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

[User] Produce a YAML document for a 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-9346457
patient_mrn: MRN-685856
prescriber: Thomas Archer
date: '2026-01-05'
medications:
- name: Lisinopril
  dosage: 20mg
  frequency: daily
  quantity: 90
- name: Atorvastatin
  dosage: 10mg
  frequency: BID
  quantity: 60


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

[User] Output transaction record as CSV.

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

Output:
customer_id,items,payment_method,subtotal,tax,timestamp,total,txn_id
242fd3fb-d1fb-4e06-b998-4ca6fd25c6b7,"[{""sku"": ""SKU-16950"", ""qty"": 3, ""price"": 120.22}, {""sku"": ""SKU-76122"", ""qty"": 1, ""price"": 377.76}, {",apple_pay,1338.06,172.92,2026-01-07T13:51:27.047573,2048.81,TXN-15638187
87fb8358-f308-4846-9f3b-8c0bf98f23e2,"[{""sku"": ""SKU-97514"", ""qty"": 1, ""price"": 442.94}, {""sku"": ""SKU-17613"", ""qty"": 1, ""price"": 461.52}, {",paypal,1014.7,73.61,2026-01-07T13:51:27.048962,1934.44,TXN-72465879
977bd55e-359b-455c-9c7e-c6496441c099,"[{""sku"": ""SKU-52889"", ""qty"": 1, ""price"": 80.16}]",paypal,1458.44,88.6,2026-01-07T13:51:27.049021,2013.4,TXN-16810043
3c39f72c-160f-4ced-8d17-a0100b62dba3,"[{""sku"": ""SKU-79186"", ""qty"": 3, ""price"": 358.13}, {""sku"": ""SKU-69189"", ""qty"": 2, ""price"": 110.22}, {",apple_pay,1293.97,103.12,2026-01-07T13:51:27.049059,1848.15,TXN-72339060


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<lab_result>
<result_id>LAB-5383313</result_id>
<patient_mrn>MRN-584871</patient_mrn>
<order_date>2026-01-06</order_date>
<panel>CMP</panel>
<results>
<test>Glucose</test>
<value>194.0</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>67.1</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Glucose</test>
<value>195.1</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>146.6</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>WBC</test>
<value>119.8</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
</lab_result>


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

[User]
Transform this CSV data into TOML format:
date,medications,patient_mrn,prescriber,rx_id
2026-01-01,"[{""name"": ""Atorvastatin"", ""dosage"": ""5mg"", ""frequency"": ""daily"", ""quantity"": 30}]",MRN-461250,Zachary Berry,RX-9036427
2026-01-02,"[{""name"": ""Metformin"", ""dosage"": ""5mg"", ""frequency"": ""TID"", ""quantity"": 60}, {""name"": ""Metformin"", """,MRN-940708,William Hall,RX-2204407
2026-01-02,"[{""name"": ""Lisinopril"", ""dosage"": ""5mg"", ""frequency"": ""daily"", ""quantity"": 90}, {""name"": ""Atorvastat",MRN-568077,Joseph Cooper,RX-1030562
2026-01-03,"[{""name"": ""Atorvastatin"", ""dosage"": ""5mg"", ""frequency"": ""TID"", ""quantity"": 30}]",MRN-183915,Heidi Gonzalez,RX-2226508
2026-01-01,"[{""name"": ""Atorvastatin"", ""dosage"": ""20mg"", ""frequency"": ""daily"", ""quantity"": 90}, {""name"": ""Atorvas",MRN-391479,Christopher Johnson,RX-8911382

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

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


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

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

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

Output:
error_id = "2a52fc1b-775b-4f0d-9bad-8f4f44e2d81f"
timestamp = "2026-01-07T13:51:25.611338"
level = "ERROR"
service = "typeService"
message = "Suggest involve part skill write left participant."
stack_trace = [ "at risk.py:441", "at strategy.py:390", "at performance.py:267", "at kind.py:265",]

[context]
user_id = "3651fff2-dc6a-4fe5-a964-ed26913f3e4b"
request_id = "f4fc48f0-6374-4e80-b666-89c2abac0904"


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

[User] Generate student assessment data in JSON format.

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

Output:
{
  "assessment_id": "ASMT-482875",
  "student_id": "STU-646713",
  "course_id": "CRS-2679",
  "type": "assignment",
  "date": "2026-01-01",
  "scores": [
    {
      "question": 1,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 3,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 9,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 10,
      "points_earned": 8,
      "points_possible": 10
    }
  ],
  "total_score": 62,
  "percentage": 98.87,
  "grade": "C"
}


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

[User] Create a XML representation of api specification.

[Assistant]
Approach:
1. Task: Create api specification in XML
2. Complexity: 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"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Pre-emptive interactive encryption API</title>
<version>1.0.0</version>
</info>
<paths>
</air>
<get>
<summary>Final democratic whatever event director guy.</summary>
<parameters>
<name>param0</name>
<in>query</in>
<type>string</type>
</parameters>
<responses>
<200>
<description>Success</description>
</200>
<400>
<description>Bad Request</description>
</400>
</responses>
</get>
<//air>
</paths>
</api_specification>


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

[User] Create a TOML representation of financial report.

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

Output:
revenue = 65816825
ticker = "IQTA"
expenses = 77578182
company = "Ramos-Wallace"


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

[User] Output experiment result as XML.

[Assistant]
Approach:
1. Task: Create experiment 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"?>
<experiment_result>
<experiment_id>EXP-734376</experiment_id>
<title>Effect of probably on skin</title>
<methodology>
<design>cohort</design>
<sample_size>800</sample_size>
<duration_days>273</duration_days>
</methodology>
<results>
<metric>efficacy</metric>
<baseline>94.92</baseline>
<endpoint>99.12</endpoint>
<p_value>0.3163</p_value>
</results>
<results>
<metric>safety</metric>
<baseline>43.8</baseline>
<endpoint>81.58</endpoint>
<p_value>0.1627</p_value>
</results>
<results>
<metric>efficacy</metric>
<baseline>31.59</baseline>
<endpoint>36.02</endpoint>
<p_value>0.4619</p_value>
</results>
<results>
<metric>efficacy</metric>
<baseline>82.54</baseline>
<endpoint>59.85</endpoint>
<p_value>0.3654</p_value>
</results>
<conclusion>significant</conclusion>
</experiment_result>


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

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

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


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

[User] Output social media post as YAML.

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

Output:
post_id: POST-52722833
platform: facebook
user_id: d42576ea-a78d-4261-852d-cbcc2fd55da5
username: justin96
content: 'Southern write three operation throw interest whether.

  Decade quality training employee. Financial out position catch finish author. Past
  over in create.

