[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-23186111",
  "platform": "twitter",
  "user_id": "85951ac5-a9b8-4154-8edc-693bcde245cf",
  "username": "srodriguez",
  "content": "Stand leave decade year collection. Republican point edge yet business.\nSuffer accept central against. Cup theory mouth side message.\nConcern magazine exactly maybe oil difficult.",
  "timestamp": "2026-01-07T13:51:25.750515",
  "hashtags": [
    "#community",
    "#whatever"
  ],
  "engagement": {
    "likes": 4745,
    "shares": 251,
    "comments": 51
  }
}

[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-23186111</post_id>
<platform>twitter</platform>
<user_id>85951ac5-a9b8-4154-8edc-693bcde245cf</user_id>
<username>srodriguez</username>
<content>Stand leave decade year collection. Republican point edge yet business.
Suffer accept central against. Cup theory mouth side message.
Concern magazine exactly maybe oil difficult.</content>
<timestamp>2026-01-07T13:51:25.750515</timestamp>
<hashtags>#community</hashtags>
<hashtags>#whatever</hashtags>
<engagement>
<likes>4745</likes>
<shares>251</shares>
<comments>51</comments>
</engagement>
</social_media_post>


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

[User]
Convert the following XML to YAML:
<?xml version="1.0" encoding="UTF-8"?>
<financial_report>
<net_income>4233102</net_income>
<metrics>
<profit_margin>14.29</profit_margin>
<roe>18.28</roe>
</metrics>
<company>Blackwell, Simpson and Pace</company>
<eps>0.79</eps>
<expenses>41343491</expenses>
</financial_report>

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

Output:
net_income: 4233102
metrics:
  profit_margin: 14.29
  roe: 18.28
company: Blackwell, Simpson and Pace
eps: 0.79
expenses: 41343491


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

[User] Output student assessment as XML.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<student_assessment>
<assessment_id>ASMT-672485</assessment_id>
<student_id>STU-183204</student_id>
<course_id>CRS-8704</course_id>
<type>quiz</type>
<date>2026-01-01</date>
<scores>
<question>1</question>
<points_earned>0</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>3</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>10</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>8</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>7</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>7</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>9</question>
<points_earned>0</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>10</question>
<points_earned>5</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>11</question>
<points_earned>5</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>12</question>
<points_earned>0</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>82</total_score>
<percentage>72.48</percentage>
<grade>A</grade>
</student_assessment>


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

[User] Generate error log data in JSON format.

[Assistant]
Approach:
1. Task: Create error log 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:
{
  "error_id": "2d978d26-6fd7-4641-b202-43ebc0760711",
  "timestamp": "2026-01-07T13:51:26.663970",
  "level": "WARNING",
  "service": "someoneService",
  "message": "Inside live none value unit Republican black.",
  "stack_trace": [
    "at role.py:276",
    "at loss.py:371"
  ],
  "context": {
    "user_id": "26f1b94c-c76e-47ab-9121-a3f8ec11053f",
    "request_id": "ce096dca-f53f-40bf-822d-ed29d8ca8dd9"
  }
}


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

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

[Assistant]
Approach:
1. Task: Create sales analytics in JSON
2. Complexity: 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:
{
  "period": "September 2023",
  "total_revenue": 9732569,
  "units_sold": 38507,
  "channels": [
    {
      "name": "retail",
      "revenue": 4979277,
      "growth": 36.06
    },
    {
      "name": "wholesale",
      "revenue": 4800863,
      "growth": 8.87
    }
  ],
  "top_products": [
    {
      "sku": "SKU-5649",
      "sales": 311811
    },
    {
      "sku": "SKU-1879",
      "sales": 391924
    },
    {
      "sku": "SKU-4665",
      "sales": 317392
    }
  ]
}


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

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

[Assistant]
Approach:
1. Task: Create transaction record 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"?>
<transaction_record>
<customer_id>5642be10-2f96-4bf3-93bb-ea73b498db7e</customer_id>
<timestamp>2026-01-07T13:51:27.704310</timestamp>
<total>2159.3</total>
<tax>150.65</tax>
<items>
<sku>SKU-21107</sku>
<qty>2</qty>
<price>436.86</price>
</items>
<items>
<sku>SKU-34269</sku>
<qty>3</qty>
<price>260.71</price>
</items>
<items>
<sku>SKU-81249</sku>
<qty>3</qty>
<price>416.92</price>
</items>
<items>
<sku>SKU-97216</sku>
<qty>3</qty>
<price>177.96</price>
</items>
</transaction_record>


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<transaction_record>
<txn_id>TXN-31892506</txn_id>
<customer_id>6c5d6d8e-2901-438d-be6d-be57a13ea5ab</customer_id>
<timestamp>2026-01-07T13:51:25.485684</timestamp>
<items>
<sku>SKU-80058</sku>
<qty>4</qty>
<price>142.37</price>
</items>
<items>
<sku>SKU-53232</sku>
<qty>1</qty>
<price>151.54</price>
</items>
<subtotal>692.94</subtotal>
<tax>100.91</tax>
<total>1647.14</total>
<payment_method>credit_card</payment_method>
</transaction_record>


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

[User] Create a YAML representation of product listing.

[Assistant]
Approach:
1. Task: Create product listing 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:
product_id: PROD-239354
name: User-centric tertiary contingency
category: electronics
price: 998.51
currency: USD
stock: 842
is_available: true
rating: 2.36
reviews: 630
specs:
  weight_kg: 0.61
  dimensions: 88x23x10cm


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

[User] Create a CSV representation of product listing.

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

Output:
category,currency,is_available,name,price,product_id,rating,reviews,specs_dimensions,specs_weight_kg,stock
books,USD,True,Operative optimizing monitoring,967.35,PROD-480886,2.99,465,82x84x37cm,39.19,887
books,USD,True,Realigned asymmetric access,345.21,PROD-941472,1.79,865,77x97x74cm,35.76,973
clothing,USD,True,Balanced multi-tasking access,540.81,PROD-349522,3.1,496,19x71x60cm,26.53,542
clothing,USD,True,User-centric asymmetric challenge,932.63,PROD-803483,2.83,181,53x68x44cm,32.13,907


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

[User] Output transaction record as JSON.

[Assistant]
Approach:
1. Task: Create transaction record 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:
{
  "items": [
    {
      "sku": "SKU-71565",
      "qty": 1,
      "price": 387.38
    },
    {
      "sku": "SKU-23891",
      "qty": 1,
      "price": 432.74
    },
    {
      "sku": "SKU-77840",
      "qty": 1,
      "price": 463.12
    },
    {
      "sku": "SKU-27496",
      "qty": 3,
      "price": 295.3
    }
  ],
  "tax": 39.55,
  "total": 1865.58,
  "customer_id": "bf96f80b-072c-4f04-82b0-c235c01681a8"
}


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

[User]
Reformat the data below from XML to CSV:
<?xml version="1.0" encoding="UTF-8"?>
<clinical_note>
<note_id>CN-3508494</note_id>
<patient>
<mrn>MRN-721804</mrn>
<age>51</age>
<gender>F</gender>
</patient>
<encounter_date>2026-01-06</encounter_date>
<chief_complaint>chest pain</chief_complaint>
<vitals>
<bp>130/109</bp>

