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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<course_syllabus>
<course_id>CRS-4765</course_id>
VMZ479
<title>Exclusive grid-enabled software 101</title>
<instructor>Amy Baker</instructor>
<credits>4</credits>
<term>Fall 2022</term>
<schedule>
<week>1</week>
<topic>show</topic>
</schedule>
<schedule>
<week>2</week>
<topic>cut</topic>
</schedule>
<schedule>
<week>3</week>
<topic>next</topic>
</schedule>
<schedule>
<week>4</week>
<topic>everything</topic>
</schedule>
<schedule>
<week>5</week>
<topic>people</topic>
</schedule>
<schedule>
<week>6</week>
<topic>international</topic>
</schedule>
<schedule>
<week>7</week>
<topic>since</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-4765",
  "code": "VMZ479",
  "title": "Exclusive grid-enabled software 101",
  "instructor": "Amy Baker",
  "credits": 4,
  "term": "Fall 2022",
  "schedule": [
    {
      "week": 1,
      "topic": "show"
    },
    {
      "week": 2,
      "topic": "cut"
    },
    {
      "week": 3,
      "topic": "next"
    },
    {
      "week": 4,
      "topic": "everything"
    },
    {
      "week": 5,
      "topic": "people"
    },
    {
      "week": 6,
      "topic": "international"
    },
    {
      "week": 7,
      "topic": "since"
    }
  ],
  "grading": {
    "homework": 30,
    "midterm": 30,
    "final": 40
  }
}


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<prescription>
<rx_id>RX-7665793</rx_id>
<patient_mrn>MRN-934255</patient_mrn>
<prescriber>Danielle Brown</prescriber>
<date>2026-01-06</date>
<medications>
<name>Atorvastatin</name>
<dosage>20mg</dosage>
<frequency>daily</frequency>
<quantity>90</quantity>
</medications>
<medications>
<name>Atorvastatin</name>
<dosage>5mg</dosage>
<frequency>BID</frequency>
<quantity>90</quantity>
</medications>
<medications>
<name>Metformin</name>
<dosage>5mg</dosage>
<frequency>BID</frequency>
<quantity>60</quantity>
</medications>
</prescription>

[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-7665793",
  "patient_mrn": "MRN-934255",
  "prescriber": "Danielle Brown",
  "date": "2026-01-06",
  "medications": [
    {
      "name": "Atorvastatin",
      "dosage": "20mg",
      "frequency": "daily",
      "quantity": 90
    },
    {
      "name": "Atorvastatin",
      "dosage": "5mg",
      "frequency": "BID",
      "quantity": 90
    },
    {
      "name": "Metformin",
      "dosage": "5mg",
      "frequency": "BID",
      "quantity": 60
    }
  ]
}


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

[User] Generate news article data in YAML format.

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

Output:
article_id: ART-8846154
headline: Phased bifurcated instruction set
author: Melanie Kennedy
published: '2026-01-02T14:27:49.190328'
section: Sports
content: 'Edge wear coach whether dog sell respond. Claim feeling meeting somebody
  four real.

  Indeed use send represent leader require. Cup attack instead discuss. Plan with
  character rule.

  Information mind company even serve. Experience pattern but certain she design speech.'
tags:
- memory
- score
- game
- join
views: 47684
shares: 4081


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

[User] Generate transaction record data in XML format.

[Assistant]
Approach:
1. Task: Create transaction record 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"?>
<transaction_record>
<txn_id>TXN-28879814</txn_id>
<customer_id>b13e97b5-e84b-41ec-9dea-05b4809cdd35</customer_id>
<timestamp>2026-01-07T13:51:25.895711</timestamp>
<items>
<sku>SKU-36351</sku>
<qty>1</qty>
<price>310.41</price>
</items>
<items>
<sku>SKU-26629</sku>
<qty>2</qty>
<price>119.44</price>
</items>
<items>
<sku>SKU-75447</sku>
<qty>3</qty>
<price>127.79</price>
</items>
<items>
<sku>SKU-81003</sku>
<qty>3</qty>
<price>336.59</price>
</items>
<subtotal>994.66</subtotal>
<tax>143.59</tax>
<total>1762.36</total>
<payment_method>apple_pay</payment_method>
</transaction_record>


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

[User] Output customer review as CSV.

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

Output:
category,content,currency,date,helpful_votes,is_available,name,price,product_id,rating,review_id,reviews,specs_dimensions,specs_weight_kg,stock,title,user_id,verified_purchase
,Brother agent radio might own development. Too strong minute building why. Cell so amount imagine si,,2026-01-03,14,,,,PROD-380257,4,REV-1132090,,,,,Young race true property less government.,251dc214-da1e-4fb5-8ea5-d107ad43f82c,False
electronics,,USD,,,True,Virtual regional access,677.44,PROD-756803,4.63,,123,82x73x56cm,34.24,587,,,
clothing,,USD,,,True,Integrated next generation algorithm,993.52,PROD-874947,2.9,,76,75x54x61cm,40.61,176,,,


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

[User] Output financial report as CSV.

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

Output:
company,eps,expenses,metrics_profit_margin,metrics_roe,net_income,quarter,revenue,ticker
"Rodriguez, Curry and Yates",7.94,55129980,29.26,9.63,12179320,Q1 2020,4863925,KWAZ
"Winters, Gregory and Miller",6.66,61031502,20.44,17.94,17910722,Q3 2021,44845570,WCND
Moore-Michael,9.53,78343526,13.93,16.71,11975775,Q3 2024,14009061,WEPE
"King, Boone and Harrison",6.81,64588695,19.24,12.65,2044424,Q3 2020,98281853,ZHAH


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

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

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

Output:
assessment_id: ASMT-577861
student_id: STU-664280
course_id: CRS-8099
type: exam
date: '2026-01-06'
scores:
- question: 1
  points_earned: 7
  points_possible: 10
- question: 2
  points_earned: 0
  points_possible: 10
- question: 3
  points_earned: 5
  points_possible: 10
- question: 4
  points_earned: 6
  points_possible: 10
- question: 5
  points_earned: 3
  points_possible: 10
- question: 6
  points_earned: 0
  points_possible: 10
- question: 7
  points_earned: 1
  points_possible: 10
total_score: 52
percentage: 81.98
grade: B


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

[User] Create a TOML representation of transaction record.

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

Output:
txn_id = "TXN-85338602"
customer_id = "ea7970e3-49c7-4d3a-bbe0-6c539dc6c3d3"
timestamp = "2026-01-07T13:51:25.620781"
subtotal = 468.67
tax = 148.91
total = 792.01
payment_method = "apple_pay"
[[items]]
sku = "SKU-22630"
qty = 3
price = 89.97


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

[User] Produce a YAML document for a prescription.

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

Output:
rx_id: RX-8246470
patient_mrn: MRN-256913
prescriber: Victor Valentine
date: '2026-01-01'
medications:
- name: Lisinopril
  dosage: 20mg
  frequency: daily
  quantity: 30
- name: Lisinopril
  dosage: 10mg
  frequency: BID
  quantity: 60
- name: Lisinopril
  dosage: 5mg
  frequency: TID
  quantity: 30


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

[User] Create a YAML representation of research paper.

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

Output:
paper_id: arXiv:2023.54834
title: Profit-focused radical throughput
authors:
- name: Scott Dunlap
  affiliation: Daniels PLC
  email: williamssheri@example.com
- name: Shawn Payne
  affiliation: Dorsey, Price and Burns
  email: smoyer@example.net
- name: Chase Lee
  affiliation: Garcia Inc
  email: burgesssarah@example.org
abstract: 'Read deal buy final thus. Sure home game rest lose.

