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

[User] Create a XML representation of research paper.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<research_paper>
<paper_id>arXiv:2020.65510</paper_id>
<title>Mandatory solution-oriented groupware</title>
<authors>
<name>Jared Fuller</name>
<affiliation>Robinson, Crawford and Johnson</affiliation>
<email>jenna58@example.net</email>
</authors>
<authors>
<name>Nancy Anderson</name>
<affiliation>Shannon-Johnson</affiliation>
<email>richdonald@example.net</email>
</authors>
<authors>
<name>Julia Neal</name>
<affiliation>Roach, Harper and Cameron</affiliation>
<email>gillcory@example.com</email>
</authors>
<abstract>Along its pressure yeah. Artist pattern nearly rich realize available skill. Month beyond rate make kid painting.</abstract>
<keywords>surface</keywords>
<keywords>consumer</keywords>
<keywords>despite</keywords>
<keywords>compare</keywords>
<keywords>protect</keywords>
<publication>
<venue>Nature</venue>
<year>2022</year>
<doi>10.8909/Qnkv</doi>
</publication>
<citations>488</citations>
<funding_source>Johnson LLC</funding_source>
</research_paper>


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

[User] Output sales analytics as XML.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<sales_analytics>
<period>September 2024</period>
<total_revenue>6726526</total_revenue>
<units_sold>45392</units_sold>
<channels>
<name>retail</name>
<revenue>2051641</revenue>
<growth>15.93</growth>
</channels>
<channels>
<name>wholesale</name>
<revenue>4340607</revenue>
<growth>-6.59</growth>
</channels>
<top_products>
<sku>SKU-7798</sku>
<sales>367269</sales>
</top_products>
<top_products>
<sku>SKU-2105</sku>
<sales>291023</sales>
</top_products>
<top_products>
<sku>SKU-5730</sku>
<sales>275348</sales>
</top_products>
</sales_analytics>


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

[User] Output customer review as XML.

[Assistant]
Approach:
1. Task: Create customer review in XML
2. Complexity: 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"?>
<customer_review>
<verified_purchase>True</verified_purchase>
<date>2026-01-05</date>
<rating>1</rating>
</customer_review>


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<error_log>
<error_id>d03afc03-94bd-4dbb-bf49-9cda441c119b</error_id>
<timestamp>2026-01-07T13:51:25.952127</timestamp>
<level>CRITICAL</level>
<service>fromService</service>
<message>Add perform politics some card score brother.</message>
<stack_trace>at send.py:152</stack_trace>
<stack_trace>at young.py:309</stack_trace>
<context>
<user_id>2b3e5573-7b69-4807-a899-cbaa4adadf38</user_id>
<request_id>beac9c14-4ae5-407d-9aae-d7a56f6790f6</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": "d03afc03-94bd-4dbb-bf49-9cda441c119b",
  "timestamp": "2026-01-07T13:51:25.952127",
  "level": "CRITICAL",
  "service": "fromService",
  "message": "Add perform politics some card score brother.",
  "stack_trace": [
    "at send.py:152",
    "at young.py:309"
  ],
  "context": {
    "user_id": "2b3e5573-7b69-4807-a899-cbaa4adadf38",
    "request_id": "beac9c14-4ae5-407d-9aae-d7a56f6790f6"
  }
}


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

[User] Generate api specification data in YAML format.

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

Output:
openapi: 3.0.0
info:
  title: Re-engineered mobile superstructure API
  version: 1.0.0
paths:
  /benefit:
    get:
      summary: Chair media space recognize doctor would second me
      parameters:
      - name: param0
        in: query
        type: string
      - name: param1
        in: query
        type: string
      - name: param2
        in: query
        type: string
      responses:
        '200':
          description: Success
        '400':
          description: Bad Request


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

[User] Generate lab result data in YAML format.

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

Output:
result_id: LAB-5383313
patient_mrn: MRN-584871
order_date: '2026-01-06'
panel: CMP
results:
- test: Glucose
  value: 194.0
  unit: g/dL
  flag: normal
- test: Hemoglobin
  value: 67.1
  unit: g/dL
  flag: low
- test: Glucose
  value: 195.1
  unit: g/dL
  flag: low
- test: Hemoglobin
  value: 146.6
  unit: mg/dL
  flag: high
- test: WBC
  value: 119.8
  unit: mg/dL
  flag: normal


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

[User] Produce a XML document for a prescription.

[Assistant]
Approach:
1. Task: Create prescription in XML
2. Complexity: 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"?>
<prescription>
<medications>
<name>Atorvastatin</name>
<dosage>10mg</dosage>
<frequency>BID</frequency>
<quantity>60</quantity>
</medications>
<rx_id>RX-5523111</rx_id>
<date>2026-01-01</date>
</prescription>


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

[User] Output clinical note as TOML.

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

Output:
note_id = "CN-6952117"
encounter_date = "2026-01-03"
chief_complaint = "headache"
[[assessment]]
problem = "hypertension"
icd10 = "J35"

[[assessment]]
problem = "hypertension"
icd10 = "K44"

[[assessment]]
problem = "hypertension"
icd10 = "I58"

[patient]
mrn = "MRN-227055"
age = 50
gender = "F"

[vitals]
bp = "146/78"
hr = 63
temp_f = 97.9


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

[User] Output lab result as TOML.

[Assistant]
Approach:
1. Task: Create lab result in TOML
2. Complexity: 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-5956795"
patient_mrn = "MRN-953048"
order_date = "2026-01-05"
panel = "CBC"
[[results]]
test = "Glucose"
value = 138.6
unit = "g/dL"
flag = "high"

[[results]]
test = "Hemoglobin"
value = 69.4
unit = "g/dL"
flag = "normal"

[[results]]
test = "Hemoglobin"
value = 89.7
unit = "g/dL"
flag = "normal"

[[results]]
test = "Hemoglobin"
value = 191.9
unit = "g/dL"
flag = "low"

[[results]]
test = "WBC"
value = 169.5
unit = "mg/dL"
flag = "low"

[[results]]
test = "Glucose"
value = 187.7
unit = "mg/dL"
flag = "low"

[[results]]
test = "WBC"
value = 120.0
unit = "mg/dL"
flag = "high"


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<sales_analytics>
<period>April 2020</period>
<total_revenue>1914989</total_revenue>
<units_sold>47758</units_sold>
<channels>
<name>wholesale</name>
<revenue>3617590</revenue>
<growth>20.48</growth>
</channels>
<channels>
<name>online</name>
<revenue>654207</revenue>
<growth>24.4</growth>
</channels>
<top_products>
<sku>SKU-4328</sku>
<sales>466200</sales>
</top_products>
<top_products>
<sku>SKU-2589</sku>
<sales>244105</sales>
</top_products>
<top_products>
<sku>SKU-7725</sku>
<sales>25778</sales>
</top_products>
</sales_analytics>


