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

[User] Generate student assessment data in TOML format.

[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-475777"
student_id = "STU-613124"
course_id = "CRS-2241"
type = "assignment"
date = "2026-01-06"
total_score = 75
percentage = 81.54
grade = "B"
[[scores]]
question = 1
points_earned = 8
points_possible = 10

[[scores]]
question = 2
points_earned = 6
points_possible = 10

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

[[scores]]
question = 4
points_earned = 1
points_possible = 10

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

[[scores]]
question = 6
points_earned = 7
points_possible = 10

[[scores]]
question = 7
points_earned = 0
points_possible = 10

[[scores]]
question = 8
points_earned = 9
points_possible = 10

[[scores]]
question = 9
points_earned = 3
points_possible = 10


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

[User]
Reformat the data below from XML to YAML:
<?xml version="1.0" encoding="UTF-8"?>
<research_paper>
<paper_id>arXiv:2021.87801</paper_id>
<title>Cross-group 24/7 methodology</title>
<authors>
<name>Scott Webb</name>
<affiliation>Chapman LLC</affiliation>
<email>juanbooth@example.com</email>
</authors>
<authors>
<name>Robert Mullins</name>
<affiliation>Robbins, Adkins and Rogers</affiliation>
<email>michaeldunn@example.org</email>
</authors>
<abstract>Reality maybe court material response cell. Middle instead husband win thousand collection.</abstract>
<keywords>girl</keywords>
<keywords>face</keywords>
<keywords>protect</keywords>
<publication>
<venue>Cell</venue>
<year>2023</year>
<doi>10.4960/byWV</doi>
</publication>
<citations>193</citations>
<funding_source>Williams Ltd</funding_source>
</research_paper>

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

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


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

[User] Create a YAML representation of transaction record.

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

Output:
txn_id: TXN-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


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

[User]
Transform this CSV data into YAML format:
contract_id,effective_date,parties,status,term_months,value
CTR-370819,2026-01-01,"[{""name"": ""Stewart, Thompson and Rogers"", ""role"": ""party_a""}, {""name"": ""Jackson, Griffin and Flowers",active,13,109351
CTR-476557,2026-01-05,"[{""name"": ""Johnson-Pierce"", ""role"": ""party_a""}, {""name"": ""Ramirez-Gonzalez"", ""role"": ""party_b""}]",pending,55,365110
CTR-277604,2026-01-05,"[{""name"": ""Sanchez Group"", ""role"": ""party_a""}, {""name"": ""Smith, French and Marshall"", ""role"": ""party",executed,29,419347
CTR-129475,2026-01-05,"[{""name"": ""Phillips PLC"", ""role"": ""party_a""}, {""name"": ""Schaefer Ltd"", ""role"": ""party_b""}]",active,39,717385

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

Output:
contract_id: CTR-370819
parties:
- name: Stewart, Thompson and Rogers
  role: party_a
- name: Jackson, Griffin and Flowers
  role: party_b
effective_date: '2026-01-01'
term_months: 13
value: 109351
status: active


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<product_listing>
<rating>4.54</rating>
<stock>843</stock>
<specs>
<weight_kg>34.7</weight_kg>
<dimensions>61x86x65cm</dimensions>
</specs>
<currency>USD</currency>
</product_listing>

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

Output:
{
  "rating": 4.54,
  "stock": 843,
  "specs": {
    "weight_kg": 34.7,
    "dimensions": "61x86x65cm"
  },
  "currency": "USD"
}


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

[User] Create a JSON representation of course syllabus.

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


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

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

[Assistant]
Approach:
1. Task: Create api specification 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,info_title,info_version,keywords,openapi,paper_id,paths_/base_get_parameters,paths_/base_get_responses_200_description,paths_/base_get_responses_400_description,paths_/base_get_summary,publication_doi,publication_venue,publication_year,title
,,,,Horizontal interactive project API,1.0.0,,3.0.0,,"[{""name"": ""param0"", ""in"": ""query"", ""type"": ""string""}]",Success,Bad Request,Management send father actually special image.,,,,
Bar sell discuss one. Action wear structure onto. Computer brother Democrat produce position various,"[{""name"": ""Felicia Lee"", ""affiliation"": ""Williams-Brown"", ""email"": ""robertjenkins@example.org""}, {""n",348,None,,,"[""security"", ""treatment"", ""sell"", ""marriage""]",,arXiv:2020.33053,,,,,10.3727/VsAZ,Science,2021,Decentralized background monitoring
"South sing then consider system catch. Choose information spring two. Ground white from.
Just born c","[{""name"": ""Katherine Stout"", ""affiliation"": ""Norris-Blackwell"", ""email"": ""josephtran@example.com""}, ",41,Camacho Group,,,"[""card"", ""mention"", ""share"", ""difficult""]",,arXiv:2020.31056,,,,,10.2465/zJMa,Science,2021,Decentralized needs-based alliance


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

[User]
Transform this TOML data into YAML format:
rating = 5
review_id = "REV-2205395"
content = "Respond order far story by area affect. Important also catch down choice office necessary political. Firm along bar.\nStuff create including star question traditional reflect. Share fast thought."

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

Output:
rating: 5
review_id: REV-2205395
content: 'Respond order far story by area affect. Important also catch down choice
  office necessary political. Firm along bar.

  Stuff create including star question traditional reflect. Share fast thought.'


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<contract>
<contract_id>CTR-274282</contract_id>
<parties>
<name>Schroeder LLC</name>
<role>party_a</role>
</parties>
<parties>
<name>Kemp-Jones</name>
<role>party_b</role>
</parties>
<effective_date>2026-01-01</effective_date>
<term_months>28</term_months>
<value>285721</value>
<status>active</status>
</contract>

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

Output:
{
  "contract_id": "CTR-274282",
  "parties": [
    {
      "name": "Schroeder LLC",
      "role": "party_a"
    },
    {
      "name": "Kemp-Jones",
      "role": "party_b"
    }
  ],
  "effective_date": "2026-01-01",
  "term_months": 28,
  "value": 285721,
  "status": "active"
}


[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-8668047
headline: Seamless local alliance
author: Alyssa Moore
published: '2026-01-02T06:22:52.413807'
section: Business
content: 'Billion up year window similar. Oil two resource next. If this tough pattern.

  Rule year push international.

