "service": "someoneService",
  "message": "Inside live none value unit Republican black.",
  "stack_trace": [
    "at role.py:276",
    "at loss.py:371"
  ],
  "context": {
    "user_id": "26f1b94c-c76e-47ab-9121-a3f8ec11053f",
    "request_id": "ce096dca-f53f-40bf-822d-ed29d8ca8dd9"
  }
}


[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:
{
  "total_revenue": 6798538,
  "channels": [
    {
      "name": "online",
      "revenue": 2139770,
      "growth": -9.99
    },
    {
      "name": "retail",
      "revenue": 1809716,
      "growth": 7.01
    }
  ],
  "top_products": [
    {
      "sku": "SKU-3049",
      "sales": 22854
    },
    {
      "sku": "SKU-5505",
      "sales": 203281
    },
    {
      "sku": "SKU-9853",
      "sales": 260538
    }
  ]
}

[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>
<total_revenue>6798538</total_revenue>
<channels>
<name>online</name>
<revenue>2139770</revenue>
<growth>-9.99</growth>
</channels>
<channels>
<name>retail</name>
<revenue>1809716</revenue>
<growth>7.01</growth>
</channels>
<top_products>
<sku>SKU-3049</sku>
<sales>22854</sales>
</top_products>
<top_products>
<sku>SKU-5505</sku>
<sales>203281</sales>
</top_products>
<top_products>
<sku>SKU-9853</sku>
<sales>260538</sales>
</top_products>
</sales_analytics>


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

[User] Create a TOML representation of lab result.

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

Output:
result_id = "LAB-2309770"
patient_mrn = "MRN-380513"
order_date = "2026-01-02"
panel = "CMP"
[[results]]
test = "Glucose"
value = 62.8
unit = "mg/dL"
flag = "normal"

[[results]]
test = "Hemoglobin"
value = 141.2
unit = "mg/dL"
flag = "high"

[[results]]
test = "WBC"
value = 75.4
unit = "g/dL"
flag = "low"

[[results]]
test = "Glucose"
value = 174.6
unit = "g/dL"
flag = "low"

[[results]]
test = "Glucose"
value = 170.1
unit = "g/dL"
flag = "low"


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

[User] Generate api specification data in XML format.

[Assistant]
Approach:
1. Task: Create api specification 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"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Centralized web-enabled hardware API</title>
<version>1.0.0</version>
</info>
<paths>
</improve>
<get>
<summary>Act attention yes herself significant recent.</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>
<//improve>
</paths>
</api_specification>


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

[User] Create a JSON representation of product listing.

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

Output:
{
  "product_id": "PROD-842353",
  "name": "Synergistic bottom-line conglomeration",
  "category": "books",
  "price": 609.49,
  "currency": "USD",
  "stock": 399,
  "is_available": true,
  "rating": 1.05,
  "reviews": 570,
  "specs": {
    "weight_kg": 25.04,
    "dimensions": "30x19x82cm"
  }
}


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

[User] Create a XML representation of experiment result.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<experiment_result>
<experiment_id>EXP-318732</experiment_id>
<title>Effect of produce on stock</title>
<methodology>
<design>observational</design>
<sample_size>303</sample_size>
<duration_days>155</duration_days>
</methodology>
<results>
<metric>safety</metric>
<baseline>20.77</baseline>
<endpoint>67.03</endpoint>
<p_value>0.1826</p_value>
</results>
<results>
<metric>safety</metric>
<baseline>69.69</baseline>
<endpoint>32.04</endpoint>
<p_value>0.1176</p_value>
</results>
<conclusion>non-significant</conclusion>
</experiment_result>


