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

[User]
Convert the following XML to YAML:
<?xml version="1.0" encoding="UTF-8"?>
<course_syllabus>
<course_id>CRS-4164</course_id>
RVR286
<title>Team-oriented incremental info-mediaries 101</title>
<instructor>Shannon Miller</instructor>
<credits>3</credits>
<term>Fall 2023</term>
<schedule>
<week>1</week>
<topic>stuff</topic>
</schedule>
<schedule>
<week>2</week>
<topic>professional</topic>
</schedule>
<schedule>
<week>3</week>
<topic>hard</topic>
</schedule>
<schedule>
<week>4</week>
<topic>rather</topic>
</schedule>
<schedule>
<week>5</week>
<topic>lawyer</topic>
</schedule>
<schedule>
<week>6</week>
<topic>camera</topic>
</schedule>
<schedule>
<week>7</week>
<topic>focus</topic>
</schedule>
<schedule>
<week>8</week>
<topic>spend</topic>
</schedule>
<schedule>
<week>9</week>
<topic>couple</topic>
</schedule>
<schedule>
<week>10</week>
<topic>quickly</topic>
</schedule>
<grading>
<homework>30</homework>
<midterm>30</midterm>
<final>40</final>
</grading>
</course_syllabus>

[Assistant]
Approach:
1. Task: Convert course syllabus from XML to 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:
course_id: CRS-4164
code: RVR286
title: Team-oriented incremental info-mediaries 101
instructor: Shannon Miller
credits: 3
term: Fall 2023
schedule:
- week: 1
  topic: stuff
- week: 2
  topic: professional
- week: 3
  topic: hard
- week: 4
  topic: rather
- week: 5
  topic: lawyer
- week: 6
  topic: camera
- week: 7
  topic: focus
- week: 8
  topic: spend
- week: 9
  topic: couple
- week: 10
  topic: quickly
grading:
  homework: 30
  midterm: 30
  final: 40


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<social_media_post>
<post_id>POST-39289028</post_id>
<platform>instagram</platform>
<user_id>a2301bd9-5c11-406a-b2a8-1c1f96bbd31c</user_id>
<username>rhodessharon</username>
<content>City window data describe address street. Environmental wall shoulder happy artist forget hospital. Chair their before reach picture serve.</content>
<timestamp>2026-01-07T13:51:26.862472</timestamp>
<hashtags>#yet</hashtags>
<hashtags>#listen</hashtags>
<engagement>
<likes>2391</likes>
<shares>751</shares>
<comments>108</comments>
</engagement>
</social_media_post>


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

[User] Generate transaction record data in CSV format.

[Assistant]
Approach:
1. Task: Create transaction record in CSV
2. Complexity: 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:
customer_id,items,payment_method,subtotal,tax,timestamp,total,txn_id
7fb2e914-3f0f-4c3f-abb9-ef22ed2c1064,"[{""sku"": ""SKU-63492"", ""qty"": 1, ""price"": 90.17}, {""sku"": ""SKU-56350"", ""qty"": 5, ""price"": 336.79}]",apple_pay,152.9,14.6,2026-01-07T13:51:26.046328,796.85,TXN-23430167
87c4cda4-0fd7-4820-a1fd-fae7e7885606,"[{""sku"": ""SKU-21380"", ""qty"": 4, ""price"": 384.37}, {""sku"": ""SKU-18480"", ""qty"": 4, ""price"": 363.77}, {",paypal,1896.87,56.98,2026-01-07T13:51:26.047314,1922.78,TXN-72278452
800cc3a6-f48f-4cf2-b7d0-cbace53d2031,"[{""sku"": ""SKU-86386"", ""qty"": 2, ""price"": 392.75}, {""sku"": ""SKU-52623"", ""qty"": 4, ""price"": 78.5}]",apple_pay,608.77,157.71,2026-01-07T13:51:26.047373,1272.69,TXN-84595534


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

[User]
Reformat the data below from JSON to CSV:
{
  "post_id": "POST-58559815",
  "platform": "instagram",
  "user_id": "0fae79ab-dabb-47f5-823b-f22743181c7c",
  "username": "ortizkristina",
  "content": "Speech can sea play. Season near story animal remain.\nOff present vote wall. Society know family build. Certain thing live rise.",
  "timestamp": "2026-01-07T13:51:26.463560",
  "hashtags": [
    "#once",
    "#it",
    "#rich",
    "#keep"
  ],
  "engagement": {
    "likes": 248,
    "shares": 32,
    "comments": 161
  }
}

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

Output:
content,engagement_comments,engagement_likes,engagement_shares,hashtags,platform,post_id,timestamp,user_id,username
"Speech can sea play. Season near story animal remain.
Off present vote wall. Society know family bui",161,248,32,"[""#once"", ""#it"", ""#rich"", ""#keep""]",instagram,POST-58559815,2026-01-07T13:51:26.463560,0fae79ab-dabb-47f5-823b-f22743181c7c,ortizkristina
"Among use blue fight meet those. Reality all throughout. One nice truth safe pressure several fly.
R",450,882,978,"[""#cost"", ""#job"", ""#talk""]",twitter,POST-72886555,2026-01-07T13:51:26.467512,97ba13e5-1ec0-415f-b3eb-2f5cd81d708a,zacharyjordan
Worry maintain person feel it democratic. Condition assume production culture color project become. ,14,9933,194,"[""#former"", ""#trouble"", ""#far"", ""#study""]",twitter,POST-79392862,2026-01-07T13:51:26.468030,6d11a1c8-b6ec-4a7b-8016-55807702679d,scottjocelyn
Step return month whole form total eat. To president them in after too. Professional voice space dif,206,9100,788,"[""#back"", ""#require""]",instagram,POST-10232040,2026-01-07T13:51:26.468566,219e9fa0-b436-41e2-bb64-5faf85a36a6c,toneal
See accept day. Peace these page group professor. Someone avoid always instead above Congress.,182,1364,598,"[""#movement"", ""#fire"", ""#end"", ""#machine""]",instagram,POST-82172316,2026-01-07T13:51:26.469008,6c2e7956-555d-4883-8b1f-01825c8ce563,david90


[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: Woods and Sons
ticker: ZCNM
quarter: Q1 2020
revenue: 42196406
expenses: 48284794
net_income: 2937548
eps: 8.84
metrics:
  profit_margin: 12.42
  roe: 23.86


[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: 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:
period: May 2020
total_revenue: 534039
units_sold: 34851
channels:
- name: retail
  revenue: 707158
  growth: 43.16
- name: wholesale
  revenue: 2548868
  growth: 26.24
top_products:
- sku: SKU-6020
  sales: 18280
- sku: SKU-3349
  sales: 458703
- sku: SKU-8781
  sales: 265385


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<transaction_record>
<txn_id>TXN-38439045</txn_id>
<customer_id>39de4165-2950-403a-b7cf-252ec7bafdcc</customer_id>
<timestamp>2026-01-07T13:51:25.757679</timestamp>
<items>
<sku>SKU-68017</sku>
<qty>5</qty>
<price>287.63</price>
</items>
<items>
<sku>SKU-13598</sku>
<qty>1</qty>
<price>397.9</price>
</items>
<items>
<sku>SKU-25253</sku>
<qty>4</qty>
<price>226.78</price>
</items>
<items>
<sku>SKU-92380</sku>
<qty>1</qty>
<price>318.47</price>
</items>
<subtotal>964.6</subtotal>
<tax>142.48</tax>
<total>1270.74</total>
<payment_method>credit_card</payment_method>
</transaction_record>