78

<temp_f>100.6</temp_f>
</vitals>
<assessment>
<problem>hypertension</problem>
<icd10>K96</icd10>
</assessment>
<assessment>
<problem>diabetes</problem>
<icd10>K86</icd10>
</assessment>
</clinical_note>

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

Output:
assessment,chief_complaint,encounter_date,note_id,patient_age,patient_gender,patient_mrn,vitals_bp,vitals_hr,vitals_temp_f
"[{""problem"": ""hypertension"", ""icd10"": ""K96""}, {""problem"": ""diabetes"", ""icd10"": ""K86""}]",chest pain,2026-01-06,CN-3508494,51,F,MRN-721804,130/109,78,100.6
"[{""problem"": ""diabetes"", ""icd10"": ""K17""}, {""problem"": ""diabetes"", ""icd10"": ""J67""}]",fever,2026-01-02,CN-1032122,33,M,MRN-189971,110/100,67,98.3
"[{""problem"": ""diabetes"", ""icd10"": ""I12""}, {""problem"": ""hypertension"", ""icd10"": ""I33""}]",fever,2026-01-03,CN-2816717,66,F,MRN-696491,159/73,67,100.0
"[{""problem"": ""diabetes"", ""icd10"": ""J14""}, {""problem"": ""hypertension"", ""icd10"": ""J24""}]",fever,2026-01-05,CN-9087372,53,M,MRN-814814,125/100,63,101.7


[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:2023.47681</paper_id>
<title>Devolved bi-directional info-mediaries</title>
<authors>
<name>Christian Randolph</name>
<affiliation>Hunt-Haynes</affiliation>
<email>patrickmaddox@example.net</email>
</authors>
<authors>
<name>Allen Lewis</name>
<affiliation>Owen PLC</affiliation>
<email>alexanderhenry@example.net</email>
</authors>
<authors>
<name>Cody Martin</name>
<affiliation>Mcknight PLC</affiliation>
<email>michael00@example.org</email>
</authors>
<abstract>Help field ten it. Pick eight last star pull. Act politics discuss.</abstract>
<keywords>hard</keywords>
<keywords>open</keywords>
<keywords>right</keywords>
<keywords>could</keywords>
<keywords>sea</keywords>
<publication>
<venue>Cell</venue>
<year>2023</year>
<doi>10.8057/cNYF</doi>
</publication>
<citations>411</citations>
<funding_source />
</research_paper>

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

Output:
{
  "paper_id": "arXiv:2023.47681",
  "title": "Devolved bi-directional info-mediaries",
  "authors": [
    {
      "name": "Christian Randolph",
      "affiliation": "Hunt-Haynes",
      "email": "patrickmaddox@example.net"
    },
    {
      "name": "Allen Lewis",
      "affiliation": "Owen PLC",
      "email": "alexanderhenry@example.net"
    },
    {
      "name": "Cody Martin",
      "affiliation": "Mcknight PLC",
      "email": "michael00@example.org"
    }
  ],
  "abstract": "Help field ten it. Pick eight last star pull. Act politics discuss.",
  "keywords": [
    "hard",
    "open",
    "right",
    "could",
    "sea"
  ],
  "publication": {
    "venue": "Cell",
    "year": 2023,
    "doi": "10.8057/cNYF"
  },
  "citations": 411,
  "funding_source": null
}


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

[User]
Transform this JSON data into TOML format:
{
  "error_id": "19a033e5-3ad7-4877-8a96-e38503174031",
  "timestamp": "2026-01-07T13:51:26.139508",
  "level": "ERROR",
  "service": "offService",
  "message": "Light method real rich option.",
  "stack_trace": [
    "at very.py:253",
    "at piece.py:469",
    "at home.py:259"
  ],
  "context": {
    "user_id": "45de80c2-9a4d-4d83-abf9-651f235bf4e8",
    "request_id": "53b4884a-375f-459c-a303-838dd3a8411e"
  }
}

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

Output:
error_id = "19a033e5-3ad7-4877-8a96-e38503174031"
timestamp = "2026-01-07T13:51:26.139508"
level = "ERROR"
service = "offService"
message = "Light method real rich option."
stack_trace = [ "at very.py:253", "at piece.py:469", "at home.py:259",]

[context]
user_id = "45de80c2-9a4d-4d83-abf9-651f235bf4e8"
request_id = "53b4884a-375f-459c-a303-838dd3a8411e"


[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
2026-01-06,"[{""name"": ""Metformin"", ""dosage"": ""10mg"", ""frequency"": ""BID"", ""quantity"": 30}, {""name"": ""Atorvastatin",MRN-990980,Andrew Kelly,RX-4278484
2026-01-04,"[{""name"": ""Atorvastatin"", ""dosage"": ""10mg"", ""frequency"": ""daily"", ""quantity"": 90}]",MRN-339837,Jessica Lyons,RX-2380006
2026-01-05,"[{""name"": ""Metformin"", ""dosage"": ""20mg"", ""frequency"": ""TID"", ""quantity"": 30}, {""name"": ""Metformin"", ",MRN-118858,Cory Jordan,RX-4834917


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

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

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

Output:
post_id = "POST-19844803"
platform = "instagram"
user_id = "eee48898-e428-4685-b6ea-d0074f4ffb8a"
username = "pinedaryan"
content = "Between past agree writer forget big. Simple glass protect job answer thank.\nGovernment prepare rather agency hard. Fear director room future hospital."
timestamp = "2026-01-07T13:51:25.753060"
hashtags = [ "#fast", "#imagine", "#carry",]

[engagement]
likes = 1299
shares = 900
comments = 90


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

[User]
Convert the following TOML to CSV:
assessment_id = "ASMT-946690"
student_id = "STU-268675"
course_id = "CRS-1216"
type = "assignment"
date = "2026-01-01"
total_score = 81
percentage = 50.49
grade = "B"
[[scores]]
question = 1
points_earned = 10
points_possible = 10

[[scores]]
question = 2
points_earned = 1
points_possible = 10

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

[[scores]]
question = 4
points_earned = 8
points_possible = 10

[[scores]]
question = 5
points_earned = 2
points_possible = 10

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

[[scores]]
question = 7
points_earned = 8
points_possible = 10

[[scores]]
question = 8
points_earned = 5
points_possible = 10

[[scores]]
question = 9
points_earned = 0
points_possible = 10

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

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

[[scores]]
question = 12
points_earned = 2
points_possible = 10

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

Output:
assessment_id,code,course_id,credits,date,grade,grading_final,grading_homework,grading_midterm,instructor,percentage,schedule,scores,student_id,term,title,total_score,type
ASMT-946690,,CRS-1216,,2026-01-01,B,,,,,50.49,,"[{""question"": 1, ""points_earned"": 10, ""points_possible"": 10}, {""question"": 2, ""points_earned"": 1, ""p",STU-268675,,,81,assignment
,UNR189,CRS-6658,4,,,40,30,30,Mr. Tyler Roach,,"[{""week"": 1, ""topic"": ""pass""}, {""week"": 2, ""topic"": ""road""}, {""week"": 3, ""topic"": ""if""}, {""week"": 4,",,,Spring 2022,Phased high-level throughput 101,,
,OOA488,CRS-9526,4,,,40,30,30,Eric Robinson,,"[{""week"": 1, ""topic"": ""side""}, {""week"": 2, ""topic"": ""final""}, {""week"": 3, ""topic"": ""others""}, {""week",,,Spring 2024,Secured system-worthy software 101,,
,BAA477,CRS-8756,4,,,40,30,30,Theresa Farrell,,"[{""week"": 1, ""topic"": ""politics""}, {""week"": 2, ""topic"": ""be""}, {""week"": 3, ""topic"": ""security""}, {""w",,,Spring 2020,Reduced client-server algorithm 101,,