  Receive charge movie remember hear theory stuff explain. Century animal decide everyone
  direction rather. Month property rock environment fine such hand remain.'
tags:
- traditional
- wish
- little
- inside
- year
views: 55093
shares: 3713


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

[User] Create a XML representation of course syllabus.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<course_syllabus>
<course_id>CRS-3440</course_id>
KLD251
<title>Reverse-engineered foreground infrastructure 101</title>
<instructor>Courtney Escobar</instructor>
<credits>4</credits>
<term>Spring 2022</term>
<schedule>
<week>1</week>
<topic>despite</topic>
</schedule>
<schedule>
<week>2</week>
<topic>choose</topic>
</schedule>
<schedule>
<week>3</week>
<topic>action</topic>
</schedule>
<schedule>
<week>4</week>
<topic>couple</topic>
</schedule>
<schedule>
<week>5</week>
<topic>big</topic>
</schedule>
<schedule>
<week>6</week>
<topic>trade</topic>
</schedule>
<schedule>
<week>7</week>
<topic>measure</topic>
</schedule>
<schedule>
<week>8</week>
<topic>music</topic>
</schedule>
<grading>
<homework>30</homework>
<midterm>30</midterm>
<final>40</final>
</grading>
</course_syllabus>


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

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

[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-4827299</result_id>
<patient_mrn>MRN-871984</patient_mrn>
<order_date>2026-01-06</order_date>
<panel>Lipid</panel>
<results>
<test>WBC</test>
<value>156.4</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
<results>
<test>WBC</test>
<value>186.0</value>
<unit>mg/dL</unit>
<flag>low</flag>
</results>
<results>
<test>WBC</test>
<value>134.8</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>WBC</test>
<value>64.1</value>
<unit>mg/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:
{
  "error_id": "ff91c212-6cce-4ac2-978d-0740381882de",
  "timestamp": "2026-01-07T13:51:27.679071",
  "level": "WARNING",
  "service": "drawService",
  "message": "Support red list product forget cut speak.",
  "stack_trace": [
    "at girl.py:186",
    "at hold.py:186"
  ],
  "context": {
    "user_id": "473e683b-291e-461f-b848-d224b7dcbd8b",
    "request_id": "454a35ad-23ee-42a8-9d57-dbf5cedbef74"
  }
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<error_log>
<error_id>ff91c212-6cce-4ac2-978d-0740381882de</error_id>
<timestamp>2026-01-07T13:51:27.679071</timestamp>
<level>WARNING</level>
<service>drawService</service>
<message>Support red list product forget cut speak.</message>
<stack_trace>at girl.py:186</stack_trace>
<stack_trace>at hold.py:186</stack_trace>
<context>
<user_id>473e683b-291e-461f-b848-d224b7dcbd8b</user_id>
<request_id>454a35ad-23ee-42a8-9d57-dbf5cedbef74</request_id>
</context>
</error_log>


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

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

[Assistant]
Approach:
1. Task: Create customer review 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:
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


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

[User] Create a TOML representation of prescription.

[Assistant]
Approach:
1. Task: Create prescription in TOML
2. Complexity: 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:
rx_id = "RX-7665793"
patient_mrn = "MRN-934255"
prescriber = "Danielle Brown"
date = "2026-01-06"
[[medications]]
name = "Atorvastatin"
dosage = "20mg"
frequency = "daily"
quantity = 90

[[medications]]
name = "Atorvastatin"
dosage = "5mg"
frequency = "BID"
quantity = 90

[[medications]]
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: 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:
author: Jenna Bryant
tags:
- most
- 'off'
- shoulder
headline: Secured composite leverage
published: '2026-01-04T22:19:16.750289'


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

[User] Generate lab result data in JSON format.

[Assistant]
Approach:
1. Task: Create lab result in JSON
2. Complexity: 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:
{
  "result_id": "LAB-5790382",
  "patient_mrn": "MRN-357903",
  "order_date": "2026-01-02",
  "panel": "CBC",
  "results": [
    {
      "test": "Glucose",
      "value": 56.1,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "Glucose",
      "value": 114.1,
      "unit": "mg/dL",
      "flag": "normal"
    },
    {
      "test": "WBC",
      "value": 154.7,
      "unit": "mg/dL",
      "flag": "low"
    },
    {
      "test": "Glucose",
      "value": 196.1,
      "unit": "g/dL",
      "flag": "normal"
    }
  ]
}


[System] You are an expert in 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: 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"?>
<sales_analytics>
<period>November 2022</period>
<total_revenue>9138741</total_revenue>
<units_sold>89798</units_sold>
<channels>
<name>wholesale</name>
<revenue>1234153</revenue>
<growth>40.64</growth>
</channels>
<channels>
<name>online</name>
<revenue>991509</revenue>
<growth>-4.15</growth>
</channels>
<top_products>
<sku>SKU-9585</sku>
<sales>30234</sales>
</top_products>
<top_products>
<sku>SKU-8072</sku>
<sales>57362</sales>
</top_products>
<top_products>
<sku>SKU-4011</sku>
<sales>249730</sales>
</top_products>
</sales_analytics>


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

[User] Generate clinical note data in CSV format.

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

Output:
assessment,chief_complaint,encounter_date,note_id,patient_age,patient_gender,patient_mrn,vitals_bp,vitals_hr,vitals_temp_f
"[{""problem"": ""diabetes"", ""icd10"": ""I24""}]",,2026-01-06,CN-3244099,61,F,MRN-470382,158/77,112,99.5
"[{""problem"": ""hypertension"", ""icd10"": ""I40""}]",headache,2026-01-05,CN-1930411,83,M,MRN-164033,174/85,78,101.9
"[{""problem"": ""hypertension"", ""icd10"": ""K23""}, {""problem"": ""hypertension"", ""icd10"": ""J13""}]",headache,2026-01-05,CN-1369458,64,M,MRN-987322,97/99,86,102.6
"[{""problem"": ""hypertension"", ""icd10"": ""K22""}, {""problem"": ""diabetes"", ""icd10"": ""J34""}, {""problem"": """,fever,2026-01-05,CN-9945813,35,F,MRN-444737,91/98,106,98.3


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

[User] Generate product listing data in TOML format.

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

Output:
product_id = "PROD-830951"
name = "Multi-layered tangible superstructure"
category = "clothing"
price = 269.31
currency = "USD"
stock = 322
is_available = true
rating = 2.21
reviews = 733

[specs]
weight_kg = 46.04
dimensions = "75x77x31cm"


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

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

[Assistant]
Approach:
1. Task: Create financial report 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:
company = "Taylor Ltd"
ticker = "AOED"
quarter = "Q1 2024"
revenue = 69752271
expenses = 52626087
net_income = 18580243
eps = 1.63

[metrics]
profit_margin = 23.4
roe = 21.22


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

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

[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
,,,1b22b6e6-0879-45de-9655-0fac03142f9b,91a6b883-2593-4790-8a1e-5acd27aad31b,0ea30289-ce13-425f-910d-da970e03d0fa,,,WARNING,Country specific information follow daughter dark.,,,,,theService,"[""at enjoy.py:340"", ""at current.py:45"", ""at hand.py:478""]",2026-01-07T13:51:25.772316,
Remember know this home computer administration worry. Prove only rise treatment. True heart probabl,"[{""name"": ""David Collins"", ""affiliation"": ""Sweeney Inc"", ""email"": ""fbutler@example.net""}, {""name"": """,394,,,,None,"[""budget"", ""discuss"", ""camera"", ""recently""]",,,arXiv:2022.97037,10.6313/pVfR,Nature,2021,,,,Ergonomic systemic capability
"Image pay artist need tonight care in religious. Sell focus Democrat drop add everybody a.
With marr","[{""name"": ""Donna Lindsey"", ""affiliation"": ""Prince and Sons"", ""email"": ""william62@example.org""}, {""na",484,,,,"Chambers, Tyler and Jimenez","[""just"", ""attention"", ""enjoy""]",,,arXiv:2021.28698,10.2717/zkdK,Cell,2024,,,,Intuitive empowering concept
Practice candidate left process. Environmental energy line win.,"[{""name"": ""Amy Buckley"", ""affiliation"": ""Williams and Sons"", ""email"": ""smithkathryn@example.net""}, {",385,,,,Rose-Johnson,"[""east"", ""could"", ""pull""]",,,arXiv:2024.41230,10.5302/Tezk,Science,2022,,,,Grass-roots dedicated open architecture


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

[User] Create a XML representation of contract.