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

Output:
{
  "txn_id": "TXN-38439045",
  "customer_id": "39de4165-2950-403a-b7cf-252ec7bafdcc",
  "timestamp": "2026-01-07T13:51:25.757679",
  "items": [
    {
      "sku": "SKU-68017",
      "qty": 5,
      "price": 287.63
    },
    {
      "sku": "SKU-13598",
      "qty": 1,
      "price": 397.9
    },
    {
      "sku": "SKU-25253",
      "qty": 4,
      "price": 226.78
    },
    {
      "sku": "SKU-92380",
      "qty": 1,
      "price": 318.47
    }
  ],
  "subtotal": 964.6,
  "tax": 142.48,
  "total": 1270.74,
  "payment_method": "credit_card"
}


[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:
{
  "patient_mrn": "MRN-135092",
  "order_date": "2026-01-02",
  "panel": "CBC",
  "results": [
    {
      "test": "Hemoglobin",
      "value": 129.6,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "Hemoglobin",
      "value": 120.7,
      "unit": "mg/dL",
      "flag": "low"
    },
    {
      "test": "Hemoglobin",
      "value": 141.8,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "Hemoglobin",
      "value": 131.3,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "Glucose",
      "value": 147.1,
      "unit": "mg/dL",
      "flag": "high"
    }
  ],
  "result_id": "LAB-9224780"
}

[Assistant]
Approach:
1. Task: Convert lab result 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"?>
<lab_result>
<patient_mrn>MRN-135092</patient_mrn>
<order_date>2026-01-02</order_date>
<panel>CBC</panel>
<results>
<test>Hemoglobin</test>
<value>129.6</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>120.7</value>
<unit>mg/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>141.8</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>131.3</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Glucose</test>
<value>147.1</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<result_id>LAB-9224780</result_id>
</lab_result>


[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: 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:
authors:
- name: Laura White
  affiliation: Coleman, Johnson and Ross
  email: jillcollins@example.com
- name: Sarah Woods
  affiliation: Durham, Thompson and White
  email: sbeard@example.com
title: Seamless cohesive projection
funding_source: null
abstract: Middle several interesting move. Wrong represent guess threat. Once paper
  represent.


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

[User]
Convert the following TOML to JSON:
note_id = "CN-4466987"
encounter_date = "2026-01-02"
chief_complaint = "headache"
[[assessment]]
problem = "diabetes"
icd10 = "K25"

[patient]
mrn = "MRN-766590"
age = 87
gender = "F"

[vitals]
bp = "147/66"
hr = 72
temp_f = 101.1

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

Output:
{
  "note_id": "CN-4466987",
  "patient": {
    "mrn": "MRN-766590",
    "age": 87,
    "gender": "F"
  },
  "encounter_date": "2026-01-02",
  "chief_complaint": "headache",
  "vitals": {
    "bp": "147/66",
    "hr": 72,
    "temp_f": 101.1
  },
  "assessment": [
    {
      "problem": "diabetes",
      "icd10": "K25"
    }
  ]
}


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

Output:
txn_id = "TXN-20904368"
customer_id = "3fe35528-f72a-4e45-bcf8-f7cb059fe7e5"
timestamp = "2026-01-07T13:51:27.778783"
subtotal = 1853.52
tax = 74.51
total = 1419.49
payment_method = "apple_pay"
[[items]]
sku = "SKU-59380"
qty = 2
price = 447.63

[[items]]
sku = "SKU-56357"
qty = 4
price = 130.56

[[items]]
sku = "SKU-96740"
qty = 2
price = 230.78

[[items]]
sku = "SKU-55928"
qty = 1
price = 169.07


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

[User] Generate student assessment data in XML format.

[Assistant]
Approach:
1. Task: Create student assessment 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"?>
<student_assessment>
<assessment_id>ASMT-817642</assessment_id>
<student_id>STU-222420</student_id>
<course_id>CRS-8326</course_id>
<type>assignment</type>
<date>2026-01-03</date>
<scores>
<question>1</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>10</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>3</question>
<points_earned>0</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>7</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>4</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>10</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>7</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>60</total_score>
<percentage>56.31</percentage>
<grade>A</grade>
</student_assessment>


[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:2023.21424"
title = "Cross-platform fault-tolerant circuit"
abstract = "Truth himself long country car environment. Free design relate hope admit learn identify."
keywords = [ "share", "feeling", "environmental",]
citations = 477
funding_source = "Barker-Wise"
[[authors]]
name = "Charlotte Sellers"
affiliation = "Armstrong-Marks"
email = "weaverelizabeth@example.com"

[[authors]]
name = "Cynthia Johnston MD"
affiliation = "Rogers Inc"
email = "ccastaneda@example.org"

[[authors]]
name = "Robert Velasquez"
affiliation = "Alvarado LLC"
email = "psullivan@example.net"

[publication]
venue = "Science"
year = 2022
doi = "10.6091/Sfwn"


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<student_assessment>
<course_id>CRS-9368</course_id>
<percentage>68.59</percentage>
<assessment_id>ASMT-453812</assessment_id>
<scores>
<question>1</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>3</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>3</question>
<points_earned>0</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>4</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>6</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>4</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>8</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>9</question>
<points_earned>5</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>10</question>
<points_earned>0</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>11</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
</student_assessment>


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

[User] Generate clinical note data in JSON format.

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

Output:
{
  "note_id": "CN-4036732",
  "patient": {
    "mrn": "MRN-366942",
    "age": 79,
    "gender": "M"
  },
  "encounter_date": "2026-01-06",
  "chief_complaint": "headache",
  "vitals": {
    "bp": "102/96",
    "hr": 61,
    "temp_f": 97.1
  },
  "assessment": [
    {
      "problem": "hypertension",
      "icd10": "K52"
    }
  ]
}


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

[User] Create a JSON representation of error log.

[Assistant]
Approach:
1. Task: Create error log in JSON
2. Complexity: 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:
{
  "service": "findService",
  "stack_trace": [
    "at watch.py:197",
    "at body.py:298",
    "at girl.py:392",
    "at red.py:350"
  ],
  "level": "ERROR",
  "message": "Head then too threat drive."
}


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

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

[Assistant]
Approach:
1. Task: Convert course syllabus 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:
{
  "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 XML format. Think step-by-step, then generate syntactically perfect XML.

[User]
Convert the following JSON to XML:
{
  "assessment_id": "ASMT-946690",
  "student_id": "STU-268675",
  "course_id": "CRS-1216",
  "type": "assignment",
  "date": "2026-01-01",
  "scores": [
    {
      "question": 1,
      "points_earned": 10,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 5,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 5,
      "points_possible": 10
    },
    {
      "question": 9,
      "points_earned": 0,
      "points_possible": 10
    },
    {
      "question": 10,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 11,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 12,
      "points_earned": 2,
      "points_possible": 10
    }
  ],
  "total_score": 81,
  "percentage": 50.49,
  "grade": "B"
}

[Assistant]
Approach:
1. Task: Convert student assessment 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"?>
<student_assessment>
<assessment_id>ASMT-946690</assessment_id>
<student_id>STU-268675</student_id>
<course_id>CRS-1216</course_id>
<type>assignment</type>
<date>2026-01-01</date>
<scores>
<question>1</question>
<points_earned>10</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>3</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>8</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>5</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>8</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>5</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>9</question>
<points_earned>0</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>10</question>
<points_earned>4</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>11</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>12</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>81</total_score>
<percentage>50.49</percentage>
<grade>B</grade>
</student_assessment>


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

[User] Output experiment result as JSON.

[Assistant]
Approach:
1. Task: Create experiment result in JSON
2. Complexity: 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:
{
  "results": [
    {
      "metric": "efficacy",
      "baseline": 40.85,
      "endpoint": 40.08,
      "p_value": 0.4196
    },
    {
      "metric": "efficacy",
      "baseline": 82.87,
      "endpoint": 28.4,
      "p_value": 0.208
    },
    {
      "metric": "efficacy",
      "baseline": 74.0,
      "endpoint": 18.43,
      "p_value": 0.3638
    },
    {
      "metric": "efficacy",
      "baseline": 50.48,
      "endpoint": 15.59,
      "p_value": 0.1146
    }
  ],
  "methodology": {
    "design": "observational",
    "sample_size": 351,
    "duration_days": 339
  },
  "conclusion": "non-significant"
}


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

[User] Create a JSON representation of contract.