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

[User]
Convert the following JSON to XML:
{
  "contract_id": "CTR-784600",
  "parties": [
    {
      "name": "Snyder-Thornton",
      "role": "party_a"
    },
    {
      "name": "Oliver Group",
      "role": "party_b"
    }
  ],
  "effective_date": "2026-01-06",
  "term_months": 16,
  "value": 53888,
  "status": "active"
}

[Assistant]
Approach:
1. Task: Convert contract 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"?>
<contract>
<contract_id>CTR-784600</contract_id>
<parties>
<name>Snyder-Thornton</name>
<role>party_a</role>
</parties>
<parties>
<name>Oliver Group</name>
<role>party_b</role>
</parties>
<effective_date>2026-01-06</effective_date>
<term_months>16</term_months>
<value>53888</value>
<status>active</status>
</contract>


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

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

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

Output:
abstract,authors,citations,content,date,funding_source,keywords,paper_id,publication_doi,publication_venue,publication_year,title,user_id
,,,It herself scene five side support onto. Shake fear western believe. Say fact shoulder investment te,2026-01-04,,,,,,,,d6e6e646-61a4-4af9-a9a1-d03d234244eb
Sport eight century too everyone. Direction very relate order toward.,"[{""name"": ""Joseph Orozco"", ""affiliation"": ""Flores, Clark and Krause"", ""email"": ""crawfordheidi@exampl",321,,,None,"[""history"", ""information"", ""discuss"", ""fine""]",arXiv:2021.57597,10.7112/HFuP,Nature,2020,Inverse non-volatile protocol,
Start old reflect agreement heavy water. Action should travel career. Difficult arrive act summer pr,"[{""name"": ""Lisa Richmond"", ""affiliation"": ""Smith-Taylor"", ""email"": ""brownjonathan@example.net""}, {""n",33,,,None,"[""training"", ""stage"", ""support""]",arXiv:2020.79870,10.7699/PryY,Nature,2024,Focused attitude-oriented website,


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

[User] Create a JSON representation of customer review.

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

Output:
{
  "title": "Exactly almost full new record save.",
  "date": "2026-01-02",
  "product_id": "PROD-922306",
  "content": "Arrive much low will teach. By possible nature learn could. Act hot whole guy experience.\nIdentify world fight stock. Force fear soon. Author night think."
}


[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:
{
  "timestamp": "2026-01-07T13:51:26.818902",
  "context": {
    "user_id": "3a96bf92-d9b7-4f9e-91da-6a15b590d5cf",
    "request_id": "d8c0cfbc-2ae8-46b8-8db8-ee3a71153dc5"
  },
  "error_id": "de32926d-7560-4176-8c16-f346784a78af"
}

[Assistant]
Approach:
1. Task: Convert error log 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"?>
<error_log>
<timestamp>2026-01-07T13:51:26.818902</timestamp>
<context>
<user_id>3a96bf92-d9b7-4f9e-91da-6a15b590d5cf</user_id>
<request_id>d8c0cfbc-2ae8-46b8-8db8-ee3a71153dc5</request_id>
</context>
<error_id>de32926d-7560-4176-8c16-f346784a78af</error_id>
</error_log>


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

[User]
Convert the following CSV to JSON:
abstract,authors,citations,funding_source,keywords,paper_id,publication_doi,publication_venue,publication_year,title
"Account fish possible democratic ok no. Accept short mention guy.
Place finish religious mean end su","[{""name"": ""Julie Mclaughlin"", ""affiliation"": ""Andrews Group"", ""email"": ""brianna81@example.org""}, {""n",60,Diaz-Salinas,"[""thank"", ""far"", ""fund"", ""get"", ""role""]",arXiv:2024.67669,10.1349/JgWc,Nature,2023,Triple-buffered dedicated knowledgebase
Participant forward situation her issue how. So building radio executive recent interesting signific,"[{""name"": ""Rachel Greene"", ""affiliation"": ""Murphy, Thomas and Rogers"", ""email"": ""lisa81@example.com""",282,Burns-Sullivan,"[""crime"", ""enough"", ""dinner"", ""baby""]",arXiv:2023.52259,10.5475/XGYe,Cell,2024,Multi-channeled systematic productivity
Loss drug address issue stock.,"[{""name"": ""Kathleen Anderson"", ""affiliation"": ""Vega-Johnson"", ""email"": ""danielcurtis@example.net""}, ",255,Everett-Weaver,"[""outside"", ""program"", ""size"", ""employee""]",arXiv:2023.27140,10.9793/jSfj,Cell,2021,Exclusive static intranet

[Assistant]
Approach:
1. Task: Convert research paper from CSV 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:2024.67669",
  "title": "Triple-buffered dedicated knowledgebase",
  "authors": [
    {
      "name": "Julie Mclaughlin",
      "affiliation": "Andrews Group",
      "email": "brianna81@example.org"
    },
    {
      "name": "Peggy Kramer",
      "affiliation": "Beasley, Edwards and Webb",
      "email": "susan35@example.com"
    }
  ],
  "abstract": "Account fish possible democratic ok no. Accept short mention guy.\nPlace finish religious mean end success. Travel into music they.",
  "keywords": [
    "thank",
    "far",
    "fund",
    "get",
    "role"
  ],
  "publication": {
    "venue": "Nature",
    "year": 2023,
    "doi": "10.1349/JgWc"
  },
  "citations": 60,
  "funding_source": "Diaz-Salinas"
}


[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: 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:
title: Exactly almost full new record save.
date: '2026-01-02'
product_id: PROD-922306
content: 'Arrive much low will teach. By possible nature learn could. Act hot whole
  guy experience.

  Identify world fight stock. Force fear soon. Author night think.'


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

[User] Generate lab result data in CSV format.

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

Output:
order_date,panel,patient_mrn,result_id,results
2026-01-04,CMP,MRN-369371,LAB-2983714,"[{""test"": ""Hemoglobin"", ""value"": 97.6, ""unit"": ""g/dL"", ""flag"": ""normal""}, {""test"": ""WBC"", ""value"": 6"
2026-01-06,CMP,MRN-845661,LAB-9796047,"[{""test"": ""Glucose"", ""value"": 51.5, ""unit"": ""mg/dL"", ""flag"": ""normal""}, {""test"": ""Glucose"", ""value"":"
2026-01-05,CMP,MRN-555169,LAB-9578711,"[{""test"": ""WBC"", ""value"": 59.0, ""unit"": ""mg/dL"", ""flag"": ""low""}, {""test"": ""Hemoglobin"", ""value"": 70."
2026-01-06,Lipid,MRN-411824,LAB-5603358,"[{""test"": ""Glucose"", ""value"": 68.0, ""unit"": ""mg/dL"", ""flag"": ""low""}, {""test"": ""Glucose"", ""value"": 18"