  Nice reduce try contain future back customer.'
timestamp: '2026-01-07T13:51:26.716888'
hashtags:
- '#report'
- '#newspaper'
engagement:
  likes: 8106
  shares: 850
  comments: 244


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<prescription>
<rx_id>RX-6036951</rx_id>
<patient_mrn>MRN-440463</patient_mrn>
<prescriber>Lisa Mathews</prescriber>
<date>2026-01-05</date>
<medications>
<name>Metformin</name>
<dosage>20mg</dosage>
<frequency>TID</frequency>
<quantity>90</quantity>
</medications>
</prescription>

[Assistant]
Approach:
1. Task: Convert prescription 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:
{
  "rx_id": "RX-6036951",
  "patient_mrn": "MRN-440463",
  "prescriber": "Lisa Mathews",
  "date": "2026-01-05",
  "medications": [
    {
      "name": "Metformin",
      "dosage": "20mg",
      "frequency": "TID",
      "quantity": 90
    }
  ]
}


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

[User]
Convert the following JSON to XML:
{
  "review_id": "REV-2691236",
  "product_id": "PROD-245093",
  "user_id": "98b0ec97-f0e6-4eda-907b-c1488d5de2f5",
  "rating": 1,
  "title": "Now new sell exist just.",
  "content": "Issue suddenly such maybe. Military they second staff end agreement.\nClose that speech alone know wish matter. Finally adult statement method.",
  "date": "2026-01-02",
  "verified_purchase": false,
  "helpful_votes": 34
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<review_id>REV-2691236</review_id>
<product_id>PROD-245093</product_id>
<user_id>98b0ec97-f0e6-4eda-907b-c1488d5de2f5</user_id>
<rating>1</rating>
<title>Now new sell exist just.</title>
<content>Issue suddenly such maybe. Military they second staff end agreement.
Close that speech alone know wish matter. Finally adult statement method.</content>
<date>2026-01-02</date>
<verified_purchase>False</verified_purchase>
<helpful_votes>34</helpful_votes>
</customer_review>


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

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

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

Output:
period: September 2023
total_revenue: 9732569
units_sold: 38507
channels:
- name: retail
  revenue: 4979277
  growth: 36.06
- name: wholesale
  revenue: 4800863
  growth: 8.87
top_products:
- sku: SKU-5649
  sales: 311811
- sku: SKU-1879
  sales: 391924
- sku: SKU-4665
  sales: 317392


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

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

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

Output:
openapi = "3.0.0"

[info]
title = "Horizontal interactive project API"
version = "1.0.0"

[paths."/base".get]
summary = "Management send father actually special image."
[[paths."/base".get.parameters]]
name = "param0"
in = "query"
type = "string"

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

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


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

[User] Create a TOML representation of transaction record.

[Assistant]
Approach:
1. Task: Create transaction record 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:
txn_id = "TXN-48552675"
customer_id = "19d3d880-f410-4b85-a35d-9c5777705d1f"
timestamp = "2026-01-07T13:51:26.837603"
subtotal = 1354.26
tax = 33.08
total = 766.28
payment_method = "paypal"
[[items]]
sku = "SKU-30306"
qty = 4
price = 206.74


[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"?>
<transaction_record>
<txn_id>TXN-23430167</txn_id>
<customer_id>7fb2e914-3f0f-4c3f-abb9-ef22ed2c1064</customer_id>
<timestamp>2026-01-07T13:51:26.046328</timestamp>
<items>
<sku>SKU-63492</sku>
<qty>1</qty>
<price>90.17</price>
</items>
<items>
<sku>SKU-56350</sku>
<qty>5</qty>
<price>336.79</price>
</items>
<subtotal>152.9</subtotal>
<tax>14.6</tax>
<total>796.85</total>
<payment_method>apple_pay</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-23430167",
  "customer_id": "7fb2e914-3f0f-4c3f-abb9-ef22ed2c1064",
  "timestamp": "2026-01-07T13:51:26.046328",
  "items": [
    {
      "sku": "SKU-63492",
      "qty": 1,
      "price": 90.17
    },
    {
      "sku": "SKU-56350",
      "qty": 5,
      "price": 336.79
    }
  ],
  "subtotal": 152.9,
  "tax": 14.6,
  "total": 796.85,
  "payment_method": "apple_pay"
}


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

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

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

Output:
verified_purchase = false
rating = 2
date = "2026-01-02"
user_id = "ccea0611-b57c-4ee0-9ab6-48c5cb4c2b4c"
title = "Nature prepare style hit cell feeling start societ"


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

[User] Generate product listing data in CSV format.

[Assistant]
Approach:
1. Task: Create product listing 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,category,citations,funding_source,is_available,keywords,paper_id,publication_doi,publication_venue,publication_year,reviews,specs_dimensions,specs_weight_kg,stock,title
,,books,,,True,,,,,,730,46x21x76cm,7.36,824,
Seek nearly give such rate surface. Difficult some although gun remain share should.,"[{""name"": ""Andrew Phillips"", ""affiliation"": ""Marquez-Smith"", ""email"": ""acarter@example.com""}, {""name",,262,None,,"[""really"", ""remain"", ""represent""]",arXiv:2023.43790,10.9209/jvGr,Science,2021,,,,,Cross-group grid-enabled methodology
Art garden weight summer future could watch. Prove strategy according above throw. Ahead black house,"[{""name"": ""John Riley"", ""affiliation"": ""Scott and Sons"", ""email"": ""jamieweber@example.org""}, {""name""",,43,"Hopkins, Arnold and Williams",,"[""happy"", ""model"", ""like"", ""front""]",arXiv:2022.44682,10.9524/rtBk,Cell,2020,,,,,Front-line human-resource paradigm


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

[User]
Convert the following JSON to XML:
{
  "effective_date": "2026-01-03",
  "value": 837359,
  "term_months": 24,
  "status": "executed"
}

[Assistant]
Approach:
1. Task: Convert contract 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"?>
<contract>
<effective_date>2026-01-03</effective_date>
<value>837359</value>
<term_months>24</term_months>
<status>executed</status>
</contract>


[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"?>
<news_article>
<article_id>ART-1823437</article_id>
<headline>Integrated content-based throughput</headline>
<author>Anna Ortiz</author>
<published>2026-01-05T06:32:59.977242</published>

Politics

<content>Success off activity him process hot whose pay. Most probably including at arm avoid media finally.
Film traditional together still member. Culture let serve home.
Choose free minute in rich after image. Family meet health offer total leave media. Education enter against foreign.</content>
<tags>base</tags>
<tags>fight</tags>
<tags>test</tags>
<views>75522</views>
<shares>3070</shares>
</news_article>

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


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

[User] Output clinical note as JSON.

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

Output:
{
  "note_id": "CN-2341842",
  "patient": {
    "mrn": "MRN-739833",
    "age": 85,
    "gender": "F"
  },
  "encounter_date": "2026-01-01",
  "chief_complaint": "fever",
  "vitals": {
    "bp": "174/60",
    "hr": 60,
    "temp_f": 98.7
  },
  "assessment": [
    {
      "problem": "diabetes",
      "icd10": "I65"
    },
    {
      "problem": "diabetes",
      "icd10": "J29"
    }
  ]
}


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

[User] Create a YAML representation of news article.

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

Output:
article_id: ART-1823437
headline: Integrated content-based throughput
author: Anna Ortiz
published: '2026-01-05T06:32:59.977242'
section: Politics
content: 'Success off activity him process hot whose pay. Most probably including
  at arm avoid media finally.

  Film traditional together still member. Culture let serve home.

  Choose free minute in rich after image. Family meet health offer total leave media.
  Education enter against foreign.'
tags:
- base
- fight
- test
views: 75522
shares: 3070


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

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

[Assistant]
Approach:
1. Task: Create api specification in XML
2. Complexity: 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>Reactive exuding frame API</title>
<version>1.0.0</version>
</info>
<paths>
</second>
<get>
<summary>Life century work throughout however miss another.</summary>
<parameters>
<name>param0</name>
<in>query</in>
<type>string</type>
</parameters>
<responses>
<200>
<description>Success</description>
</200>
<400>
<description>Bad Request</description>
</400>
</responses>
</get>
<//second>
</paths>
</api_specification>


[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: 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:
paper_id: arXiv:2021.87801
title: Cross-group 24/7 methodology
authors:
- name: Scott Webb
  affiliation: Chapman LLC
  email: juanbooth@example.com
- name: Robert Mullins
  affiliation: Robbins, Adkins and Rogers
  email: michaeldunn@example.org
abstract: Reality maybe court material response cell. Middle instead husband win thousand
  collection.
keywords:
- girl
- face
- protect
publication:
  venue: Cell
  year: 2023
  doi: 10.4960/byWV
citations: 193
funding_source: Williams Ltd


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

[User] Output social media post as YAML.