  Those any reality if teach.

  Main never still little study clearly today.'
keywords:
- measure
- stage
- scene
- reason
publication:
  venue: Science
  year: 2020
  doi: 10.8776/UhOT
citations: 388
funding_source: Reese-Perez


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

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

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

Output:
service: findService
stack_trace:
- at watch.py:197
- at body.py:298
- at girl.py:392
- at red.py:350
level: ERROR
message: Head then too threat drive.


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

[User] Output student assessment as TOML.

[Assistant]
Approach:
1. Task: Create student assessment 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:
assessment_id = "ASMT-852879"
student_id = "STU-517758"
course_id = "CRS-9070"
type = "exam"
date = "2026-01-04"
total_score = 58
percentage = 53.23
grade = "C"
[[scores]]
question = 1
points_earned = 4
points_possible = 10

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

[[scores]]
question = 3
points_earned = 1
points_possible = 10

[[scores]]
question = 4
points_earned = 2
points_possible = 10

[[scores]]
question = 5
points_earned = 7
points_possible = 10

[[scores]]
question = 6
points_earned = 4
points_possible = 10

[[scores]]
question = 7
points_earned = 3
points_possible = 10

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

[[scores]]
question = 9
points_earned = 7
points_possible = 10

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

[[scores]]
question = 11
points_earned = 6
points_possible = 10

[[scores]]
question = 12
points_earned = 8
points_possible = 10


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

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

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

Output:
error_id = "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]
Convert the following YAML to XML:
company: Rodriguez, Sanchez and French
ticker: TOPI
quarter: Q3 2022
revenue: 30596216
expenses: 79425858
net_income: 10739155
eps: 9.27
metrics:
  profit_margin: 21.79
  roe: 22.32

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<financial_report>
<company>Rodriguez, Sanchez and French</company>
<ticker>TOPI</ticker>
<quarter>Q3 2022</quarter>
<revenue>30596216</revenue>
<expenses>79425858</expenses>
<net_income>10739155</net_income>
<eps>9.27</eps>
<metrics>
<profit_margin>21.79</profit_margin>
<roe>22.32</roe>
</metrics>
</financial_report>


[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"?>
<sales_analytics>
<period>September 2022</period>
<total_revenue>4880286</total_revenue>
<units_sold>74173</units_sold>
<channels>
<name>retail</name>
<revenue>2000312</revenue>
<growth>0.96</growth>
</channels>
<channels>
<name>wholesale</name>
<revenue>3751658</revenue>
<growth>-3.19</growth>
</channels>
<top_products>
<sku>SKU-6977</sku>
<sales>264067</sales>
</top_products>
<top_products>
<sku>SKU-7032</sku>
<sales>443161</sales>
</top_products>
<top_products>
<sku>SKU-1793</sku>
<sales>209512</sales>
</top_products>
</sales_analytics>

[Assistant]
Approach:
1. Task: Convert sales analytics 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:
{
  "period": "September 2022",
  "total_revenue": 4880286,
  "units_sold": 74173,
  "channels": [
    {
      "name": "retail",
      "revenue": 2000312,
      "growth": 0.96
    },
    {
      "name": "wholesale",
      "revenue": 3751658,
      "growth": -3.19
    }
  ],
  "top_products": [
    {
      "sku": "SKU-6977",
      "sales": 264067
    },
    {
      "sku": "SKU-7032",
      "sales": 443161
    },
    {
      "sku": "SKU-1793",
      "sales": 209512
    }
  ]
}


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


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<experiment_result>
<experiment_id>EXP-734376</experiment_id>
<title>Effect of probably on skin</title>
<methodology>
<design>cohort</design>
<sample_size>800</sample_size>
<duration_days>273</duration_days>
</methodology>
<results>
<metric>efficacy</metric>
<baseline>94.92</baseline>
<endpoint>99.12</endpoint>
<p_value>0.3163</p_value>
</results>
<results>
<metric>safety</metric>
<baseline>43.8</baseline>
<endpoint>81.58</endpoint>
<p_value>0.1627</p_value>
</results>
<results>
<metric>efficacy</metric>
<baseline>31.59</baseline>
<endpoint>36.02</endpoint>
<p_value>0.4619</p_value>
</results>
<results>
<metric>efficacy</metric>
<baseline>82.54</baseline>
<endpoint>59.85</endpoint>
<p_value>0.3654</p_value>
</results>
<conclusion>significant</conclusion>
</experiment_result>


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

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

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

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


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

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

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


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

[User] Output student assessment as CSV.

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

Output:
assessment_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-744456,,CRS-3021,,2026-01-03,C,,,,,89.67,,"[{""question"": 1, ""points_earned"": 7, ""points_possible"": 10}, {""question"": 2, ""points_earned"": 2, ""po",STU-954920,,,97,exam
,GIH430,CRS-8635,3,,,40,30,30,Kimberly Farley,,"[{""week"": 1, ""topic"": ""scene""}, {""week"": 2, ""topic"": ""subject""}, {""week"": 3, ""topic"": ""around""}, {""w",,,Spring 2020,Future-proofed explicit parallelism 101,,
,ZWE316,CRS-2197,3,,,40,30,30,Jennifer Wright,,"[{""week"": 1, ""topic"": ""such""}, {""week"": 2, ""topic"": ""rise""}, {""week"": 3, ""topic"": ""as""}, {""week"": 4,",,,Fall 2021,Future-proofed asynchronous success 101,,


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

[User] Create a XML representation of sales analytics.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<sales_analytics>
<period>May 2020</period>
<total_revenue>534039</total_revenue>
<units_sold>34851</units_sold>
<channels>
<name>retail</name>
<revenue>707158</revenue>
<growth>43.16</growth>
</channels>
<channels>
<name>wholesale</name>
<revenue>2548868</revenue>
<growth>26.24</growth>
</channels>
<top_products>
<sku>SKU-6020</sku>
<sales>18280</sales>
</top_products>
<top_products>
<sku>SKU-3349</sku>
<sales>458703</sales>
</top_products>
<top_products>
<sku>SKU-8781</sku>
<sales>265385</sales>
</top_products>
</sales_analytics>


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

[User] Output research paper as CSV.

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

Output:
abstract,authors,citations,funding_source,keywords,paper_id,publication_doi,publication_venue,publication_year,title
Behavior skin nation pay behind remain. Then put again. Process participant current all.,"[{""name"": ""Todd Hall MD"", ""affiliation"": ""Nunez-Nguyen"", ""email"": ""grhodes@example.net""}, {""name"": """,194,None,"[""design"", ""him"", ""blue"", ""less"", ""fine""]",arXiv:2023.87771,10.6248/yEgY,Nature,2020,User-centric stable ability
Air guess power. Relationship blood respond smile begin report time.,"[{""name"": ""Sean Vasquez"", ""affiliation"": ""Parker-Odonnell"", ""email"": ""oliviawright@example.com""}, {""",358,Barnett-Lopez,"[""five"", ""up"", ""cold"", ""check""]",arXiv:2020.97251,10.2234/TyWg,Nature,2022,Synchronized attitude-oriented leverage
"Assume likely need if call bill also. Trade listen popular.
Away skin himself common suddenly.","[{""name"": ""Heather Willis"", ""affiliation"": ""Allen-Garza"", ""email"": ""osmith@example.com""}, {""name"": """,258,None,"[""mention"", ""music"", ""nothing""]",arXiv:2024.96155,10.3081/IzFq,Science,2021,Cross-platform explicit middleware


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

[User] Create a CSV representation of news article.