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

[User]
Transform this TOML data into XML format:
period = "January 2022"
total_revenue = 7456708
units_sold = 82349
[[channels]]
name = "wholesale"
revenue = 3622404
growth = -8.05

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

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

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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<sales_analytics>
<period>January 2022</period>
<total_revenue>7456708</total_revenue>
<units_sold>82349</units_sold>
<channels>
<name>wholesale</name>
<revenue>3622404</revenue>
<growth>-8.05</growth>
</channels>
<channels>
<name>online</name>
<revenue>1893923</revenue>
<growth>2.21</growth>
</channels>
<top_products>
<sku>SKU-2073</sku>
<sales>98550</sales>
</top_products>
<top_products>
<sku>SKU-3707</sku>
<sales>233488</sales>
</top_products>
<top_products>
<sku>SKU-7843</sku>
<sales>172526</sales>
</top_products>
</sales_analytics>


[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:
{
  "txn_id": "TXN-31892506",
  "customer_id": "6c5d6d8e-2901-438d-be6d-be57a13ea5ab",
  "timestamp": "2026-01-07T13:51:25.485684",
  "items": [
    {
      "sku": "SKU-80058",
      "qty": 4,
      "price": 142.37
    },
    {
      "sku": "SKU-53232",
      "qty": 1,
      "price": 151.54
    }
  ],
  "subtotal": 692.94,
  "tax": 100.91,
  "total": 1647.14,
  "payment_method": "credit_card"
}

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

Output:
customer_id,items,payment_method,subtotal,tax,timestamp,total,txn_id
6c5d6d8e-2901-438d-be6d-be57a13ea5ab,"[{""sku"": ""SKU-80058"", ""qty"": 4, ""price"": 142.37}, {""sku"": ""SKU-53232"", ""qty"": 1, ""price"": 151.54}]",credit_card,692.94,100.91,2026-01-07T13:51:25.485684,1647.14,TXN-31892506
caa3761a-6a20-4997-8e7b-8b59dc65583f,"[{""sku"": ""SKU-35611"", ""qty"": 2, ""price"": 466.35}, {""sku"": ""SKU-67548"", ""qty"": 4, ""price"": 438.97}]",credit_card,562.95,89.07,2026-01-07T13:51:25.486989,1854.68,TXN-71277750
80d57893-35e9-44db-ba14-6690f353094b,"[{""sku"": ""SKU-55211"", ""qty"": 2, ""price"": 80.18}, {""sku"": ""SKU-96216"", ""qty"": 3, ""price"": 213.79}, {""",paypal,1690.11,146.72,2026-01-07T13:51:25.487028,615.14,TXN-24165791
6672f762-2e33-4ffe-9c62-0e3036095a13,"[{""sku"": ""SKU-24671"", ""qty"": 2, ""price"": 435.92}, {""sku"": ""SKU-47501"", ""qty"": 1, ""price"": 302.24}, {",paypal,782.78,14.93,2026-01-07T13:51:25.487068,397.24,TXN-57476836
7590f444-e2a2-401b-b1d9-2ce01a9b19d7,"[{""sku"": ""SKU-38974"", ""qty"": 4, ""price"": 150.47}]",apple_pay,1688.94,114.36,2026-01-07T13:51:25.487105,1418.8,TXN-13852806


[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: 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:
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 TOML format. Think step-by-step, then generate syntactically perfect TOML.

[User] Produce a TOML document for a prescription.

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

Output:
rx_id = "RX-3684509"
patient_mrn = "MRN-644382"
prescriber = "Chelsea Henson"
date = "2026-01-04"
[[medications]]
name = "Atorvastatin"
dosage = "10mg"
frequency = "BID"
quantity = 60

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

[[medications]]
name = "Metformin"
dosage = "10mg"
frequency = "TID"
quantity = 60


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

[User] Create a TOML representation of prescription.

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

Output:
rx_id = "RX-1795504"
patient_mrn = "MRN-355763"
prescriber = "Henry Padilla"
date = "2026-01-01"
[[medications]]
name = "Metformin"
dosage = "20mg"
frequency = "daily"
quantity = 90


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

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

[Assistant]
Approach:
1. Task: Create social media post in TOML
2. Complexity: 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:
post_id = "POST-66277640"
platform = "instagram"
user_id = "7e83a029-16e2-49ad-a855-906c882abe46"
username = "reynoldstaylor"
content = "Thousand book animal myself wear beautiful. Room rock couple reality her.\nJoin town travel agency value improve way. Heavy late science mind develop consider ability."
timestamp = "2026-01-07T13:51:26.676406"
hashtags = [ "#case", "#along", "#only", "#have",]

[engagement]
likes = 9942
shares = 119
comments = 368


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

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

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

Output:
conclusion,experiment_id,methodology_design,methodology_duration_days,methodology_sample_size,results,title
non-significant,EXP-139463,RCT,284,371,"[{""metric"": ""safety"", ""baseline"": 91.61, ""endpoint"": 76.9, ""p_value"": 0.4003}, {""metric"": ""safety"", ",Effect of quite on arm
non-significant,EXP-891818,RCT,217,896,"[{""metric"": ""efficacy"", ""baseline"": 33.54, ""endpoint"": 92.71, ""p_value"": 0.0692}, {""metric"": ""effica",Effect of respond on seat
non-significant,EXP-251231,cohort,63,899,"[{""metric"": ""safety"", ""baseline"": 86.52, ""endpoint"": 98.63, ""p_value"": 0.0577}, {""metric"": ""efficacy",Effect of eye on alone


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

[User] Generate error log data in YAML format.

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

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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<review_id>REV-4235678</review_id>
<product_id>PROD-754494</product_id>
<user_id>29638f7d-f697-4ae7-8fde-a1a70bcd6476</user_id>
<rating>5</rating>
<title>Help program law water necessary return clearly.</title>
<content>Team hold course throw center open enjoy old. Huge candidate still act decade civil. Safe middle indeed.</content>
<date>2026-01-03</date>
<verified_purchase>False</verified_purchase>
<helpful_votes>98</helpful_votes>
</customer_review>


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

[User] Create a CSV representation of contract.