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

Output:
post_id: POST-90196326
platform: facebook
user_id: 146c178d-e548-4357-8cd4-e8464cea2f9b
username: kevincunningham
content: 'Three would identify method across operation opportunity.

  What realize number. Country perform simple team player. Improve order east mother
  news magazine trade.

  Central thus simple thousand morning.'
timestamp: '2026-01-07T13:51:26.698310'
hashtags:
- '#pay'
- '#keep'
engagement:
  likes: 458
  shares: 383
  comments: 63


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

[User] Output lab result as CSV.

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

Output:
order_date,panel,patient_mrn,result_id,results
2026-01-01,Lipid,MRN-906692,LAB-2604144,"[{""test"": ""Hemoglobin"", ""value"": 180.3, ""unit"": ""mg/dL"", ""flag"": ""high""}, {""test"": ""Glucose"", ""value"
2026-01-01,CMP,MRN-936399,LAB-7233753,"[{""test"": ""Glucose"", ""value"": 89.5, ""unit"": ""g/dL"", ""flag"": ""normal""}, {""test"": ""Glucose"", ""value"": "
2026-01-06,CMP,MRN-672524,LAB-7849777,"[{""test"": ""Glucose"", ""value"": 141.7, ""unit"": ""g/dL"", ""flag"": ""normal""}, {""test"": ""WBC"", ""value"": 138"
2026-01-03,CBC,MRN-141755,LAB-9674105,"[{""test"": ""WBC"", ""value"": 54.9, ""unit"": ""g/dL"", ""flag"": ""normal""}, {""test"": ""Glucose"", ""value"": 120."


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

[User] Create a CSV representation of customer review.

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

Output:
category,content,currency,date,helpful_votes,is_available,name,price,product_id,rating,review_id,reviews,specs_dimensions,specs_weight_kg,stock,title,user_id,verified_purchase
,City not either situation all along might. Under could expect build member. Fish ready onto white ma,,2026-01-05,57,,,,PROD-894495,4,REV-1521978,,,,,Great how data open such.,0e93d4dc-0d39-4af2-8ec3-d8d1250011b9,False
clothing,,USD,,,True,Stand-alone 24hour hub,371.23,PROD-850043,2.78,,189,84x27x73cm,37.91,746,,,
electronics,,USD,,,True,Organic interactive attitude,784.86,PROD-898233,2.42,,893,82x73x47cm,14.1,460,,,
electronics,,USD,,,True,Future-proofed web-enabled productivity,996.83,PROD-131902,2.17,,89,73x74x91cm,20.0,287,,,
clothing,,USD,,,True,Right-sized high-level database,735.04,PROD-550858,1.07,,740,79x97x28cm,30.18,810,,,


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

[User] Output sales analytics as TOML.

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

Output:
period = "December 2023"
total_revenue = 5338205
units_sold = 90572
[[channels]]
name = "wholesale"
revenue = 2316482
growth = -1.07

[[channels]]
name = "online"
revenue = 3744469
growth = -0.81

[[top_products]]
sku = "SKU-4601"
sales = 454934

[[top_products]]
sku = "SKU-9892"
sales = 55264

[[top_products]]
sku = "SKU-8319"
sales = 254442


[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"?>
<contract>
<contract_id>CTR-896633</contract_id>
<parties>
<name>Smith-Cross</name>
<role>party_a</role>
</parties>
<parties>
<name>Carrillo and Sons</name>
<role>party_b</role>
</parties>
<effective_date>2026-01-03</effective_date>
<term_months>21</term_months>
<value>926875</value>
<status>pending</status>
</contract>

[Assistant]
Approach:
1. Task: Convert contract 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:
{
  "contract_id": "CTR-896633",
  "parties": [
    {
      "name": "Smith-Cross",
      "role": "party_a"
    },
    {
      "name": "Carrillo and Sons",
      "role": "party_b"
    }
  ],
  "effective_date": "2026-01-03",
  "term_months": 21,
  "value": 926875,
  "status": "pending"
}


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

[User]
Reformat the data below from XML to CSV:
<?xml version="1.0" encoding="UTF-8"?>
<lab_result>
<patient_mrn>MRN-119365</patient_mrn>
<order_date>2026-01-05</order_date>
<results>
<test>Glucose</test>
<value>134.6</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>69.4</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Glucose</test>
<value>85.6</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>WBC</test>
<value>69.6</value>
<unit>mg/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>79.1</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
</lab_result>

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

Output:
abstract,authors,citations,funding_source,keywords,order_date,paper_id,patient_mrn,publication_doi,publication_venue,publication_year,results,title
,,,,,2026-01-05,,MRN-119365,,,,"[{""test"": ""Glucose"", ""value"": 134.6, ""unit"": ""g/dL"", ""flag"": ""high""}, {""test"": ""Hemoglobin"", ""value""",
Must without hear trouble. Source keep leader face.,"[{""name"": ""Alexander Owen"", ""affiliation"": ""Edwards, Wu and Gray"", ""email"": ""kristen20@example.net""}",182,"Knapp, Garcia and Mason","[""admit"", ""pattern"", ""even"", ""two""]",,arXiv:2021.41704,,10.3254/BAYi,Nature,2024,,Object-based tangible success
Late stock news deep read it. Which anything hundred interview medical learn officer hear. Eat event,"[{""name"": ""Daniel Woods"", ""affiliation"": ""Woodward Inc"", ""email"": ""dayala@example.com""}, {""name"": ""M",401,Andrews-Jefferson,"[""PM"", ""life"", ""media"", ""page"", ""vote""]",,arXiv:2023.72311,,10.9582/QgPG,Science,2021,,Distributed demand-driven system engine


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

[User] Generate lab result data in YAML format.

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

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

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

[Assistant]
Approach:
1. Task: Convert experiment result 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:
{
  "experiment_id": "EXP-160417",
  "title": "Effect of agree on both",
  "methodology": {
    "design": "cohort",
    "sample_size": 663,
    "duration_days": 354
  },
  "results": [
    {
      "metric": "safety",
      "baseline": 13.92,
      "endpoint": 49.07,
      "p_value": 0.4102
    },
    {
      "metric": "safety",
      "baseline": 15.99,
      "endpoint": 65.81,
      "p_value": 0.3043
    },
    {
      "metric": "efficacy",
      "baseline": 46.51,
      "endpoint": 82.23,
      "p_value": 0.4775
    }
  ],
  "conclusion": "non-significant"
}


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

[User] Create a CSV representation of clinical note.

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

Output:
assessment,chief_complaint,encounter_date,note_id,patient_age,patient_gender,patient_mrn,vitals_bp,vitals_hr,vitals_temp_f
"[{""problem"": ""diabetes"", ""icd10"": ""J60""}, {""problem"": ""diabetes"", ""icd10"": ""K69""}, {""problem"": ""hype",fever,2026-01-06,CN-8348908,84,F,MRN-109351,157/81,101,97.1
"[{""problem"": ""hypertension"", ""icd10"": ""K33""}]",fever,2026-01-06,CN-6922777,55,M,MRN-891432,166/71,87,98.4
"[{""problem"": ""diabetes"", ""icd10"": ""I10""}]",headache,2026-01-01,CN-5739175,90,F,MRN-779126,115/69,105,99.9
"[{""problem"": ""hypertension"", ""icd10"": ""I83""}, {""problem"": ""diabetes"", ""icd10"": ""J47""}]",headache,2026-01-02,CN-3133028,74,F,MRN-838873,143/96,120,99.8
"[{""problem"": ""hypertension"", ""icd10"": ""I78""}, {""problem"": ""hypertension"", ""icd10"": ""J31""}]",fever,2026-01-06,CN-9471857,69,M,MRN-459579,106/89,98,99.3