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

Output:
{
  "contract_id": "CTR-504304",
  "parties": [
    {
      "name": "Waters-Vega",
      "role": "party_a"
    },
    {
      "name": "Petty, Thompson and Dillon",
      "role": "party_b"
    }
  ],
  "effective_date": "2026-01-01",
  "term_months": 50,
  "value": 407863,
  "status": "executed"
}


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

[User]
Convert the following JSON to XML:
{
  "order_date": "2026-01-01",
  "panel": "Lipid",
  "patient_mrn": "MRN-952425",
  "result_id": "LAB-8958063",
  "results": [
    {
      "test": "Glucose",
      "value": 142.4,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 196.3,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 74.4,
      "unit": "mg/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 119.9,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "WBC",
      "value": 99.2,
      "unit": "mg/dL",
      "flag": "normal"
    },
    {
      "test": "Glucose",
      "value": 51.3,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "Glucose",
      "value": 186.5,
      "unit": "mg/dL",
      "flag": "low"
    }
  ]
}

[Assistant]
Approach:
1. Task: Convert lab result 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"?>
<lab_result>
<order_date>2026-01-01</order_date>
<panel>Lipid</panel>
<patient_mrn>MRN-952425</patient_mrn>
<result_id>LAB-8958063</result_id>
<results>
<test>Glucose</test>
<value>142.4</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>196.3</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>74.4</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>119.9</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>WBC</test>
<value>99.2</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Glucose</test>
<value>51.3</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Glucose</test>
<value>186.5</value>
<unit>mg/dL</unit>
<flag>low</flag>
</results>
</lab_result>


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

[User] Output api specification as XML.

[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>Secured well-modulated policy API</title>
<version>1.0.0</version>
</info>
<paths>
</article>
<get>
<summary>During certainly full.</summary>
<parameters>
<name>param0</name>
<in>query</in>
<type>string</type>
</parameters>
<parameters>
<name>param1</name>
<in>query</in>
<type>string</type>
</parameters>
<parameters>
<name>param2</name>
<in>query</in>
<type>string</type>
</parameters>
<responses>
<200>
<description>Success</description>
</200>
<400>
<description>Bad Request</description>
</400>
</responses>
</get>
<//article>
</paths>
</api_specification>


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

[User] Produce a JSON document for a prescription.

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

Output:
{
  "rx_id": "RX-9458448",
  "patient_mrn": "MRN-362998",
  "prescriber": "Courtney Hansen",
  "date": "2026-01-02",
  "medications": [
    {
      "name": "Lisinopril",
      "dosage": "10mg",
      "frequency": "BID",
      "quantity": 30
    }
  ]
}


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

[User] Create a YAML representation of transaction record.

[Assistant]
Approach:
1. Task: Create transaction record 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:
txn_id: TXN-38439045
customer_id: 39de4165-2950-403a-b7cf-252ec7bafdcc
timestamp: '2026-01-07T13:51:25.757679'
items:
- sku: SKU-68017
  qty: 5
  price: 287.63
- sku: SKU-13598
  qty: 1
  price: 397.9
- sku: SKU-25253
  qty: 4
  price: 226.78
- sku: SKU-92380
  qty: 1
  price: 318.47
subtotal: 964.6
tax: 142.48
total: 1270.74
payment_method: credit_card


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

[User] Output experiment result as TOML.

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

Output:
experiment_id = "EXP-393268"
title = "Effect of themselves on time"
conclusion = "significant"
[[results]]
metric = "efficacy"
baseline = 34.76
endpoint = 73.98
p_value = 0.4055

[[results]]
metric = "safety"
baseline = 70.26
endpoint = 84.17
p_value = 0.253

[[results]]
metric = "safety"
baseline = 22.1
endpoint = 56.91
p_value = 0.1172

[methodology]
design = "RCT"
sample_size = 237
duration_days = 116


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

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

[Assistant]
Approach:
1. Task: Create sales analytics 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,channels,citations,funding_source,keywords,paper_id,publication_doi,publication_venue,publication_year,title,top_products,total_revenue
,,"[{""name"": ""online"", ""revenue"": 2139770, ""growth"": -9.99}, {""name"": ""retail"", ""revenue"": 1809716, ""gr",,,,,,,,,"[{""sku"": ""SKU-3049"", ""sales"": 22854}, {""sku"": ""SKU-5505"", ""sales"": 203281}, {""sku"": ""SKU-9853"", ""sal",6798538
During street next across over recognize few analysis. Never level television subject this street ta,"[{""name"": ""Brendan Kidd"", ""affiliation"": ""Lucero-Watkins"", ""email"": ""mnielsen@example.net""}, {""name""",,500,None,"[""which"", ""involve"", ""man""]",arXiv:2024.56940,10.6475/mvhp,Science,2024,Ameliorated mission-critical contingency,,
Course ok work class. Without way effect model campaign than serious. Position price husband clear e,"[{""name"": ""Brian Henry"", ""affiliation"": ""Brown Group"", ""email"": ""barberjason@example.org""}, {""name"":",,196,Robertson Ltd,"[""increase"", ""president"", ""summer"", ""down""]",arXiv:2022.62603,10.3958/SLjb,Cell,2024,Self-enabling regional solution,,
School goal discuss food including. Pm view their foreign range mission news read. Event wear great ,"[{""name"": ""Maria Bell"", ""affiliation"": ""Stewart, Suarez and Cruz"", ""email"": ""billy19@example.net""}, ",,409,None,"[""land"", ""my"", ""international"", ""possible"", ""truth""]",arXiv:2024.83113,10.6971/qmzs,Cell,2021,Configurable asynchronous migration,,


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

[User]
Convert the following TOML to YAML:
product_id = "PROD-524008"
name = "Implemented multimedia focus group"
category = "electronics"
price = 524.9
currency = "USD"
stock = 714
is_available = true
rating = 2.56
reviews = 633

[specs]
weight_kg = 40.1
dimensions = "80x44x77cm"

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

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


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

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

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

Output:
{
  "post_id": "POST-69367106",
  "platform": "twitter",
  "user_id": "7643b70d-1c60-436f-974e-7bc6cee5e032",
  "username": "gordonalexander",
  "content": "See personal couple road president most next. Laugh teach lawyer character work present.\nPage give education middle. Couple save view media instead police guy. Enough test notice capital size.",
  "timestamp": "2026-01-07T13:51:25.991400",
  "hashtags": [
    "#PM",
    "#stage",
    "#government"
  ],
  "engagement": {
    "likes": 1911,
    "shares": 761,
    "comments": 62
  }
}


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

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

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

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


[System] You are an expert in 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: 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-2063</course_id>
FAH301
<title>Ameliorated zero administration productivity 101</title>
<instructor>Aaron Bailey</instructor>
<credits>4</credits>
<term>Fall 2023</term>
<schedule>
<week>1</week>
<topic>health</topic>
</schedule>
<schedule>
<week>2</week>
<topic>buy</topic>
</schedule>
<schedule>
<week>3</week>
<topic>conference</topic>
</schedule>
<schedule>
<week>4</week>
<topic>late</topic>
</schedule>
<schedule>
<week>5</week>
<topic>fear</topic>
</schedule>
<schedule>
<week>6</week>
<topic>ability</topic>
</schedule>
<schedule>
<week>7</week>
<topic>control</topic>
</schedule>
<schedule>
<week>8</week>
<topic>choose</topic>
</schedule>
<schedule>
<week>9</week>
<topic>measure</topic>
</schedule>
<schedule>
<week>10</week>
<topic>social</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]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<clinical_note>
<note_id>CN-4315709</note_id>
<patient>
<mrn>MRN-534874</mrn>
<age>89</age>
<gender>M</gender>
</patient>
<encounter_date>2026-01-02</encounter_date>
<chief_complaint>chest pain</chief_complaint>
<vitals>
<bp>165/61</bp>

112

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

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


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

[User] Create a TOML representation of student assessment.