[Assistant]
Approach:
1. Task: Create contract in CSV
2. Complexity: 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:
contract_id,effective_date,parties,status,term_months,value
CTR-123472,2026-01-06,"[{""name"": ""Palmer-White"", ""role"": ""party_a""}, {""name"": ""Rodriguez-Moore"", ""role"": ""party_b""}]",pending,59,388976
CTR-687289,2026-01-02,"[{""name"": ""Bautista-White"", ""role"": ""party_a""}, {""name"": ""Mcknight-Randall"", ""role"": ""party_b""}]",executed,59,119035
CTR-882257,2026-01-05,"[{""name"": ""Edwards Ltd"", ""role"": ""party_a""}, {""name"": ""Butler-Griffin"", ""role"": ""party_b""}]",executed,45,645813
CTR-609332,2026-01-03,"[{""name"": ""Taylor and Sons"", ""role"": ""party_a""}, {""name"": ""Gordon-Sanchez"", ""role"": ""party_b""}]",active,33,510180


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

[User]
Convert the following JSON to YAML:
{
  "course_id": "CRS-3948",
  "code": "CSZ142",
  "title": "Intuitive foreground functionalities 101",
  "instructor": "Robert Carter",
  "credits": 4,
  "term": "Fall 2022",
  "schedule": [
    {
      "week": 1,
      "topic": "manage"
    },
    {
      "week": 2,
      "topic": "catch"
    },
    {
      "week": 3,
      "topic": "people"
    },
    {
      "week": 4,
      "topic": "out"
    },
    {
      "week": 5,
      "topic": "story"
    },
    {
      "week": 6,
      "topic": "share"
    },
    {
      "week": 7,
      "topic": "become"
    },
    {
      "week": 8,
      "topic": "part"
    },
    {
      "week": 9,
      "topic": "cell"
    }
  ],
  "grading": {
    "homework": 30,
    "midterm": 30,
    "final": 40
  }
}

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

Output:
course_id: CRS-3948
code: CSZ142
title: Intuitive foreground functionalities 101
instructor: Robert Carter
credits: 4
term: Fall 2022
schedule:
- week: 1
  topic: manage
- week: 2
  topic: catch
- week: 3
  topic: people
- week: 4
  topic: out
- week: 5
  topic: story
- week: 6
  topic: share
- week: 7
  topic: become
- week: 8
  topic: part
- week: 9
  topic: cell
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]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<student_assessment>
<assessment_id>ASMT-744456</assessment_id>
<student_id>STU-954920</student_id>
<course_id>CRS-3021</course_id>
<type>exam</type>
<date>2026-01-03</date>
<scores>
<question>1</question>
<points_earned>7</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>2</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>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>10</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>5</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>9</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>10</question>
<points_earned>3</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>11</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>12</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>97</total_score>
<percentage>89.67</percentage>
<grade>C</grade>
</student_assessment>

[Assistant]
Approach:
1. Task: Convert student assessment 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:
{
  "assessment_id": "ASMT-744456",
  "student_id": "STU-954920",
  "course_id": "CRS-3021",
  "type": "exam",
  "date": "2026-01-03",
  "scores": [
    {
      "question": 1,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 5,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 10,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 5,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 9,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 10,
      "points_earned": 3,
      "points_possible": 10
    },
    {
      "question": 11,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 12,
      "points_earned": 9,
      "points_possible": 10
    }
  ],
  "total_score": 97,
  "percentage": 89.67,
  "grade": "C"
}


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

[User]
Convert the following JSON to XML:
{
  "post_id": "POST-25055870",
  "platform": "twitter",
  "user_id": "28837af0-4898-41b2-8a38-faf0e2d7f431",
  "username": "khahn",
  "content": "Serve student science today general. Tell risk ball quickly technology.\nDrive because generation support gun message majority. Though do old.",
  "timestamp": "2026-01-07T13:51:27.403909",
  "hashtags": [
    "#conference",
    "#body"
  ],
  "engagement": {
    "likes": 9394,
    "shares": 444,
    "comments": 203
  }
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<social_media_post>
<post_id>POST-25055870</post_id>
<platform>twitter</platform>
<user_id>28837af0-4898-41b2-8a38-faf0e2d7f431</user_id>
<username>khahn</username>
<content>Serve student science today general. Tell risk ball quickly technology.
Drive because generation support gun message majority. Though do old.</content>
<timestamp>2026-01-07T13:51:27.403909</timestamp>
<hashtags>#conference</hashtags>
<hashtags>#body</hashtags>
<engagement>
<likes>9394</likes>
<shares>444</shares>
<comments>203</comments>
</engagement>
</social_media_post>


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<lab_result>
<result_id>LAB-9017474</result_id>
<patient_mrn>MRN-783803</patient_mrn>
<order_date>2026-01-04</order_date>
<panel>Lipid</panel>
<results>
<test>Glucose</test>
<value>65.6</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Glucose</test>
<value>160.2</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>WBC</test>
<value>142.4</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Glucose</test>
<value>179.9</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>97.3</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>148.5</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>174.6</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
</lab_result>


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

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

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

Output:
openapi = "3.0.0"

[info]
title = "Robust demand-driven hub API"
version = "1.0.0"

[paths."/finally".get]
summary = "Describe experience pick treatment up remain withi"
[[paths."/finally".get.parameters]]
name = "param0"
in = "query"
type = "string"

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

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

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

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


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

[User] Output social media post as XML.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<social_media_post>
<post_id>POST-54622203</post_id>
<platform>instagram</platform>
<user_id>1456e108-0a50-4482-8f1a-b1cb2398a121</user_id>
<username>fullersteven</username>
<content>Card these member kid western growth. Staff draw say early town general. Large break interesting ten against open.
Any fine power truth. Big like investment simple whatever education.</content>
<timestamp>2026-01-07T13:51:25.504049</timestamp>
<hashtags>#deep</hashtags>
<hashtags>#yes</hashtags>
<hashtags>#long</hashtags>
<hashtags>#including</hashtags>
<engagement>
<likes>464</likes>
<shares>699</shares>
<comments>294</comments>
</engagement>
</social_media_post>


[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-1812594"
patient_mrn = "MRN-755137"
order_date = "2026-01-06"
panel = "CMP"
[[results]]
test = "Glucose"
value = 131.9
unit = "mg/dL"
flag = "normal"

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

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

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


[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:
rx_id: RX-5336793
patient_mrn: MRN-644295
prescriber: Thomas Ponce
date: '2026-01-03'
medications:
- name: Atorvastatin
  dosage: 5mg
  frequency: BID
  quantity: 90
- name: Atorvastatin
  dosage: 5mg
  frequency: daily
  quantity: 30
- name: Atorvastatin
  dosage: 10mg
  frequency: BID
  quantity: 30

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

Output:
{
  "rx_id": "RX-5336793",
  "patient_mrn": "MRN-644295",
  "prescriber": "Thomas Ponce",
  "date": "2026-01-03",
  "medications": [
    {
      "name": "Atorvastatin",
      "dosage": "5mg",
      "frequency": "BID",
      "quantity": 90
    },
    {
      "name": "Atorvastatin",
      "dosage": "5mg",
      "frequency": "daily",
      "quantity": 30
    },
    {
      "name": "Atorvastatin",
      "dosage": "10mg",
      "frequency": "BID",
      "quantity": 30
    }
  ]
}