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

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

[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:2021.53732</paper_id>
<title>De-engineered exuding monitoring</title>
<authors>
<name>Joseph Johnson</name>
<affiliation>Mccann, Romero and Ortiz</affiliation>
<email>wcook@example.org</email>
</authors>
<authors>
<name>Mr. Henry Thomas</name>
<affiliation>Clarke-Williams</affiliation>
<email>mlittle@example.com</email>
</authors>
<abstract>Cut happen you after talk trial accept she. Country church development card. Learn support son service.</abstract>
<keywords>positive</keywords>
<keywords>American</keywords>
<keywords>hand</keywords>
<keywords>sure</keywords>
<publication>
<venue>Science</venue>
<year>2024</year>
<doi>10.3815/gTFt</doi>
</publication>
<citations>88</citations>
<funding_source>Kim LLC</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: medium - 5-8 fields, 2-3 levels
3. Format rules: header row, comma-separated, quoted fields with commas
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
abstract,authors,channels,citations,funding_source,keywords,paper_id,period,publication_doi,publication_venue,publication_year,title,top_products,total_revenue,units_sold
,,"[{""name"": ""wholesale"", ""revenue"": 2780960, ""growth"": 22.76}, {""name"": ""retail"", ""revenue"": 4140341, ",,,,,June 2021,,,,,"[{""sku"": ""SKU-8636"", ""sales"": 261407}, {""sku"": ""SKU-9950"", ""sales"": 107242}, {""sku"": ""SKU-8311"", ""sa",4317671,11582
Fire truth true citizen determine. Baby though draw become low experience participant. Artist free a,"[{""name"": ""Kayla Cobb"", ""affiliation"": ""Hunter, Wilson and Davis"", ""email"": ""laceypotter@example.org",,1,Arellano Inc,"[""chance"", ""card"", ""finally"", ""usually"", ""six""]",arXiv:2020.77957,,10.4716/TNvb,Nature,2021,Universal cohesive product,,,
A from feel. Look indeed beat here. She party rule center this few power.,"[{""name"": ""Timothy Williams"", ""affiliation"": ""Hall-Beck"", ""email"": ""wking@example.org""}, {""name"": ""J",,34,"Davis, Calhoun and Patterson","[""explain"", ""design"", ""bed"", ""see"", ""both""]",arXiv:2020.49188,,10.3811/NLdi,Cell,2022,Visionary modular structure,,,
Reality lead strategy yet either sense Mr increase. Face hour mention prepare relate performance bed,"[{""name"": ""Jose Saunders"", ""affiliation"": ""Martinez-Wallace"", ""email"": ""dpotts@example.org""}, {""name",,191,"Hernandez, Delacruz and Stark","[""describe"", ""first"", ""party"", ""article"", ""enjoy""]",arXiv:2022.63932,,10.4741/aTmg,Cell,2022,Innovative motivating help-desk,,,


[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:
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

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


[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: 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"?>
<research_paper>
<paper_id>arXiv:2024.31964</paper_id>
<title>Optimized solution-oriented success</title>
<authors>
<name>Meagan Sutton</name>
<affiliation>Williamson, Mitchell and Smith</affiliation>
<email>davilabridget@example.com</email>
</authors>
<authors>
<name>William Gross</name>
<affiliation>Miller and Sons</affiliation>
<email>linda03@example.net</email>
</authors>
<abstract>Price while never. Night great must well remain. Share less reveal often.</abstract>
<keywords>less</keywords>
<keywords>radio</keywords>
<keywords>spend</keywords>
<keywords>which</keywords>
<publication>
<venue>Science</venue>
<year>2023</year>
<doi>10.4651/vEqE</doi>
</publication>
<citations>155</citations>
<funding_source />
</research_paper>


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<error_log>
<error_id>c6e14566-270a-4a5f-a250-5239ca9174ac</error_id>
<timestamp>2026-01-07T13:51:26.338486</timestamp>
<level>ERROR</level>
<service>humanService</service>
<message>Fear she east talk better central.</message>
<stack_trace>at college.py:218</stack_trace>
<stack_trace>at economy.py:209</stack_trace>
<stack_trace>at let.py:252</stack_trace>
<stack_trace>at whole.py:18</stack_trace>
<context>
<user_id>bda2bdb3-cc4e-4711-8927-aa42dc72d462</user_id>
<request_id>c7d51186-07ee-4743-a193-c5688ac0d6c5</request_id>
</context>
</error_log>

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

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


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

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

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

Output:
paper_id: arXiv:2022.79764
title: Progressive exuding adapter
authors:
- name: Gary Johnson
  affiliation: Wolf Group
  email: jamie40@example.org
- name: Lisa Ortega
  affiliation: Wells, Flores and Cooper
  email: nicholas25@example.com
- name: Kimberly Alvarez
  affiliation: Lewis-Hunt
  email: bookersteven@example.com
abstract: Win both purpose hour professor table.
keywords:
- office
- during
- more
- apply
- program
publication:
  venue: Nature
  year: 2023
  doi: 10.1780/NyHo
citations: 258
funding_source: Espinoza, Khan and Lowe


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

[User] Output news article as XML.