[Assistant]
Approach:
1. Task: Create student assessment 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:
date = "2026-01-01"
total_score = 85
student_id = "STU-920172"


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

[User]
Convert the following JSON to XML:
{
  "assessment_id": "ASMT-817642",
  "student_id": "STU-222420",
  "course_id": "CRS-8326",
  "type": "assignment",
  "date": "2026-01-03",
  "scores": [
    {
      "question": 1,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 10,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 0,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 10,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 7,
      "points_possible": 10
    }
  ],
  "total_score": 60,
  "percentage": 56.31,
  "grade": "A"
}

[Assistant]
Approach:
1. Task: Convert student assessment 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"?>
<student_assessment>
<assessment_id>ASMT-817642</assessment_id>
<student_id>STU-222420</student_id>
<course_id>CRS-8326</course_id>
<type>assignment</type>
<date>2026-01-03</date>
<scores>
<question>1</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>10</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>3</question>
<points_earned>0</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>7</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>4</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>10</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>7</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>60</total_score>
<percentage>56.31</percentage>
<grade>A</grade>
</student_assessment>


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

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

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

Output:
{
  "review_id": "REV-1132090",
  "product_id": "PROD-380257",
  "user_id": "251dc214-da1e-4fb5-8ea5-d107ad43f82c",
  "rating": 4,
  "title": "Young race true property less government.",
  "content": "Brother agent radio might own development. Too strong minute building why. Cell so amount imagine simple.\nCourt every deal change allow last practice. Western far thus.",
  "date": "2026-01-03",
  "verified_purchase": false,
  "helpful_votes": 14
}


[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"?>
<customer_review>
<review_id>REV-7169946</review_id>
<product_id>PROD-908355</product_id>
<user_id>109a43ce-0a9d-47ca-b5cc-5940dcb3a5c0</user_id>
<rating>3</rating>
<title>Suffer kid daughter race still baby.</title>
<content>Young lot card leave book. Thank agency tree shake. Manage organization reduce from sort soldier.
Run rich marriage parent discover kitchen. Positive person baby list positive really range.</content>
<date>2026-01-05</date>
<verified_purchase>True</verified_purchase>
<helpful_votes>3</helpful_votes>
</customer_review>

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

Output:
{
  "review_id": "REV-7169946",
  "product_id": "PROD-908355",
  "user_id": "109a43ce-0a9d-47ca-b5cc-5940dcb3a5c0",
  "rating": 3,
  "title": "Suffer kid daughter race still baby.",
  "content": "Young lot card leave book. Thank agency tree shake. Manage organization reduce from sort soldier.\nRun rich marriage parent discover kitchen. Positive person baby list positive really range.",
  "date": "2026-01-05",
  "verified_purchase": true,
  "helpful_votes": 3
}


[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:
{
  "txn_id": "TXN-79156891",
  "customer_id": "5450ecc9-30b8-498f-a527-04ec3de16dd8",
  "timestamp": "2026-01-07T13:51:26.258900",
  "items": [
    {
      "sku": "SKU-81880",
      "qty": 4,
      "price": 401.7
    },
    {
      "sku": "SKU-99718",
      "qty": 5,
      "price": 334.37
    },
    {
      "sku": "SKU-65882",
      "qty": 3,
      "price": 292.8
    },
    {
      "sku": "SKU-88201",
      "qty": 2,
      "price": 114.91
    }
  ],
  "subtotal": 258.62,
  "tax": 22.79,
  "total": 1713.37,
  "payment_method": "paypal"
}

[Assistant]
Approach:
1. Task: Convert transaction record 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"?>
<transaction_record>
<txn_id>TXN-79156891</txn_id>
<customer_id>5450ecc9-30b8-498f-a527-04ec3de16dd8</customer_id>
<timestamp>2026-01-07T13:51:26.258900</timestamp>
<items>
<sku>SKU-81880</sku>
<qty>4</qty>
<price>401.7</price>
</items>
<items>
<sku>SKU-99718</sku>
<qty>5</qty>
<price>334.37</price>
</items>
<items>
<sku>SKU-65882</sku>
<qty>3</qty>
<price>292.8</price>
</items>
<items>
<sku>SKU-88201</sku>
<qty>2</qty>
<price>114.91</price>
</items>
<subtotal>258.62</subtotal>
<tax>22.79</tax>
<total>1713.37</total>
<payment_method>paypal</payment_method>
</transaction_record>


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

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

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

Output:
result_id = "LAB-1120026"
patient_mrn = "MRN-824701"
order_date = "2026-01-06"
panel = "CBC"
[[results]]
test = "Glucose"
value = 168.8
unit = "g/dL"
flag = "high"

[[results]]
test = "Glucose"
value = 98.1
unit = "mg/dL"
flag = "high"

[[results]]
test = "Glucose"
value = 137.9
unit = "mg/dL"
flag = "normal"

[[results]]
test = "Glucose"
value = 107.7
unit = "g/dL"
flag = "low"


[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"?>
<financial_report>
<company>Rodriguez, Curry and Yates</company>
<ticker>KWAZ</ticker>
<quarter>Q1 2020</quarter>
<revenue>4863925</revenue>
<expenses>55129980</expenses>
<net_income>12179320</net_income>
<eps>7.94</eps>
<metrics>
<profit_margin>29.26</profit_margin>
<roe>9.63</roe>
</metrics>
</financial_report>

[Assistant]
Approach:
1. Task: Convert financial report from XML 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:
company,eps,expenses,metrics_profit_margin,metrics_roe,net_income,quarter,revenue,ticker
"Rodriguez, Curry and Yates",7.94,55129980,29.26,9.63,12179320,Q1 2020,4863925,KWAZ
Jones-Vincent,4.65,31539722,13.67,22.7,14909526,Q2 2021,54014313,YZAO
Jimenez-Bean,1.76,54891353,26.24,6.62,12331228,Q3 2020,4701481,PBCO


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

[User] Generate course syllabus data in YAML format.

[Assistant]
Approach:
1. Task: Create course syllabus 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:
schedule:
- week: 1
  topic: table
- week: 2
  topic: team
- week: 3
  topic: miss
- week: 4
  topic: face
- week: 5
  topic: sort
- week: 6
  topic: board
- week: 7
  topic: effect
- week: 8
  topic: still
- week: 9
  topic: training
- week: 10
  topic: different
code: GHC481
grading:
  homework: 30
  midterm: 30
  final: 40
term: Spring 2020
credits: 4


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<course_syllabus>
<course_id>CRS-6873</course_id>
GDK183
<title>Grass-roots 24/7 emulation 101</title>
<instructor>Melinda Thompson</instructor>
<credits>3</credits>
<term>Fall 2020</term>
<schedule>
<week>1</week>
<topic>girl</topic>
</schedule>
<schedule>
<week>2</week>
<topic>explain</topic>
</schedule>
<schedule>
<week>3</week>
<topic>center</topic>
</schedule>
<schedule>
<week>4</week>
<topic>almost</topic>
</schedule>
<schedule>
<week>5</week>
<topic>property</topic>
</schedule>
<schedule>
<week>6</week>
<topic>call</topic>
</schedule>
<schedule>
<week>7</week>
<topic>bad</topic>
</schedule>
<schedule>
<week>8</week>
<topic>study</topic>
</schedule>
<schedule>
<week>9</week>
<topic>campaign</topic>
</schedule>
<schedule>
<week>10</week>
<topic>performance</topic>
</schedule>
<schedule>
<week>11</week>
<topic>sport</topic>
</schedule>
<grading>
<homework>30</homework>
<midterm>30</midterm>
<final>40</final>
</grading>
</course_syllabus>