[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"?>
<prescription>
<rx_id>RX-5305677</rx_id>
<patient_mrn>MRN-215469</patient_mrn>
<prescriber>Jeremy Hatfield</prescriber>
<date>2026-01-03</date>
<medications>
<name>Metformin</name>
<dosage>10mg</dosage>
<frequency>daily</frequency>
<quantity>90</quantity>
</medications>
<medications>
<name>Metformin</name>
<dosage>5mg</dosage>
<frequency>daily</frequency>
<quantity>30</quantity>
</medications>
<medications>
<name>Atorvastatin</name>
<dosage>10mg</dosage>
<frequency>BID</frequency>
<quantity>90</quantity>
</medications>
</prescription>

[Assistant]
Approach:
1. Task: Convert prescription 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:
{
  "rx_id": "RX-5305677",
  "patient_mrn": "MRN-215469",
  "prescriber": "Jeremy Hatfield",
  "date": "2026-01-03",
  "medications": [
    {
      "name": "Metformin",
      "dosage": "10mg",
      "frequency": "daily",
      "quantity": 90
    },
    {
      "name": "Metformin",
      "dosage": "5mg",
      "frequency": "daily",
      "quantity": 30
    },
    {
      "name": "Atorvastatin",
      "dosage": "10mg",
      "frequency": "BID",
      "quantity": 90
    }
  ]
}


[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"?>
<student_assessment>
<assessment_id>ASMT-554535</assessment_id>
<student_id>STU-693793</student_id>
<course_id>CRS-9992</course_id>
<type>exam</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>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>6</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>1</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>2</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>10</question>
<points_earned>3</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>86</total_score>
<percentage>63.99</percentage>
<grade>B</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-554535",
  "student_id": "STU-693793",
  "course_id": "CRS-9992",
  "type": "exam",
  "date": "2026-01-03",
  "scores": [
    {
      "question": 1,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 6,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 6,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 6,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 9,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 10,
      "points_earned": 3,
      "points_possible": 10
    }
  ],
  "total_score": 86,
  "percentage": 63.99,
  "grade": "B"
}


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

[User] Generate lab result data in TOML format.

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

Output:
result_id = "LAB-5387789"
patient_mrn = "MRN-887521"
order_date = "2026-01-05"
panel = "CBC"
[[results]]
test = "WBC"
value = 66.6
unit = "mg/dL"
flag = "normal"

[[results]]
test = "Glucose"
value = 111.4
unit = "mg/dL"
flag = "high"

[[results]]
test = "Hemoglobin"
value = 168.1
unit = "g/dL"
flag = "high"

[[results]]
test = "Hemoglobin"
value = 136.7
unit = "g/dL"
flag = "low"

[[results]]
test = "WBC"
value = 148.7
unit = "g/dL"
flag = "low"

[[results]]
test = "Glucose"
value = 86.9
unit = "mg/dL"
flag = "normal"


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<product_listing>
<product_id>PROD-141484</product_id>
<name>Managed bandwidth-monitored focus group</name>
<category>books</category>
<price>751.35</price>
<currency>USD</currency>
<stock>108</stock>
<is_available>True</is_available>
<rating>2.94</rating>
<reviews>250</reviews>
<specs>
<weight_kg>6.41</weight_kg>
<dimensions>15x82x35cm</dimensions>
</specs>
</product_listing>

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

Output:
{
  "product_id": "PROD-141484",
  "name": "Managed bandwidth-monitored focus group",
  "category": "books",
  "price": 751.35,
  "currency": "USD",
  "stock": 108,
  "is_available": true,
  "rating": 2.94,
  "reviews": 250,
  "specs": {
    "weight_kg": 6.41,
    "dimensions": "15x82x35cm"
  }
}


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<error_log>
<error_id>249c5a8d-effc-4f5a-9a18-79860cd86eba</error_id>
<timestamp>2026-01-07T13:51:25.844189</timestamp>
<level>CRITICAL</level>
<service>createService</service>
<message>Capital carry as agree member lead one.</message>
<stack_trace>at sign.py:359</stack_trace>
<stack_trace>at college.py:115</stack_trace>
<stack_trace>at try.py:133</stack_trace>
<context>
<user_id>e110a198-5d8a-4242-b2e4-6ec6ae49ca80</user_id>
<request_id>939e8b37-2ce6-4ba0-bde6-ca285c8d396c</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": "249c5a8d-effc-4f5a-9a18-79860cd86eba",
  "timestamp": "2026-01-07T13:51:25.844189",
  "level": "CRITICAL",
  "service": "createService",
  "message": "Capital carry as agree member lead one.",
  "stack_trace": [
    "at sign.py:359",
    "at college.py:115",
    "at try.py:133"
  ],
  "context": {
    "user_id": "e110a198-5d8a-4242-b2e4-6ec6ae49ca80",
    "request_id": "939e8b37-2ce6-4ba0-bde6-ca285c8d396c"
  }
}


[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: 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"?>
<student_assessment>
<assessment_id>ASMT-350362</assessment_id>
<student_id>STU-421536</student_id>
<course_id>CRS-1231</course_id>
<type>exam</type>
<date>2026-01-01</date>
<scores>
<question>1</question>
<points_earned>2</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>8</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>8</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>6</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>5</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>9</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>10</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>11</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>51</total_score>
<percentage>80.6</percentage>
<grade>A</grade>
</student_assessment>


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

[User] Output course syllabus as TOML.

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

Output:
course_id = "CRS-2281"
code = "NHA456"
title = "Profit-focused mission-critical hardware 101"
instructor = "Natalie Middleton"
credits = 3
term = "Spring 2024"
[[schedule]]
week = 1
topic = "its"

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

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

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

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

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

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

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

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

[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]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<research_paper>
<paper_id>arXiv:2023.57642</paper_id>
<title>Organized clear-thinking projection</title>
<authors>
<name>Thomas Harrison</name>
<affiliation>Benjamin, Peterson and James</affiliation>
<email>martinjoseph@example.com</email>
</authors>
<authors>
<name>Samantha Phillips</name>
<affiliation>Carpenter Ltd</affiliation>
<email>hawkinssarah@example.com</email>
</authors>
<abstract>Leg third those over. Almost state money hear condition little.
Manager minute writer manager. Walk hand situation similar media back fill huge.</abstract>
<keywords>decade</keywords>
<keywords>kitchen</keywords>
<keywords>discover</keywords>
<keywords>wide</keywords>
<publication>
<venue>Cell</venue>
<year>2023</year>
<doi>10.5371/HWME</doi>
</publication>
<citations>306</citations>
<funding_source />
</research_paper>

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

Output:
{
  "paper_id": "arXiv:2023.57642",
  "title": "Organized clear-thinking projection",
  "authors": [
    {
      "name": "Thomas Harrison",
      "affiliation": "Benjamin, Peterson and James",
      "email": "martinjoseph@example.com"
    },
    {
      "name": "Samantha Phillips",
      "affiliation": "Carpenter Ltd",
      "email": "hawkinssarah@example.com"
    }
  ],
  "abstract": "Leg third those over. Almost state money hear condition little.\nManager minute writer manager. Walk hand situation similar media back fill huge.",
  "keywords": [
    "decade",
    "kitchen",
    "discover",
    "wide"
  ],
  "publication": {
    "venue": "Cell",
    "year": 2023,
    "doi": "10.5371/HWME"
  },
  "citations": 306,
  "funding_source": null
}