[Assistant]
Approach:
1. Task: Create news article 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"?>
<news_article>
<article_id>ART-1748125</article_id>
<headline>Customizable leadingedge structure</headline>
<author>Sandra Bennett</author>
<published>2026-01-03T22:52:42.741679</published>

Sports

<content>Majority meeting sound have week public pass. Major food relate spend seven.
Indeed run fund.
Federal right stuff difficult alone miss. Stuff rest model job deep knowledge pull force. Too follow face husband every. Hit important agreement rather card west want.</content>
<tags>subject</tags>
<tags>attention</tags>
<tags>class</tags>
<tags>campaign</tags>
<tags>second</tags>
<views>63827</views>
<shares>2505</shares>
</news_article>


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<student_assessment>
<date>2026-01-01</date>
<total_score>85</total_score>
<student_id>STU-920172</student_id>
</student_assessment>

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

Output:
{
  "date": "2026-01-01",
  "total_score": 85,
  "student_id": "STU-920172"
}


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<contract>
<contract_id>CTR-619223</contract_id>
<parties>
<name>Mcdaniel LLC</name>
<role>party_a</role>
</parties>
<parties>
<name>Hunt-Bowman</name>
<role>party_b</role>
</parties>
<effective_date>2026-01-03</effective_date>
<term_months>21</term_months>
<value>87478</value>
<status>pending</status>
</contract>

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

Output:
{
  "contract_id": "CTR-619223",
  "parties": [
    {
      "name": "Mcdaniel LLC",
      "role": "party_a"
    },
    {
      "name": "Hunt-Bowman",
      "role": "party_b"
    }
  ],
  "effective_date": "2026-01-03",
  "term_months": 21,
  "value": 87478,
  "status": "pending"
}


[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"?>
<lab_result>
<result_id>LAB-2309770</result_id>
<patient_mrn>MRN-380513</patient_mrn>
<order_date>2026-01-02</order_date>
<panel>CMP</panel>
<results>
<test>Glucose</test>
<value>62.8</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>141.2</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>WBC</test>
<value>75.4</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Glucose</test>
<value>174.6</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Glucose</test>
<value>170.1</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
</lab_result>

[Assistant]
Approach:
1. Task: Convert lab result 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:
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"

[[results]]
test = "Hemoglobin"
value = 141.2
unit = "mg/dL"
flag = "high"

[[results]]
test = "WBC"
value = 75.4
unit = "g/dL"
flag = "low"

[[results]]
test = "Glucose"
value = 174.6
unit = "g/dL"
flag = "low"

[[results]]
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:
{
  "experiment_id": "EXP-330074",
  "title": "Effect of politics on stop",
  "methodology": {
    "design": "RCT",
    "sample_size": 328,
    "duration_days": 247
  },
  "results": [
    {
      "metric": "efficacy",
      "baseline": 34.54,
      "endpoint": 53.32,
      "p_value": 0.0487
    },
    {
      "metric": "safety",
      "baseline": 10.4,
      "endpoint": 13.84,
      "p_value": 0.1164
    },
    {
      "metric": "efficacy",
      "baseline": 78.27,
      "endpoint": 47.78,
      "p_value": 0.0781
    }
  ],
  "conclusion": "non-significant"
}

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

Output:
experiment_id: EXP-330074
title: Effect of politics on stop
methodology:
  design: RCT
  sample_size: 328
  duration_days: 247
results:
- metric: efficacy
  baseline: 34.54
  endpoint: 53.32
  p_value: 0.0487
- metric: safety
  baseline: 10.4
  endpoint: 13.84
  p_value: 0.1164
- metric: efficacy
  baseline: 78.27
  endpoint: 47.78
  p_value: 0.0781
conclusion: non-significant


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

[User] Output product listing as CSV.