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


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

[User] Create a XML representation of error log.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<error_log>
<error_id>21bf982e-3e24-486f-a8ed-fe9e0227df3b</error_id>
<timestamp>2026-01-07T13:51:27.797574</timestamp>
<level>CRITICAL</level>
<service>letService</service>
<message>Story quite another important.</message>
<stack_trace>at decision.py:100</stack_trace>
<stack_trace>at sing.py:289</stack_trace>
<stack_trace>at long.py:325</stack_trace>
<stack_trace>at special.py:174</stack_trace>
<context>
<user_id>8c36ba55-183c-4481-9cd9-dc049447888c</user_id>
<request_id>089e0eaa-71d8-4f30-a2f1-bac42a6b74a3</request_id>
</context>
</error_log>


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

[User] Create a TOML representation of customer review.

[Assistant]
Approach:
1. Task: Create customer review 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:
review_id = "REV-8075236"
product_id = "PROD-326180"
user_id = "e70c9373-b1ad-41a5-8939-e3c28041d8f5"
rating = 4
title = "Most teacher Mrs system watch."
content = "Address music major. Magazine three about. Security ready result improve.\nHand other collection name wife remain. Speech perhaps newspaper. Talk place third about writer billion physical."
date = "2026-01-03"
verified_purchase = false
helpful_votes = 50


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

[User] Create a TOML representation of customer review.

[Assistant]
Approach:
1. Task: Create customer review 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:
review_id = "REV-3637179"
product_id = "PROD-905516"
user_id = "cbc145e7-7f32-438c-ba90-61711bf65a15"
rating = 1
title = "Hand ok join you population."
content = "Develop particularly receive thing process sister source. Ago short fact start meeting note need. However music factor my million scene use."
date = "2026-01-03"
verified_purchase = false
helpful_votes = 42


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

[User] Produce a JSON document for a news article.

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

Output:
{
  "article_id": "ART-1748125",
  "headline": "Customizable leadingedge structure",
  "author": "Sandra Bennett",
  "published": "2026-01-03T22:52:42.741679",
  "section": "Sports",
  "content": "Majority meeting sound have week public pass. Major food relate spend seven.\nIndeed run fund.\nFederal right stuff difficult alone miss. Stuff rest model job deep knowledge pull force. Too follow face husband every. Hit important agreement rather card west want.",
  "tags": [
    "subject",
    "attention",
    "class",
    "campaign",
    "second"
  ],
  "views": 63827,
  "shares": 2505
}


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

[User] Generate experiment result data in YAML format.

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

Output:
results:
- metric: efficacy
  baseline: 40.85
  endpoint: 40.08
  p_value: 0.4196
- metric: efficacy
  baseline: 82.87
  endpoint: 28.4
  p_value: 0.208
- metric: efficacy
  baseline: 74.0
  endpoint: 18.43
  p_value: 0.3638
- metric: efficacy
  baseline: 50.48
  endpoint: 15.59
  p_value: 0.1146
methodology:
  design: observational
  sample_size: 351
  duration_days: 339
conclusion: non-significant


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

[User]
Transform this JSON data into XML format:
{
  "info": {
    "title": "Multi-tiered directional knowledge user API",
    "version": "1.0.0"
  },
  "openapi": "3.0.0",
  "paths": {
    "/require": {
      "get": {
        "summary": "Suffer kid pull bed decision rest.",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          },
          {
            "name": "param1",
            "in": "query",
            "type": "string"
          },
          {
            "name": "param2",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  }
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<api_specification>
<info>
<title>Multi-tiered directional knowledge user API</title>
<version>1.0.0</version>
</info>
<openapi>3.0.0</openapi>
<paths>
</require>
<get>
<summary>Suffer kid pull bed decision rest.</summary>
<parameters>
<name>param0</name>
<in>query</in>
<type>string</type>
</parameters>
<parameters>
<name>param1</name>
<in>query</in>
<type>string</type>
</parameters>
<parameters>
<name>param2</name>
<in>query</in>
<type>string</type>
</parameters>
<responses>
<200>
<description>Success</description>
</200>
<400>
<description>Bad Request</description>
</400>
</responses>
</get>
<//require>
</paths>
</api_specification>


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

[User]
Convert the following YAML to XML:
result_id: LAB-8547948
patient_mrn: MRN-375584
order_date: '2026-01-05'
panel: Lipid
results:
- test: WBC
  value: 136.4
  unit: mg/dL
  flag: low
- test: Glucose
  value: 110.1
  unit: mg/dL
  flag: normal
- test: Glucose
  value: 77.6
  unit: mg/dL
  flag: high
- test: Glucose
  value: 164.2
  unit: g/dL
  flag: normal
- test: Hemoglobin
  value: 53.3
  unit: g/dL
  flag: high

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

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


[System] You are an expert in 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>
<info>
<title>Grass-roots 6thgeneration ability API</title>
<version>1.0.0</version>
</info>
<paths>
</million>
<get>
<summary>About little above investment already magazine.</summary>
<parameters>
<name>param0</name>
<in>query</in>
<type>string</type>
</parameters>
<responses>
<200>
<description>Success</description>
</200>
<400>
<description>Bad Request</description>
</400>
</responses>
</get>
<//million>
</paths>
</api_specification>

[Assistant]
Approach:
1. Task: Convert api specification 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:
{
  "openapi": "3.0.0",
  "info": {
    "title": "Grass-roots 6thgeneration ability API",
    "version": "1.0.0"
  },
  "paths": {
    "/million": {
      "get": {
        "summary": "About little above investment already magazine.",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  }
}


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

[User] Output course syllabus as XML.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<course_syllabus>
<course_id>CRS-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>


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

[User] Output prescription as CSV.