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

Output:
article_id,author,content,headline,published,section,shares,tags,views
ART-8846154,Melanie Kennedy,"Edge wear coach whether dog sell respond. Claim feeling meeting somebody four real.
Indeed use send ",Phased bifurcated instruction set,2026-01-02T14:27:49.190328,Sports,4081,"[""memory"", ""score"", ""game"", ""join""]",47684
ART-1589378,Joshua Mccarty,"Present large red note environmental. His summer necessary training. Usually fear miss far.
Main cha",Distributed intangible Internet solution,2026-01-05T13:21:22.467585,Sports,3582,"[""even"", ""down"", ""across""]",26524
ART-4357359,Todd Fisher,Finish relationship story. Pass true appear continue turn want down. Speak direction around company ,Optimized upward-trending moderator,2026-01-06T00:29:04.008895,Politics,3411,"[""subject"", ""sometimes"", ""difficult"", ""change""]",22849
ART-7347226,Douglas Cox,"Specific enjoy each trade.
Hospital yet himself as. Coach land soldier you stage look federal. Movie",Universal dedicated throughput,2026-01-03T22:33:33.827043,Sports,2304,"[""everyone"", ""food"", ""late"", ""only""]",95174


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

[User]
Transform this JSON data into XML format:
{
  "result_id": "LAB-3941350",
  "patient_mrn": "MRN-739958",
  "order_date": "2026-01-01",
  "panel": "CBC",
  "results": [
    {
      "test": "Glucose",
      "value": 134.1,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "WBC",
      "value": 188.7,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "Hemoglobin",
      "value": 142.9,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "Hemoglobin",
      "value": 117.3,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "Glucose",
      "value": 159.8,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "WBC",
      "value": 131.5,
      "unit": "g/dL",
      "flag": "normal"
    }
  ]
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<lab_result>
<result_id>LAB-3941350</result_id>
<patient_mrn>MRN-739958</patient_mrn>
<order_date>2026-01-01</order_date>
<panel>CBC</panel>
<results>
<test>Glucose</test>
<value>134.1</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>WBC</test>
<value>188.7</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>142.9</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>117.3</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Glucose</test>
<value>159.8</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>WBC</test>
<value>131.5</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
</lab_result>


[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-39289028",
  "platform": "instagram",
  "user_id": "a2301bd9-5c11-406a-b2a8-1c1f96bbd31c",
  "username": "rhodessharon",
  "content": "City window data describe address street. Environmental wall shoulder happy artist forget hospital. Chair their before reach picture serve.",
  "timestamp": "2026-01-07T13:51:26.862472",
  "hashtags": [
    "#yet",
    "#listen"
  ],
  "engagement": {
    "likes": 2391,
    "shares": 751,
    "comments": 108
  }
}

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


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

[User] Create a TOML representation of lab result.

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

Output:
result_id = "LAB-2604144"
patient_mrn = "MRN-906692"
order_date = "2026-01-01"
panel = "Lipid"
[[results]]
test = "Hemoglobin"
value = 180.3
unit = "mg/dL"
flag = "high"

[[results]]
test = "Glucose"
value = 97.8
unit = "mg/dL"
flag = "normal"

[[results]]
test = "Glucose"
value = 88.1
unit = "g/dL"
flag = "high"

[[results]]
test = "Glucose"
value = 65.1
unit = "mg/dL"
flag = "high"

[[results]]
test = "Hemoglobin"
value = 95.1
unit = "g/dL"
flag = "high"

[[results]]
test = "Glucose"
value = 86.1
unit = "mg/dL"
flag = "low"

[[results]]
test = "Hemoglobin"
value = 152.8
unit = "mg/dL"
flag = "normal"


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

[User] Create a YAML representation of clinical note.

[Assistant]
Approach:
1. Task: Create clinical note 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:
note_id: CN-8348908
patient:
  mrn: MRN-109351
  age: 84
  gender: F
encounter_date: '2026-01-06'
chief_complaint: fever
vitals:
  bp: 157/81
  hr: 101
  temp_f: 97.1
assessment:
- problem: diabetes
  icd10: J60
- problem: diabetes
  icd10: K69
- problem: hypertension
  icd10: J80


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

[User] Output error log as CSV.

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

Output:
abstract,authors,citations,context_request_id,context_user_id,error_id,funding_source,keywords,level,message,paper_id,publication_doi,publication_venue,publication_year,service,stack_trace,timestamp,title
,,,b35b2bd7-dc59-4d80-ba5d-dc21fa7f0bf7,d753ac0c-8931-4c37-8bd5-01413aaaba41,fd278ff8-fdfc-4b1d-81ec-31cf5ce70502,,,ERROR,Attack candidate in give wish tree.,,,,,heartService,"[""at thousand.py:354"", ""at forget.py:20"", ""at consider.py:392""]",2026-01-07T13:51:26.554266,
Tell treat forward conference level religious. Pick anyone huge be.,"[{""name"": ""Sandra Diaz"", ""affiliation"": ""Miller, Jimenez and Chapman"", ""email"": ""brandon49@example.c",207,,,,Roman-Martinez,"[""size"", ""Democrat"", ""final"", ""opportunity"", ""various""]",,,arXiv:2022.52852,10.6006/bbQM,Nature,2022,,,,Intuitive web-enabled utilization
"Detail what note pay.
Cut among artist drive away evidence.
Result low southern within yeah differen","[{""name"": ""Debra Flores"", ""affiliation"": ""Wright LLC"", ""email"": ""peter57@example.org""}, {""name"": ""Ju",440,,,,Tyler-Thomas,"[""thousand"", ""explain"", ""how"", ""give"", ""responsibility""]",,,arXiv:2021.84700,10.4898/XJFH,Cell,2024,,,,Configurable systemic artificial intelligence
"Six good generation account. Major not bar blue enter else support.
Which religious tend month telev","[{""name"": ""Dana Blankenship"", ""affiliation"": ""Cunningham-Williams"", ""email"": ""vmartin@example.net""},",495,,,,None,"[""play"", ""throw"", ""whole"", ""still"", ""land""]",,,arXiv:2024.43912,10.9920/PJFL,Science,2024,,,,Public-key foreground hardware


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

[User]
Transform this JSON data into CSV format:
{
  "txn_id": "TXN-85338602",
  "customer_id": "ea7970e3-49c7-4d3a-bbe0-6c539dc6c3d3",
  "timestamp": "2026-01-07T13:51:25.620781",
  "items": [
    {
      "sku": "SKU-22630",
      "qty": 3,
      "price": 89.97
    }
  ],
  "subtotal": 468.67,
  "tax": 148.91,
  "total": 792.01,
  "payment_method": "apple_pay"
}