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

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

[Assistant]
Approach:
1. Task: Create social media post 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:
{
  "post_id": "POST-20150897",
  "platform": "instagram",
  "user_id": "ace3958f-4578-4576-9236-9cbfc1f62953",
  "username": "spatrick",
  "content": "About industry woman size. Available box return camera public time. Establish outside ability sport describe air who.\nCertain miss girl different both wife. Blood relationship if model.",
  "timestamp": "2026-01-07T13:51:25.995017",
  "hashtags": [
    "#share",
    "#prevent",
    "#entire",
    "#owner"
  ],
  "engagement": {
    "likes": 3129,
    "shares": 891,
    "comments": 28
  }
}


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<error_log>
<error_id>3ee04eb7-6a96-4708-8070-7816402d081f</error_id>
<timestamp>2026-01-07T13:51:26.236854</timestamp>
<level>ERROR</level>
<service>checkService</service>
<message>Base information cell production decade back.</message>
<stack_trace>at quality.py:463</stack_trace>
<stack_trace>at but.py:317</stack_trace>
<context>
<user_id>9d5113f2-65b2-4f61-b9b2-2b011fc1bc1b</user_id>
<request_id>f5a78ca9-3dcc-4c14-bcea-f5b7936cdde5</request_id>
</context>
</error_log>

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

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


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

[User]
Reformat the data below from YAML to XML:
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

[Assistant]
Approach:
1. Task: Convert financial report 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"?>
<financial_report>
<company>Taylor Ltd</company>
<ticker>AOED</ticker>
<quarter>Q1 2024</quarter>
<revenue>69752271</revenue>
<expenses>52626087</expenses>
<net_income>18580243</net_income>
<eps>1.63</eps>
<metrics>
<profit_margin>23.4</profit_margin>
<roe>21.22</roe>
</metrics>
</financial_report>


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<experiment_result>
<experiment_id>EXP-500587</experiment_id>
<title>Effect of seem on put</title>
<methodology>
<design>cohort</design>
<sample_size>806</sample_size>
<duration_days>332</duration_days>
</methodology>
<results>
<metric>safety</metric>
<baseline>59.15</baseline>
<endpoint>80.7</endpoint>
<p_value>0.0751</p_value>
</results>
<results>
<metric>efficacy</metric>
<baseline>25.67</baseline>
<endpoint>99.48</endpoint>
<p_value>0.1142</p_value>
</results>
<results>
<metric>safety</metric>
<baseline>72.29</baseline>
<endpoint>18.69</endpoint>
<p_value>0.2768</p_value>
</results>
<results>
<metric>safety</metric>
<baseline>16.24</baseline>
<endpoint>94.98</endpoint>
<p_value>0.315</p_value>
</results>
<conclusion>significant</conclusion>
</experiment_result>

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

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

[User] Generate api specification data in YAML format.

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

Output:
openapi: 3.0.0
info:
  title: Streamlined logistical help-desk API
  version: 1.0.0
paths:
  /grow:
    get:
      summary: Will entire deep source history.
      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 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"?>
<clinical_note>
<note_id>CN-5754690</note_id>
<patient>
<mrn>MRN-521303</mrn>
<age>32</age>
<gender>M</gender>
</patient>
<encounter_date>2026-01-05</encounter_date>
<chief_complaint>fever</chief_complaint>
<vitals>
<bp>101/104</bp>

85

<temp_f>99.3</temp_f>
</vitals>
<assessment>
<problem>diabetes</problem>
<icd10>K80</icd10>
</assessment>
</clinical_note>

[Assistant]
Approach:
1. Task: Convert clinical note 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:
{
  "note_id": "CN-5754690",
  "patient": {
    "mrn": "MRN-521303",
    "age": 32,
    "gender": "M"
  },
  "encounter_date": "2026-01-05",
  "chief_complaint": "fever",
  "vitals": {
    "bp": "101/104",
    "hr": 85,
    "temp_f": 99.3
  },
  "assessment": [
    {
      "problem": "diabetes",
      "icd10": "K80"
    }
  ]
}


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<research_paper>
<paper_id>arXiv:2020.86983</paper_id>
<title>Reverse-engineered national Graphical User Interface</title>
<authors>
<name>Wesley Murphy</name>
<affiliation>Nunez, Meyer and Snow</affiliation>
<email>nina74@example.net</email>
</authors>
<authors>
<name>Richard Morgan</name>
<affiliation>Hall-Jones</affiliation>
<email>justin85@example.org</email>
</authors>
<authors>
<name>Anthony Johnson</name>
<affiliation>Kelley-Murphy</affiliation>
<email>srichmond@example.com</email>
</authors>
<abstract>Sure finally site who truth. Close stop when low. Check news mother democratic.</abstract>
<keywords>old</keywords>
<keywords>indeed</keywords>
<keywords>general</keywords>
<keywords>claim</keywords>
<keywords>every</keywords>
<publication>
<venue>Nature</venue>
<year>2024</year>
<doi>10.2539/QMDE</doi>
</publication>
<citations>221</citations>
<funding_source />
</research_paper>

[Assistant]
Approach:
1. Task: Convert research paper 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:
{
  "paper_id": "arXiv:2020.86983",
  "title": "Reverse-engineered national Graphical User Interface",
  "authors": [
    {
      "name": "Wesley Murphy",
      "affiliation": "Nunez, Meyer and Snow",
      "email": "nina74@example.net"
    },
    {
      "name": "Richard Morgan",
      "affiliation": "Hall-Jones",
      "email": "justin85@example.org"
    },
    {
      "name": "Anthony Johnson",
      "affiliation": "Kelley-Murphy",
      "email": "srichmond@example.com"
    }
  ],
  "abstract": "Sure finally site who truth. Close stop when low. Check news mother democratic.",
  "keywords": [
    "old",
    "indeed",
    "general",
    "claim",
    "every"
  ],
  "publication": {
    "venue": "Nature",
    "year": 2024,
    "doi": "10.2539/QMDE"
  },
  "citations": 221,
  "funding_source": null
}


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<transaction_record>
<timestamp>2026-01-07T13:51:25.400660</timestamp>
<items>
<sku>SKU-41387</sku>
<qty>1</qty>
<price>386.75</price>
</items>
<txn_id>TXN-44773795</txn_id>
<customer_id>acd22e98-51a5-48fa-ad66-a69b8fba3f2b</customer_id>
<tax>171.02</tax>
</transaction_record>

[Assistant]
Approach:
1. Task: Convert transaction record 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:
{
  "timestamp": "2026-01-07T13:51:25.400660",
  "items": [
    {
      "sku": "SKU-41387",
      "qty": 1,
      "price": 386.75
    }
  ],
  "txn_id": "TXN-44773795",
  "customer_id": "acd22e98-51a5-48fa-ad66-a69b8fba3f2b",
  "tax": 171.02
}


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

[User] Output customer review as YAML.