[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:
{
  "info": {
    "title": "Object-based multimedia secured line API",
    "version": "1.0.0"
  },
  "openapi": "3.0.0",
  "paths": {
    "/party": {
      "get": {
        "summary": "Discussion partner stay wear again.",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          },
          {
            "name": "param1",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  }
}

[Assistant]
Approach:
1. Task: Convert api specification from JSON to XML
2. Complexity: 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"?>
<api_specification>
<info>
<title>Object-based multimedia secured line API</title>
<version>1.0.0</version>
</info>
<openapi>3.0.0</openapi>
<paths>
</party>
<get>
<summary>Discussion partner stay wear again.</summary>
<parameters>
<name>param0</name>
<in>query</in>
<type>string</type>
</parameters>
<parameters>
<name>param1</name>
<in>query</in>
<type>string</type>
</parameters>
<responses>
<200>
<description>Success</description>
</200>
<400>
<description>Bad Request</description>
</400>
</responses>
</get>
<//party>
</paths>
</api_specification>


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<clinical_note>
<note_id>CN-4493327</note_id>
<patient>
<mrn>MRN-934301</mrn>
<age>62</age>
<gender>F</gender>
</patient>
<encounter_date>2026-01-06</encounter_date>
<chief_complaint>fever</chief_complaint>
<vitals>
<bp>141/91</bp>

100

<temp_f>98.5</temp_f>
</vitals>
<assessment>
<problem>diabetes</problem>
<icd10>I32</icd10>
</assessment>
</clinical_note>


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

[User]
Convert the following YAML to CSV:
experiment_id: EXP-137327
title: Effect of class on read
methodology:
  design: RCT
  sample_size: 679
  duration_days: 111
results:
- metric: safety
  baseline: 73.26
  endpoint: 72.84
  p_value: 0.0533
- metric: efficacy
  baseline: 49.24
  endpoint: 28.3
  p_value: 0.0809
conclusion: significant

[Assistant]
Approach:
1. Task: Convert experiment result from YAML 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:
conclusion,experiment_id,methodology_design,methodology_duration_days,methodology_sample_size,results,title
significant,EXP-137327,RCT,111,679,"[{""metric"": ""safety"", ""baseline"": 73.26, ""endpoint"": 72.84, ""p_value"": 0.0533}, {""metric"": ""efficacy",Effect of class on read
non-significant,EXP-337989,RCT,200,453,"[{""metric"": ""efficacy"", ""baseline"": 83.47, ""endpoint"": 20.08, ""p_value"": 0.2404}, {""metric"": ""effica",Effect of whom on option
non-significant,EXP-610551,cohort,77,541,"[{""metric"": ""efficacy"", ""baseline"": 20.47, ""endpoint"": 63.09, ""p_value"": 0.4414}, {""metric"": ""effica",Effect of late on since
significant,EXP-574374,RCT,176,740,"[{""metric"": ""efficacy"", ""baseline"": 61.76, ""endpoint"": 50.18, ""p_value"": 0.122}, {""metric"": ""efficac",Effect of stuff on live


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<financial_report>
<company>Becker-Martinez</company>
<ticker>QZXR</ticker>
<quarter>Q4 2021</quarter>
<revenue>48919598</revenue>
<expenses>50274851</expenses>
<net_income>7284021</net_income>
<eps>2.39</eps>
<metrics>
<profit_margin>17.0</profit_margin>
<roe>10.6</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 experiment result.

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

Output:
experiment_id: EXP-818679
title: Effect of begin on task
methodology:
  design: RCT
  sample_size: 180
  duration_days: 157
results:
- metric: safety
  baseline: 17.77
  endpoint: 32.37
  p_value: 0.477
- metric: safety
  baseline: 20.98
  endpoint: 13.84
  p_value: 0.2984
conclusion: non-significant


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

[User] Output error log as YAML.

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

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


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

[User] Create a XML representation of course syllabus.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<course_syllabus>
<course_id>CRS-9141</course_id>
ESH384
<title>Inverse real-time hardware 101</title>
<instructor>Matthew Boyd</instructor>
<credits>4</credits>
<term>Fall 2022</term>
<schedule>
<week>1</week>
<topic>western</topic>
</schedule>
<schedule>
<week>2</week>
<topic>since</topic>
</schedule>
<schedule>
<week>3</week>
<topic>later</topic>
</schedule>
<schedule>
<week>4</week>
<topic>next</topic>
</schedule>
<schedule>
<week>5</week>
<topic>tree</topic>
</schedule>
<schedule>
<week>6</week>
<topic>until</topic>
</schedule>
<schedule>
<week>7</week>
<topic>everything</topic>
</schedule>
<schedule>
<week>8</week>
<topic>until</topic>
</schedule>
<schedule>
<week>9</week>
<topic>how</topic>
</schedule>
<schedule>
<week>10</week>
<topic>test</topic>
</schedule>
<schedule>
<week>11</week>
<topic>half</topic>
</schedule>
<grading>
<homework>30</homework>
<midterm>30</midterm>
<final>40</final>
</grading>
</course_syllabus>


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<lab_result>
<result_id>LAB-8547948</result_id>
<patient_mrn>MRN-375584</patient_mrn>
<order_date>2026-01-05</order_date>
<panel>Lipid</panel>
<results>
<test>WBC</test>
<value>136.4</value>
<unit>mg/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Glucose</test>
<value>110.1</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Glucose</test>
<value>77.6</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Glucose</test>
<value>164.2</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>53.3</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
</lab_result>

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

Output:
{
  "result_id": "LAB-8547948",
  "patient_mrn": "MRN-375584",
  "order_date": "2026-01-05",
  "panel": "Lipid",
  "results": [
    {
      "test": "WBC",
      "value": 136.4,
      "unit": "mg/dL",
      "flag": "low"
    },
    {
      "test": "Glucose",
      "value": 110.1,
      "unit": "mg/dL",
      "flag": "normal"
    },
    {
      "test": "Glucose",
      "value": 77.6,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "Glucose",
      "value": 164.2,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 53.3,
      "unit": "g/dL",
      "flag": "high"
    }
  ]
}


[System] You are an expert in 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:2024.40808"
title = "Versatile systematic infrastructure"
abstract = "Face direction whom party go follow. According meet pick hit environmental resource glass."
keywords = [ "service", "walk", "although", "several", "against",]
citations = 172
funding_source = "Bautista, Saunders and Delgado"
[[authors]]
name = "Andres Compton"
affiliation = "Knight, Wyatt and Mccarty"
email = "lawsontammy@example.org"

[[authors]]
name = "Michael Mcgrath"
affiliation = "Garcia, Davis and Caldwell"
email = "madison05@example.net"

[publication]
venue = "Cell"
year = 2021
doi = "10.1740/TuDe"


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

[User] Output customer review as JSON.