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

[User]
Transform this JSON data into XML format:
{
  "post_id": "POST-78526123",
  "platform": "twitter",
  "user_id": "17596017-ad50-41af-8dc2-8746d15af00d",
  "username": "qsharp",
  "content": "Seven behavior less water pretty.\nRock key include. Kind than game agreement.\nPaper position reduce purpose I affect wait threat. Third effect newspaper before include decision recently million.",
  "timestamp": "2026-01-07T13:51:27.460227",
  "hashtags": [
    "#draw",
    "#five",
    "#culture",
    "#sport"
  ],
  "engagement": {
    "likes": 1826,
    "shares": 489,
    "comments": 393
  }
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<social_media_post>
<post_id>POST-78526123</post_id>
<platform>twitter</platform>
<user_id>17596017-ad50-41af-8dc2-8746d15af00d</user_id>
<username>qsharp</username>
<content>Seven behavior less water pretty.
Rock key include. Kind than game agreement.
Paper position reduce purpose I affect wait threat. Third effect newspaper before include decision recently million.</content>
<timestamp>2026-01-07T13:51:27.460227</timestamp>
<hashtags>#draw</hashtags>
<hashtags>#five</hashtags>
<hashtags>#culture</hashtags>
<hashtags>#sport</hashtags>
<engagement>
<likes>1826</likes>
<shares>489</shares>
<comments>393</comments>
</engagement>
</social_media_post>


[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-9456</course_id>
KDS432
<title>Multi-channeled local complexity 101</title>
<instructor>Kenneth Rogers</instructor>
<credits>3</credits>
<term>Fall 2020</term>
<schedule>
<week>1</week>
<topic>activity</topic>
</schedule>
<schedule>
<week>2</week>
<topic>foot</topic>
</schedule>
<schedule>
<week>3</week>
<topic>reason</topic>
</schedule>
<schedule>
<week>4</week>
<topic>rule</topic>
</schedule>
<schedule>
<week>5</week>
<topic>paper</topic>
</schedule>
<schedule>
<week>6</week>
<topic>current</topic>
</schedule>
<schedule>
<week>7</week>
<topic>scene</topic>
</schedule>
<schedule>
<week>8</week>
<topic>later</topic>
</schedule>
<schedule>
<week>9</week>
<topic>choice</topic>
</schedule>
<schedule>
<week>10</week>
<topic>box</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-9456",
  "code": "KDS432",
  "title": "Multi-channeled local complexity 101",
  "instructor": "Kenneth Rogers",
  "credits": 3,
  "term": "Fall 2020",
  "schedule": [
    {
      "week": 1,
      "topic": "activity"
    },
    {
      "week": 2,
      "topic": "foot"
    },
    {
      "week": 3,
      "topic": "reason"
    },
    {
      "week": 4,
      "topic": "rule"
    },
    {
      "week": 5,
      "topic": "paper"
    },
    {
      "week": 6,
      "topic": "current"
    },
    {
      "week": 7,
      "topic": "scene"
    },
    {
      "week": 8,
      "topic": "later"
    },
    {
      "week": 9,
      "topic": "choice"
    },
    {
      "week": 10,
      "topic": "box"
    }
  ],
  "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 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>Eaton, Mccarty and Lopez</company>
<ticker>OWKB</ticker>
<quarter>Q3 2021</quarter>
<revenue>46227283</revenue>
<expenses>75330506</expenses>
<net_income>13309525</net_income>
<eps>4.82</eps>
<metrics>
<profit_margin>29.61</profit_margin>
<roe>8.93</roe>
</metrics>
</financial_report>


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

[User] Output customer review as CSV.

[Assistant]
Approach:
1. Task: Create customer review in CSV
2. Complexity: 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
,"Character walk loss rock me social gun.
Center choice either push. Push stop yourself.",,2026-01-01,26,,,,PROD-346187,1,REV-2575466,,,,,Possible modern last rate memory fight conference ,320eb87e-12bd-44ab-bb47-6fec45bd5144,False
books,,USD,,,True,Universal attitude-oriented analyzer,97.08,PROD-498494,4.2,,9,54x51x43cm,45.83,876,,,
books,,USD,,,True,Synergized eco-centric standardization,371.42,PROD-370975,4.89,,42,29x36x56cm,32.13,93,,,


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<student_assessment>
<assessment_id>ASMT-225883</assessment_id>
<student_id>STU-314827</student_id>
<course_id>CRS-2408</course_id>
<type>quiz</type>
<date>2026-01-01</date>
<scores>
<question>1</question>
<points_earned>8</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>3</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>7</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>3</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>3</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>4</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>9</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>10</question>
<points_earned>10</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>11</question>
<points_earned>4</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>12</question>
<points_earned>10</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>13</question>
<points_earned>8</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>99</total_score>
<percentage>82.0</percentage>
<grade>B</grade>
</student_assessment>

[Assistant]
Approach:
1. Task: Convert student assessment 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:
{
  "assessment_id": "ASMT-225883",
  "student_id": "STU-314827",
  "course_id": "CRS-2408",
  "type": "quiz",
  "date": "2026-01-01",
  "scores": [
    {
      "question": 1,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 3,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 3,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 9,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 10,
      "points_earned": 10,
      "points_possible": 10
    },
    {
      "question": 11,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 12,
      "points_earned": 10,
      "points_possible": 10
    },
    {
      "question": 13,
      "points_earned": 8,
      "points_possible": 10
    }
  ],
  "total_score": 99,
  "percentage": 82.0,
  "grade": "B"
}


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

[User] Output customer review as YAML.

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

Output:
review_id: REV-9546377
product_id: PROD-108034
user_id: d01ac4e1-ccd9-4273-9fe0-9ca6afc6af77
rating: 4
title: Appear speak sure list.
content: Today offer none role certain reach. Second Mr official enjoy movement turn
  city. Name employee early much first sit.
date: '2026-01-01'
verified_purchase: true
helpful_votes: 43


[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>Robust demand-driven hub API</title>
<version>1.0.0</version>
</info>
<paths>
</finally>
<get>
<summary>Describe experience pick treatment up remain withi</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>
<//finally>
</paths>
</api_specification>


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

[User] Output product listing as TOML.

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

Output:
product_id = "PROD-319304"
name = "Self-enabling clear-thinking help-desk"
category = "clothing"
price = 510.64
currency = "USD"
stock = 595
is_available = true
rating = 2.22
reviews = 791

[specs]
weight_kg = 30.42
dimensions = "12x58x39cm"


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

[User] Output research paper as JSON.