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

Output:
customer_id,items,payment_method,subtotal,tax,timestamp,total,txn_id
ea7970e3-49c7-4d3a-bbe0-6c539dc6c3d3,"[{""sku"": ""SKU-22630"", ""qty"": 3, ""price"": 89.97}]",apple_pay,468.67,148.91,2026-01-07T13:51:25.620781,792.01,TXN-85338602
a37edfa3-5645-4583-a20a-67b9e8b49d68,"[{""sku"": ""SKU-17068"", ""qty"": 2, ""price"": 287.87}]",credit_card,394.17,7.91,2026-01-07T13:51:25.621933,1055.34,TXN-38529500
4006be7a-72db-42ea-ae10-8dbc41c96dde,"[{""sku"": ""SKU-48833"", ""qty"": 3, ""price"": 241.36}]",apple_pay,1172.69,77.01,2026-01-07T13:51:25.621974,1914.48,TXN-54206477
11c778fd-d168-42bc-a1ce-d773dfedc804,"[{""sku"": ""SKU-21722"", ""qty"": 1, ""price"": 480.74}, {""sku"": ""SKU-59910"", ""qty"": 1, ""price"": 339.81}, {",credit_card,507.4,5.04,2026-01-07T13:51:25.622008,264.18,TXN-31515746
03826a18-809e-44c2-93c8-9bc15374fc0c,"[{""sku"": ""SKU-19075"", ""qty"": 4, ""price"": 319.47}, {""sku"": ""SKU-18268"", ""qty"": 1, ""price"": 67.12}, {""",credit_card,455.63,77.85,2026-01-07T13:51:25.622052,1810.41,TXN-80826527


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

[User]
Reformat the data below from JSON to XML:
{
  "txn_id": "TXN-20904368",
  "customer_id": "3fe35528-f72a-4e45-bcf8-f7cb059fe7e5",
  "timestamp": "2026-01-07T13:51:27.778783",
  "items": [
    {
      "sku": "SKU-59380",
      "qty": 2,
      "price": 447.63
    },
    {
      "sku": "SKU-56357",
      "qty": 4,
      "price": 130.56
    },
    {
      "sku": "SKU-96740",
      "qty": 2,
      "price": 230.78
    },
    {
      "sku": "SKU-55928",
      "qty": 1,
      "price": 169.07
    }
  ],
  "subtotal": 1853.52,
  "tax": 74.51,
  "total": 1419.49,
  "payment_method": "apple_pay"
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<transaction_record>
<txn_id>TXN-20904368</txn_id>
<customer_id>3fe35528-f72a-4e45-bcf8-f7cb059fe7e5</customer_id>
<timestamp>2026-01-07T13:51:27.778783</timestamp>
<items>
<sku>SKU-59380</sku>
<qty>2</qty>
<price>447.63</price>
</items>
<items>
<sku>SKU-56357</sku>
<qty>4</qty>
<price>130.56</price>
</items>
<items>
<sku>SKU-96740</sku>
<qty>2</qty>
<price>230.78</price>
</items>
<items>
<sku>SKU-55928</sku>
<qty>1</qty>
<price>169.07</price>
</items>
<subtotal>1853.52</subtotal>
<tax>74.51</tax>
<total>1419.49</total>
<payment_method>apple_pay</payment_method>
</transaction_record>


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

[User] Generate course syllabus data in JSON format.

[Assistant]
Approach:
1. Task: Create course syllabus in JSON
2. Complexity: 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:
{
  "course_id": "CRS-4513",
  "code": "NEE477",
  "title": "Exclusive bottom-line artificial intelligence 101",
  "instructor": "Jaime Roman",
  "credits": 3,
  "term": "Spring 2022",
  "schedule": [
    {
      "week": 1,
      "topic": "marriage"
    },
    {
      "week": 2,
      "topic": "wonder"
    },
    {
      "week": 3,
      "topic": "system"
    },
    {
      "week": 4,
      "topic": "order"
    },
    {
      "week": 5,
      "topic": "very"
    },
    {
      "week": 6,
      "topic": "laugh"
    },
    {
      "week": 7,
      "topic": "practice"
    },
    {
      "week": 8,
      "topic": "sister"
    },
    {
      "week": 9,
      "topic": "join"
    },
    {
      "week": 10,
      "topic": "expect"
    }
  ],
  "grading": {
    "homework": 30,
    "midterm": 30,
    "final": 40
  }
}


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

[User]
Reformat the data below from JSON to XML:
{
  "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"
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<student_assessment>
<assessment_id>ASMT-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>


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

[User] Create a TOML representation of error log.

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


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

[User] Create a YAML representation of experiment result.

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

Output:
experiment_id: EXP-725280
title: Effect of city on expert
methodology:
  design: observational
  sample_size: 907
  duration_days: 166
results:
- metric: safety
  baseline: 43.19
  endpoint: 64.81
  p_value: 0.4813
- metric: safety
  baseline: 71.73
  endpoint: 68.14
  p_value: 0.0851
- metric: safety
  baseline: 77.12
  endpoint: 63.9
  p_value: 0.1154
conclusion: significant


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

[User]
Transform this TOML data into JSON format:
error_id = "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"

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

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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<sales_analytics>
<period>March 2022</period>
<total_revenue>2472943</total_revenue>
<units_sold>2053</units_sold>
<channels>
<name>wholesale</name>
<revenue>3703587</revenue>
<growth>38.49</growth>
</channels>
<channels>
<name>retail</name>
<revenue>3200920</revenue>
<growth>-8.82</growth>
</channels>
<top_products>
<sku>SKU-8959</sku>
<sales>220308</sales>
</top_products>
<top_products>
<sku>SKU-7189</sku>
<sales>206126</sales>
</top_products>
<top_products>
<sku>SKU-5359</sku>
<sales>225947</sales>
</top_products>
</sales_analytics>

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

Output:
{
  "period": "March 2022",
  "total_revenue": 2472943,
  "units_sold": 2053,
  "channels": [
    {
      "name": "wholesale",
      "revenue": 3703587,
      "growth": 38.49
    },
    {
      "name": "retail",
      "revenue": 3200920,
      "growth": -8.82
    }
  ],
  "top_products": [
    {
      "sku": "SKU-8959",
      "sales": 220308
    },
    {
      "sku": "SKU-7189",
      "sales": 206126
    },
    {
      "sku": "SKU-5359",
      "sales": 225947
    }
  ]
}


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

[User]
Reformat the data below from YAML to TOML:
period: March 2022
total_revenue: 2472943
units_sold: 2053
channels:
- name: wholesale
  revenue: 3703587
  growth: 38.49
- name: retail
  revenue: 3200920
  growth: -8.82
top_products:
- sku: SKU-8959
  sales: 220308
- sku: SKU-7189
  sales: 206126
- sku: SKU-5359
  sales: 225947

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

Output:
period = "March 2022"
total_revenue = 2472943
units_sold = 2053
[[channels]]
name = "wholesale"
revenue = 3703587
growth = 38.49

[[channels]]
name = "retail"
revenue = 3200920
growth = -8.82

[[top_products]]
sku = "SKU-8959"
sales = 220308

[[top_products]]
sku = "SKU-7189"
sales = 206126

[[top_products]]
sku = "SKU-5359"
sales = 225947


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

[User] Create a TOML representation of financial report.

[Assistant]
Approach:
1. Task: Create financial report in TOML
2. Complexity: 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:
company = "Thompson LLC"
ticker = "QQLN"
quarter = "Q2 2020"
revenue = 63838743
expenses = 967762
net_income = 16633381
eps = 0.69

[metrics]
profit_margin = 22.56
roe = 23.58


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

[User]
Transform this YAML data into JSON format:
title: Polarized methodical algorithm
authors:
- name: Caroline Barnes
  affiliation: Parker Ltd
  email: angelajackson@example.net
- name: Mario Boyd
  affiliation: Johnson, Barber and Higgins
  email: lfuller@example.com
funding_source: null

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

Output:
{
  "title": "Polarized methodical algorithm",
  "authors": [
    {
      "name": "Caroline Barnes",
      "affiliation": "Parker Ltd",
      "email": "angelajackson@example.net"
    },
    {
      "name": "Mario Boyd",
      "affiliation": "Johnson, Barber and Higgins",
      "email": "lfuller@example.com"
    }
  ],
  "funding_source": null
}


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

[User] Generate sales analytics data in CSV format.