[Assistant]
Approach:
1. Task: Create customer review in YAML
2. Complexity: 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-1417017
product_id: PROD-561113
user_id: 58368812-841f-4b65-a63f-bf59f81a4b62
rating: 2
title: Miss entire student source like impact.
content: Particularly myself court bring vote business boy lawyer. Economy name wonder
  thank a charge. Successful value site thus. Exist election about task reason.
date: '2026-01-04'
verified_purchase: false
helpful_votes: 17


[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"?>
<lab_result>
<patient_mrn>MRN-119365</patient_mrn>
<order_date>2026-01-05</order_date>
<results>
<test>Glucose</test>
<value>134.6</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>69.4</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Glucose</test>
<value>85.6</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>WBC</test>
<value>69.6</value>
<unit>mg/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>79.1</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
</lab_result>

[Assistant]
Approach:
1. Task: Convert lab result from XML to 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:
{
  "patient_mrn": "MRN-119365",
  "order_date": "2026-01-05",
  "results": [
    {
      "test": "Glucose",
      "value": 134.6,
      "unit": "g/dL",
      "flag": "high"
    },
    {
      "test": "Hemoglobin",
      "value": 69.4,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "Glucose",
      "value": 85.6,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "WBC",
      "value": 69.6,
      "unit": "mg/dL",
      "flag": "low"
    },
    {
      "test": "Hemoglobin",
      "value": 79.1,
      "unit": "g/dL",
      "flag": "high"
    }
  ]
}


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

[User] Generate transaction record data in JSON format.

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


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

[User]
Convert the following TOML to YAML:
review_id = "REV-5911912"
product_id = "PROD-652506"
user_id = "e81c58cf-1a13-4302-a93a-5e1fbbfd28db"
rating = 3
title = "Their husband whole president threat argue."
content = "Happen member step can deal animal fine. Like among study from book.\nDemocratic significant every sport next want. List religious computer rise wrong."
date = "2026-01-02"
verified_purchase = true
helpful_votes = 61

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

Output:
review_id: REV-5911912
product_id: PROD-652506
user_id: e81c58cf-1a13-4302-a93a-5e1fbbfd28db
rating: 3
title: Their husband whole president threat argue.
content: 'Happen member step can deal animal fine. Like among study from book.

  Democratic significant every sport next want. List religious computer rise wrong.'
date: '2026-01-02'
verified_purchase: true
helpful_votes: 61


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

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

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


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

[User] Output clinical note as XML.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<clinical_note>
<note_id>CN-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>


[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:
{
  "rx_id": "RX-3472120",
  "patient_mrn": "MRN-972429",
  "prescriber": "Matthew Bennett",
  "date": "2026-01-06",
  "medications": [
    {
      "name": "Atorvastatin",
      "dosage": "10mg",
      "frequency": "daily",
      "quantity": 60
    }
  ]
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<prescription>
<rx_id>RX-3472120</rx_id>
<patient_mrn>MRN-972429</patient_mrn>
<prescriber>Matthew Bennett</prescriber>
<date>2026-01-06</date>
<medications>
<name>Atorvastatin</name>
<dosage>10mg</dosage>
<frequency>daily</frequency>
<quantity>60</quantity>
</medications>
</prescription>


[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: 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:
code,course_id,credits,grading_final,grading_homework,grading_midterm,instructor,schedule,term,title
,CRS-7759,4,40,30,30,Matthew Johnson,"[{""week"": 1, ""topic"": ""meet""}, {""week"": 2, ""topic"": ""around""}, {""week"": 3, ""topic"": ""college""}, {""we",,
JNK131,CRS-1132,4,40,30,30,Nicholas Miranda,"[{""week"": 1, ""topic"": ""glass""}, {""week"": 2, ""topic"": ""avoid""}, {""week"": 3, ""topic"": ""message""}, {""we",Spring 2023,Object-based exuding productivity 101
GEH438,CRS-5068,4,40,30,30,Daniel Gardner,"[{""week"": 1, ""topic"": ""between""}, {""week"": 2, ""topic"": ""fine""}, {""week"": 3, ""topic"": ""finally""}, {""w",Spring 2023,Integrated discrete interface 101
FIZ162,CRS-9744,4,40,30,30,Mary Schultz,"[{""week"": 1, ""topic"": ""personal""}, {""week"": 2, ""topic"": ""pay""}, {""week"": 3, ""topic"": ""rest""}, {""week",Spring 2020,Seamless zero tolerance task-force 101


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

[User]
Convert the following JSON to XML:
{
  "paper_id": "arXiv:2020.93852",
  "title": "Reactive solution-oriented circuit",
  "authors": [
    {
      "name": "Jennifer Gray",
      "affiliation": "Bryant, Lewis and Wells",
      "email": "spalmer@example.com"
    },
    {
      "name": "David Brown",
      "affiliation": "Cortez, Cook and Ross",
      "email": "melvin21@example.com"
    }
  ],
  "abstract": "Law fund huge better or. Federal forward north law. Work available call never.\nCarry cultural day front resource write. Southern white pattern fear.",
  "keywords": [
    "wind",
    "wife",
    "report",
    "financial"
  ],
  "publication": {
    "venue": "Cell",
    "year": 2023,
    "doi": "10.1277/DPuH"
  },
  "citations": 45,
  "funding_source": null
}

[Assistant]
Approach:
1. Task: Convert research paper 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"?>
<research_paper>
<paper_id>arXiv:2020.93852</paper_id>
<title>Reactive solution-oriented circuit</title>
<authors>
<name>Jennifer Gray</name>
<affiliation>Bryant, Lewis and Wells</affiliation>
<email>spalmer@example.com</email>
</authors>
<authors>
<name>David Brown</name>
<affiliation>Cortez, Cook and Ross</affiliation>
<email>melvin21@example.com</email>
</authors>
<abstract>Law fund huge better or. Federal forward north law. Work available call never.
Carry cultural day front resource write. Southern white pattern fear.</abstract>
<keywords>wind</keywords>
<keywords>wife</keywords>
<keywords>report</keywords>
<keywords>financial</keywords>
<publication>
<venue>Cell</venue>
<year>2023</year>
<doi>10.1277/DPuH</doi>
</publication>
<citations>45</citations>
<funding_source />
</research_paper>


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

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

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

Output:
period = "September 2022"
total_revenue = 4880286
units_sold = 74173
[[channels]]
name = "retail"
revenue = 2000312
growth = 0.96

[[channels]]
name = "wholesale"
revenue = 3751658
growth = -3.19

[[top_products]]
sku = "SKU-6977"
sales = 264067

[[top_products]]
sku = "SKU-7032"
sales = 443161

[[top_products]]
sku = "SKU-1793"
sales = 209512


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

[User] Output student assessment as CSV.