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

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


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

[User]
Reformat the data below from XML to YAML:
<?xml version="1.0" encoding="UTF-8"?>
<financial_report>
<revenue>81140617</revenue>
<metrics>
<profit_margin>25.46</profit_margin>
<roe>20.6</roe>
</metrics>
<quarter>Q1 2021</quarter>
</financial_report>

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

Output:
revenue: 81140617
metrics:
  profit_margin: 25.46
  roe: 20.6
quarter: Q1 2021


[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"?>
<product_listing>
<product_id>PROD-597223</product_id>
<name>Proactive tertiary database</name>
<category>books</category>
<price>435.77</price>
<currency>USD</currency>
<stock>111</stock>
<is_available>True</is_available>
<rating>1.73</rating>
<reviews>539</reviews>
<specs>
<weight_kg>19.61</weight_kg>
<dimensions>87x91x85cm</dimensions>
</specs>
</product_listing>

[Assistant]
Approach:
1. Task: Convert product listing 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:
{
  "product_id": "PROD-597223",
  "name": "Proactive tertiary database",
  "category": "books",
  "price": 435.77,
  "currency": "USD",
  "stock": 111,
  "is_available": true,
  "rating": 1.73,
  "reviews": 539,
  "specs": {
    "weight_kg": 19.61,
    "dimensions": "87x91x85cm"
  }
}


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

[User] Create a YAML representation of error log.

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

Output:
error_id: e78ff1cc-d984-499d-9fcf-126ccada9355
timestamp: '2026-01-07T13:51:26.607679'
level: WARNING
service: generationService
message: Bag difference growth have leader yeah him.
stack_trace:
- at teach.py:30
- at poor.py:409
context:
  user_id: e8daac99-0bad-4fb0-ae26-78525528db85
  request_id: a6fe9e0f-a1a6-42b2-ab77-98b8bb662a52


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Intuitive disintermediate website API</title>
<version>1.0.0</version>
</info>
<paths>
</reality>
<get>
<summary>Activity public whole paper there relationship tas</summary>
<parameters>
<name>param0</name>
<in>query</in>
<type>string</type>
</parameters>
<parameters>
<name>param1</name>
<in>query</in>
<type>string</type>
</parameters>
<responses>
<200>
<description>Success</description>
</200>
<400>
<description>Bad Request</description>
</400>
</responses>
</get>
<//reality>
</paths>
</api_specification>

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

Output:
{
  "openapi": "3.0.0",
  "info": {
    "title": "Intuitive disintermediate website API",
    "version": "1.0.0"
  },
  "paths": {
    "/reality": {
      "get": {
        "summary": "Activity public whole paper there relationship tas",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          },
          {
            "name": "param1",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  }
}


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

[User]
Transform this JSON data into XML format:
{
  "post_id": "POST-52722833",
  "platform": "facebook",
  "user_id": "d42576ea-a78d-4261-852d-cbcc2fd55da5",
  "username": "justin96",
  "content": "Southern write three operation throw interest whether.\nDecade quality training employee. Financial out position catch finish author. Past over in create.\nNice reduce try contain future back customer.",
  "timestamp": "2026-01-07T13:51:26.716888",
  "hashtags": [
    "#report",
    "#newspaper"
  ],
  "engagement": {
    "likes": 8106,
    "shares": 850,
    "comments": 244
  }
}

[Assistant]
Approach:
1. Task: Convert social media post 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"?>
<social_media_post>
<post_id>POST-52722833</post_id>
<platform>facebook</platform>
<user_id>d42576ea-a78d-4261-852d-cbcc2fd55da5</user_id>
<username>justin96</username>
<content>Southern write three operation throw interest whether.
Decade quality training employee. Financial out position catch finish author. Past over in create.
Nice reduce try contain future back customer.</content>
<timestamp>2026-01-07T13:51:26.716888</timestamp>
<hashtags>#report</hashtags>
<hashtags>#newspaper</hashtags>
<engagement>
<likes>8106</likes>
<shares>850</shares>
<comments>244</comments>
</engagement>
</social_media_post>


[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:
article_id: ART-9178511
headline: Fully-configurable secondary access
author: Gabrielle Daugherty
published: '2026-01-05T07:34:40.744934'
section: Tech
content: 'Lawyer might home mouth end so science. Hope attention strong public teach
  person beautiful though. Really decision land evening year.

  Just role ground discover. Five stand writer floor.'
tags:
- maybe
- glass
- election
- moment
views: 24250
shares: 778

[Assistant]
Approach:
1. Task: Convert news article 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:
{
  "article_id": "ART-9178511",
  "headline": "Fully-configurable secondary access",
  "author": "Gabrielle Daugherty",
  "published": "2026-01-05T07:34:40.744934",
  "section": "Tech",
  "content": "Lawyer might home mouth end so science. Hope attention strong public teach person beautiful though. Really decision land evening year.\nJust role ground discover. Five stand writer floor.",
  "tags": [
    "maybe",
    "glass",
    "election",
    "moment"
  ],
  "views": 24250,
  "shares": 778
}


[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:
{
  "rating": 2,
  "verified_purchase": true,
  "helpful_votes": 29,
  "date": "2026-01-01",
  "user_id": "ed843147-0604-46c9-98b2-def8aa0c8a20"
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<rating>2</rating>
<verified_purchase>True</verified_purchase>
<helpful_votes>29</helpful_votes>
<date>2026-01-01</date>
<user_id>ed843147-0604-46c9-98b2-def8aa0c8a20</user_id>
</customer_review>


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

[User] Create a TOML representation of sales analytics.

[Assistant]
Approach:
1. Task: Create sales analytics in TOML
2. Complexity: 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:
period = "February 2024"
total_revenue = 3108970
units_sold = 70292
[[channels]]
name = "online"
revenue = 1867975
growth = -2.95

[[channels]]
name = "retail"
revenue = 1947932
growth = 22.54

[[top_products]]
sku = "SKU-5409"
sales = 492017

[[top_products]]
sku = "SKU-4816"
sales = 486050

[[top_products]]
sku = "SKU-9957"
sales = 44038


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

[User]
Transform this XML data into CSV format:
<?xml version="1.0" encoding="UTF-8"?>
<student_assessment>
<assessment_id>ASMT-530397</assessment_id>
<student_id>STU-509684</student_id>
<course_id>CRS-8191</course_id>
<type>quiz</type>
<date>2026-01-01</date>
<scores>
<question>1</question>
<points_earned>3</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>5</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>3</question>
<points_earned>4</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>6</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>0</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>3</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>6</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>10</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>11</question>
<points_earned>7</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>12</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>13</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>14</question>
<points_earned>7</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>91</total_score>
<percentage>61.03</percentage>
<grade>A</grade>
</student_assessment>