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

Output:
category,currency,is_available,name,price,product_id,rating,reviews,specs_dimensions,specs_weight_kg,stock
books,USD,True,Universal eco-centric approach,208.68,PROD-125540,4.53,925,45x91x83cm,20.35,879
books,USD,True,Multi-channeled zero-defect data-warehouse,217.23,PROD-945438,2.92,542,27x49x90cm,32.98,221
electronics,USD,True,Quality-focused cohesive budgetary management,918.44,PROD-425720,4.68,599,49x93x50cm,34.53,435
clothing,USD,True,Enhanced uniform paradigm,272.01,PROD-700627,3.32,377,45x52x53cm,13.1,49


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

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

[Assistant]
Approach:
1. Task: Create customer review in YAML
2. Complexity: 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-1384784
product_id: PROD-499626
user_id: 4c396b1f-b1b7-4ef7-9587-0fda03a6f7f9
rating: 1
title: Respond out five.
content: 'I stay little Democrat money where stop. Than development activity.

  Along ahead their standard early nor reason. Fight with minute learn soldier understand.'
date: '2026-01-05'
verified_purchase: false
helpful_votes: 94


[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:
{
  "subtotal": 1655.93,
  "items": [
    {
      "sku": "SKU-62708",
      "qty": 3,
      "price": 121.39
    }
  ],
  "tax": 19.12,
  "total": 1424.63
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<transaction_record>
<subtotal>1655.93</subtotal>
<items>
<sku>SKU-62708</sku>
<qty>3</qty>
<price>121.39</price>
</items>
<tax>19.12</tax>
<total>1424.63</total>
</transaction_record>


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

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

[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>
<is_available>True</is_available>
<rating>1.03</rating>
<category>electronics</category>
<price>302.74</price>
</product_listing>


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

[User] Create a YAML representation of student assessment.

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

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


[System] You are an expert in 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-4787173</review_id>
<product_id>PROD-746934</product_id>
<user_id>a1638e54-91af-4e5f-be10-465327f3fbf6</user_id>
<rating>4</rating>
<title>Rock company surface either million.</title>
<content>Suddenly plant stay thank project hand me. Commercial his road carry training trip.</content>
<date>2026-01-02</date>
<verified_purchase>True</verified_purchase>
<helpful_votes>3</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-4787173",
  "product_id": "PROD-746934",
  "user_id": "a1638e54-91af-4e5f-be10-465327f3fbf6",
  "rating": 4,
  "title": "Rock company surface either million.",
  "content": "Suddenly plant stay thank project hand me. Commercial his road carry training trip.",
  "date": "2026-01-02",
  "verified_purchase": true,
  "helpful_votes": 3
}


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

[User] Output prescription as YAML.

[Assistant]
Approach:
1. Task: Create prescription 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:
rx_id: RX-9719971
patient_mrn: MRN-909141
prescriber: Heather Stephens
date: '2026-01-05'
medications:
- name: Atorvastatin
  dosage: 20mg
  frequency: daily
  quantity: 30


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

[User]
Reformat the data below from JSON to XML:
{
  "note_id": "CN-4466987",
  "patient": {
    "mrn": "MRN-766590",
    "age": 87,
    "gender": "F"
  },
  "encounter_date": "2026-01-02",
  "chief_complaint": "headache",
  "vitals": {
    "bp": "147/66",
    "hr": 72,
    "temp_f": 101.1
  },
  "assessment": [
    {
      "problem": "diabetes",
      "icd10": "K25"
    }
  ]
}

[Assistant]
Approach:
1. Task: Convert clinical note 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"?>
<clinical_note>
<note_id>CN-4466987</note_id>
<patient>
<mrn>MRN-766590</mrn>
<age>87</age>
<gender>F</gender>
</patient>
<encounter_date>2026-01-02</encounter_date>
<chief_complaint>headache</chief_complaint>
<vitals>
<bp>147/66</bp>

72

<temp_f>101.1</temp_f>
</vitals>
<assessment>
<problem>diabetes</problem>
<icd10>K25</icd10>
</assessment>
</clinical_note>


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

[User] Output product listing as JSON.

[Assistant]
Approach:
1. Task: Create product listing 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:
{
  "specs": {
    "weight_kg": 8.02,
    "dimensions": "62x22x22cm"
  },
  "name": "Universal fault-tolerant service-desk",
  "price": 907.33,
  "reviews": 493
}


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

[User]
Transform this JSON data into YAML format:
{
  "grade": "A",
  "course_id": "CRS-4519",
  "total_score": 75
}

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

Output:
grade: A
course_id: CRS-4519
total_score: 75


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

[User] Generate transaction record data in CSV format.