[Assistant]
Approach:
1. Task: Create prescription 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:
date,medications,patient_mrn,prescriber,rx_id
2026-01-02,"[{""name"": ""Atorvastatin"", ""dosage"": ""20mg"", ""frequency"": ""BID"", ""quantity"": 90}, {""name"": ""Atorvasta",MRN-726192,Jessica Warner,RX-3022361
2026-01-03,"[{""name"": ""Atorvastatin"", ""dosage"": ""10mg"", ""frequency"": ""TID"", ""quantity"": 60}, {""name"": ""Atorvasta",MRN-885805,Thomas Morris,RX-7631483
2026-01-02,"[{""name"": ""Metformin"", ""dosage"": ""5mg"", ""frequency"": ""BID"", ""quantity"": 30}, {""name"": ""Lisinopril"", ",MRN-354257,Heather Gonzalez,RX-8243883
2026-01-03,"[{""name"": ""Metformin"", ""dosage"": ""5mg"", ""frequency"": ""TID"", ""quantity"": 90}]",MRN-565982,Robert Collins,RX-2112661


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

[User]
Convert the following TOML to XML:
experiment_id = "EXP-139463"
title = "Effect of quite on arm"
conclusion = "non-significant"
[[results]]
metric = "safety"
baseline = 91.61
endpoint = 76.9
p_value = 0.4003

[[results]]
metric = "safety"
baseline = 58.96
endpoint = 23.83
p_value = 0.3437

[[results]]
metric = "safety"
baseline = 23.31
endpoint = 88.63
p_value = 0.3018

[methodology]
design = "RCT"
sample_size = 371
duration_days = 284

[Assistant]
Approach:
1. Task: Convert experiment result 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"?>
<experiment_result>
<experiment_id>EXP-139463</experiment_id>
<title>Effect of quite on arm</title>
<methodology>
<design>RCT</design>
<sample_size>371</sample_size>
<duration_days>284</duration_days>
</methodology>
<results>
<metric>safety</metric>
<baseline>91.61</baseline>
<endpoint>76.9</endpoint>
<p_value>0.4003</p_value>
</results>
<results>
<metric>safety</metric>
<baseline>58.96</baseline>
<endpoint>23.83</endpoint>
<p_value>0.3437</p_value>
</results>
<results>
<metric>safety</metric>
<baseline>23.31</baseline>
<endpoint>88.63</endpoint>
<p_value>0.3018</p_value>
</results>
<conclusion>non-significant</conclusion>
</experiment_result>


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

[User] Output course syllabus as CSV.

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

Output:
code,course_id,credits,grading_final,grading_homework,grading_midterm,instructor,schedule,term,title
WQT213,CRS-9279,3,40,30,30,Mariah Wilson,"[{""week"": 1, ""topic"": ""together""}, {""week"": 2, ""topic"": ""statement""}, {""week"": 3, ""topic"": ""these""},",Fall 2020,Ameliorated 3rdgeneration groupware 101
BBZ401,CRS-5888,3,40,30,30,Jacob Brady,"[{""week"": 1, ""topic"": ""about""}, {""week"": 2, ""topic"": ""push""}, {""week"": 3, ""topic"": ""above""}, {""week""",Spring 2024,Universal zero tolerance initiative 101
PEC429,CRS-2614,3,40,30,30,Antonio Ritter,"[{""week"": 1, ""topic"": ""laugh""}, {""week"": 2, ""topic"": ""ahead""}, {""week"": 3, ""topic"": ""dream""}, {""week",Spring 2024,Proactive tangible knowledgebase 101


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

[User] Generate financial report data in XML format.

[Assistant]
Approach:
1. Task: Create financial report 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"?>
<financial_report>
<revenue>65816825</revenue>
<ticker>IQTA</ticker>
<expenses>77578182</expenses>
<company>Ramos-Wallace</company>
</financial_report>


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

[User] Create a CSV representation of clinical note.

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

Output:
assessment,chief_complaint,encounter_date,note_id,patient_age,patient_gender,patient_mrn,vitals_bp,vitals_hr,vitals_temp_f
"[{""problem"": ""diabetes"", ""icd10"": ""I65""}, {""problem"": ""diabetes"", ""icd10"": ""J29""}]",fever,2026-01-01,CN-2341842,85,F,MRN-739833,174/60,60,98.7
"[{""problem"": ""diabetes"", ""icd10"": ""J18""}]",chest pain,2026-01-02,CN-8863909,35,F,MRN-888837,159/66,106,98.1
"[{""problem"": ""diabetes"", ""icd10"": ""I59""}, {""problem"": ""diabetes"", ""icd10"": ""J29""}]",chest pain,2026-01-04,CN-1566893,50,F,MRN-182318,95/72,112,97.6
"[{""problem"": ""diabetes"", ""icd10"": ""K82""}, {""problem"": ""hypertension"", ""icd10"": ""I77""}, {""problem"": """,headache,2026-01-02,CN-1373235,58,F,MRN-292528,130/109,86,98.9


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

[User] Output api specification as JSON.

[Assistant]
Approach:
1. Task: Create api specification 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:
{
  "openapi": "3.0.0",
  "info": {
    "title": "Stand-alone dedicated complexity API",
    "version": "1.0.0"
  },
  "paths": {
    "/hear": {
      "get": {
        "summary": "Chance cultural sort including high.",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          },
          {
            "name": "param1",
            "in": "query",
            "type": "string"
          },
          {
            "name": "param2",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  }
}


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<title>Career hospital always money word day.</title>
<helpful_votes>95</helpful_votes>
<review_id>REV-5250684</review_id>
<verified_purchase>False</verified_purchase>
<date>2026-01-01</date>
</customer_review>


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

[User] Create a JSON representation of student assessment.

[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-458464",
  "student_id": "STU-453066",
  "course_id": "CRS-7675",
  "type": "assignment",
  "date": "2026-01-06",
  "scores": [
    {
      "question": 1,
      "points_earned": 0,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 0,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 3,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 9,
      "points_earned": 8,
      "points_possible": 10
    }
  ],
  "total_score": 67,
  "percentage": 65.79,
  "grade": "B"
}


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

[User] Output social media post as XML.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<social_media_post>
<post_id>POST-49469407</post_id>
<platform>instagram</platform>
<user_id>c776cd7c-2538-4c81-83c8-03afd724bed1</user_id>
<username>donald18</username>
<content>Knowledge between friend wife property kid out. Trouble recent member sort arrive foot space good.</content>
<timestamp>2026-01-07T13:51:26.031233</timestamp>
<hashtags>#daughter</hashtags>
<hashtags>#after</hashtags>
<hashtags>#affect</hashtags>
<hashtags>#goal</hashtags>
<engagement>
<likes>2564</likes>
<shares>187</shares>
<comments>95</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 course syllabus.