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

Output:
{
  "course_id": "CRS-6873",
  "code": "GDK183",
  "title": "Grass-roots 24/7 emulation 101",
  "instructor": "Melinda Thompson",
  "credits": 3,
  "term": "Fall 2020",
  "schedule": [
    {
      "week": 1,
      "topic": "girl"
    },
    {
      "week": 2,
      "topic": "explain"
    },
    {
      "week": 3,
      "topic": "center"
    },
    {
      "week": 4,
      "topic": "almost"
    },
    {
      "week": 5,
      "topic": "property"
    },
    {
      "week": 6,
      "topic": "call"
    },
    {
      "week": 7,
      "topic": "bad"
    },
    {
      "week": 8,
      "topic": "study"
    },
    {
      "week": 9,
      "topic": "campaign"
    },
    {
      "week": 10,
      "topic": "performance"
    },
    {
      "week": 11,
      "topic": "sport"
    }
  ],
  "grading": {
    "homework": 30,
    "midterm": 30,
    "final": 40
  }
}


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

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

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

Output:
abstract,authors,channels,citations,funding_source,keywords,paper_id,period,publication_doi,publication_venue,publication_year,title,top_products,total_revenue,units_sold
,,"[{""name"": ""online"", ""revenue"": 4865933, ""growth"": 41.22}, {""name"": ""wholesale"", ""revenue"": 4636446, ",,,,,February 2020,,,,,"[{""sku"": ""SKU-3361"", ""sales"": 360256}, {""sku"": ""SKU-1576"", ""sales"": 355717}, {""sku"": ""SKU-8891"", ""sa",5010605,4486
Congress understand concern table. Record ten suggest toward tough prevent. Because cup point piece.,"[{""name"": ""Denise Cox"", ""affiliation"": ""Swanson Ltd"", ""email"": ""kaitlyn05@example.net""}, {""name"": ""A",,472,None,"[""adult"", ""another"", ""dream"", ""night""]",arXiv:2022.46319,,10.5337/ymxz,Cell,2021,Reverse-engineered local data-warehouse,,,
"Western require save Mrs full. Ahead arrive need. Case up discover card wall.
Hotel market research ","[{""name"": ""Scott Byrd"", ""affiliation"": ""Franco, Smith and Santos"", ""email"": ""hernandezerica@example.",,156,None,"[""more"", ""day"", ""cup"", ""beat""]",arXiv:2023.99149,,10.4522/qWHe,Cell,2023,Multi-lateral mission-critical hardware,,,


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

[User]
Transform this YAML data into JSON format:
result_id: LAB-9017474
patient_mrn: MRN-783803
order_date: '2026-01-04'
panel: Lipid
results:
- test: Glucose
  value: 65.6
  unit: mg/dL
  flag: high
- test: Glucose
  value: 160.2
  unit: mg/dL
  flag: normal
- test: WBC
  value: 142.4
  unit: g/dL
  flag: normal
- test: Glucose
  value: 179.9
  unit: mg/dL
  flag: normal
- test: Hemoglobin
  value: 97.3
  unit: g/dL
  flag: normal
- test: Hemoglobin
  value: 148.5
  unit: g/dL
  flag: high
- test: Hemoglobin
  value: 174.6
  unit: g/dL
  flag: normal

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

Output:
{
  "result_id": "LAB-9017474",
  "patient_mrn": "MRN-783803",
  "order_date": "2026-01-04",
  "panel": "Lipid",
  "results": [
    {
      "test": "Glucose",
      "value": 65.6,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "Glucose",
      "value": 160.2,
      "unit": "mg/dL",
      "flag": "normal"
    },
    {
      "test": "WBC",
      "value": 142.4,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "Glucose",
      "value": 179.9,
      "unit": "mg/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 97.3,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 148.5,
      "unit": "g/dL",
      "flag": "high"
    },
    {
      "test": "Hemoglobin",
      "value": 174.6,
      "unit": "g/dL",
      "flag": "normal"
    }
  ]
}


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

[User] Output sales analytics as JSON.

[Assistant]
Approach:
1. Task: Create sales analytics in JSON
2. Complexity: 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": "January 2022",
  "total_revenue": 7456708,
  "units_sold": 82349,
  "channels": [
    {
      "name": "wholesale",
      "revenue": 3622404,
      "growth": -8.05
    },
    {
      "name": "online",
      "revenue": 1893923,
      "growth": 2.21
    }
  ],
  "top_products": [
    {
      "sku": "SKU-2073",
      "sales": 98550
    },
    {
      "sku": "SKU-3707",
      "sales": 233488
    },
    {
      "sku": "SKU-7843",
      "sales": 172526
    }
  ]
}


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

[User] Generate product listing data in XML format.

[Assistant]
Approach:
1. Task: Create product listing in XML
2. Complexity: 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"?>
<product_listing>
<product_id>PROD-480886</product_id>
<name>Operative optimizing monitoring</name>
<category>books</category>
<price>967.35</price>
<currency>USD</currency>
<stock>887</stock>
<is_available>True</is_available>
<rating>2.99</rating>
<reviews>465</reviews>
<specs>
<weight_kg>39.19</weight_kg>
<dimensions>82x84x37cm</dimensions>
</specs>
</product_listing>


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

[User]
Transform this XML data into TOML format:
<?xml version="1.0" encoding="UTF-8"?>
<product_listing>
<product_id>PROD-738287</product_id>
<name>Function-based dedicated installation</name>
<category>electronics</category>
<price>364.53</price>
<currency>USD</currency>
<stock>956</stock>
<is_available>True</is_available>
<rating>1.64</rating>
<reviews>854</reviews>
<specs>
<weight_kg>19.72</weight_kg>
<dimensions>48x33x88cm</dimensions>
</specs>
</product_listing>

[Assistant]
Approach:
1. Task: Convert product listing from XML to 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:
product_id = "PROD-738287"
name = "Function-based dedicated installation"
category = "electronics"
price = 364.53
currency = "USD"
stock = 956
is_available = true
rating = 1.64
reviews = 854

[specs]
weight_kg = 19.72
dimensions = "48x33x88cm"


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

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

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

Output:
category,content,currency,date,helpful_votes,is_available,name,price,product_id,rating,review_id,reviews,specs_dimensions,specs_weight_kg,stock,title,user_id,verified_purchase
,"Young lot card leave book. Thank agency tree shake. Manage organization reduce from sort soldier.
Ru",,2026-01-05,3,,,,PROD-908355,3,REV-7169946,,,,,Suffer kid daughter race still baby.,109a43ce-0a9d-47ca-b5cc-5940dcb3a5c0,True
books,,USD,,,True,Visionary grid-enabled conglomeration,51.48,PROD-867602,1.81,,805,92x21x35cm,36.35,357,,,
clothing,,USD,,,True,Phased 24hour concept,47.66,PROD-942624,3.22,,761,24x51x47cm,13.73,327,,,
books,,USD,,,True,Synergized asymmetric service-desk,657.59,PROD-282002,1.77,,708,94x86x69cm,7.54,795,,,
clothing,,USD,,,True,Re-contextualized full-range algorithm,168.58,PROD-778066,4.84,,5,97x93x64cm,10.22,758,,,


[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:
{
  "course_id": "CRS-9368",
  "percentage": 68.59,
  "assessment_id": "ASMT-453812",
  "scores": [
    {
      "question": 1,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 3,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 0,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 6,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 9,
      "points_earned": 5,
      "points_possible": 10
    },
    {
      "question": 10,
      "points_earned": 0,
      "points_possible": 10
    },
    {
      "question": 11,
      "points_earned": 2,
      "points_possible": 10
    }
  ]
}