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

Output:
abstract,authors,citations,customer_id,funding_source,keywords,paper_id,payment_method,publication_doi,publication_venue,publication_year,title,total
,,,fe237049-a4a1-4a5c-af14-940bbb31d0e7,,,,paypal,,,,,1227.54
Individual education outside particular student expert eye. Could sort already race candidate.,"[{""name"": ""Deborah Richardson"", ""affiliation"": ""Smith LLC"", ""email"": ""danielsbrett@example.com""}, {""",79,,None,"[""interest"", ""dream"", ""far"", ""understand""]",arXiv:2022.45556,,10.6940/WzuX,Cell,2020,Compatible 3rdgeneration analyzer,
Affect within second road run push. Five drive late leave open eye cold. Account operation white nic,"[{""name"": ""Justin Lucas"", ""affiliation"": ""Williams, Williams and Cameron"", ""email"": ""sylvia38@exampl",81,,"Allen, Aguilar and Smith","[""factor"", ""deep"", ""he"", ""model"", ""head""]",arXiv:2024.92466,,10.8648/mRXC,Nature,2021,Innovative zero-defect neural-net,
"Laugh almost high different appear.
Guess return yet you table over. Have who foot whose wait health","[{""name"": ""Sydney Smith"", ""affiliation"": ""Brewer, Jacobs and Rodriguez"", ""email"": ""weaverkathleen@ex",300,,None,"[""little"", ""method"", ""know"", ""perform""]",arXiv:2022.28425,,10.1596/JaQF,Cell,2024,Universal impactful collaboration,


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

[User] Output api specification as CSV.

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

Output:
abstract,authors,citations,funding_source,info_title,info_version,keywords,openapi,paper_id,paths_/rule_get_parameters,paths_/rule_get_responses_200_description,paths_/rule_get_responses_400_description,paths_/rule_get_summary,publication_doi,publication_venue,publication_year,title
,,,,Cross-group bottom-line algorithm API,1.0.0,,3.0.0,,"[{""name"": ""param0"", ""in"": ""query"", ""type"": ""string""}, {""name"": ""param1"", ""in"": ""query"", ""type"": ""str",Success,Bad Request,Center available level environment per away author,,,,
Art necessary because just far. Information someone task PM. Never if why.,"[{""name"": ""Mr. Phillip Miller"", ""affiliation"": ""Mclaughlin, Anderson and Pierce"", ""email"": ""sharonsm",327,None,,,"[""customer"", ""age"", ""trouble""]",,arXiv:2021.19335,,,,,10.9579/ucXg,Science,2020,Right-sized bottom-line customer loyalty
Purpose meeting most strategy hand alone official. Rise movie me son former force cultural. Difficul,"[{""name"": ""Erin Griffin"", ""affiliation"": ""Chapman-Monroe"", ""email"": ""jorgewerner@example.org""}, {""na",265,"Scott, Johnson and Chandler",,,"[""rise"", ""data"", ""quickly""]",,arXiv:2022.50803,,,,,10.4965/BkKb,Nature,2023,Enterprise-wide methodical throughput


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

Output:
content,engagement_comments,engagement_likes,engagement_shares,hashtags,platform,post_id,timestamp,user_id,username
"Determine live compare center as direction. Eye experience low wear. If south level.
Worry expect st",146,2214,878,"[""#culture"", ""#whole"", ""#central""]",facebook,POST-18209344,2026-01-07T13:51:27.602464,8880ae5d-22ce-466e-ac5d-224201417b5e,xmcbride
Read hundred fire democratic class computer not second. System whom possible leader conference finis,490,1695,292,"[""#less"", ""#far"", ""#determine""]",instagram,POST-71900733,2026-01-07T13:51:27.603972,8ae3dfa0-cd37-472f-8775-1e4c1e3b39e3,briangriffin
West exist growth nor several. View time suddenly rest. Recognize show second with manage parent cap,196,246,604,"[""#my"", ""#reduce"", ""#lawyer"", ""#join""]",twitter,POST-94789158,2026-01-07T13:51:27.604355,df8a6bb0-d59b-4683-843c-36e587452965,millsjohn


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

[User] Create a XML representation of lab result.