[Assistant]
Approach:
1. Task: Create student assessment in CSV
2. Complexity: 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_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-946690,,CRS-1216,,2026-01-01,B,,,,,50.49,,"[{""question"": 1, ""points_earned"": 10, ""points_possible"": 10}, {""question"": 2, ""points_earned"": 1, ""p",STU-268675,,,81,assignment
,UST237,CRS-1318,3,,,40,30,30,Stephen Andrews DVM,,"[{""week"": 1, ""topic"": ""hour""}, {""week"": 2, ""topic"": ""like""}, {""week"": 3, ""topic"": ""news""}, {""week"": ",,,Spring 2024,Balanced high-level functionalities 101,,
,OQM217,CRS-1503,3,,,40,30,30,Jennifer Wade,,"[{""week"": 1, ""topic"": ""certain""}, {""week"": 2, ""topic"": ""also""}, {""week"": 3, ""topic"": ""late""}, {""week",,,Fall 2024,Distributed system-worthy encryption 101,,
,VNX493,CRS-1388,4,,,40,30,30,Jennifer Howard,,"[{""week"": 1, ""topic"": ""above""}, {""week"": 2, ""topic"": ""politics""}, {""week"": 3, ""topic"": ""second""}, {""",,,Spring 2023,Focused grid-enabled Local Area Network 101,,


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<date>2026-01-04</date>
<user_id>d6e6e646-61a4-4af9-a9a1-d03d234244eb</user_id>
<content>It herself scene five side support onto. Shake fear western believe. Say fact shoulder investment television pretty suffer.
Ground listen official hand at indeed. Effort thus wife control.</content>
</customer_review>

[Assistant]
Approach:
1. Task: Convert customer review 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:
{
  "date": "2026-01-04",
  "user_id": "d6e6e646-61a4-4af9-a9a1-d03d234244eb",
  "content": "It herself scene five side support onto. Shake fear western believe. Say fact shoulder investment television pretty suffer.\nGround listen official hand at indeed. Effort thus wife control."
}


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

[User]
Transform this XML data into YAML format:
<?xml version="1.0" encoding="UTF-8"?>
<sales_analytics>
<period>March 2022</period>
<total_revenue>6503980</total_revenue>
<units_sold>7670</units_sold>
<channels>
<name>retail</name>
<revenue>3279241</revenue>
<growth>22.76</growth>
</channels>
<channels>
<name>wholesale</name>
<revenue>1469640</revenue>
<growth>16.07</growth>
</channels>
<top_products>
<sku>SKU-8081</sku>
<sales>71747</sales>
</top_products>
<top_products>
<sku>SKU-8211</sku>
<sales>475825</sales>
</top_products>
<top_products>
<sku>SKU-4565</sku>
<sales>485553</sales>
</top_products>
</sales_analytics>

[Assistant]
Approach:
1. Task: Convert sales analytics 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:
period: March 2022
total_revenue: 6503980
units_sold: 7670
channels:
- name: retail
  revenue: 3279241
  growth: 22.76
- name: wholesale
  revenue: 1469640
  growth: 16.07
top_products:
- sku: SKU-8081
  sales: 71747
- sku: SKU-8211
  sales: 475825
- sku: SKU-4565
  sales: 485553


[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"?>
<news_article>
<article_id>ART-3682408</article_id>
<headline>Decentralized stable neural-net</headline>
<author>Thomas Acevedo</author>
<published>2026-01-01T11:30:40.673887</published>

Business

<content>Cold trial recognize improve nice between these. Happy herself suggest impact tell easy.
Start movie up social real effort. Onto federal prepare class direction rest.
News party school five bit. Trouble box year how.
Pressure respond nature. Prepare ball put happen.</content>
<tags>movie</tags>
<tags>it</tags>
<tags>chance</tags>
<views>12438</views>
<shares>1329</shares>
</news_article>

[Assistant]
Approach:
1. Task: Convert news article 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:
{
  "article_id": "ART-3682408",
  "headline": "Decentralized stable neural-net",
  "author": "Thomas Acevedo",
  "published": "2026-01-01T11:30:40.673887",
  "section": "Business",
  "content": "Cold trial recognize improve nice between these. Happy herself suggest impact tell easy.\nStart movie up social real effort. Onto federal prepare class direction rest.\nNews party school five bit. Trouble box year how.\nPressure respond nature. Prepare ball put happen.",
  "tags": [
    "movie",
    "it",
    "chance"
  ],
  "views": 12438,
  "shares": 1329
}


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

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

Output:
rx_id: RX-9458448
patient_mrn: MRN-362998
prescriber: Courtney Hansen
date: '2026-01-02'
medications:
- name: Lisinopril
  dosage: 10mg
  frequency: BID
  quantity: 30


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

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


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

[User] Output transaction record as XML.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<transaction_record>
<txn_id>TXN-72432123</txn_id>
<customer_id>d14101dd-b47b-4916-b7e5-0ad54eefbb55</customer_id>
<timestamp>2026-01-07T13:51:26.808008</timestamp>
<items>
<sku>SKU-29323</sku>
<qty>2</qty>
<price>70.49</price>
</items>
<items>
<sku>SKU-65460</sku>
<qty>3</qty>
<price>466.32</price>
</items>
<items>
<sku>SKU-59283</sku>
<qty>1</qty>
<price>149.96</price>
</items>
<items>
<sku>SKU-68579</sku>
<qty>2</qty>
<price>13.04</price>
</items>
<subtotal>1301.16</subtotal>
<tax>124.54</tax>
<total>239.49</total>
<payment_method>apple_pay</payment_method>
</transaction_record>


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

[User]
Convert the following JSON to YAML:
{
  "result_id": "LAB-3990665",
  "patient_mrn": "MRN-508219",
  "order_date": "2026-01-04",
  "panel": "Lipid",
  "results": [
    {
      "test": "Hemoglobin",
      "value": 80.7,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "Glucose",
      "value": 90.9,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 138.0,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "WBC",
      "value": 131.3,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "Glucose",
      "value": 172.4,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "WBC",
      "value": 151.6,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "Hemoglobin",
      "value": 188.6,
      "unit": "g/dL",
      "flag": "high"
    }
  ]
}

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

Output:
result_id: LAB-3990665
patient_mrn: MRN-508219
order_date: '2026-01-04'
panel: Lipid
results:
- test: Hemoglobin
  value: 80.7
  unit: g/dL
  flag: low
- test: Glucose
  value: 90.9
  unit: g/dL
  flag: normal
- test: Hemoglobin
  value: 138.0
  unit: g/dL
  flag: low
- test: WBC
  value: 131.3
  unit: g/dL
  flag: normal
- test: Glucose
  value: 172.4
  unit: g/dL
  flag: normal
- test: WBC
  value: 151.6
  unit: g/dL
  flag: low
- test: Hemoglobin
  value: 188.6
  unit: g/dL
  flag: high


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

[User] Create a YAML representation of research paper.

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

Output:
paper_id: arXiv:2023.21424
title: Cross-platform fault-tolerant circuit
authors:
- name: Charlotte Sellers
  affiliation: Armstrong-Marks
  email: weaverelizabeth@example.com
- name: Cynthia Johnston MD
  affiliation: Rogers Inc
  email: ccastaneda@example.org
- name: Robert Velasquez
  affiliation: Alvarado LLC
  email: psullivan@example.net
abstract: Truth himself long country car environment. Free design relate hope admit
  learn identify.
keywords:
- share
- feeling
- environmental
publication:
  venue: Science
  year: 2022
  doi: 10.6091/Sfwn
citations: 477
funding_source: Barker-Wise


[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"?>
<lab_result>
<result_id>LAB-9047593</result_id>
<patient_mrn>MRN-478989</patient_mrn>
<order_date>2026-01-06</order_date>
<panel>CMP</panel>
<results>
<test>Hemoglobin</test>
<value>171.8</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>WBC</test>
<value>58.0</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>WBC</test>
<value>78.7</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Glucose</test>
<value>138.7</value>
<unit>mg/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>51.5</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>141.9</value>
<unit>mg/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>191.7</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
</lab_result>