[Assistant]
Approach:
1. Task: Create course syllabus 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:
course_id = "CRS-8422"
code = "OMY437"
title = "Optimized upward-trending conglomeration 101"
instructor = "Rodney Anderson"
credits = 3
term = "Spring 2023"
[[schedule]]
week = 1
topic = "answer"

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

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

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

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

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

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

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


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<prescription>
<rx_id>RX-1795504</rx_id>
<patient_mrn>MRN-355763</patient_mrn>
<prescriber>Henry Padilla</prescriber>
<date>2026-01-01</date>
<medications>
<name>Metformin</name>
<dosage>20mg</dosage>
<frequency>daily</frequency>
<quantity>90</quantity>
</medications>
</prescription>

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

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


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

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

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


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

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

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

Output:
review_id: REV-1369973
product_id: PROD-861575
user_id: a55bb48c-5dcb-464a-b952-9d377a4cb9c4
rating: 1
title: Relationship job find one allow law through.
content: Now decide senior fact big window yourself. Difference appear seat coach
  rather once politics. Modern always able physical Republican best draw land.
date: '2026-01-02'
verified_purchase: true
helpful_votes: 8


[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-3366717,Linda Clark,"Anything music blood how public to. Even student idea piece if. Whom phone rich long.
Look memory he",Integrated bi-directional complexity,2026-01-07T13:19:20.433040,Tech,1143,"[""necessary"", ""listen"", ""employee"", ""here""]",75939
ART-8466498,Bobby Kelly,"Maybe white between teacher without reduce sit. Happy seem edge result happy network.
Place even par",Advanced 3rdgeneration data-warehouse,2026-01-05T07:24:30.511933,Tech,1249,"[""concern"", ""effort"", ""always"", ""sister""]",6422
ART-7588265,Danielle Fitzpatrick,"Fight court PM paper its far. Loss two these summer.
Miss though listen know fire experience. Recent",Ergonomic tangible alliance,2026-01-01T06:37:50.352281,Tech,1983,"[""particular"", ""chair"", ""sure"", ""none"", ""parent""]",94629
ART-1970064,Jenny Jenkins,True government just of school second police machine. Democratic professional parent concern the lin,Down-sized 5thgeneration installation,2026-01-02T12:45:50.826581,Tech,2405,"[""race"", ""yes"", ""three""]",44858


[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:
{
  "rx_id": "RX-5855932",
  "patient_mrn": "MRN-921122",
  "prescriber": "Spencer Smith",
  "date": "2026-01-05",
  "medications": [
    {
      "name": "Metformin",
      "dosage": "20mg",
      "frequency": "daily",
      "quantity": 30
    }
  ]
}

[Assistant]
Approach:
1. Task: Convert prescription 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"?>
<prescription>
<rx_id>RX-5855932</rx_id>
<patient_mrn>MRN-921122</patient_mrn>
<prescriber>Spencer Smith</prescriber>
<date>2026-01-05</date>
<medications>
<name>Metformin</name>
<dosage>20mg</dosage>
<frequency>daily</frequency>
<quantity>30</quantity>
</medications>
</prescription>


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

[User] Generate student assessment data in CSV format.

[Assistant]
Approach:
1. Task: Create student assessment in CSV
2. Complexity: 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-766800,,CRS-8819,,2026-01-03,A,,,,,71.71,,"[{""question"": 1, ""points_earned"": 8, ""points_possible"": 10}, {""question"": 2, ""points_earned"": 3, ""po",STU-927295,,,99,assignment
,RAW376,CRS-7280,4,,,40,30,30,Tracy Mills,,"[{""week"": 1, ""topic"": ""send""}, {""week"": 2, ""topic"": ""measure""}, {""week"": 3, ""topic"": ""feel""}, {""week",,,Fall 2020,Self-enabling encompassing collaboration 101,,
,ZUC178,CRS-5973,3,,,40,30,30,Jamie Walker,,"[{""week"": 1, ""topic"": ""crime""}, {""week"": 2, ""topic"": ""mission""}, {""week"": 3, ""topic"": ""cold""}, {""wee",,,Spring 2024,Profit-focused intermediate service-desk 101,,


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

[User] Generate customer review data in TOML format.

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


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

[User] Create a TOML representation of customer review.

[Assistant]
Approach:
1. Task: Create customer review 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:
review_id = "REV-9982202"
product_id = "PROD-452864"
user_id = "015289de-7f3e-45e2-b1d0-7fe22aff92a9"
rating = 3
title = "Example center fill free."
content = "North describe old attention usually third. Important wish security ago somebody remain everyone modern. Significant chair place throughout study administration American."
date = "2026-01-04"
verified_purchase = false
helpful_votes = 34


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

[User] Output clinical note as CSV.

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

Output:
assessment,chief_complaint,encounter_date,note_id,patient_age,patient_gender,patient_mrn,vitals_bp,vitals_hr,vitals_temp_f
,,2026-01-03,CN-2646438,41,M,MRN-771263,,,
"[{""problem"": ""hypertension"", ""icd10"": ""J35""}]",fever,2026-01-02,CN-4026207,45,M,MRN-741024,104/83,63,99.9
"[{""problem"": ""hypertension"", ""icd10"": ""I39""}, {""problem"": ""hypertension"", ""icd10"": ""K82""}]",chest pain,2026-01-02,CN-2698715,39,F,MRN-808918,132/92,90,97.1


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<contract>
<contract_id>CTR-324198</contract_id>
<parties>
<name>Alvarado-Barnes</name>
<role>party_a</role>
</parties>
<parties>
<name>Lopez, Price and Melendez</name>
<role>party_b</role>
</parties>
<effective_date>2026-01-06</effective_date>
<term_months>34</term_months>
<value>725205</value>
<status>pending</status>
</contract>

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

Output:
{
  "contract_id": "CTR-324198",
  "parties": [
    {
      "name": "Alvarado-Barnes",
      "role": "party_a"
    },
    {
      "name": "Lopez, Price and Melendez",
      "role": "party_b"
    }
  ],
  "effective_date": "2026-01-06",
  "term_months": 34,
  "value": 725205,
  "status": "pending"
}


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

[User]
Convert the following JSON to XML:
{
  "post_id": "POST-49469407",
  "platform": "instagram",
  "user_id": "c776cd7c-2538-4c81-83c8-03afd724bed1",
  "username": "donald18",
  "content": "Knowledge between friend wife property kid out. Trouble recent member sort arrive foot space good.",
  "timestamp": "2026-01-07T13:51:26.031233",
  "hashtags": [
    "#daughter",
    "#after",
    "#affect",
    "#goal"
  ],
  "engagement": {
    "likes": 2564,
    "shares": 187,
    "comments": 95
  }
}

[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-49469407</post_id>
<platform>instagram</platform>
<user_id>c776cd7c-2538-4c81-83c8-03afd724bed1</user_id>
<username>donald18</username>
<content>Knowledge between friend wife property kid out. Trouble recent member sort arrive foot space good.</content>
<timestamp>2026-01-07T13:51:26.031233</timestamp>
<hashtags>#daughter</hashtags>
<hashtags>#after</hashtags>
<hashtags>#affect</hashtags>
<hashtags>#goal</hashtags>
<engagement>
<likes>2564</likes>
<shares>187</shares>
<comments>95</comments>
</engagement>
</social_media_post>


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

[User] Create a YAML representation of course syllabus.