[Assistant]
Approach:
1. Task: Create customer review 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:
{
  "rating": 5,
  "review_id": "REV-2205395",
  "content": "Respond order far story by area affect. Important also catch down choice office necessary political. Firm along bar.\nStuff create including star question traditional reflect. Share fast thought."
}


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

[User]
Convert the following JSON to XML:
{
  "rx_id": "RX-9036427",
  "patient_mrn": "MRN-461250",
  "prescriber": "Zachary Berry",
  "date": "2026-01-01",
  "medications": [
    {
      "name": "Atorvastatin",
      "dosage": "5mg",
      "frequency": "daily",
      "quantity": 30
    }
  ]
}

[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-9036427</rx_id>
<patient_mrn>MRN-461250</patient_mrn>
<prescriber>Zachary Berry</prescriber>
<date>2026-01-01</date>
<medications>
<name>Atorvastatin</name>
<dosage>5mg</dosage>
<frequency>daily</frequency>
<quantity>30</quantity>
</medications>
</prescription>


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

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

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

Output:
total_score: 97
scores:
- question: 1
  points_earned: 0
  points_possible: 10
- question: 2
  points_earned: 4
  points_possible: 10
- question: 3
  points_earned: 10
  points_possible: 10
- question: 4
  points_earned: 5
  points_possible: 10
- question: 5
  points_earned: 4
  points_possible: 10
- question: 6
  points_earned: 2
  points_possible: 10
- question: 7
  points_earned: 1
  points_possible: 10
- question: 8
  points_earned: 5
  points_possible: 10
- question: 9
  points_earned: 3
  points_possible: 10
- question: 10
  points_earned: 9
  points_possible: 10
- question: 11
  points_earned: 5
  points_possible: 10
percentage: 78.32
course_id: CRS-4089


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

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


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

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

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

Output:
{
  "period": "December 2023",
  "total_revenue": 5338205,
  "units_sold": 90572,
  "channels": [
    {
      "name": "wholesale",
      "revenue": 2316482,
      "growth": -1.07
    },
    {
      "name": "online",
      "revenue": 3744469,
      "growth": -0.81
    }
  ],
  "top_products": [
    {
      "sku": "SKU-4601",
      "sales": 454934
    },
    {
      "sku": "SKU-9892",
      "sales": 55264
    },
    {
      "sku": "SKU-8319",
      "sales": 254442
    }
  ]
}


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

[User] Create a XML representation of error log.

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

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


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

[User]
Convert the following TOML to JSON:
total_score = 96
percentage = 61.11
student_id = "STU-785727"

[Assistant]
Approach:
1. Task: Convert student assessment from TOML 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:
{
  "total_score": 96,
  "percentage": 61.11,
  "student_id": "STU-785727"
}


[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:
content: 'Capital way what customer unit skill. Arm bar occur article mouth enjoy.
  Exactly approach mention single.

  Strong who against entire.

  Kid television artist dream back agency. Need main ago investment job behavior.'
published: '2026-01-03T04:54:27.964292'
views: 73181
headline: Vision-oriented analyzing groupware
section: Business

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<news_article>
<content>Capital way what customer unit skill. Arm bar occur article mouth enjoy. Exactly approach mention single.
Strong who against entire.
Kid television artist dream back agency. Need main ago investment job behavior.</content>
<published>2026-01-03T04:54:27.964292</published>
<views>73181</views>
<headline>Vision-oriented analyzing groupware</headline>

Business

</news_article>


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<course_syllabus>
<course_id>CRS-7514</course_id>
NOO384
<title>Fundamental encompassing database 101</title>
<instructor>Lori Martinez</instructor>
<credits>4</credits>
<term>Fall 2024</term>
<schedule>
<week>1</week>
<topic>bar</topic>
</schedule>
<schedule>
<week>2</week>
<topic>population</topic>
</schedule>
<schedule>
<week>3</week>
<topic>thus</topic>
</schedule>
<schedule>
<week>4</week>
<topic>manage</topic>
</schedule>
<schedule>
<week>5</week>
<topic>purpose</topic>
</schedule>
<schedule>
<week>6</week>
<topic>look</topic>
</schedule>
<schedule>
<week>7</week>
<topic>nothing</topic>
</schedule>
<schedule>
<week>8</week>
<topic>remember</topic>
</schedule>
<schedule>
<week>9</week>
<topic>song</topic>
</schedule>
<schedule>
<week>10</week>
<topic>ahead</topic>
</schedule>
<schedule>
<week>11</week>
<topic>pass</topic>
</schedule>
<grading>
<homework>30</homework>
<midterm>30</midterm>
<final>40</final>
</grading>
</course_syllabus>


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

[User]
Reformat the data below from JSON to XML:
{
  "contract_id": "CTR-544771",
  "parties": [
    {
      "name": "Prince-Finley",
      "role": "party_a"
    },
    {
      "name": "Stone LLC",
      "role": "party_b"
    }
  ],
  "effective_date": "2026-01-02",
  "term_months": 52,
  "value": 394049,
  "status": "active"
}

[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-544771</contract_id>
<parties>
<name>Prince-Finley</name>
<role>party_a</role>
</parties>
<parties>
<name>Stone LLC</name>
<role>party_b</role>
</parties>
<effective_date>2026-01-02</effective_date>
<term_months>52</term_months>
<value>394049</value>
<status>active</status>
</contract>


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

[User] Generate customer review data in CSV format.

[Assistant]
Approach:
1. Task: Create customer review in CSV
2. Complexity: 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,date,funding_source,helpful_votes,keywords,paper_id,publication_doi,publication_venue,publication_year,rating,title,user_id,verified_purchase
,,,2026-01-01,,29,,,,,,2,,ed843147-0604-46c9-98b2-def8aa0c8a20,True
Bank class likely best. Act describe cut support finally clearly.,"[{""name"": ""Stephen Cochran"", ""affiliation"": ""Joyce-Murphy"", ""email"": ""leezachary@example.net""}, {""na",273,,None,,"[""new"", ""break"", ""act""]",arXiv:2020.35826,10.4911/gceR,Science,2022,,Self-enabling zero-defect capability,,
Training participant represent major within figure. Small full pull new education after every.,"[{""name"": ""Matthew Caldwell"", ""affiliation"": ""Armstrong-Warren"", ""email"": ""lmorgan@example.net""}, {""",172,,None,,"[""yet"", ""degree"", ""administration"", ""make"", ""suffer""]",arXiv:2022.46159,10.6550/sdLM,Nature,2024,,Face-to-face asynchronous methodology,,


[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-110536",
  "name": "Organized didactic parallelism",
  "category": "clothing",
  "price": 68.12,
  "currency": "USD",
  "stock": 153,
  "is_available": true,
  "rating": 1.45,
  "reviews": 277,
  "specs": {
    "weight_kg": 1.85,
    "dimensions": "33x70x14cm"
  }
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<product_listing>
<product_id>PROD-110536</product_id>
<name>Organized didactic parallelism</name>
<category>clothing</category>
<price>68.12</price>
<currency>USD</currency>
<stock>153</stock>
<is_available>True</is_available>
<rating>1.45</rating>
<reviews>277</reviews>
<specs>
<weight_kg>1.85</weight_kg>
<dimensions>33x70x14cm</dimensions>
</specs>
</product_listing>


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

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

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

Output:
post_id: POST-64636774
platform: instagram
user_id: 180a1898-015f-483f-94a7-e771a6fb148e
username: melissa16
content: Use Mr only week. Crime form attention. Right world stand surface rate three.
timestamp: '2026-01-07T13:51:26.942814'
hashtags:
- '#economic'
- '#speak'
engagement:
  likes: 9998
  shares: 653
  comments: 4


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

[User] Output lab result as TOML.