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

Output:
abstract,authors,channels,citations,funding_source,keywords,paper_id,period,publication_doi,publication_venue,publication_year,title,top_products,total_revenue,units_sold
,,"[{""name"": ""wholesale"", ""revenue"": 2975287, ""growth"": -1.88}, {""name"": ""online"", ""revenue"": 2665464, ",,,,,June 2021,,,,,"[{""sku"": ""SKU-1172"", ""sales"": 348860}, {""sku"": ""SKU-4431"", ""sales"": 479568}, {""sku"": ""SKU-6244"", ""sa",1467254,63744
Place your cold visit student main. Manage bed relationship simple stay play thought. Sea leader tel,"[{""name"": ""Amy Wood"", ""affiliation"": ""Riley-Jones"", ""email"": ""aprilwoods@example.com""}, {""name"": ""Am",,202,None,"[""deep"", ""impact"", ""discussion"", ""smile""]",arXiv:2020.65454,,10.1876/SEmK,Cell,2021,Proactive asynchronous encoding,,,
Out still reality room system hair. Bank long turn production day. Almost arrive trip agent.,"[{""name"": ""Samuel Johnson"", ""affiliation"": ""Barrera, Romero and Mills"", ""email"": ""davidcampbell@exam",,124,None,"[""key"", ""tonight"", ""very""]",arXiv:2023.91779,,10.7790/Catx,Science,2021,Versatile well-modulated Local Area Network,,,


[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:
{
  "product_id": "PROD-480886",
  "name": "Operative optimizing monitoring",
  "category": "books",
  "price": 967.35,
  "currency": "USD",
  "stock": 887,
  "is_available": true,
  "rating": 2.99,
  "reviews": 465,
  "specs": {
    "weight_kg": 39.19,
    "dimensions": "82x84x37cm"
  }
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<product_listing>
<product_id>PROD-480886</product_id>
<name>Operative optimizing monitoring</name>
<category>books</category>
<price>967.35</price>
<currency>USD</currency>
<stock>887</stock>
<is_available>True</is_available>
<rating>2.99</rating>
<reviews>465</reviews>
<specs>
<weight_kg>39.19</weight_kg>
<dimensions>82x84x37cm</dimensions>
</specs>
</product_listing>


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

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

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

Output:
{
  "paper_id": "arXiv:2024.66116",
  "title": "Quality-focused grid-enabled service-desk",
  "authors": [
    {
      "name": "David Cohen",
      "affiliation": "Lopez and Sons",
      "email": "mark98@example.com"
    },
    {
      "name": "Ashley Spencer",
      "affiliation": "Hood Ltd",
      "email": "pbailey@example.org"
    },
    {
      "name": "Robin Lynch",
      "affiliation": "Camacho, Nelson and Perez",
      "email": "samantha44@example.net"
    }
  ],
  "abstract": "Body exactly last operation trouble. Financial whole check management chance eat us. Likely wrong explain by would born only.",
  "keywords": [
    "rather",
    "hair",
    "attorney",
    "chance",
    "bring"
  ],
  "publication": {
    "venue": "Cell",
    "year": 2020,
    "doi": "10.7468/EeJM"
  },
  "citations": 174,
  "funding_source": null
}


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

[User] Generate news article data in XML format.

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

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

Politics

<tags>machine</tags>
<tags>fund</tags>
<tags>station</tags>
<tags>our</tags>
<published>2026-01-05T17:58:55.100855</published>
<views>86295</views>
</news_article>


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

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

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

Output:
post_id: POST-66277640
platform: instagram
user_id: 7e83a029-16e2-49ad-a855-906c882abe46
username: reynoldstaylor
content: 'Thousand book animal myself wear beautiful. Room rock couple reality her.

  Join town travel agency value improve way. Heavy late science mind develop consider
  ability.'
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 YAML format. Think step-by-step, then generate syntactically perfect YAML.

[User]
Reformat the data below from TOML to YAML:
review_id = "REV-9529513"
product_id = "PROD-542599"
user_id = "67bb80c4-7c72-4c1b-886f-8186f18f45e3"
rating = 3
title = "Money face statement talk day."
content = "Candidate stuff mission end nature hundred. Recently game stage agreement. Seem central blood add environment several.\nSet less job reveal protect. Similar second staff owner international major."
date = "2026-01-01"
verified_purchase = true
helpful_votes = 8

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

Output:
review_id: REV-9529513
product_id: PROD-542599
user_id: 67bb80c4-7c72-4c1b-886f-8186f18f45e3
rating: 3
title: Money face statement talk day.
content: 'Candidate stuff mission end nature hundred. Recently game stage agreement.
  Seem central blood add environment several.

  Set less job reveal protect. Similar second staff owner international major.'
date: '2026-01-01'
verified_purchase: true
helpful_votes: 8


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

[User] Output financial report as JSON.

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

Output:
{
  "company": "Richard Ltd",
  "ticker": "XHCL",
  "quarter": "Q4 2020",
  "revenue": 71255223,
  "expenses": 54916122,
  "net_income": 1190834,
  "eps": 4.63,
  "metrics": {
    "profit_margin": 14.39,
    "roe": 19.33
  }
}


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

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

[Assistant]
Approach:
1. Task: Create financial report 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:
company: Richard Ltd
ticker: XHCL
quarter: Q4 2020
revenue: 71255223
expenses: 54916122
net_income: 1190834
eps: 4.63
metrics:
  profit_margin: 14.39
  roe: 19.33


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

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

[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>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>


[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:
{
  "company": "Brooks LLC",
  "ticker": "HFOB",
  "quarter": "Q1 2020",
  "revenue": 30917299,
  "expenses": 61265128,
  "net_income": 10426094,
  "eps": 3.56,
  "metrics": {
    "profit_margin": 26.89,
    "roe": 20.49
  }
}

[Assistant]
Approach:
1. Task: Convert financial report 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"?>
<financial_report>
<company>Brooks LLC</company>
<ticker>HFOB</ticker>
<quarter>Q1 2020</quarter>
<revenue>30917299</revenue>
<expenses>61265128</expenses>
<net_income>10426094</net_income>
<eps>3.56</eps>
<metrics>
<profit_margin>26.89</profit_margin>
<roe>20.49</roe>
</metrics>
</financial_report>


[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-480886</product_id>
<name>Operative optimizing monitoring</name>
<category>books</category>
<price>967.35</price>
<currency>USD</currency>
<stock>887</stock>
<is_available>True</is_available>
<rating>2.99</rating>
<reviews>465</reviews>
<specs>
<weight_kg>39.19</weight_kg>
<dimensions>82x84x37cm</dimensions>
</specs>
</product_listing>

[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-480886",
  "name": "Operative optimizing monitoring",
  "category": "books",
  "price": 967.35,
  "currency": "USD",
  "stock": 887,
  "is_available": true,
  "rating": 2.99,
  "reviews": 465,
  "specs": {
    "weight_kg": 39.19,
    "dimensions": "82x84x37cm"
  }
}


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

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

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


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

[User] Output research paper as CSV.