[Assistant]
Approach:
1. Task: Create course syllabus in YAML
2. Complexity: 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:
course_id: CRS-9141
code: ESH384
title: Inverse real-time hardware 101
instructor: Matthew Boyd
credits: 4
term: Fall 2022
schedule:
- week: 1
  topic: western
- week: 2
  topic: since
- week: 3
  topic: later
- week: 4
  topic: next
- week: 5
  topic: tree
- week: 6
  topic: until
- week: 7
  topic: everything
- week: 8
  topic: until
- week: 9
  topic: how
- week: 10
  topic: test
- week: 11
  topic: half
grading:
  homework: 30
  midterm: 30
  final: 40


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

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

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

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


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

[User] Create a XML representation of clinical note.

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

72

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


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

[User]
Reformat the data below from JSON to XML:
{
  "post_id": "POST-46905875",
  "platform": "instagram",
  "user_id": "2079b341-d50b-4860-ba15-aa28bbe0f5b3",
  "username": "xhernandez",
  "content": "Serious degree upon late.\nPainting throughout direction indicate night. Political business voice street child. Across between ready. Majority red mission prepare state.",
  "timestamp": "2026-01-07T13:51:26.735117",
  "hashtags": [
    "#easy",
    "#miss"
  ],
  "engagement": {
    "likes": 6808,
    "shares": 9,
    "comments": 24
  }
}

[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-46905875</post_id>
<platform>instagram</platform>
<user_id>2079b341-d50b-4860-ba15-aa28bbe0f5b3</user_id>
<username>xhernandez</username>
<content>Serious degree upon late.
Painting throughout direction indicate night. Political business voice street child. Across between ready. Majority red mission prepare state.</content>
<timestamp>2026-01-07T13:51:26.735117</timestamp>
<hashtags>#easy</hashtags>
<hashtags>#miss</hashtags>
<engagement>
<likes>6808</likes>
<shares>9</shares>
<comments>24</comments>
</engagement>
</social_media_post>


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

[User] Generate experiment result data in JSON format.

[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-500587",
  "title": "Effect of seem on put",
  "methodology": {
    "design": "cohort",
    "sample_size": 806,
    "duration_days": 332
  },
  "results": [
    {
      "metric": "safety",
      "baseline": 59.15,
      "endpoint": 80.7,
      "p_value": 0.0751
    },
    {
      "metric": "efficacy",
      "baseline": 25.67,
      "endpoint": 99.48,
      "p_value": 0.1142
    },
    {
      "metric": "safety",
      "baseline": 72.29,
      "endpoint": 18.69,
      "p_value": 0.2768
    },
    {
      "metric": "safety",
      "baseline": 16.24,
      "endpoint": 94.98,
      "p_value": 0.315
    }
  ],
  "conclusion": "significant"
}


[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:
{
  "period": "April 2020",
  "total_revenue": 1914989,
  "units_sold": 47758,
  "channels": [
    {
      "name": "wholesale",
      "revenue": 3617590,
      "growth": 20.48
    },
    {
      "name": "online",
      "revenue": 654207,
      "growth": 24.4
    }
  ],
  "top_products": [
    {
      "sku": "SKU-4328",
      "sales": 466200
    },
    {
      "sku": "SKU-2589",
      "sales": 244105
    },
    {
      "sku": "SKU-7725",
      "sales": 25778
    }
  ]
}

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

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


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

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

[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
Full with spend role first drive. Want man instead today bed hand character.,"[{""name"": ""Clayton Martinez"", ""affiliation"": ""Flores, Levy and Farmer"", ""email"": ""kathy80@example.or",395,None,"[""bed"", ""very"", ""population""]",arXiv:2023.99214,10.4640/CkqB,Nature,2023,Integrated mobile database
Wind trade think then leave develop. Technology serious personal view. Yet myself small window final,"[{""name"": ""Juan Gonzalez"", ""affiliation"": ""Craig Inc"", ""email"": ""danielmurphy@example.com""}, {""name""",439,Perez Inc,"[""not"", ""senior"", ""director"", ""Congress"", ""result""]",arXiv:2024.11173,10.7286/mDvM,Nature,2020,Realigned static project
Account alone whatever year become rate save. Production hotel admit later fast hit.,"[{""name"": ""Jennifer Walls"", ""affiliation"": ""Hayes-Hubbard"", ""email"": ""rochatyler@example.net""}, {""na",346,None,"[""event"", ""meet"", ""within"", ""class"", ""training""]",arXiv:2022.40670,10.8585/cQLU,Cell,2024,Multi-lateral 5thgeneration conglomeration
Enter allow buy might seat increase research. Computer practice cup teacher word road nearly. Agains,"[{""name"": ""Tony Dominguez"", ""affiliation"": ""Gonzalez PLC"", ""email"": ""ywarren@example.org""}, {""name"":",69,None,"[""gas"", ""society"", ""cup"", ""every""]",arXiv:2023.18353,10.7144/IFGG,Science,2023,Persevering bi-directional intranet


[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": "03dcbba2-8070-483e-a807-51e4c6301bf5",
  "timestamp": "2026-01-07T13:51:27.875594",
  "level": "WARNING",
  "service": "stockService",
  "message": "Feel garden dark.",
  "stack_trace": [
    "at another.py:304",
    "at happy.py:331",
    "at record.py:415"
  ],
  "context": {
    "user_id": "cedcf075-a01b-42e9-acdc-a300ea843992",
    "request_id": "acbfd7fd-a4ab-431b-a098-ac4537826f14"
  }
}

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

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


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

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

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


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

[User] Create a JSON representation of financial report.

[Assistant]
Approach:
1. Task: Create financial report in JSON
2. Complexity: 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": "Smith-Glover",
  "ticker": "JROI",
  "quarter": "Q3 2023",
  "revenue": 95238846,
  "expenses": 30652579,
  "net_income": 5856951,
  "eps": 7.31,
  "metrics": {
    "profit_margin": 9.94,
    "roe": 10.91
  }
}


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

[User] Create a YAML representation of contract.

[Assistant]
Approach:
1. Task: Create contract in YAML
2. Complexity: 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:
effective_date: '2026-01-02'
term_months: 54
status: pending


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

[User] Create a TOML representation of news article.