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

Output:
{
  "result_id": "LAB-9047593",
  "patient_mrn": "MRN-478989",
  "order_date": "2026-01-06",
  "panel": "CMP",
  "results": [
    {
      "test": "Hemoglobin",
      "value": 171.8,
      "unit": "mg/dL",
      "flag": "normal"
    },
    {
      "test": "WBC",
      "value": 58.0,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "WBC",
      "value": 78.7,
      "unit": "mg/dL",
      "flag": "normal"
    },
    {
      "test": "Glucose",
      "value": 138.7,
      "unit": "mg/dL",
      "flag": "low"
    },
    {
      "test": "Hemoglobin",
      "value": 51.5,
      "unit": "g/dL",
      "flag": "high"
    },
    {
      "test": "Hemoglobin",
      "value": 141.9,
      "unit": "mg/dL",
      "flag": "low"
    },
    {
      "test": "Hemoglobin",
      "value": 191.7,
      "unit": "mg/dL",
      "flag": "high"
    }
  ]
}


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<clinical_note>
<note_id>CN-7237025</note_id>
<patient>
<mrn>MRN-276187</mrn>
<age>53</age>
<gender>F</gender>
</patient>
<encounter_date>2026-01-06</encounter_date>
<chief_complaint>fever</chief_complaint>
<vitals>
<bp>95/82</bp>

103

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

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


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

[User] Output clinical note as XML.

[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-1129442</note_id>
<patient>
<mrn>MRN-895859</mrn>
<age>79</age>
<gender>M</gender>
</patient>
<encounter_date>2026-01-03</encounter_date>
<chief_complaint>headache</chief_complaint>
<vitals>
<bp>127/81</bp>

117

<temp_f>102.4</temp_f>
</vitals>
<assessment>
<problem>hypertension</problem>
<icd10>J46</icd10>
</assessment>
</clinical_note>


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

[User]
Convert the following JSON to XML:
{
  "product_id": "PROD-141484",
  "name": "Managed bandwidth-monitored focus group",
  "category": "books",
  "price": 751.35,
  "currency": "USD",
  "stock": 108,
  "is_available": true,
  "rating": 2.94,
  "reviews": 250,
  "specs": {
    "weight_kg": 6.41,
    "dimensions": "15x82x35cm"
  }
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<product_listing>
<product_id>PROD-141484</product_id>
<name>Managed bandwidth-monitored focus group</name>
<category>books</category>
<price>751.35</price>
<currency>USD</currency>
<stock>108</stock>
<is_available>True</is_available>
<rating>2.94</rating>
<reviews>250</reviews>
<specs>
<weight_kg>6.41</weight_kg>
<dimensions>15x82x35cm</dimensions>
</specs>
</product_listing>


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<transaction_record>
<txn_id>TXN-79156891</txn_id>
<customer_id>5450ecc9-30b8-498f-a527-04ec3de16dd8</customer_id>
<timestamp>2026-01-07T13:51:26.258900</timestamp>
<items>
<sku>SKU-81880</sku>
<qty>4</qty>
<price>401.7</price>
</items>
<items>
<sku>SKU-99718</sku>
<qty>5</qty>
<price>334.37</price>
</items>
<items>
<sku>SKU-65882</sku>
<qty>3</qty>
<price>292.8</price>
</items>
<items>
<sku>SKU-88201</sku>
<qty>2</qty>
<price>114.91</price>
</items>
<subtotal>258.62</subtotal>
<tax>22.79</tax>
<total>1713.37</total>
<payment_method>paypal</payment_method>
</transaction_record>


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

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

[Assistant]
Approach:
1. Task: Create social media post 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"?>
<social_media_post>
<post_id>POST-18209344</post_id>
<platform>facebook</platform>
<user_id>8880ae5d-22ce-466e-ac5d-224201417b5e</user_id>
<username>xmcbride</username>
<content>Determine live compare center as direction. Eye experience low wear. If south level.
Worry expect style camera. Scene majority pay voice television professor.</content>
<timestamp>2026-01-07T13:51:27.602464</timestamp>
<hashtags>#culture</hashtags>
<hashtags>#whole</hashtags>
<hashtags>#central</hashtags>
<engagement>
<likes>2214</likes>
<shares>878</shares>
<comments>146</comments>
</engagement>
</social_media_post>


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

[User] Create a CSV representation of 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
Woods and Sons,8.84,48284794,12.42,23.86,2937548,Q1 2020,42196406,ZCNM
Mccullough-Johnson,3.29,11563013,26.21,13.94,4117277,Q1 2020,6857674,DPES
Stewart LLC,2.14,11938447,29.71,11.96,10336255,Q3 2023,46802875,KLMH
White and Sons,6.27,65693877,17.06,7.33,1849662,Q4 2023,54335533,JDVS
Barnes-Carter,8.04,17747243,11.66,7.91,5504686,Q4 2020,81696490,YHYS


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<review_id>REV-1417017</review_id>
<product_id>PROD-561113</product_id>
<user_id>58368812-841f-4b65-a63f-bf59f81a4b62</user_id>
<rating>2</rating>
<title>Miss entire student source like impact.</title>
<content>Particularly myself court bring vote business boy lawyer. Economy name wonder thank a charge. Successful value site thus. Exist election about task reason.</content>
<date>2026-01-04</date>
<verified_purchase>False</verified_purchase>
<helpful_votes>17</helpful_votes>
</customer_review>

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

Output:
{
  "review_id": "REV-1417017",
  "product_id": "PROD-561113",
  "user_id": "58368812-841f-4b65-a63f-bf59f81a4b62",
  "rating": 2,
  "title": "Miss entire student source like impact.",
  "content": "Particularly myself court bring vote business boy lawyer. Economy name wonder thank a charge. Successful value site thus. Exist election about task reason.",
  "date": "2026-01-04",
  "verified_purchase": false,
  "helpful_votes": 17
}


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

[User] Produce a YAML document for a contract.

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

Output:
contract_id: CTR-313579
parties:
- name: Roberts, Newton and Ortiz
  role: party_a
- name: Garcia PLC
  role: party_b
effective_date: '2026-01-01'
term_months: 55
value: 108642
status: active


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<student_assessment>
<assessment_id>ASMT-458464</assessment_id>
<student_id>STU-453066</student_id>
<course_id>CRS-7675</course_id>
<type>assignment</type>
<date>2026-01-06</date>
<scores>
<question>1</question>
<points_earned>0</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>3</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>4</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>4</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>0</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>3</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>7</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>9</question>
<points_earned>8</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>67</total_score>
<percentage>65.79</percentage>
<grade>B</grade>
</student_assessment>


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

[User] Output financial report as CSV.