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

Output:
abstract,authors,citations,funding_source,keywords,paper_id,publication_doi,publication_venue,publication_year,title
Body exactly last operation trouble. Financial whole check management chance eat us. Likely wrong ex,"[{""name"": ""David Cohen"", ""affiliation"": ""Lopez and Sons"", ""email"": ""mark98@example.com""}, {""name"": """,174,None,"[""rather"", ""hair"", ""attorney"", ""chance"", ""bring""]",arXiv:2024.66116,10.7468/EeJM,Cell,2020,Quality-focused grid-enabled service-desk
Expert just pretty hair investment. Culture spring style give stuff possible some. Economy computer ,"[{""name"": ""Sandra Hooper"", ""affiliation"": ""Jensen Ltd"", ""email"": ""leslie48@example.com""}, {""name"": """,345,None,"[""last"", ""almost"", ""job"", ""sign"", ""down""]",arXiv:2021.40455,10.5292/iAxh,Science,2021,Persevering mobile software
Coach personal class appear country whom place. Fill paper build appear for.,"[{""name"": ""Christine Brown"", ""affiliation"": ""Beck, Scott and Mcintosh"", ""email"": ""jacobpratt@example",301,None,"[""purpose"", ""dark"", ""should"", ""hold""]",arXiv:2023.16319,10.3987/Ampj,Cell,2020,Progressive system-worthy core
Field indicate pattern make billion should area decide. Down here answer you. Everyone although low ,"[{""name"": ""Margaret Hernandez"", ""affiliation"": ""Wheeler, Jones and Mckinney"", ""email"": ""kathy56@exam",298,None,"[""instead"", ""rate"", ""teacher"", ""above"", ""know""]",arXiv:2022.56148,10.8232/sKnC,Cell,2022,Open-architected real-time orchestration


[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"?>
<social_media_post>
<post_id>POST-90196326</post_id>
<platform>facebook</platform>
<user_id>146c178d-e548-4357-8cd4-e8464cea2f9b</user_id>
<username>kevincunningham</username>
<content>Three would identify method across operation opportunity.
What realize number. Country perform simple team player. Improve order east mother news magazine trade.
Central thus simple thousand morning.</content>
<timestamp>2026-01-07T13:51:26.698310</timestamp>
<hashtags>#pay</hashtags>
<hashtags>#keep</hashtags>
<engagement>
<likes>458</likes>
<shares>383</shares>
<comments>63</comments>
</engagement>
</social_media_post>

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

Output:
{
  "post_id": "POST-90196326",
  "platform": "facebook",
  "user_id": "146c178d-e548-4357-8cd4-e8464cea2f9b",
  "username": "kevincunningham",
  "content": "Three would identify method across operation opportunity.\nWhat realize number. Country perform simple team player. Improve order east mother news magazine trade.\nCentral thus simple thousand morning.",
  "timestamp": "2026-01-07T13:51:26.698310",
  "hashtags": [
    "#pay",
    "#keep"
  ],
  "engagement": {
    "likes": 458,
    "shares": 383,
    "comments": 63
  }
}


[System] You are an expert in 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"?>
<prescription>
<rx_id>RX-2317847</rx_id>
<patient_mrn>MRN-412331</patient_mrn>
<prescriber>Tammy Adams</prescriber>
<date>2026-01-01</date>
<medications>
<name>Lisinopril</name>
<dosage>10mg</dosage>
<frequency>BID</frequency>
<quantity>60</quantity>
</medications>
<medications>
<name>Lisinopril</name>
<dosage>10mg</dosage>
<frequency>BID</frequency>
<quantity>90</quantity>
</medications>
<medications>
<name>Atorvastatin</name>
<dosage>5mg</dosage>
<frequency>BID</frequency>
<quantity>30</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-2317847",
  "patient_mrn": "MRN-412331",
  "prescriber": "Tammy Adams",
  "date": "2026-01-01",
  "medications": [
    {
      "name": "Lisinopril",
      "dosage": "10mg",
      "frequency": "BID",
      "quantity": 60
    },
    {
      "name": "Lisinopril",
      "dosage": "10mg",
      "frequency": "BID",
      "quantity": 90
    },
    {
      "name": "Atorvastatin",
      "dosage": "5mg",
      "frequency": "BID",
      "quantity": 30
    }
  ]
}


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

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

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

Output:
content,engagement_comments,engagement_likes,engagement_shares,hashtags,platform,post_id,timestamp,user_id,username
Use Mr only week. Crime form attention. Right world stand surface rate three.,4,9998,653,"[""#economic"", ""#speak""]",instagram,POST-64636774,2026-01-07T13:51:26.942814,180a1898-015f-483f-94a7-e771a6fb148e,melissa16
"Writer federal successful clear off customer. Season sea from first production might.
Word accept jo",335,511,57,"[""#why"", ""#person"", ""#hair"", ""#report""]",instagram,POST-70210719,2026-01-07T13:51:26.944069,66a30fd9-2e5b-4aee-b36c-f8023b183634,rmorrison
Message practice long eight course pretty try business. Thing school price black matter worker offic,93,6048,277,"[""#dinner"", ""#property"", ""#Congress""]",facebook,POST-57430305,2026-01-07T13:51:26.944466,c1cc934d-97e2-4193-b2a4-e9aa13791883,ashleyshepard
"Anyone though them she our. Table open camera raise.
Very measure thus fish must audience exist. Pro",233,2899,835,"[""#strategy"", ""#design"", ""#experience"", ""#win""]",twitter,POST-92749855,2026-01-07T13:51:26.944789,c7caaaa1-ad49-41d4-85b9-4891e07c47cc,ohawkins


[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-9529513
product_id: PROD-542599
user_id: 67bb80c4-7c72-4c1b-886f-8186f18f45e3
rating: 3
title: Money face statement talk day.
content: 'Candidate stuff mission end nature hundred. Recently game stage agreement.
  Seem central blood add environment several.

  Set less job reveal protect. Similar second staff owner international major.'
date: '2026-01-01'
verified_purchase: true
helpful_votes: 8


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

[User] Create a TOML representation of experiment result.

[Assistant]
Approach:
1. Task: Create experiment 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:
experiment_id = "EXP-168652"
title = "Effect of green on from"
conclusion = "non-significant"
[[results]]
metric = "safety"
baseline = 24.16
endpoint = 44.82
p_value = 0.0559

[[results]]
metric = "efficacy"
baseline = 16.54
endpoint = 28.48
p_value = 0.2997

[methodology]
design = "cohort"
sample_size = 797
duration_days = 186


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

[User] Output clinical note as YAML.

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

Output:
vitals:
  bp: 131/104
  hr: 84
  temp_f: 99.9
note_id: CN-3823498
encounter_date: '2026-01-06'


[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: 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:
order_date = "2026-01-05"
panel = "Lipid"
[[results]]
test = "Hemoglobin"
value = 95.5
unit = "g/dL"
flag = "low"

[[results]]
test = "Hemoglobin"
value = 52.7
unit = "mg/dL"
flag = "high"

[[results]]
test = "Glucose"
value = 142.9
unit = "mg/dL"
flag = "low"

[[results]]
test = "Glucose"
value = 146.5
unit = "mg/dL"
flag = "high"


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<api_specification>
<openapi>3.0.0</openapi>
<paths>
</somebody>
<get>
<summary>Threat common organization project.</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>
<//somebody>
</paths>
<info>
<title>Networked system-worthy project API</title>
<version>1.0.0</version>
</info>
</api_specification>

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

Output:
{
  "openapi": "3.0.0",
  "paths": {
    "/somebody": {
      "get": {
        "summary": "Threat common organization project.",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          },
          {
            "name": "param1",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  },
  "info": {
    "title": "Networked system-worthy project API",
    "version": "1.0.0"
  }
}


[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"?>
<product_listing>
<product_id>PROD-791864</product_id>
<name>Decentralized heuristic migration</name>
<category>books</category>
<price>124.58</price>
<currency>USD</currency>
<stock>601</stock>
<is_available>True</is_available>
<rating>3.59</rating>
<reviews>538</reviews>
<specs>
<weight_kg>9.83</weight_kg>
<dimensions>30x16x25cm</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-791864",
  "name": "Decentralized heuristic migration",
  "category": "books",
  "price": 124.58,
  "currency": "USD",
  "stock": 601,
  "is_available": true,
  "rating": 3.59,
  "reviews": 538,
  "specs": {
    "weight_kg": 9.83,
    "dimensions": "30x16x25cm"
  }
}


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

[User] Generate clinical note data in TOML format.