[Assistant]
Approach:
1. Task: Create lab result in XML
2. Complexity: 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"?>
<lab_result>
<result_id>LAB-3793814</result_id>
<patient_mrn>MRN-247204</patient_mrn>
<order_date>2026-01-03</order_date>
<panel>CBC</panel>
<results>
<test>Hemoglobin</test>
<value>188.2</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>WBC</test>
<value>197.7</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Glucose</test>
<value>196.4</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Glucose</test>
<value>193.9</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Glucose</test>
<value>197.2</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>109.5</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
</lab_result>


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

[User] Output experiment result as JSON.

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

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


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<error_log>
<service>findService</service>
<stack_trace>at watch.py:197</stack_trace>
<stack_trace>at body.py:298</stack_trace>
<stack_trace>at girl.py:392</stack_trace>
<stack_trace>at red.py:350</stack_trace>
<level>ERROR</level>
<message>Head then too threat drive.</message>
</error_log>

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

Output:
{
  "service": "findService",
  "stack_trace": [
    "at watch.py:197",
    "at body.py:298",
    "at girl.py:392",
    "at red.py:350"
  ],
  "level": "ERROR",
  "message": "Head then too threat drive."
}


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

[User] Create a JSON representation of course syllabus.

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

Output:
{
  "course_id": "CRS-9141",
  "code": "ESH384",
  "title": "Inverse real-time hardware 101",
  "instructor": "Matthew Boyd",
  "credits": 4,
  "term": "Fall 2022",
  "schedule": [
    {
      "week": 1,
      "topic": "western"
    },
    {
      "week": 2,
      "topic": "since"
    },
    {
      "week": 3,
      "topic": "later"
    },
    {
      "week": 4,
      "topic": "next"
    },
    {
      "week": 5,
      "topic": "tree"
    },
    {
      "week": 6,
      "topic": "until"
    },
    {
      "week": 7,
      "topic": "everything"
    },
    {
      "week": 8,
      "topic": "until"
    },
    {
      "week": 9,
      "topic": "how"
    },
    {
      "week": 10,
      "topic": "test"
    },
    {
      "week": 11,
      "topic": "half"
    }
  ],
  "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]
Reformat the data below from JSON to CSV:
{
  "article_id": "ART-2188860",
  "headline": "Advanced well-modulated service-desk",
  "author": "Michael Logan",
  "published": "2026-01-03T08:09:52.608144",
  "section": "Politics",
  "content": "Include start build no effort continue. Mention sister mention threat.\nChoose herself case writer question over. Hand quickly house send shoulder expert hour.\nAll probably suffer law consider kitchen relationship. Data population personal past security but across.",
  "tags": [
    "hear",
    "civil",
    "might",
    "way",
    "win"
  ],
  "views": 35184,
  "shares": 1092
}

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

Output:
article_id,author,content,headline,published,section,shares,tags,views
ART-2188860,Michael Logan,"Include start build no effort continue. Mention sister mention threat.
Choose herself case writer qu",Advanced well-modulated service-desk,2026-01-03T08:09:52.608144,Politics,1092,"[""hear"", ""civil"", ""might"", ""way"", ""win""]",35184
ART-8331327,Kenneth Price,Military explain especially bank no loss low. Face identify simple police politics executive. Fish a,Streamlined grid-enabled encoding,2026-01-02T15:29:07.783374,Sports,659,"[""data"", ""trade"", ""front"", ""wrong"", ""phone""]",7773
ART-3732564,Jonathon Hunter,Need final green cold activity thus. Stock artist price across. Discussion but another wide stock wa,Ergonomic foreground methodology,2026-01-02T16:06:09.986745,Politics,4217,"[""business"", ""society"", ""growth""]",30424
ART-4379135,Mark Pope,"By campaign worker she parent. White see sort with grow pattern.
Who benefit we lawyer arrive requir",Compatible heuristic portal,2026-01-03T03:19:51.715732,Politics,425,"[""my"", ""main"", ""throughout"", ""scientist""]",5028
ART-2162694,Stephanie Harrison,"Near fact live spring too. Road treat yard person.
Quality lay apply character exactly. Mouth mainta",De-engineered local process improvement,2026-01-03T15:34:28.887808,Politics,1909,"[""focus"", ""paper"", ""with""]",67820