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

Output:
article_id = "ART-9801838"
headline = "Multi-lateral didactic encryption"
author = "Jeffrey Gordon"
published = "2026-01-04T05:36:27.140251"
section = "Business"
content = "Partner energy whose simply half because long. Pattern include thousand care four against.\nScene center certainly letter already rate among. Do amount account court term same.\nStep usually ground onto study myself."
tags = [ "word", "public", "near",]
views = 26731
shares = 4423


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

[User]
Convert the following JSON to XML:
{
  "encounter_date": "2026-01-03",
  "note_id": "CN-2646438",
  "patient": {
    "mrn": "MRN-771263",
    "age": 41,
    "gender": "M"
  }
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<clinical_note>
<encounter_date>2026-01-03</encounter_date>
<note_id>CN-2646438</note_id>
<patient>
<mrn>MRN-771263</mrn>
<age>41</age>
<gender>M</gender>
</patient>
</clinical_note>


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

[User] Output sales analytics as XML.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<sales_analytics>
<period>June 2024</period>
<total_revenue>5319249</total_revenue>
<units_sold>96009</units_sold>
<channels>
<name>wholesale</name>
<revenue>941227</revenue>
<growth>26.4</growth>
</channels>
<channels>
<name>retail</name>
<revenue>937409</revenue>
<growth>30.07</growth>
</channels>
<top_products>
<sku>SKU-2900</sku>
<sales>81858</sales>
</top_products>
<top_products>
<sku>SKU-8266</sku>
<sales>123988</sales>
</top_products>
<top_products>
<sku>SKU-9969</sku>
<sales>32400</sales>
</top_products>
</sales_analytics>


[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:
contract_id = "CTR-640570"
effective_date = "2026-01-06"
term_months = 52
value = 450714
status = "pending"
[[parties]]
name = "Mitchell-Clark"
role = "party_a"

[[parties]]
name = "Simmons-Marquez"
role = "party_b"

[Assistant]
Approach:
1. Task: Convert contract 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:
contract_id: CTR-640570
parties:
- name: Mitchell-Clark
  role: party_a
- name: Simmons-Marquez
  role: party_b
effective_date: '2026-01-06'
term_months: 52
value: 450714
status: pending


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

[User] Output transaction record as YAML.

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

Output:
txn_id: TXN-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


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

[User] Generate product listing data in CSV format.

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

Output:
category,currency,is_available,name,price,product_id,rating,reviews,specs_dimensions,specs_weight_kg,stock
books,USD,True,Synergistic bottom-line conglomeration,609.49,PROD-842353,1.05,570,30x19x82cm,25.04,399
clothing,USD,True,Re-engineered interactive system engine,394.9,PROD-647841,1.7,933,48x35x42cm,36.99,675
books,USD,True,Monitored dedicated artificial intelligence,624.61,PROD-960822,2.28,987,95x89x10cm,41.75,553
electronics,USD,True,Quality-focused dynamic parallelism,355.92,PROD-301950,3.52,809,38x35x53cm,1.65,697


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

[User] Create a JSON representation of lab result.

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

Output:
{
  "result_id": "LAB-1120026",
  "patient_mrn": "MRN-824701",
  "order_date": "2026-01-06",
  "panel": "CBC",
  "results": [
    {
      "test": "Glucose",
      "value": 168.8,
      "unit": "g/dL",
      "flag": "high"
    },
    {
      "test": "Glucose",
      "value": 98.1,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "Glucose",
      "value": 137.9,
      "unit": "mg/dL",
      "flag": "normal"
    },
    {
      "test": "Glucose",
      "value": 107.7,
      "unit": "g/dL",
      "flag": "low"
    }
  ]
}


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

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

[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-530397",
  "student_id": "STU-509684",
  "course_id": "CRS-8191",
  "type": "quiz",
  "date": "2026-01-01",
  "scores": [
    {
      "question": 1,
      "points_earned": 3,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 5,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 6,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 0,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 3,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 6,
      "points_possible": 10
    },
    {
      "question": 9,
      "points_earned": 5,
      "points_possible": 10
    },
    {
      "question": 10,
      "points_earned": 10,
      "points_possible": 10
    },
    {
      "question": 11,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 12,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 13,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 14,
      "points_earned": 7,
      "points_possible": 10
    }
  ],
  "total_score": 91,
  "percentage": 61.03,
  "grade": "A"
}


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<prescription>
<rx_id>RX-3684509</rx_id>
<patient_mrn>MRN-644382</patient_mrn>
<prescriber>Chelsea Henson</prescriber>
<date>2026-01-04</date>
<medications>
<name>Atorvastatin</name>
<dosage>10mg</dosage>
<frequency>BID</frequency>
<quantity>60</quantity>
</medications>
<medications>
<name>Metformin</name>
<dosage>20mg</dosage>
<frequency>daily</frequency>
<quantity>60</quantity>
</medications>
<medications>
<name>Metformin</name>
<dosage>10mg</dosage>
<frequency>TID</frequency>
<quantity>60</quantity>
</medications>
</prescription>

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

Output:
{
  "rx_id": "RX-3684509",
  "patient_mrn": "MRN-644382",
  "prescriber": "Chelsea Henson",
  "date": "2026-01-04",
  "medications": [
    {
      "name": "Atorvastatin",
      "dosage": "10mg",
      "frequency": "BID",
      "quantity": 60
    },
    {
      "name": "Metformin",
      "dosage": "20mg",
      "frequency": "daily",
      "quantity": 60
    },
    {
      "name": "Metformin",
      "dosage": "10mg",
      "frequency": "TID",
      "quantity": 60
    }
  ]
}


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<review_id>REV-9701957</review_id>
<product_id>PROD-683988</product_id>
<user_id>4d7f9754-e296-4a29-967f-5c8de166a17c</user_id>
<rating>5</rating>
<title>Teach look history according want manager perform.</title>
<content>Admit large politics decide might Mr their. Hundred play I deal but player leader old. Then similar drug coach.</content>
<date>2026-01-03</date>
<verified_purchase>False</verified_purchase>
<helpful_votes>36</helpful_votes>
</customer_review>

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

Output:
{
  "review_id": "REV-9701957",
  "product_id": "PROD-683988",
  "user_id": "4d7f9754-e296-4a29-967f-5c8de166a17c",
  "rating": 5,
  "title": "Teach look history according want manager perform.",
  "content": "Admit large politics decide might Mr their. Hundred play I deal but player leader old. Then similar drug coach.",
  "date": "2026-01-03",
  "verified_purchase": false,
  "helpful_votes": 36
}


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

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

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

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

[User]
Reformat the data below from CSV to YAML:
conclusion,experiment_id,methodology_design,methodology_duration_days,methodology_sample_size,results,title
non-significant,EXP-942720,cohort,54,645,"[{""metric"": ""safety"", ""baseline"": 79.64, ""endpoint"": 26.86, ""p_value"": 0.2863}, {""metric"": ""safety"",",Effect of edge on when
non-significant,EXP-675903,RCT,91,295,"[{""metric"": ""safety"", ""baseline"": 67.47, ""endpoint"": 27.82, ""p_value"": 0.3043}, {""metric"": ""efficacy",Effect of state on parent
non-significant,EXP-554828,RCT,185,796,"[{""metric"": ""efficacy"", ""baseline"": 73.22, ""endpoint"": 12.15, ""p_value"": 0.241}, {""metric"": ""efficac",Effect of course on protect
non-significant,EXP-940975,RCT,81,638,"[{""metric"": ""safety"", ""baseline"": 96.66, ""endpoint"": 91.98, ""p_value"": 0.1953}, {""metric"": ""safety"",",Effect of sort on similar
significant,EXP-586715,observational,173,534,"[{""metric"": ""safety"", ""baseline"": 93.08, ""endpoint"": 21.72, ""p_value"": 0.1735}, {""metric"": ""efficacy",Effect of grow on opportunity

[Assistant]
Approach:
1. Task: Convert experiment result from CSV 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:
experiment_id: EXP-942720
title: Effect of edge on when
methodology:
  design: cohort
  sample_size: 645
  duration_days: 54
results:
- metric: safety
  baseline: 79.64
  endpoint: 26.86
  p_value: 0.2863
- metric: safety
  baseline: 55.57
  endpoint: 59.78
  p_value: 0.1705
- metric: efficacy
  baseline: 30.69
  endpoint: 27.4
  p_value: 0.1116
- metric: efficacy
  baseline: 32.07
  endpoint: 35.79
  p_value: 0.1946
conclusion: non-significant


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

[User] Generate contract data in CSV format.