[Assistant]
Approach:
1. Task: Create clinical note in TOML
2. Complexity: 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:
note_id = "CN-3759937"

[patient]
mrn = "MRN-802088"
age = 30
gender = "M"

[vitals]
bp = "119/74"
hr = 67
temp_f = 100.9


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

[User] Generate prescription data in CSV format.

[Assistant]
Approach:
1. Task: Create prescription 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:
date,medications,patient_mrn,prescriber,rx_id
2026-01-01,"[{""name"": ""Atorvastatin"", ""dosage"": ""5mg"", ""frequency"": ""daily"", ""quantity"": 30}]",MRN-461250,Zachary Berry,RX-9036427
2026-01-06,"[{""name"": ""Lisinopril"", ""dosage"": ""20mg"", ""frequency"": ""BID"", ""quantity"": 30}]",MRN-382426,Angela Dean,RX-5066446
2026-01-05,"[{""name"": ""Lisinopril"", ""dosage"": ""5mg"", ""frequency"": ""BID"", ""quantity"": 90}, {""name"": ""Atorvastatin",MRN-797304,Adam Rhodes,RX-6899420
2026-01-04,"[{""name"": ""Lisinopril"", ""dosage"": ""20mg"", ""frequency"": ""daily"", ""quantity"": 30}]",MRN-585952,Clinton Barber,RX-1654491


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

[User] Output lab result as JSON.

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

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


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

[User] Create a YAML representation of news article.

[Assistant]
Approach:
1. Task: Create news article in YAML
2. Complexity: 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:
article_id: ART-6180455
headline: Grass-roots multi-tasking hub
author: David Espinoza
published: '2026-01-07T13:20:10.771283'
section: Politics
content: 'Either large lot east. Show everybody away city election happy my. Believe
  left sure mother.

  Whom game determine road little. Sing this character. Agent fill kitchen themselves
  agreement.

  Woman draw budget stage. Star cultural old president where national success.'
tags:
- size
- commercial
- president
- city
- expect
views: 43396
shares: 2564


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

[User] Generate sales analytics data in TOML format.

[Assistant]
Approach:
1. Task: Create sales analytics in TOML
2. Complexity: 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:
total_revenue = 6798538
[[channels]]
name = "online"
revenue = 2139770
growth = -9.99

[[channels]]
name = "retail"
revenue = 1809716
growth = 7.01

[[top_products]]
sku = "SKU-3049"
sales = 22854

[[top_products]]
sku = "SKU-5505"
sales = 203281

[[top_products]]
sku = "SKU-9853"
sales = 260538


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

[User] Create a YAML representation of lab result.

[Assistant]
Approach:
1. Task: Create lab result in YAML
2. Complexity: 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-5796495
patient_mrn: MRN-496025
order_date: '2026-01-06'
panel: Lipid
results:
- test: Hemoglobin
  value: 74.9
  unit: g/dL
  flag: low
- test: Hemoglobin
  value: 68.3
  unit: mg/dL
  flag: low
- test: WBC
  value: 121.2
  unit: mg/dL
  flag: normal
- test: Hemoglobin
  value: 142.6
  unit: g/dL
  flag: normal


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

[User] Create a TOML representation of 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 = "Pre-emptive interactive encryption API"
version = "1.0.0"

[paths."/air".get]
summary = "Final democratic whatever event director guy."
[[paths."/air".get.parameters]]
name = "param0"
in = "query"
type = "string"

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

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


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

[User] Output news article as YAML.

[Assistant]
Approach:
1. Task: Create news article 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:
article_id: ART-3281345
headline: Streamlined object-oriented toolset
author: James Dunn
published: '2026-01-03T08:23:33.060508'
section: Politics
content: 'Win take among professor. Glass reflect black similar future. Risk than
  tree.

  Economic sit plan. Available then already skill up reason back. Course his threat
  growth physical parent truth.

  Laugh article pull goal. Believe those few.'
tags:
- hit
- summer
- official
- rather
views: 75669
shares: 293


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

[User] Generate transaction record data in CSV format.

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

Output:
customer_id,items,payment_method,subtotal,tax,timestamp,total,txn_id
681a59bc-1151-4d49-8e75-1af0878315cb,"[{""sku"": ""SKU-50616"", ""qty"": 3, ""price"": 180.94}, {""sku"": ""SKU-82812"", ""qty"": 5, ""price"": 490.31}]",credit_card,948.16,93.65,2026-01-07T13:51:26.087659,1389.7,TXN-98000345
dc509191-62a7-44ae-a2ab-da6cec5f8979,"[{""sku"": ""SKU-22697"", ""qty"": 2, ""price"": 448.84}, {""sku"": ""SKU-56792"", ""qty"": 5, ""price"": 381.22}]",apple_pay,702.77,170.87,2026-01-07T13:51:26.088644,1080.03,TXN-11419070
28deb733-3707-49e4-ba0a-6dd69946ff62,"[{""sku"": ""SKU-12511"", ""qty"": 3, ""price"": 86.7}, {""sku"": ""SKU-20037"", ""qty"": 1, ""price"": 221.54}]",paypal,1272.6,154.45,2026-01-07T13:51:26.088726,1509.73,TXN-59684037
e0045088-d8a1-49df-9b9b-3f4b41c4c539,"[{""sku"": ""SKU-38820"", ""qty"": 5, ""price"": 229.12}, {""sku"": ""SKU-78522"", ""qty"": 3, ""price"": 81.24}]",paypal,1662.99,25.52,2026-01-07T13:51:26.088769,1317.08,TXN-28300223
591fa43f-4fbe-456b-9faf-2ba197d3b76c,"[{""sku"": ""SKU-89088"", ""qty"": 2, ""price"": 198.99}, {""sku"": ""SKU-45884"", ""qty"": 3, ""price"": 497.4}]",paypal,1873.81,58.47,2026-01-07T13:51:26.088805,1465.25,TXN-31534749


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

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

Output:
article_id,author,content,headline,published,section,shares,tags,views
ART-9628131,,Range condition class leader wrong subject wait. Stop we prevent particular front method. Force item,Re-contextualized logistical paradigm,,,,,
ART-1870604,Ryan Simpson,Write commercial their language school my community benefit. Sign organization read federal peace fa,Expanded non-volatile function,2026-01-05T05:21:17.768743,Business,1928,"[""education"", ""else"", ""left"", ""score"", ""particularly""]",58718
ART-6625773,Judith Stone,"Claim box analysis. Worker break former doctor good question.
Rise fall answer during section. Ball ",Organized exuding function,2026-01-05T11:48:19.735227,Politics,1472,"[""figure"", ""chance"", ""pay""]",82858
ART-6006255,James Watson,Reveal cold off dark use inside finally success. Unit cultural structure entire event human watch. T,Switchable attitude-oriented process improvement,2026-01-04T17:55:31.499204,Tech,4582,"[""small"", ""travel"", ""popular""]",71325
ART-3293534,Megan Scott,"She record citizen. Away nice own nice.
Over year film tax year material method. Ball imagine cultur",Cross-platform reciprocal paradigm,2026-01-02T22:51:52.027029,Business,1734,"[""accept"", ""plant"", ""successful"", ""exist""]",46560


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

[User] Generate contract data in JSON format.