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

Output:
result_id = "LAB-4911961"
patient_mrn = "MRN-250544"
order_date = "2026-01-03"
panel = "CBC"
[[results]]
test = "Hemoglobin"
value = 121.1
unit = "g/dL"
flag = "normal"

[[results]]
test = "Hemoglobin"
value = 77.4
unit = "mg/dL"
flag = "high"

[[results]]
test = "Glucose"
value = 107.3
unit = "g/dL"
flag = "high"

[[results]]
test = "Glucose"
value = 172.8
unit = "g/dL"
flag = "normal"

[[results]]
test = "Hemoglobin"
value = 166.2
unit = "mg/dL"
flag = "normal"

[[results]]
test = "Hemoglobin"
value = 140.6
unit = "g/dL"
flag = "normal"

[[results]]
test = "WBC"
value = 120.4
unit = "mg/dL"
flag = "normal"


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

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

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

Output:
paper_id = "arXiv:2023.99214"
title = "Integrated mobile database"
abstract = "Full with spend role first drive. Want man instead today bed hand character."
keywords = [ "bed", "very", "population",]
citations = 395
[[authors]]
name = "Clayton Martinez"
affiliation = "Flores, Levy and Farmer"
email = "kathy80@example.org"

[[authors]]
name = "Susan Bennett"
affiliation = "Collins, Daniel and Lyons"
email = "shawnjefferson@example.org"

[publication]
venue = "Nature"
year = 2023
doi = "10.4640/CkqB"


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

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

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

Output:
conclusion,experiment_id,methodology_design,methodology_duration_days,methodology_sample_size,results,title
non-significant,EXP-168652,cohort,186,797,"[{""metric"": ""safety"", ""baseline"": 24.16, ""endpoint"": 44.82, ""p_value"": 0.0559}, {""metric"": ""efficacy",Effect of green on from
significant,EXP-193330,RCT,348,373,"[{""metric"": ""safety"", ""baseline"": 97.78, ""endpoint"": 93.18, ""p_value"": 0.1711}, {""metric"": ""efficacy",Effect of want on blue
non-significant,EXP-196207,cohort,247,138,"[{""metric"": ""safety"", ""baseline"": 66.41, ""endpoint"": 58.9, ""p_value"": 0.4479}, {""metric"": ""efficacy""",Effect of movement on hour
significant,EXP-756418,observational,95,354,"[{""metric"": ""safety"", ""baseline"": 23.07, ""endpoint"": 70.47, ""p_value"": 0.0038}, {""metric"": ""safety"",",Effect of wife on base
significant,EXP-711496,RCT,172,102,"[{""metric"": ""efficacy"", ""baseline"": 60.35, ""endpoint"": 41.41, ""p_value"": 0.261}, {""metric"": ""safety""",Effect of quite on wind


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

[User] Output social media post as CSV.

[Assistant]
Approach:
1. Task: Create social media post 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:
content,engagement_comments,engagement_likes,engagement_shares,hashtags,platform,post_id,timestamp,user_id,username
,84,6676,196,"[""#pretty"", ""#admit"", ""#available""]",,POST-61351209,,5e546096-8461-4a3f-84e6-813e9e89a39c,nicholasalvarez
Industry with mention stuff identify inside drive. Yet college just spend human. Partner describe mi,45,9770,690,"[""#family"", ""#animal"", ""#answer""]",twitter,POST-12732976,2026-01-07T13:51:25.763150,26df7d4a-f4ec-4d57-b9a4-3c85fdd3bc37,philipleach
Argue rock practice check moment sense. Newspaper produce policy surface tend of together.,290,456,539,"[""#choice"", ""#hold"", ""#range"", ""#place""]",instagram,POST-32024645,2026-01-07T13:51:25.763559,f22f6923-475e-4a4c-afd9-6d277ca449d5,gwhite


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

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

[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:
{
  "reviews": 730,
  "category": "books",
  "stock": 824,
  "is_available": true,
  "specs": {
    "weight_kg": 7.36,
    "dimensions": "46x21x76cm"
  }
}


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<product_listing>
<specs>
<weight_kg>41.33</weight_kg>
<dimensions>19x24x69cm</dimensions>
</specs>
<price>743.81</price>
<is_available>True</is_available>
<rating>2.69</rating>
<stock>485</stock>
</product_listing>

[Assistant]
Approach:
1. Task: Convert product listing 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:
{
  "specs": {
    "weight_kg": 41.33,
    "dimensions": "19x24x69cm"
  },
  "price": 743.81,
  "is_available": true,
  "rating": 2.69,
  "stock": 485
}


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

[User] Output research paper as YAML.

[Assistant]
Approach:
1. Task: Create research paper 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:
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 CSV format. Think step-by-step, then generate syntactically perfect CSV.

[User] Generate student assessment data in CSV format.

[Assistant]
Approach:
1. Task: Create student assessment in CSV
2. Complexity: 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,date,funding_source,keywords,paper_id,publication_doi,publication_venue,publication_year,student_id,title,total_score
,,,2026-01-01,,,,,,,STU-920172,,85
Form knowledge energy also. Star order five say. Let smile those.,"[{""name"": ""Kathryn Green"", ""affiliation"": ""Valdez Group"", ""email"": ""robert41@example.com""}, {""name"":",347,,"Walsh, Dominguez and Calhoun","[""over"", ""second"", ""picture"", ""rise"", ""campaign""]",arXiv:2024.35496,10.8342/DbzY,Nature,2022,,Total user-facing interface,
Doctor painting yes condition several. They research for.,"[{""name"": ""Tanner Gomez"", ""affiliation"": ""Farmer, Nash and Ford"", ""email"": ""ortiztyrone@example.com""",158,,"Whitaker, Pearson and Franklin","[""church"", ""beyond"", ""action""]",arXiv:2022.93834,10.3346/bhDf,Cell,2021,,Devolved zero tolerance leverage,
Movie draw film nearly heart home. Sea because world lead identify three interest.,"[{""name"": ""Denise Jones"", ""affiliation"": ""Smith-Clark"", ""email"": ""michelle76@example.com""}, {""name"":",86,,None,"[""open"", ""when"", ""budget"", ""player"", ""raise""]",arXiv:2024.92240,10.8758/pGUx,Nature,2020,,Compatible composite matrix,
Should someone good minute test front point. Suffer watch generation investment agreement.,"[{""name"": ""David Wallace"", ""affiliation"": ""Hernandez-Nichols"", ""email"": ""whitneyaustin@example.org""}",325,,None,"[""future"", ""threat"", ""since""]",arXiv:2021.90473,10.3643/Jwku,Nature,2021,,Decentralized hybrid projection,


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

[User] Create a CSV representation of course syllabus.

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

Output:
code,course_id,credits,grading_final,grading_homework,grading_midterm,instructor,schedule,term,title
NEE477,CRS-4513,3,40,30,30,Jaime Roman,"[{""week"": 1, ""topic"": ""marriage""}, {""week"": 2, ""topic"": ""wonder""}, {""week"": 3, ""topic"": ""system""}, {",Spring 2022,Exclusive bottom-line artificial intelligence 101
SCU225,CRS-8607,3,40,30,30,Lori Ford,"[{""week"": 1, ""topic"": ""history""}, {""week"": 2, ""topic"": ""dream""}, {""week"": 3, ""topic"": ""ball""}, {""wee",Fall 2020,Expanded leadingedge product 101
HWY494,CRS-2327,4,40,30,30,Angela Lin,"[{""week"": 1, ""topic"": ""fall""}, {""week"": 2, ""topic"": ""red""}, {""week"": 3, ""topic"": ""its""}, {""week"": 4,",Spring 2024,Persistent secondary forecast 101
XGG195,CRS-8248,3,40,30,30,Joseph Ramsey,"[{""week"": 1, ""topic"": ""blue""}, {""week"": 2, ""topic"": ""know""}, {""week"": 3, ""topic"": ""hour""}, {""week"": ",Spring 2021,Seamless multimedia orchestration 101


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

[User] Create a TOML representation of sales analytics.

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

Output:
period = "September 2024"
total_revenue = 6726526
units_sold = 45392
[[channels]]
name = "retail"
revenue = 2051641
growth = 15.93

[[channels]]
name = "wholesale"
revenue = 4340607
growth = -6.59

[[top_products]]
sku = "SKU-7798"
sales = 367269

[[top_products]]
sku = "SKU-2105"
sales = 291023

[[top_products]]
sku = "SKU-5730"
sales = 275348


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

[User] Create a CSV representation of sales analytics.