[Assistant]
Approach:
1. Task: Create financial report in CSV
2. Complexity: 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:
company,eps,expenses,metrics_profit_margin,metrics_roe,net_income,quarter,revenue,ticker
Clark-Pearson,,54498119,,,,,,OKCY
Vasquez-Rivera,2.43,27692062,7.78,17.16,10417989,Q4 2022,52572071,BITM
"Moreno, Sanchez and Barker",8.48,3120252,28.3,10.73,2344594,Q3 2021,51185832,CDDE


[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"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Stand-alone dedicated complexity API</title>
<version>1.0.0</version>
</info>
<paths>
</hear>
<get>
<summary>Chance cultural sort including high.</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>
<//hear>
</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": "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]
Reformat the data below from JSON to XML:
{
  "openapi": "3.0.0",
  "info": {
    "title": "Distributed high-level website API",
    "version": "1.0.0"
  },
  "paths": {
    "/next": {
      "get": {
        "summary": "Movie my movie common adult.",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          },
          {
            "name": "param1",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  }
}

[Assistant]
Approach:
1. Task: Convert api specification from JSON to XML
2. Complexity: 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"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Distributed high-level website API</title>
<version>1.0.0</version>
</info>
<paths>
</next>
<get>
<summary>Movie my movie common adult.</summary>
<parameters>
<name>param0</name>
<in>query</in>
<type>string</type>
</parameters>
<parameters>
<name>param1</name>
<in>query</in>
<type>string</type>
</parameters>
<responses>
<200>
<description>Success</description>
</200>
<400>
<description>Bad Request</description>
</400>
</responses>
</get>
<//next>
</paths>
</api_specification>


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

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

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

Output:
category,currency,is_available,name,price,product_id,rating,reviews,specs_dimensions,specs_weight_kg,stock
electronics,USD,True,Seamless optimal task-force,975.8,PROD-831490,2.71,121,52x27x46cm,17.77,924
books,USD,True,Multi-tiered 3rdgeneration moderator,891.91,PROD-947142,2.08,340,70x36x54cm,29.77,598
clothing,USD,True,Decentralized foreground model,869.65,PROD-350123,3.01,559,16x68x66cm,39.07,657


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

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

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

Output:
product_id = "PROD-524008"
name = "Implemented multimedia focus group"
category = "electronics"
price = 524.9
currency = "USD"
stock = 714
is_available = true
rating = 2.56
reviews = 633

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


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

[User]
Transform this JSON data into XML format:
{
  "course_id": "CRS-3440",
  "code": "KLD251",
  "title": "Reverse-engineered foreground infrastructure 101",
  "instructor": "Courtney Escobar",
  "credits": 4,
  "term": "Spring 2022",
  "schedule": [
    {
      "week": 1,
      "topic": "despite"
    },
    {
      "week": 2,
      "topic": "choose"
    },
    {
      "week": 3,
      "topic": "action"
    },
    {
      "week": 4,
      "topic": "couple"
    },
    {
      "week": 5,
      "topic": "big"
    },
    {
      "week": 6,
      "topic": "trade"
    },
    {
      "week": 7,
      "topic": "measure"
    },
    {
      "week": 8,
      "topic": "music"
    }
  ],
  "grading": {
    "homework": 30,
    "midterm": 30,
    "final": 40
  }
}

[Assistant]
Approach:
1. Task: Convert course syllabus 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"?>
<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 JSON format. Think step-by-step, then generate syntactically perfect JSON.

[User] Create a JSON representation of clinical note.

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


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

[User] Generate student assessment data in YAML format.

[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-817642
student_id: STU-222420
course_id: CRS-8326
type: assignment
date: '2026-01-03'
scores:
- question: 1
  points_earned: 9
  points_possible: 10
- question: 2
  points_earned: 10
  points_possible: 10
- question: 3
  points_earned: 0
  points_possible: 10
- question: 4
  points_earned: 2
  points_possible: 10
- question: 5
  points_earned: 7
  points_possible: 10
- question: 6
  points_earned: 4
  points_possible: 10
- question: 7
  points_earned: 10
  points_possible: 10
- question: 8
  points_earned: 7
  points_possible: 10
total_score: 60
percentage: 56.31
grade: A


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

[User] Create a YAML representation of prescription.

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

Output:
rx_id: RX-1565761
patient_mrn: MRN-226686
prescriber: Regina Martin
date: '2026-01-03'
medications:
- name: Metformin
  dosage: 20mg
  frequency: TID
  quantity: 60
- name: Atorvastatin
  dosage: 20mg
  frequency: BID
  quantity: 90


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

[User] Generate sales analytics data in TOML format.

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

Output:
period = "July 2021"
total_revenue = 5979422
units_sold = 82076
[[channels]]
name = "retail"
revenue = 3460112
growth = 36.85

[[channels]]
name = "online"
revenue = 3983364
growth = 5.55

[[top_products]]
sku = "SKU-1065"
sales = 105510

[[top_products]]
sku = "SKU-4043"
sales = 281142

[[top_products]]
sku = "SKU-1338"
sales = 43006


[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: 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 = "Centralized web-enabled hardware API"
version = "1.0.0"

[paths."/improve".get]
summary = "Act attention yes herself significant recent."
[[paths."/improve".get.parameters]]
name = "param0"
in = "query"
type = "string"

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

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

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

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


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

[User]
Convert the following JSON to XML:
{
  "quarter": "Q3 2022",
  "company": "Dunn-Byrd",
  "expenses": 58548919,
  "eps": 9.56,
  "ticker": "ATGQ"
}

[Assistant]
Approach:
1. Task: Convert financial report 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"?>
<financial_report>
<quarter>Q3 2022</quarter>
<company>Dunn-Byrd</company>
<expenses>58548919</expenses>
<eps>9.56</eps>
<ticker>ATGQ</ticker>
</financial_report>


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

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

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

Output:
{
  "assessment_id": "ASMT-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 YAML format. Think step-by-step, then generate syntactically perfect YAML.

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

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

Output:
post_id: POST-19357850
platform: twitter
user_id: 664b960b-1331-492f-addd-e9b37d21656f
username: mbaldwin
content: Forward front agreement cover hour we remember ask. Read glass few word mother
  deep TV.
timestamp: '2026-01-07T13:51:27.605837'
hashtags:
- '#cost'
- '#he'
- '#relationship'
engagement:
  likes: 304
  shares: 796
  comments: 124


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

[User] Output clinical note as YAML.

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

Output:
encounter_date: '2026-01-03'
note_id: CN-2646438
patient:
  mrn: MRN-771263
  age: 41
  gender: M


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

[User] Generate error log data in JSON format.

[Assistant]
Approach:
1. Task: Create error log 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:
{
  "error_id": "3ee04eb7-6a96-4708-8070-7816402d081f",
  "timestamp": "2026-01-07T13:51:26.236854",
  "level": "ERROR",
  "service": "checkService",
  "message": "Base information cell production decade back.",
  "stack_trace": [
    "at quality.py:463",
    "at but.py:317"
  ],
  "context": {
    "user_id": "9d5113f2-65b2-4f61-b9b2-2b011fc1bc1b",
    "request_id": "f5a78ca9-3dcc-4c14-bcea-f5b7936cdde5"
  }
}


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<financial_report>
<expenses>54498119</expenses>
<ticker>OKCY</ticker>
<company>Clark-Pearson</company>
</financial_report>

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

Output:
{
  "expenses": 54498119,
  "ticker": "OKCY",
  "company": "Clark-Pearson"
}


[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-86945311</post_id>
<platform>facebook</platform>
<user_id>b9da037c-f6cd-4ced-8c95-ca7562cf6118</user_id>
<username>martinsteven</username>
<content>Forget late prevent year cold able arrive. Few possible himself sing community. Activity campaign sure south. Chance on none line best magazine education.</content>
<timestamp>2026-01-07T13:51:26.810240</timestamp>
<hashtags>#drop</hashtags>
<hashtags>#consider</hashtags>
<hashtags>#nature</hashtags>
<hashtags>#all</hashtags>
<engagement>
<likes>3344</likes>
<shares>900</shares>
<comments>482</comments>
</engagement>
</social_media_post>