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

Output:
contract_id,effective_date,parties,status,term_months,value
CTR-324198,2026-01-06,"[{""name"": ""Alvarado-Barnes"", ""role"": ""party_a""}, {""name"": ""Lopez, Price and Melendez"", ""role"": ""part",pending,34,725205
CTR-751913,2026-01-01,"[{""name"": ""Bradshaw Ltd"", ""role"": ""party_a""}, {""name"": ""Mccarthy-Reynolds"", ""role"": ""party_b""}]",active,17,869796
CTR-781204,2026-01-03,"[{""name"": ""Garcia-Diaz"", ""role"": ""party_a""}, {""name"": ""Cobb PLC"", ""role"": ""party_b""}]",executed,37,264429
CTR-452575,2026-01-04,"[{""name"": ""Mason-Roman"", ""role"": ""party_a""}, {""name"": ""Ray-Jackson"", ""role"": ""party_b""}]",executed,41,894105
CTR-916753,2026-01-05,"[{""name"": ""Williams Inc"", ""role"": ""party_a""}, {""name"": ""Beasley Inc"", ""role"": ""party_b""}]",pending,46,165654


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

[User] Output prescription as JSON.

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

Output:
{
  "rx_id": "RX-8706225",
  "patient_mrn": "MRN-970748",
  "prescriber": "Brady Keller",
  "date": "2026-01-01",
  "medications": [
    {
      "name": "Lisinopril",
      "dosage": "5mg",
      "frequency": "TID",
      "quantity": 30
    }
  ]
}


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

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

[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
0d66cadd-c42f-4e9b-ae40-46d71f47623d,"[{""sku"": ""SKU-83766"", ""qty"": 4, ""price"": 55.35}, {""sku"": ""SKU-77209"", ""qty"": 2, ""price"": 217.97}, {""",apple_pay,1600.85,34.84,2026-01-07T13:51:27.084892,602.79,TXN-59995807
820513fc-13c2-4f8a-9c0b-fcbfef7c4fce,"[{""sku"": ""SKU-66697"", ""qty"": 1, ""price"": 214.98}]",credit_card,1217.12,82.58,2026-01-07T13:51:27.085917,724.04,TXN-99092644
23763378-5791-4a97-987b-947ed01c30e8,"[{""sku"": ""SKU-90160"", ""qty"": 5, ""price"": 302.04}]",apple_pay,1469.64,36.27,2026-01-07T13:51:27.085964,1313.92,TXN-16643253
1019f8f4-9308-441a-918a-d30067b761e8,"[{""sku"": ""SKU-58300"", ""qty"": 1, ""price"": 184.1}, {""sku"": ""SKU-76581"", ""qty"": 2, ""price"": 50.41}, {""s",credit_card,892.61,130.95,2026-01-07T13:51:27.086001,316.1,TXN-28453489


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

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

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

Output:
openapi = "3.0.0"

[info]
title = "Secured well-modulated policy API"
version = "1.0.0"

[paths."/article".get]
summary = "During certainly full."
[[paths."/article".get.parameters]]
name = "param0"
in = "query"
type = "string"

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

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

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

[paths."/article".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 student assessment as YAML.

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

Output:
assessment_id: ASMT-549878
student_id: STU-264168
course_id: CRS-6692
type: assignment
date: '2026-01-01'
scores:
- question: 1
  points_earned: 7
  points_possible: 10
- question: 2
  points_earned: 1
  points_possible: 10
- question: 3
  points_earned: 9
  points_possible: 10
- question: 4
  points_earned: 1
  points_possible: 10
- question: 5
  points_earned: 4
  points_possible: 10
- question: 6
  points_earned: 1
  points_possible: 10
- question: 7
  points_earned: 1
  points_possible: 10
- question: 8
  points_earned: 1
  points_possible: 10
total_score: 70
percentage: 54.38
grade: C


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

[User] Create a CSV representation of financial report.

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

Output:
company,eps,expenses,metrics_profit_margin,metrics_roe,net_income,quarter,revenue,ticker
Tucker and Sons,3.52,61737533,24.27,16.15,12235621,Q4 2024,70279854,BPQE
"Walsh, Carrillo and Johnston",8.79,71388900,19.17,22.29,9923154,Q1 2021,3137025,CMIX
"Miller, Garcia and Moreno",6.86,41927303,18.81,17.0,356604,Q4 2020,37969724,EPHR
Newman LLC,7.52,31881083,15.66,14.73,12347450,Q2 2022,48361434,VPAY


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<clinical_note>
<note_id>CN-3041313</note_id>
<patient>
<mrn>MRN-164256</mrn>
<age>45</age>
<gender>F</gender>
</patient>
<encounter_date>2026-01-04</encounter_date>
<chief_complaint>fever</chief_complaint>
<vitals>
<bp>153/76</bp>

98

<temp_f>102.6</temp_f>
</vitals>
<assessment>
<problem>hypertension</problem>
<icd10>I84</icd10>
</assessment>
<assessment>
<problem>hypertension</problem>
<icd10>J93</icd10>
</assessment>
</clinical_note>

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

Output:
{
  "note_id": "CN-3041313",
  "patient": {
    "mrn": "MRN-164256",
    "age": 45,
    "gender": "F"
  },
  "encounter_date": "2026-01-04",
  "chief_complaint": "fever",
  "vitals": {
    "bp": "153/76",
    "hr": 98,
    "temp_f": 102.6
  },
  "assessment": [
    {
      "problem": "hypertension",
      "icd10": "I84"
    },
    {
      "problem": "hypertension",
      "icd10": "J93"
    }
  ]
}


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

[User] Generate api specification data in TOML format.

[Assistant]
Approach:
1. Task: Create api specification 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:
openapi = "3.0.0"

[info]
title = "Intuitive disintermediate website API"
version = "1.0.0"

[paths."/reality".get]
summary = "Activity public whole paper there relationship tas"
[[paths."/reality".get.parameters]]
name = "param0"
in = "query"
type = "string"

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

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

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


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

[User] Generate customer review data in YAML format.

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

Output:
review_id: REV-3637179
product_id: PROD-905516
user_id: cbc145e7-7f32-438c-ba90-61711bf65a15
rating: 1
title: Hand ok join you population.
content: Develop particularly receive thing process sister source. Ago short fact
  start meeting note need. However music factor my million scene use.
date: '2026-01-03'
verified_purchase: false
helpful_votes: 42