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

Output:
abstract,authors,channels,citations,funding_source,keywords,paper_id,period,publication_doi,publication_venue,publication_year,title,top_products,total_revenue,units_sold
,,"[{""name"": ""retail"", ""revenue"": 1112533, ""growth"": 2.85}, {""name"": ""wholesale"", ""revenue"": 3150615, """,,,,,October 2022,,,,,"[{""sku"": ""SKU-7795"", ""sales"": 492045}, {""sku"": ""SKU-5231"", ""sales"": 195976}, {""sku"": ""SKU-5539"", ""sa",4790876,72609
Message military play director. Game finish set indicate upon computer happy. Meeting anything commo,"[{""name"": ""Rebecca Martinez"", ""affiliation"": ""Hinton-Sullivan"", ""email"": ""jason64@example.net""}, {""n",,241,"Lowe, Wheeler and Gilbert","[""must"", ""attorney"", ""tree"", ""away"", ""line""]",arXiv:2020.61573,,10.6487/Wsrp,Science,2024,Monitored mission-critical process improvement,,,
Fund choice moment as respond land television. Chair continue thank bank consumer group.,"[{""name"": ""Peter Smith"", ""affiliation"": ""Fitzgerald Inc"", ""email"": ""emilybuck@example.org""}, {""name""",,76,Wolfe-Durham,"[""enough"", ""call"", ""teacher""]",arXiv:2024.36099,,10.1108/ctTp,Nature,2021,De-engineered didactic secured line,,,
Project star step after understand air. Campaign project yeah mother.,"[{""name"": ""Janice Anderson"", ""affiliation"": ""Burke, Perry and Reynolds"", ""email"": ""sandra31@example.",,154,"Howard, Ellis and Castaneda","[""truth"", ""level"", ""heart""]",arXiv:2023.87671,,10.4646/neEK,Cell,2024,Reverse-engineered reciprocal time-frame,,,


[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:
{
  "article_id": "ART-8846154",
  "headline": "Phased bifurcated instruction set",
  "author": "Melanie Kennedy",
  "published": "2026-01-02T14:27:49.190328",
  "section": "Sports",
  "content": "Edge wear coach whether dog sell respond. Claim feeling meeting somebody four real.\nIndeed use send represent leader require. Cup attack instead discuss. Plan with character rule.\nInformation mind company even serve. Experience pattern but certain she design speech.",
  "tags": [
    "memory",
    "score",
    "game",
    "join"
  ],
  "views": 47684,
  "shares": 4081
}

[Assistant]
Approach:
1. Task: Convert news article 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"?>
<news_article>
<article_id>ART-8846154</article_id>
<headline>Phased bifurcated instruction set</headline>
<author>Melanie Kennedy</author>
<published>2026-01-02T14:27:49.190328</published>

Sports

<content>Edge wear coach whether dog sell respond. Claim feeling meeting somebody four real.
Indeed use send represent leader require. Cup attack instead discuss. Plan with character rule.
Information mind company even serve. Experience pattern but certain she design speech.</content>
<tags>memory</tags>
<tags>score</tags>
<tags>game</tags>
<tags>join</tags>
<views>47684</views>
<shares>4081</shares>
</news_article>


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

[User] Create a TOML representation of course syllabus.

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

Output:
course_id = "CRS-5704"
code = "BXM405"
title = "Profit-focused responsive throughput 101"
instructor = "Emily Bryan"
credits = 3
term = "Spring 2021"
[[schedule]]
week = 1
topic = "southern"

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

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

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

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

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

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

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

[[schedule]]
week = 9
topic = "throw"

[[schedule]]
week = 10
topic = "second"

[[schedule]]
week = 11
topic = "authority"

[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] Produce a JSON document for a lab result.

[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-2441646",
  "patient_mrn": "MRN-228148",
  "order_date": "2026-01-01",
  "panel": "Lipid",
  "results": [
    {
      "test": "Glucose",
      "value": 81.9,
      "unit": "g/dL",
      "flag": "high"
    },
    {
      "test": "WBC",
      "value": 107.7,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "Hemoglobin",
      "value": 101.6,
      "unit": "mg/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 197.9,
      "unit": "g/dL",
      "flag": "low"
    }
  ]
}


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<lab_result>
<result_id>LAB-5490961</result_id>
<patient_mrn>MRN-709917</patient_mrn>
<order_date>2026-01-03</order_date>
<panel>CBC</panel>
<results>
<test>Glucose</test>
<value>146.9</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>119.4</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>WBC</test>
<value>95.1</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>73.3</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Glucose</test>
<value>166.8</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>WBC</test>
<value>98.8</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
</lab_result>

[Assistant]
Approach:
1. Task: Convert lab result 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:
{
  "result_id": "LAB-5490961",
  "patient_mrn": "MRN-709917",
  "order_date": "2026-01-03",
  "panel": "CBC",
  "results": [
    {
      "test": "Glucose",
      "value": 146.9,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "Hemoglobin",
      "value": 119.4,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "WBC",
      "value": 95.1,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "Hemoglobin",
      "value": 73.3,
      "unit": "g/dL",
      "flag": "high"
    },
    {
      "test": "Glucose",
      "value": 166.8,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "WBC",
      "value": 98.8,
      "unit": "g/dL",
      "flag": "high"
    }
  ]
}


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

[User] Generate financial report data in JSON format.

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


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

[User] Generate clinical note data in TOML format.

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

Output:
note_id = "CN-4493327"
encounter_date = "2026-01-06"
chief_complaint = "fever"
[[assessment]]
problem = "diabetes"
icd10 = "I32"

[patient]
mrn = "MRN-934301"
age = 62
gender = "F"

[vitals]
bp = "141/91"
hr = 100
temp_f = 98.5


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

[User]
Convert the following JSON to XML:
{
  "period": "February 2020",
  "total_revenue": 5010605,
  "units_sold": 4486,
  "channels": [
    {
      "name": "online",
      "revenue": 4865933,
      "growth": 41.22
    },
    {
      "name": "wholesale",
      "revenue": 4636446,
      "growth": 21.68
    }
  ],
  "top_products": [
    {
      "sku": "SKU-3361",
      "sales": 360256
    },
    {
      "sku": "SKU-1576",
      "sales": 355717
    },
    {
      "sku": "SKU-8891",
      "sales": 396344
    }
  ]
}

[Assistant]
Approach:
1. Task: Convert sales analytics 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"?>
<sales_analytics>
<period>February 2020</period>
<total_revenue>5010605</total_revenue>
<units_sold>4486</units_sold>
<channels>
<name>online</name>
<revenue>4865933</revenue>
<growth>41.22</growth>
</channels>
<channels>
<name>wholesale</name>
<revenue>4636446</revenue>
<growth>21.68</growth>
</channels>
<top_products>
<sku>SKU-3361</sku>
<sales>360256</sales>
</top_products>
<top_products>
<sku>SKU-1576</sku>
<sales>355717</sales>
</top_products>
<top_products>
<sku>SKU-8891</sku>
<sales>396344</sales>
</top_products>
</sales_analytics>


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

[User] Generate transaction record data in TOML format.

[Assistant]
Approach:
1. Task: Create transaction record 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:
txn_id = "TXN-30876983"
customer_id = "b5aca191-66fe-49e0-85ce-2d363d5ef454"
timestamp = "2026-01-07T13:51:26.163076"
subtotal = 199.93
tax = 118.13
total = 913.78
payment_method = "apple_pay"
[[items]]
sku = "SKU-56664"
qty = 2
price = 285.83

[[items]]
sku = "SKU-25305"
qty = 1
price = 45.15

[[items]]
sku = "SKU-78820"
qty = 4
price = 47.49


[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-210763"
name = "Team-oriented grid-enabled support"
category = "clothing"
price = 360.14
currency = "USD"
stock = 657
is_available = true
rating = 3.34
reviews = 923

[specs]
weight_kg = 14.15
dimensions = "28x80x26cm"


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

[User] Generate news article data in TOML format.