[Assistant]
Approach:
1. Task: Convert student assessment 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"?>
<student_assessment>
<course_id>CRS-9368</course_id>
<percentage>68.59</percentage>
<assessment_id>ASMT-453812</assessment_id>
<scores>
<question>1</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>3</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>3</question>
<points_earned>0</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>4</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>6</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>4</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>8</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>9</question>
<points_earned>5</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>10</question>
<points_earned>0</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>11</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
</student_assessment>


[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:
{
  "course_id": "CRS-3741",
  "code": "XMJ312",
  "title": "Managed incremental focus group 101",
  "instructor": "Rachel Diaz",
  "credits": 4,
  "term": "Fall 2021",
  "schedule": [
    {
      "week": 1,
      "topic": "body"
    },
    {
      "week": 2,
      "topic": "rather"
    },
    {
      "week": 3,
      "topic": "song"
    },
    {
      "week": 4,
      "topic": "child"
    },
    {
      "week": 5,
      "topic": "born"
    },
    {
      "week": 6,
      "topic": "beyond"
    },
    {
      "week": 7,
      "topic": "there"
    }
  ],
  "grading": {
    "homework": 30,
    "midterm": 30,
    "final": 40
  }
}

[Assistant]
Approach:
1. Task: Convert course syllabus 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"?>
<course_syllabus>
<course_id>CRS-3741</course_id>
XMJ312
<title>Managed incremental focus group 101</title>
<instructor>Rachel Diaz</instructor>
<credits>4</credits>
<term>Fall 2021</term>
<schedule>
<week>1</week>
<topic>body</topic>
</schedule>
<schedule>
<week>2</week>
<topic>rather</topic>
</schedule>
<schedule>
<week>3</week>
<topic>song</topic>
</schedule>
<schedule>
<week>4</week>
<topic>child</topic>
</schedule>
<schedule>
<week>5</week>
<topic>born</topic>
</schedule>
<schedule>
<week>6</week>
<topic>beyond</topic>
</schedule>
<schedule>
<week>7</week>
<topic>there</topic>
</schedule>
<grading>
<homework>30</homework>
<midterm>30</midterm>
<final>40</final>
</grading>
</course_syllabus>


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

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

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

Output:
course_id = "CRS-4513"
code = "NEE477"
title = "Exclusive bottom-line artificial intelligence 101"
instructor = "Jaime Roman"
credits = 3
term = "Spring 2022"
[[schedule]]
week = 1
topic = "marriage"

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

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

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

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

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

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

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

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

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

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


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<sales_analytics>
<period>September 2023</period>
<total_revenue>9732569</total_revenue>
<units_sold>38507</units_sold>
<channels>
<name>retail</name>
<revenue>4979277</revenue>
<growth>36.06</growth>
</channels>
<channels>
<name>wholesale</name>
<revenue>4800863</revenue>
<growth>8.87</growth>
</channels>
<top_products>
<sku>SKU-5649</sku>
<sales>311811</sales>
</top_products>
<top_products>
<sku>SKU-1879</sku>
<sales>391924</sales>
</top_products>
<top_products>
<sku>SKU-4665</sku>
<sales>317392</sales>
</top_products>
</sales_analytics>

[Assistant]
Approach:
1. Task: Convert sales analytics 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:
{
  "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 CSV format. Think step-by-step, then generate syntactically perfect CSV.

[User] Create a CSV representation of product listing.

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

Output:
category,currency,is_available,name,price,product_id,rating,reviews,specs_dimensions,specs_weight_kg,stock
books,USD,True,Managed bandwidth-monitored focus group,751.35,PROD-141484,2.94,250,15x82x35cm,6.41,108
clothing,USD,True,Automated multi-tasking ability,526.0,PROD-262963,3.66,820,73x64x100cm,37.92,219
books,USD,True,Versatile global functionalities,80.34,PROD-534873,4.21,937,31x65x30cm,1.33,532
clothing,USD,True,Diverse encompassing instruction set,53.31,PROD-645686,4.87,141,84x15x38cm,34.37,994


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

[User]
Convert the following JSON to XML:
{
  "openapi": "3.0.0",
  "info": {
    "title": "Upgradable 4thgeneration middleware API",
    "version": "1.0.0"
  },
  "paths": {
    "/pass": {
      "get": {
        "summary": "Story amount nor bed night get message.",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  }
}

[Assistant]
Approach:
1. Task: Convert api specification from JSON to XML
2. Complexity: 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"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Upgradable 4thgeneration middleware API</title>
<version>1.0.0</version>
</info>
<paths>
</pass>
<get>
<summary>Story amount nor bed night get message.</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>
<//pass>
</paths>
</api_specification>


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

[User] Create a CSV representation of financial report.

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

Output:
abstract,authors,citations,funding_source,keywords,metrics_profit_margin,metrics_roe,paper_id,publication_doi,publication_venue,publication_year,quarter,revenue,title
,,,,,25.46,20.6,,,,,Q1 2021,81140617,
"Responsibility try hold issue value.
Bag clearly seven star. At tough soon.","[{""name"": ""Johnny Zimmerman"", ""affiliation"": ""Gregory-Wong"", ""email"": ""annettemcclure@example.org""},",342,None,"[""sister"", ""worry"", ""glass"", ""lay"", ""total""]",,,arXiv:2020.87735,10.9314/BMva,Cell,2022,,,Cross-group 24hour hierarchy
Recently food always pull open consider. Those several main exist hope friend.,"[{""name"": ""Matthew Hill"", ""affiliation"": ""Jenkins, Boyd and Arnold"", ""email"": ""georgejacqueline@exam",20,None,"[""artist"", ""decade"", ""these"", ""former"", ""science""]",,,arXiv:2023.41102,10.1708/sXPD,Science,2024,,,Expanded object-oriented superstructure


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

[User] Produce a JSON document for a prescription.

[Assistant]
Approach:
1. Task: Create prescription 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:
{
  "rx_id": "RX-8350891",
  "patient_mrn": "MRN-446802",
  "prescriber": "James Bryant",
  "date": "2026-01-03",
  "medications": [
    {
      "name": "Lisinopril",
      "dosage": "10mg",
      "frequency": "daily",
      "quantity": 90
    },
    {
      "name": "Metformin",
      "dosage": "20mg",
      "frequency": "TID",
      "quantity": 30
    }
  ]
}


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

[User] Output news article as CSV.

[Assistant]
Approach:
1. Task: Create news article 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:
article_id,author,content,headline,published,section,shares,tags,views
ART-2388619,Paula Martinez,Choice list strong let reason. Education class ok front impact successful. Huge professor happen dat,Switchable tertiary collaboration,2026-01-07T02:15:35.006278,Politics,1794,"[""hair"", ""democratic"", ""financial"", ""huge"", ""available""]",74003
ART-8369767,Mark Marshall,Describe food tree perhaps particular. Garden TV decade daughter over. Fight color culture political,User-centric encompassing capacity,2026-01-03T10:01:34.253370,Business,107,"[""size"", ""when"", ""important""]",53618
ART-4531966,Mark Rice,"Budget prevent red suggest. Project take bill service weight ahead.
Network region everyone view. Of",Pre-emptive solution-oriented focus group,2026-01-05T02:15:33.275235,Business,4518,"[""them"", ""play"", ""success"", ""product""]",84715
ART-1261179,James Roach,Summer matter especially also. Measure office such allow everything behavior include. Stand beat rad,Enhanced multimedia ability,2026-01-07T12:07:54.350837,Tech,4893,"[""mention"", ""son"", ""politics""]",2417


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

[User]
Convert the following YAML to XML:
post_id: POST-18209344
platform: facebook
user_id: 8880ae5d-22ce-466e-ac5d-224201417b5e
username: xmcbride
content: 'Determine live compare center as direction. Eye experience low wear. If
  south level.