[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"?>
<experiment_result>
<experiment_id>EXP-506156</experiment_id>
<title>Effect of window on soldier</title>
<methodology>
<design>observational</design>
<sample_size>884</sample_size>
<duration_days>87</duration_days>
</methodology>
<results>
<metric>safety</metric>
<baseline>32.86</baseline>
<endpoint>81.82</endpoint>
<p_value>0.3265</p_value>
</results>
<results>
<metric>efficacy</metric>
<baseline>88.84</baseline>
<endpoint>10.2</endpoint>
<p_value>0.448</p_value>
</results>
<results>
<metric>safety</metric>
<baseline>27.68</baseline>
<endpoint>60.55</endpoint>
<p_value>0.1062</p_value>
</results>
<results>
<metric>safety</metric>
<baseline>51.8</baseline>
<endpoint>89.23</endpoint>
<p_value>0.4543</p_value>
</results>
<conclusion>significant</conclusion>
</experiment_result>

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

Output:
{
  "experiment_id": "EXP-506156",
  "title": "Effect of window on soldier",
  "methodology": {
    "design": "observational",
    "sample_size": 884,
    "duration_days": 87
  },
  "results": [
    {
      "metric": "safety",
      "baseline": 32.86,
      "endpoint": 81.82,
      "p_value": 0.3265
    },
    {
      "metric": "efficacy",
      "baseline": 88.84,
      "endpoint": 10.2,
      "p_value": 0.448
    },
    {
      "metric": "safety",
      "baseline": 27.68,
      "endpoint": 60.55,
      "p_value": 0.1062
    },
    {
      "metric": "safety",
      "baseline": 51.8,
      "endpoint": 89.23,
      "p_value": 0.4543
    }
  ],
  "conclusion": "significant"
}


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

[User] Output lab result as JSON.

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

Output:
{
  "result_id": "LAB-4827299",
  "patient_mrn": "MRN-871984",
  "order_date": "2026-01-06",
  "panel": "Lipid",
  "results": [
    {
      "test": "WBC",
      "value": 156.4,
      "unit": "g/dL",
      "flag": "high"
    },
    {
      "test": "WBC",
      "value": 186.0,
      "unit": "mg/dL",
      "flag": "low"
    },
    {
      "test": "WBC",
      "value": 134.8,
      "unit": "mg/dL",
      "flag": "normal"
    },
    {
      "test": "WBC",
      "value": 64.1,
      "unit": "mg/dL",
      "flag": "normal"
    }
  ]
}


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

[User] Generate sales analytics data in TOML format.

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

Output:
period = "June 2024"
total_revenue = 5319249
units_sold = 96009
[[channels]]
name = "wholesale"
revenue = 941227
growth = 26.4

[[channels]]
name = "retail"
revenue = 937409
growth = 30.07

[[top_products]]
sku = "SKU-2900"
sales = 81858

[[top_products]]
sku = "SKU-8266"
sales = 123988

[[top_products]]
sku = "SKU-9969"
sales = 32400


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

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

[Assistant]
Approach:
1. Task: Create social media post in XML
2. Complexity: 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-23186111</post_id>
<platform>twitter</platform>
<user_id>85951ac5-a9b8-4154-8edc-693bcde245cf</user_id>
<username>srodriguez</username>
<content>Stand leave decade year collection. Republican point edge yet business.
Suffer accept central against. Cup theory mouth side message.
Concern magazine exactly maybe oil difficult.</content>
<timestamp>2026-01-07T13:51:25.750515</timestamp>
<hashtags>#community</hashtags>
<hashtags>#whatever</hashtags>
<engagement>
<likes>4745</likes>
<shares>251</shares>
<comments>51</comments>
</engagement>
</social_media_post>


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

[User] Output experiment result as JSON.

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

Output:
{
  "experiment_id": "EXP-690622",
  "title": "Effect of drug on effect",
  "methodology": {
    "design": "RCT",
    "sample_size": 718,
    "duration_days": 247
  },
  "results": [
    {
      "metric": "efficacy",
      "baseline": 65.65,
      "endpoint": 47.19,
      "p_value": 0.4009
    },
    {
      "metric": "efficacy",
      "baseline": 18.88,
      "endpoint": 49.79,
      "p_value": 0.0184
    },
    {
      "metric": "efficacy",
      "baseline": 32.37,
      "endpoint": 97.44,
      "p_value": 0.3919
    }
  ],
  "conclusion": "non-significant"
}