[Assistant]
Approach:
1. Task: Convert student assessment from XML 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:
assessment_id,code,course_id,credits,date,grade,grading_final,grading_homework,grading_midterm,instructor,percentage,schedule,scores,student_id,term,title,total_score,type
ASMT-530397,,CRS-8191,,2026-01-01,A,,,,,61.03,,"[{""question"": 1, ""points_earned"": 3, ""points_possible"": 10}, {""question"": 2, ""points_earned"": 5, ""po",STU-509684,,,91,quiz
,ICK407,CRS-5936,3,,,40,30,30,Ashley Johnson,,"[{""week"": 1, ""topic"": ""energy""}, {""week"": 2, ""topic"": ""it""}, {""week"": 3, ""topic"": ""day""}, {""week"": 4",,,Spring 2021,Fully-configurable mobile function 101,,
,OSR350,CRS-3047,4,,,40,30,30,Warren Ortiz,,"[{""week"": 1, ""topic"": ""poor""}, {""week"": 2, ""topic"": ""when""}, {""week"": 3, ""topic"": ""as""}, {""week"": 4,",,,Spring 2021,Programmable multi-tasking complexity 101,,
,VQW327,CRS-3627,4,,,40,30,30,Sandra Bell,,"[{""week"": 1, ""topic"": ""feeling""}, {""week"": 2, ""topic"": ""each""}, {""week"": 3, ""topic"": ""sing""}, {""week",,,Spring 2021,Upgradable intangible methodology 101,,


[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:
{
  "error_id": "92d36993-19b1-4c19-9b64-8b4669c6636f",
  "timestamp": "2026-01-07T13:51:27.222487",
  "level": "WARNING",
  "service": "voiceService",
  "message": "Analysis beautiful attack blue eye.",
  "stack_trace": [
    "at well.py:163",
    "at will.py:421",
    "at run.py:384",
    "at TV.py:103"
  ],
  "context": {
    "user_id": "c92bcb8f-c109-47f8-aa13-b43737a1fc38",
    "request_id": "f4cb6737-30c9-41ef-814b-34c3ec971deb"
  }
}

[Assistant]
Approach:
1. Task: Convert error log 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"?>
<error_log>
<error_id>92d36993-19b1-4c19-9b64-8b4669c6636f</error_id>
<timestamp>2026-01-07T13:51:27.222487</timestamp>
<level>WARNING</level>
<service>voiceService</service>
<message>Analysis beautiful attack blue eye.</message>
<stack_trace>at well.py:163</stack_trace>
<stack_trace>at will.py:421</stack_trace>
<stack_trace>at run.py:384</stack_trace>
<stack_trace>at TV.py:103</stack_trace>
<context>
<user_id>c92bcb8f-c109-47f8-aa13-b43737a1fc38</user_id>
<request_id>f4cb6737-30c9-41ef-814b-34c3ec971deb</request_id>
</context>
</error_log>


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

[User] Output news article as JSON.

[Assistant]
Approach:
1. Task: Create news article 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:
{
  "article_id": "ART-8172649",
  "headline": "Triple-buffered responsive model",
  "author": "Rachel Clark",
  "published": "2026-01-03T00:35:22.551008",
  "section": "Business",
  "content": "Pattern capital time compare include night top. Large than important morning.\nCard authority protect present return while middle. Development miss write five.",
  "tags": [
    "consider",
    "whatever",
    "part",
    "however",
    "special"
  ],
  "views": 49705,
  "shares": 392
}


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


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

[User] Produce a XML document for a prescription.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<prescription>
<rx_id>RX-9719971</rx_id>
<patient_mrn>MRN-909141</patient_mrn>
<prescriber>Heather Stephens</prescriber>
<date>2026-01-05</date>
<medications>
<name>Atorvastatin</name>
<dosage>20mg</dosage>
<frequency>daily</frequency>
<quantity>30</quantity>
</medications>
</prescription>


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

[User] Generate lab result data in YAML format.

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

Output:
result_id: LAB-5790382
patient_mrn: MRN-357903
order_date: '2026-01-02'
panel: CBC
results:
- test: Glucose
  value: 56.1
  unit: mg/dL
  flag: high
- test: Glucose
  value: 114.1
  unit: mg/dL
  flag: normal
- test: WBC
  value: 154.7
  unit: mg/dL
  flag: low
- test: Glucose
  value: 196.1
  unit: g/dL
  flag: normal


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

[User] Generate api specification data in CSV format.

[Assistant]
Approach:
1. Task: Create api specification 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,info_title,info_version,keywords,openapi,paper_id,paths_/require_get_parameters,paths_/require_get_responses_200_description,paths_/require_get_responses_400_description,paths_/require_get_summary,publication_doi,publication_venue,publication_year,title
,,,,Multi-tiered directional knowledge user API,1.0.0,,3.0.0,,"[{""name"": ""param0"", ""in"": ""query"", ""type"": ""string""}, {""name"": ""param1"", ""in"": ""query"", ""type"": ""str",Success,Bad Request,Suffer kid pull bed decision rest.,,,,
Fall decide study beautiful. Mission particularly mind plant serve together attack. Professional fac,"[{""name"": ""Chelsea Parker DDS"", ""affiliation"": ""Dean, Torres and Brooks"", ""email"": ""richardrivera@ex",1,"Martinez, Garza and Green",,,"[""car"", ""write"", ""sell"", ""stay"", ""star""]",,arXiv:2021.30764,,,,,10.6397/FfzO,Cell,2020,Cross-group 24/7 capability
Attack might grow follow fill hand. Sign much between serve will through.,"[{""name"": ""Alyssa Marshall"", ""affiliation"": ""Wheeler-Brown"", ""email"": ""smiddleton@example.org""}, {""n",309,"Schwartz, Webb and Humphrey",,,"[""movie"", ""teach"", ""common"", ""important""]",,arXiv:2024.90263,,,,,10.5157/EoIW,Science,2021,Function-based impactful software
Necessary recent condition mind cut. Size cell item or like Democrat. Explain able effort type.,"[{""name"": ""Rachel Mack"", ""affiliation"": ""Acevedo LLC"", ""email"": ""deborah29@example.org""}, {""name"": """,55,Hansen-Hamilton,,,"[""detail"", ""fish"", ""find"", ""because""]",,arXiv:2021.26898,,,,,10.2626/rVkO,Cell,2024,Virtual maximized forecast


[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:
grade = "A"
course_id = "CRS-4519"
total_score = 75


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

[User] Create a XML representation of financial report.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<financial_report>
<company>Tucker and Sons</company>
<ticker>BPQE</ticker>
<quarter>Q4 2024</quarter>
<revenue>70279854</revenue>
<expenses>61737533</expenses>
<net_income>12235621</net_income>
<eps>3.52</eps>
<metrics>
<profit_margin>24.27</profit_margin>
<roe>16.15</roe>
</metrics>
</financial_report>


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

[User]
Reformat the data below from JSON to TOML:
{
  "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 TOML
2. Complexity: simple - 3-5 fields, minimal nesting
3. Format rules: key=value syntax, [sections], proper types
4. Structure: Organize data logically with appropriate nesting
5. Transform values to match the target format specifications.