  Worry expect style camera. Scene majority pay voice television professor.'
timestamp: '2026-01-07T13:51:27.602464'
hashtags:
- '#culture'
- '#whole'
- '#central'
engagement:
  likes: 2214
  shares: 878
  comments: 146

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<social_media_post>
<post_id>POST-18209344</post_id>
<platform>facebook</platform>
<user_id>8880ae5d-22ce-466e-ac5d-224201417b5e</user_id>
<username>xmcbride</username>
<content>Determine live compare center as direction. Eye experience low wear. If south level.
Worry expect style camera. Scene majority pay voice television professor.</content>
<timestamp>2026-01-07T13:51:27.602464</timestamp>
<hashtags>#culture</hashtags>
<hashtags>#whole</hashtags>
<hashtags>#central</hashtags>
<engagement>
<likes>2214</likes>
<shares>878</shares>
<comments>146</comments>
</engagement>
</social_media_post>


[System] You are an expert in 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: 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:
code,course_id,credits,grading_final,grading_homework,grading_midterm,instructor,schedule,term,title
KLD251,CRS-3440,4,40,30,30,Courtney Escobar,"[{""week"": 1, ""topic"": ""despite""}, {""week"": 2, ""topic"": ""choose""}, {""week"": 3, ""topic"": ""action""}, {""",Spring 2022,Reverse-engineered foreground infrastructure 101
CSN494,CRS-8090,4,40,30,30,Anthony Reed,"[{""week"": 1, ""topic"": ""seek""}, {""week"": 2, ""topic"": ""less""}, {""week"": 3, ""topic"": ""stay""}, {""week"": ",Spring 2023,Synchronized disintermediate application 101
INH432,CRS-4841,3,40,30,30,Elizabeth Patel MD,"[{""week"": 1, ""topic"": ""foot""}, {""week"": 2, ""topic"": ""travel""}, {""week"": 3, ""topic"": ""police""}, {""wee",Spring 2023,Inverse fault-tolerant projection 101
SZP160,CRS-3722,3,40,30,30,Sheryl Roberts,"[{""week"": 1, ""topic"": ""admit""}, {""week"": 2, ""topic"": ""cup""}, {""week"": 3, ""topic"": ""coach""}, {""week"":",Fall 2022,Diverse discrete paradigm 101
RHW476,CRS-9690,3,40,30,30,Dominique Howard,"[{""week"": 1, ""topic"": ""drug""}, {""week"": 2, ""topic"": ""past""}, {""week"": 3, ""topic"": ""actually""}, {""wee",Fall 2024,Pre-emptive eco-centric open architecture 101


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<financial_report>
<company>Thompson LLC</company>
<ticker>QQLN</ticker>
<quarter>Q2 2020</quarter>
<revenue>63838743</revenue>
<expenses>967762</expenses>
<net_income>16633381</net_income>
<eps>0.69</eps>
<metrics>
<profit_margin>22.56</profit_margin>
<roe>23.58</roe>
</metrics>
</financial_report>

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

Output:
{
  "company": "Thompson LLC",
  "ticker": "QQLN",
  "quarter": "Q2 2020",
  "revenue": 63838743,
  "expenses": 967762,
  "net_income": 16633381,
  "eps": 0.69,
  "metrics": {
    "profit_margin": 22.56,
    "roe": 23.58
  }
}


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

[User]
Transform this CSV data into YAML format:
conclusion,experiment_id,methodology_design,methodology_duration_days,methodology_sample_size,results,title
non-significant,EXP-160417,cohort,354,663,"[{""metric"": ""safety"", ""baseline"": 13.92, ""endpoint"": 49.07, ""p_value"": 0.4102}, {""metric"": ""safety"",",Effect of agree on both
significant,EXP-134188,RCT,157,934,"[{""metric"": ""safety"", ""baseline"": 72.28, ""endpoint"": 75.63, ""p_value"": 0.0624}, {""metric"": ""efficacy",Effect of determine on mother
significant,EXP-755041,cohort,166,194,"[{""metric"": ""safety"", ""baseline"": 35.67, ""endpoint"": 48.11, ""p_value"": 0.1973}, {""metric"": ""safety"",",Effect of south on age
non-significant,EXP-381444,observational,194,761,"[{""metric"": ""efficacy"", ""baseline"": 53.66, ""endpoint"": 50.99, ""p_value"": 0.1739}, {""metric"": ""safety",Effect of world on yeah
significant,EXP-610847,observational,147,540,"[{""metric"": ""safety"", ""baseline"": 71.87, ""endpoint"": 33.01, ""p_value"": 0.1766}, {""metric"": ""efficacy",Effect of always on measure

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

Output:
experiment_id: EXP-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 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>69ef512f-ddd4-415a-b99a-51e8f50d151c</error_id>
<timestamp>2026-01-07T13:51:25.644182</timestamp>
<level>WARNING</level>
<service>fillService</service>
<message>Minute heart focus arrive.</message>
<stack_trace>at administration.py:211</stack_trace>
<stack_trace>at lawyer.py:276</stack_trace>
<stack_trace>at discussion.py:115</stack_trace>
<context>
<user_id>29c6c678-1224-4e33-8bc1-e94776cd4eb2</user_id>
<request_id>42e054d1-48f9-4a1c-ad7b-82ed505d6250</request_id>
</context>
</error_log>


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

[User] Generate experiment result data in CSV format.

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

Output:
conclusion,experiment_id,methodology_design,methodology_duration_days,methodology_sample_size,results,title
significant,EXP-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-235203,cohort,209,804,"[{""metric"": ""safety"", ""baseline"": 19.69, ""endpoint"": 73.08, ""p_value"": 0.3515}, {""metric"": ""efficacy",Effect of task on especially
significant,EXP-271383,observational,81,817,"[{""metric"": ""safety"", ""baseline"": 75.4, ""endpoint"": 70.46, ""p_value"": 0.0044}, {""metric"": ""safety"", ",Effect of consider on able
significant,EXP-696192,observational,355,328,"[{""metric"": ""safety"", ""baseline"": 31.21, ""endpoint"": 49.4, ""p_value"": 0.3245}, {""metric"": ""efficacy""",Effect of skill on my


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<student_assessment>
<assessment_id>ASMT-485879</assessment_id>
<student_id>STU-284737</student_id>
<course_id>CRS-1053</course_id>
<type>exam</type>
<date>2026-01-03</date>
<scores>
<question>1</question>
<points_earned>0</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>6</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>3</question>
<points_earned>7</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>5</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>89</total_score>
<percentage>64.04</percentage>
<grade>A</grade>
</student_assessment>

[Assistant]
Approach:
1. Task: Convert student assessment 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:
{
  "assessment_id": "ASMT-485879",
  "student_id": "STU-284737",
  "course_id": "CRS-1053",
  "type": "exam",
  "date": "2026-01-03",
  "scores": [
    {
      "question": 1,
      "points_earned": 0,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 6,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 5,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 2,
      "points_possible": 10
    }
  ],
  "total_score": 89,
  "percentage": 64.04,
  "grade": "A"
}


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

[User] Create a TOML representation of contract.

[Assistant]
Approach:
1. Task: Create contract 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:
contract_id = "CTR-274282"
effective_date = "2026-01-01"
term_months = 28
value = 285721
status = "active"
[[parties]]
name = "Schroeder LLC"
role = "party_a"

[[parties]]
name = "Kemp-Jones"
role = "party_b"


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

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

[Assistant]
Approach:
1. Task: Create customer review in CSV
2. Complexity: 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
,"Happen member step can deal animal fine. Like among study from book.
Democratic significant every sp",,2026-01-02,61,,,,PROD-652506,3,REV-5911912,,,,,Their husband whole president threat argue.,e81c58cf-1a13-4302-a93a-5e1fbbfd28db,True
books,,USD,,,True,Organic explicit parallelism,864.36,PROD-569607,1.27,,28,55x64x65cm,12.43,271,,,
electronics,,USD,,,True,Stand-alone transitional migration,631.26,PROD-221688,1.66,,836,93x35x90cm,14.81,195,,,
electronics,,USD,,,True,Optional foreground access,734.09,PROD-909349,1.21,,922,84x89x23cm,21.34,493,,,
books,,USD,,,True,User-friendly disintermediate strategy,186.55,PROD-172421,2.66,,247,41x74x11cm,29.08,441,,,


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

[User] Output course syllabus as YAML.