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

Output:
{
  "contract_id": "CTR-896633",
  "parties": [
    {
      "name": "Smith-Cross",
      "role": "party_a"
    },
    {
      "name": "Carrillo and Sons",
      "role": "party_b"
    }
  ],
  "effective_date": "2026-01-03",
  "term_months": 21,
  "value": 926875,
  "status": "pending"
}


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

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

[Assistant]
Approach:
1. Task: Create error log in YAML
2. Complexity: 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: 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 TOML format. Think step-by-step, then generate syntactically perfect TOML.

[User] Produce a TOML document for a contract.

[Assistant]
Approach:
1. Task: Create contract 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:
value = 911148
contract_id = "CTR-919818"
status = "active"
term_months = 18
[[parties]]
name = "Riggs, Carey and Rojas"
role = "party_a"

[[parties]]
name = "Mcdowell-Koch"
role = "party_b"


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

[User] Output student assessment as JSON.

[Assistant]
Approach:
1. Task: Create student assessment 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:
{
  "assessment_id": "ASMT-852879",
  "student_id": "STU-517758",
  "course_id": "CRS-9070",
  "type": "exam",
  "date": "2026-01-04",
  "scores": [
    {
      "question": 1,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 10,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 3,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 10,
      "points_possible": 10
    },
    {
      "question": 9,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 10,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 11,
      "points_earned": 6,
      "points_possible": 10
    },
    {
      "question": 12,
      "points_earned": 8,
      "points_possible": 10
    }
  ],
  "total_score": 58,
  "percentage": 53.23,
  "grade": "C"
}


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

[User] Create a JSON representation of experiment result.

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

Output:
{
  "experiment_id": "EXP-137327",
  "title": "Effect of class on read",
  "methodology": {
    "design": "RCT",
    "sample_size": 679,
    "duration_days": 111
  },
  "results": [
    {
      "metric": "safety",
      "baseline": 73.26,
      "endpoint": 72.84,
      "p_value": 0.0533
    },
    {
      "metric": "efficacy",
      "baseline": 49.24,
      "endpoint": 28.3,
      "p_value": 0.0809
    }
  ],
  "conclusion": "significant"
}


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

[User] Output research paper as CSV.

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

Output:
abstract,authors,citations,funding_source,keywords,paper_id,publication_doi,publication_venue,publication_year,title
Stand season mind indicate either. Buy gas keep skin.,"[{""name"": ""Edwin Moore"", ""affiliation"": ""Smith-Jones"", ""email"": ""bowenzachary@example.net""}, {""name""",204,None,"[""stock"", ""member"", ""laugh"", ""language"", ""right""]",arXiv:2020.57295,10.9461/HDZk,Cell,2022,Persevering global groupware
"Campaign reduce best study pay. Away anything benefit old seven.
That natural throughout performance","[{""name"": ""Carolyn Riggs"", ""affiliation"": ""Hurley and Sons"", ""email"": ""bethany75@example.com""}, {""na",331,None,"[""way"", ""growth"", ""opportunity"", ""among"", ""safe""]",arXiv:2020.38799,10.5163/rwTY,Cell,2022,Upgradable modular frame
"Affect usually certain second. Worker pressure free staff life.
True movie southern tough sit one. P","[{""name"": ""Karen Ortiz"", ""affiliation"": ""Wheeler-Vasquez"", ""email"": ""richardward@example.org""}, {""na",407,Bennett and Sons,"[""strong"", ""whom"", ""condition""]",arXiv:2022.38316,10.8643/oaXz,Science,2020,Total 24/7 approach


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

[User] Generate course syllabus data in JSON format.

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

Output:
{
  "grading": {
    "homework": 30,
    "midterm": 30,
    "final": 40
  },
  "credits": 4,
  "course_id": "CRS-7759",
  "schedule": [
    {
      "week": 1,
      "topic": "meet"
    },
    {
      "week": 2,
      "topic": "around"
    },
    {
      "week": 3,
      "topic": "college"
    },
    {
      "week": 4,
      "topic": "fly"
    },
    {
      "week": 5,
      "topic": "summer"
    },
    {
      "week": 6,
      "topic": "painting"
    },
    {
      "week": 7,
      "topic": "size"
    },
    {
      "week": 8,
      "topic": "off"
    },
    {
      "week": 9,
      "topic": "point"
    },
    {
      "week": 10,
      "topic": "light"
    },
    {
      "week": 11,
      "topic": "nothing"
    }
  ],
  "instructor": "Matthew Johnson"
}


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<financial_report>
<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 JSON
2. Complexity: simple - 3-5 fields, minimal nesting
3. Format rules: proper braces/brackets, quoted keys, correct value types
4. Structure: Organize data logically with appropriate nesting
5. Transform values to match the target format specifications.

Output:
{
  "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] Output financial report as JSON.

[Assistant]
Approach:
1. Task: Create financial report 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:
{
  "company": "Rodriguez, Sanchez and French",
  "ticker": "TOPI",
  "quarter": "Q3 2022",
  "revenue": 30596216,
  "expenses": 79425858,
  "net_income": 10739155,
  "eps": 9.27,
  "metrics": {
    "profit_margin": 21.79,
    "roe": 22.32
  }
}


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

[User]
Reformat the data below from TOML to XML:
course_id = "CRS-5704"
code = "BXM405"
title = "Profit-focused responsive throughput 101"
instructor = "Emily Bryan"
credits = 3
term = "Spring 2021"
[[schedule]]
week = 1
topic = "southern"

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

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

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

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

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

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

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

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

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

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

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

[Assistant]
Approach:
1. Task: Convert course syllabus 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"?>
<course_syllabus>
<course_id>CRS-5704</course_id>
BXM405
<title>Profit-focused responsive throughput 101</title>
<instructor>Emily Bryan</instructor>
<credits>3</credits>
<term>Spring 2021</term>
<schedule>
<week>1</week>
<topic>southern</topic>
</schedule>
<schedule>
<week>2</week>
<topic>raise</topic>
</schedule>
<schedule>
<week>3</week>
<topic>across</topic>
</schedule>
<schedule>
<week>4</week>
<topic>teacher</topic>
</schedule>
<schedule>
<week>5</week>
<topic>service</topic>
</schedule>
<schedule>
<week>6</week>
<topic>body</topic>
</schedule>
<schedule>
<week>7</week>
<topic>practice</topic>
</schedule>
<schedule>
<week>8</week>
<topic>authority</topic>
</schedule>
<schedule>
<week>9</week>
<topic>throw</topic>
</schedule>
<schedule>
<week>10</week>
<topic>second</topic>
</schedule>
<schedule>
<week>11</week>
<topic>authority</topic>
</schedule>
<grading>
<homework>30</homework>
<midterm>30</midterm>
<final>40</final>
</grading>
</course_syllabus>