Output:
course_id = "CRS-9368"
percentage = 68.59
assessment_id = "ASMT-453812"
[[scores]]
question = 1
points_earned = 2
points_possible = 10

[[scores]]
question = 2
points_earned = 3
points_possible = 10

[[scores]]
question = 3
points_earned = 0
points_possible = 10

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

[[scores]]
question = 5
points_earned = 6
points_possible = 10

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

[[scores]]
question = 7
points_earned = 4
points_possible = 10

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

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

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

[[scores]]
question = 11
points_earned = 2
points_possible = 10


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

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

[Assistant]
Approach:
1. Task: Convert course syllabus 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:
code,course_id,credits,grading_final,grading_homework,grading_midterm,instructor,schedule,term,title
ESH384,CRS-9141,4,40,30,30,Matthew Boyd,"[{""week"": 1, ""topic"": ""western""}, {""week"": 2, ""topic"": ""since""}, {""week"": 3, ""topic"": ""later""}, {""we",Fall 2022,Inverse real-time hardware 101
JKU244,CRS-6370,3,40,30,30,Teresa Davis,"[{""week"": 1, ""topic"": ""nearly""}, {""week"": 2, ""topic"": ""base""}, {""week"": 3, ""topic"": ""already""}, {""we",Fall 2021,Reactive 4thgeneration parallelism 101
HEF399,CRS-4457,4,40,30,30,Alexander Dominguez,"[{""week"": 1, ""topic"": ""may""}, {""week"": 2, ""topic"": ""beat""}, {""week"": 3, ""topic"": ""find""}, {""week"": 4",Spring 2023,User-friendly 24hour customer loyalty 101
ZLN329,CRS-9809,3,40,30,30,Eddie Keller DDS,"[{""week"": 1, ""topic"": ""put""}, {""week"": 2, ""topic"": ""travel""}, {""week"": 3, ""topic"": ""he""}, {""week"": 4",Fall 2020,Enterprise-wide interactive orchestration 101


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

[User] Create a CSV representation of clinical note.

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

Output:
assessment,chief_complaint,encounter_date,note_id,patient_age,patient_gender,patient_mrn,vitals_bp,vitals_hr,vitals_temp_f
"[{""problem"": ""hypertension"", ""icd10"": ""I84""}, {""problem"": ""hypertension"", ""icd10"": ""J93""}]",fever,2026-01-04,CN-3041313,45,F,MRN-164256,153/76,98,102.6
"[{""problem"": ""hypertension"", ""icd10"": ""J61""}, {""problem"": ""hypertension"", ""icd10"": ""J73""}, {""problem",fever,2026-01-04,CN-9118958,22,M,MRN-715481,152/110,104,101.5
"[{""problem"": ""hypertension"", ""icd10"": ""I40""}, {""problem"": ""diabetes"", ""icd10"": ""I81""}, {""problem"": """,fever,2026-01-02,CN-1695362,88,F,MRN-680581,151/88,102,97.4
"[{""problem"": ""hypertension"", ""icd10"": ""I99""}]",headache,2026-01-03,CN-9479053,75,F,MRN-826265,131/90,71,100.8
"[{""problem"": ""hypertension"", ""icd10"": ""K57""}, {""problem"": ""hypertension"", ""icd10"": ""I93""}]",headache,2026-01-02,CN-5728651,81,M,MRN-273132,118/76,81,102.3


[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"?>
<student_assessment>
<assessment_id>ASMT-672485</assessment_id>
<student_id>STU-183204</student_id>
<course_id>CRS-8704</course_id>
<type>quiz</type>
<date>2026-01-01</date>
<scores>
<question>1</question>
<points_earned>0</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>3</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>10</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>8</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>7</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>7</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>5</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>11</question>
<points_earned>5</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>12</question>
<points_earned>0</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>82</total_score>
<percentage>72.48</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-672485",
  "student_id": "STU-183204",
  "course_id": "CRS-8704",
  "type": "quiz",
  "date": "2026-01-01",
  "scores": [
    {
      "question": 1,
      "points_earned": 0,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 10,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 9,
      "points_earned": 0,
      "points_possible": 10
    },
    {
      "question": 10,
      "points_earned": 5,
      "points_possible": 10
    },
    {
      "question": 11,
      "points_earned": 5,
      "points_possible": 10
    },
    {
      "question": 12,
      "points_earned": 0,
      "points_possible": 10
    }
  ],
  "total_score": 82,
  "percentage": 72.48,
  "grade": "A"
}


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

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

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

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


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

[User] Create a XML representation of news article.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<news_article>
<article_id>ART-2650245</article_id>
<headline>Enhanced multimedia hub</headline>
<author>Jennifer Davis</author>
<published>2026-01-02T17:44:08.333575</published>

Tech

<content>Late situation both data share market. These foot health box.
Pay me together western ever story cup. Game production million happy reveal. Attorney bill shake crime eat finally drive.
Choice four concern cold test. Road executive policy official season increase.</content>
<tags>future</tags>
<tags>here</tags>
<tags>new</tags>
<views>46115</views>
<shares>2819</shares>
</news_article>


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

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

[Assistant]
Approach:
1. Task: Convert error log 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"?>
<error_log>
<error_id>424897c8-d97d-4bfb-9c1a-7b6e63fd6096</error_id>
<timestamp>2026-01-07T13:51:27.529237</timestamp>
<level>ERROR</level>
<service>heartService</service>
<message>How these anyone stop indeed.</message>
<stack_trace>at manage.py:289</stack_trace>
<stack_trace>at thing.py:107</stack_trace>
<stack_trace>at guy.py:172</stack_trace>
<stack_trace>at seat.py:479</stack_trace>
<context>
<user_id>082cc3eb-3997-4d99-990c-f696ca4ee534</user_id>
<request_id>0f3326d0-3afd-48c1-9c4d-32cc8b0c5920</request_id>
</context>
</error_log>


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

[User] Generate lab result data in XML format.

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

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


[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-948175",
  "student_id": "STU-160858",
  "course_id": "CRS-5368",
  "type": "assignment",
  "date": "2026-01-03",
  "scores": [
    {
      "question": 1,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 2,
      "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": 1,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 3,
      "points_possible": 10
    },
    {
      "question": 9,
      "points_earned": 9,
      "points_possible": 10
    }
  ],
  "total_score": 89,
  "percentage": 96.29,
  "grade": "B"
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<student_assessment>
<assessment_id>ASMT-948175</assessment_id>
<student_id>STU-160858</student_id>
<course_id>CRS-5368</course_id>
<type>assignment</type>
<date>2026-01-03</date>
<scores>
<question>1</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>9</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>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>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>3</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>9</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>89</total_score>
<percentage>96.29</percentage>
<grade>B</grade>
</student_assessment>