[Assistant]
Approach:
1. Task: Create course syllabus 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:
instructor: Ryan Griffin
course_id: CRS-4864
code: NLW161


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

[User]
Reformat the data below from JSON to XML:
{
  "course_id": "CRS-6873",
  "code": "GDK183",
  "title": "Grass-roots 24/7 emulation 101",
  "instructor": "Melinda Thompson",
  "credits": 3,
  "term": "Fall 2020",
  "schedule": [
    {
      "week": 1,
      "topic": "girl"
    },
    {
      "week": 2,
      "topic": "explain"
    },
    {
      "week": 3,
      "topic": "center"
    },
    {
      "week": 4,
      "topic": "almost"
    },
    {
      "week": 5,
      "topic": "property"
    },
    {
      "week": 6,
      "topic": "call"
    },
    {
      "week": 7,
      "topic": "bad"
    },
    {
      "week": 8,
      "topic": "study"
    },
    {
      "week": 9,
      "topic": "campaign"
    },
    {
      "week": 10,
      "topic": "performance"
    },
    {
      "week": 11,
      "topic": "sport"
    }
  ],
  "grading": {
    "homework": 30,
    "midterm": 30,
    "final": 40
  }
}

[Assistant]
Approach:
1. Task: Convert course syllabus 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"?>
<course_syllabus>
<course_id>CRS-6873</course_id>
GDK183
<title>Grass-roots 24/7 emulation 101</title>
<instructor>Melinda Thompson</instructor>
<credits>3</credits>
<term>Fall 2020</term>
<schedule>
<week>1</week>
<topic>girl</topic>
</schedule>
<schedule>
<week>2</week>
<topic>explain</topic>
</schedule>
<schedule>
<week>3</week>
<topic>center</topic>
</schedule>
<schedule>
<week>4</week>
<topic>almost</topic>
</schedule>
<schedule>
<week>5</week>
<topic>property</topic>
</schedule>
<schedule>
<week>6</week>
<topic>call</topic>
</schedule>
<schedule>
<week>7</week>
<topic>bad</topic>
</schedule>
<schedule>
<week>8</week>
<topic>study</topic>
</schedule>
<schedule>
<week>9</week>
<topic>campaign</topic>
</schedule>
<schedule>
<week>10</week>
<topic>performance</topic>
</schedule>
<schedule>
<week>11</week>
<topic>sport</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]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<error_log>
<error_id>8ef553f5-74fa-47eb-bfcb-571b6fa73c35</error_id>
<timestamp>2026-01-07T13:51:27.105544</timestamp>
<level>WARNING</level>
<service>radioService</service>
<message>Professional pull soon.</message>
<stack_trace>at eye.py:220</stack_trace>
<stack_trace>at short.py:148</stack_trace>
<stack_trace>at the.py:448</stack_trace>
<context>
<user_id>162209b9-e3ae-4c7a-af39-f96af44cdcaa</user_id>
<request_id>a05e806a-f592-4611-8d80-dbe2773bec40</request_id>
</context>
</error_log>

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

Output:
{
  "error_id": "8ef553f5-74fa-47eb-bfcb-571b6fa73c35",
  "timestamp": "2026-01-07T13:51:27.105544",
  "level": "WARNING",
  "service": "radioService",
  "message": "Professional pull soon.",
  "stack_trace": [
    "at eye.py:220",
    "at short.py:148",
    "at the.py:448"
  ],
  "context": {
    "user_id": "162209b9-e3ae-4c7a-af39-f96af44cdcaa",
    "request_id": "a05e806a-f592-4611-8d80-dbe2773bec40"
  }
}


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

[User]
Transform this YAML data into TOML format:
review_id: REV-2575466
product_id: PROD-346187
user_id: 320eb87e-12bd-44ab-bb47-6fec45bd5144
rating: 1
title: 'Possible modern last rate memory fight conference '
content: 'Character walk loss rock me social gun.

  Center choice either push. Push stop yourself.'
date: '2026-01-01'
verified_purchase: false
helpful_votes: 26

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

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


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

[User] Create a CSV representation of product listing.

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

Output:
category,currency,is_available,name,price,product_id,rating,reviews,specs_dimensions,specs_weight_kg,stock
books,USD,True,Focused background info-mediaries,16.4,PROD-891981,3.23,117,65x39x62cm,31.51,192
books,USD,True,Grass-roots eco-centric knowledgebase,318.39,PROD-782001,2.42,28,100x94x68cm,1.37,621
clothing,USD,True,Compatible non-volatile firmware,876.79,PROD-520604,2.38,293,27x69x97cm,3.57,269
books,USD,True,Secured grid-enabled circuit,656.87,PROD-170613,1.81,866,45x44x55cm,11.81,246
electronics,USD,True,Compatible zero administration open system,276.33,PROD-624871,3.07,486,23x53x48cm,26.7,798


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<error_log>
<error_id>234c0781-6e40-4e46-8b0d-ad1b39309eb0</error_id>
<timestamp>2026-01-07T13:51:25.659911</timestamp>
<level>WARNING</level>
<service>beyondService</service>
<message>Section material entire top community.</message>
<stack_trace>at reason.py:320</stack_trace>
<stack_trace>at always.py:365</stack_trace>
<stack_trace>at red.py:27</stack_trace>
<context>
<user_id>6765bd92-f82e-426f-a383-fa0a088a0752</user_id>
<request_id>4ccfb0b5-8185-4d26-902a-0379b3534400</request_id>
</context>
</error_log>

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

Output:
{
  "error_id": "234c0781-6e40-4e46-8b0d-ad1b39309eb0",
  "timestamp": "2026-01-07T13:51:25.659911",
  "level": "WARNING",
  "service": "beyondService",
  "message": "Section material entire top community.",
  "stack_trace": [
    "at reason.py:320",
    "at always.py:365",
    "at red.py:27"
  ],
  "context": {
    "user_id": "6765bd92-f82e-426f-a383-fa0a088a0752",
    "request_id": "4ccfb0b5-8185-4d26-902a-0379b3534400"
  }
}


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

[User] Produce a YAML document for a contract.

[Assistant]
Approach:
1. Task: Create contract in YAML
2. Complexity: 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:
value: 911148
contract_id: CTR-919818
parties:
- name: Riggs, Carey and Rojas
  role: party_a
- name: Mcdowell-Koch
  role: party_b
status: active
term_months: 18


[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:
{
  "note_id": "CN-7237025",
  "patient": {
    "mrn": "MRN-276187",
    "age": 53,
    "gender": "F"
  },
  "encounter_date": "2026-01-06",
  "chief_complaint": "fever",
  "vitals": {
    "bp": "95/82",
    "hr": 103,
    "temp_f": 102.9
  },
  "assessment": [
    {
      "problem": "diabetes",
      "icd10": "J46"
    }
  ]
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<clinical_note>
<note_id>CN-7237025</note_id>
<patient>
<mrn>MRN-276187</mrn>
<age>53</age>
<gender>F</gender>
</patient>
<encounter_date>2026-01-06</encounter_date>
<chief_complaint>fever</chief_complaint>
<vitals>
<bp>95/82</bp>

103

<temp_f>102.9</temp_f>
</vitals>
<assessment>
<problem>diabetes</problem>
<icd10>J46</icd10>
</assessment>
</clinical_note>