[Assistant]
Approach:
1. Task: Create news article 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:
article_id = "ART-8668047"
headline = "Seamless local alliance"
author = "Alyssa Moore"
published = "2026-01-02T06:22:52.413807"
section = "Business"
content = "Billion up year window similar. Oil two resource next. If this tough pattern.\nRule year push international.\nReceive charge movie remember hear theory stuff explain. Century animal decide everyone direction rather. Month property rock environment fine such hand remain."
tags = [ "traditional", "wish", "little", "inside", "year",]
views = 55093
shares = 3713


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

[User] Output financial report as YAML.

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

Output:
company: Mcintyre, French and Sherman
ticker: GRIC
quarter: Q4 2021
revenue: 78125638
expenses: 13448897
net_income: 14876002
eps: 9.04
metrics:
  profit_margin: 9.81
  roe: 23.34


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

[User]
Transform this TOML data into YAML format:
result_id = "LAB-1812594"
patient_mrn = "MRN-755137"
order_date = "2026-01-06"
panel = "CMP"
[[results]]
test = "Glucose"
value = 131.9
unit = "mg/dL"
flag = "normal"

[[results]]
test = "Glucose"
value = 183.7
unit = "g/dL"
flag = "normal"

[[results]]
test = "WBC"
value = 130.1
unit = "mg/dL"
flag = "high"

[[results]]
test = "Hemoglobin"
value = 178.3
unit = "g/dL"
flag = "low"

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

Output:
result_id: LAB-1812594
patient_mrn: MRN-755137
order_date: '2026-01-06'
panel: CMP
results:
- test: Glucose
  value: 131.9
  unit: mg/dL
  flag: normal
- test: Glucose
  value: 183.7
  unit: g/dL
  flag: normal
- test: WBC
  value: 130.1
  unit: mg/dL
  flag: high
- test: Hemoglobin
  value: 178.3
  unit: g/dL
  flag: low


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

[User] Create a YAML representation of course syllabus.

[Assistant]
Approach:
1. Task: Create course syllabus 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:
course_id: CRS-7514
code: NOO384
title: Fundamental encompassing database 101
instructor: Lori Martinez
credits: 4
term: Fall 2024
schedule:
- week: 1
  topic: bar
- week: 2
  topic: population
- week: 3
  topic: thus
- week: 4
  topic: manage
- week: 5
  topic: purpose
- week: 6
  topic: look
- week: 7
  topic: nothing
- week: 8
  topic: remember
- week: 9
  topic: song
- week: 10
  topic: ahead
- week: 11
  topic: pass
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] Output social media post as CSV.

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

Output:
content,engagement_comments,engagement_likes,engagement_shares,hashtags,platform,post_id,timestamp,user_id,username
Subject watch side owner new. Quality million clear hand clearly environmental. Forget face machine ,152,5322,327,"[""#plan"", ""#area"", ""#foreign""]",facebook,POST-93814090,2026-01-07T13:51:26.454281,6a4446e9-5537-4ba1-bf03-5db2d36e07b9,tonyaguzman
"Should skill and raise never. Figure region that.
Impact necessary throughout wide. Make level custo",416,5986,378,"[""#trade"", ""#defense"", ""#process"", ""#PM""]",facebook,POST-98792445,2026-01-07T13:51:26.455878,c13956c2-5a2b-4dc6-bf5b-d03a07afb919,joshuabarton
Kitchen opportunity end such best camera. Whatever produce moment toward attack. High pattern indivi,115,8204,391,"[""#service"", ""#simply""]",instagram,POST-93506543,2026-01-07T13:51:26.456284,eca0fb16-e50c-4b56-93e4-64009a08f621,johnsonclaudia


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

[User]
Convert the following CSV to TOML:
company,eps,expenses,metrics_profit_margin,metrics_roe,net_income,quarter,revenue,ticker
Brooks LLC,3.56,61265128,26.89,20.49,10426094,Q1 2020,30917299,HFOB
"Hudson, Gonzalez and Miller",7.87,13398751,22.16,18.63,1487413,Q3 2023,35018610,CRCK
Stuart Ltd,5.56,30971314,21.6,17.05,16394087,Q2 2024,60394669,THVO
Colon-Collins,3.88,46847760,29.15,10.57,9946903,Q3 2020,53355151,HHLS

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

Output:
company = "Brooks LLC"
ticker = "HFOB"
quarter = "Q1 2020"
revenue = 30917299
expenses = 61265128
net_income = 10426094
eps = 3.56

[metrics]
profit_margin = 26.89
roe = 20.49


[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
Responsibility this statement area thing imagine free. Under quickly treatment ever end social milit,396,923,56,"[""#involve"", ""#fact"", ""#rest""]",instagram,POST-29576154,2026-01-07T13:51:27.160344,b3774d2a-dced-4164-bd7b-7d043d7ec920,boydkaren
"Wait civil PM letter. Method there citizen investment stuff center.
Thought east government maintain",347,5506,165,"[""#during"", ""#piece"", ""#visit""]",instagram,POST-67986368,2026-01-07T13:51:27.162092,4804510c-f070-4cd2-9f0d-2029729aa8ee,scottmurphy
Wonder budget during wish seek state quickly. Another group ability certainly model hand. Plan quali,257,5617,828,"[""#want"", ""#deal""]",instagram,POST-69963067,2026-01-07T13:51:27.162412,b5e89c6c-57e4-43bf-a7f4-958b580026e5,marcus55


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

[User] Create a XML representation of error log.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<error_log>
<error_id>03dcbba2-8070-483e-a807-51e4c6301bf5</error_id>
<timestamp>2026-01-07T13:51:27.875594</timestamp>
<level>WARNING</level>
<service>stockService</service>
<message>Feel garden dark.</message>
<stack_trace>at another.py:304</stack_trace>
<stack_trace>at happy.py:331</stack_trace>
<stack_trace>at record.py:415</stack_trace>
<context>
<user_id>cedcf075-a01b-42e9-acdc-a300ea843992</user_id>
<request_id>acbfd7fd-a4ab-431b-a098-ac4537826f14</request_id>
</context>
</error_log>


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

[User]
Transform this JSON data into XML format:
{
  "result_id": "LAB-8547948",
  "patient_mrn": "MRN-375584",
  "order_date": "2026-01-05",
  "panel": "Lipid",
  "results": [
    {
      "test": "WBC",
      "value": 136.4,
      "unit": "mg/dL",
      "flag": "low"
    },
    {
      "test": "Glucose",
      "value": 110.1,
      "unit": "mg/dL",
      "flag": "normal"
    },
    {
      "test": "Glucose",
      "value": 77.6,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "Glucose",
      "value": 164.2,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 53.3,
      "unit": "g/dL",
      "flag": "high"
    }
  ]
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<lab_result>
<result_id>LAB-8547948</result_id>
<patient_mrn>MRN-375584</patient_mrn>
<order_date>2026-01-05</order_date>
<panel>Lipid</panel>
<results>
<test>WBC</test>
<value>136.4</value>
<unit>mg/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Glucose</test>
<value>110.1</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Glucose</test>
<value>77.6</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Glucose</test>
<value>164.2</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>53.3</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
</lab_result>


[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: 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:
product_id = "PROD-428311"
name = "Object-based value-added workforce"
category = "books"
price = 802.3
currency = "USD"
stock = 719
is_available = true
rating = 1.5
reviews = 81

[specs]
weight_kg = 27.85
dimensions = "99x87x32cm"