[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-4911961</result_id>
<patient_mrn>MRN-250544</patient_mrn>
<order_date>2026-01-03</order_date>
<panel>CBC</panel>
<results>
<test>Hemoglobin</test>
<value>121.1</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>77.4</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Glucose</test>
<value>107.3</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Glucose</test>
<value>172.8</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>166.2</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>140.6</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>WBC</test>
<value>120.4</value>
<unit>mg/dL</unit>
<flag>normal</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-4911961",
  "patient_mrn": "MRN-250544",
  "order_date": "2026-01-03",
  "panel": "CBC",
  "results": [
    {
      "test": "Hemoglobin",
      "value": 121.1,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 77.4,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "Glucose",
      "value": 107.3,
      "unit": "g/dL",
      "flag": "high"
    },
    {
      "test": "Glucose",
      "value": 172.8,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 166.2,
      "unit": "mg/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 140.6,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "WBC",
      "value": 120.4,
      "unit": "mg/dL",
      "flag": "normal"
    }
  ]
}


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

[User] Create a TOML representation of api specification.

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

Output:
openapi = "3.0.0"

[info]
title = "Organic analyzing strategy API"
version = "1.0.0"

[paths."/similar".get]
summary = "Natural see lot recently."
[[paths."/similar".get.parameters]]
name = "param0"
in = "query"
type = "string"

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

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

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


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

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

[Assistant]
Approach:
1. Task: Create social media post 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:
post_id = "POST-93814090"
platform = "facebook"
user_id = "6a4446e9-5537-4ba1-bf03-5db2d36e07b9"
username = "tonyaguzman"
content = "Subject watch side owner new. Quality million clear hand clearly environmental. Forget face machine little check."
timestamp = "2026-01-07T13:51:26.454281"
hashtags = [ "#plan", "#area", "#foreign",]

[engagement]
likes = 5322
shares = 327
comments = 152


[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
2026-01-04,"[{""name"": ""Lisinopril"", ""dosage"": ""20mg"", ""frequency"": ""TID"", ""quantity"": 30}, {""name"": ""Metformin"",",MRN-740510,William Hebert,RX-7328466
2026-01-02,"[{""name"": ""Metformin"", ""dosage"": ""20mg"", ""frequency"": ""daily"", ""quantity"": 90}, {""name"": ""Atorvastat",MRN-724944,Lori Hoffman,RX-4648169
2026-01-01,"[{""name"": ""Lisinopril"", ""dosage"": ""10mg"", ""frequency"": ""TID"", ""quantity"": 90}, {""name"": ""Metformin"",",MRN-660152,Spencer Jones,RX-2159087
2026-01-02,"[{""name"": ""Lisinopril"", ""dosage"": ""20mg"", ""frequency"": ""BID"", ""quantity"": 30}, {""name"": ""Lisinopril""",MRN-977247,Dawn Landry,RX-8707601


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<contract>
<contract_id>CTR-640570</contract_id>
<parties>
<name>Mitchell-Clark</name>
<role>party_a</role>
</parties>
<parties>
<name>Simmons-Marquez</name>
<role>party_b</role>
</parties>
<effective_date>2026-01-06</effective_date>
<term_months>52</term_months>
<value>450714</value>
<status>pending</status>
</contract>

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

Output:
{
  "contract_id": "CTR-640570",
  "parties": [
    {
      "name": "Mitchell-Clark",
      "role": "party_a"
    },
    {
      "name": "Simmons-Marquez",
      "role": "party_b"
    }
  ],
  "effective_date": "2026-01-06",
  "term_months": 52,
  "value": 450714,
  "status": "pending"
}


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

[User] Output clinical note as CSV.

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

Output:
assessment,chief_complaint,encounter_date,note_id,patient_age,patient_gender,patient_mrn,vitals_bp,vitals_hr,vitals_temp_f
"[{""problem"": ""diabetes"", ""icd10"": ""I12""}, {""problem"": ""diabetes"", ""icd10"": ""K62""}]",chest pain,2026-01-02,CN-4315709,89,M,MRN-534874,165/61,112,99.4
"[{""problem"": ""hypertension"", ""icd10"": ""J81""}]",chest pain,2026-01-04,CN-6665857,20,F,MRN-120861,94/88,100,99.8
"[{""problem"": ""hypertension"", ""icd10"": ""K64""}, {""problem"": ""diabetes"", ""icd10"": ""K61""}]",fever,2026-01-01,CN-9714125,46,F,MRN-417686,114/85,88,97.7
"[{""problem"": ""diabetes"", ""icd10"": ""I15""}, {""problem"": ""diabetes"", ""icd10"": ""I86""}, {""problem"": ""diab",chest pain,2026-01-02,CN-5835083,30,M,MRN-466005,116/72,80,97.4


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

[User] Output experiment result as CSV.

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

Output:
conclusion,experiment_id,methodology_design,methodology_duration_days,methodology_sample_size,results,title
significant,EXP-500587,cohort,332,806,"[{""metric"": ""safety"", ""baseline"": 59.15, ""endpoint"": 80.7, ""p_value"": 0.0751}, {""metric"": ""efficacy""",Effect of seem on put
non-significant,EXP-866330,RCT,189,113,"[{""metric"": ""safety"", ""baseline"": 21.66, ""endpoint"": 72.95, ""p_value"": 0.4354}, {""metric"": ""safety"",",Effect of she on appear
non-significant,EXP-755861,cohort,72,554,"[{""metric"": ""safety"", ""baseline"": 32.87, ""endpoint"": 56.17, ""p_value"": 0.0583}, {""metric"": ""safety"",",Effect of hospital on agent


[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-1120026</result_id>
<patient_mrn>MRN-824701</patient_mrn>
<order_date>2026-01-06</order_date>
<panel>CBC</panel>
<results>
<test>Glucose</test>
<value>168.8</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Glucose</test>
<value>98.1</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Glucose</test>
<value>137.9</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Glucose</test>
<value>107.7</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
</lab_result>

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


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

[User] Create a XML representation of financial report.

[Assistant]
Approach:
1. Task: Create financial report in XML
2. Complexity: 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"?>
<financial_report>
<company>Hardy-Nguyen</company>
<ticker>ZAMS</ticker>
<quarter>Q3 2024</quarter>
<revenue>23201336</revenue>
<expenses>30350118</expenses>
<net_income>14673850</net_income>
<eps>3.22</eps>
<metrics>
<profit_margin>18.82</profit_margin>
<roe>21.21</roe>
</metrics>
</financial_report>


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

[User] Produce a TOML document for a clinical note.

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

Output:
note_id = "CN-8348908"
encounter_date = "2026-01-06"
chief_complaint = "fever"
[[assessment]]
problem = "diabetes"
icd10 = "J60"

[[assessment]]
problem = "diabetes"
icd10 = "K69"

[[assessment]]
problem = "hypertension"
icd10 = "J80"

[patient]
mrn = "MRN-109351"
age = 84
gender = "F"

[vitals]
bp = "157/81"
hr = 101
temp_f = 97.1


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

[User] Output transaction record as YAML.

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

Output:
txn_id: TXN-95106885
customer_id: 9090a0a6-3421-4a93-9d6e-78b6a1f8fed7
timestamp: '2026-01-07T13:51:27.692524'
items:
- sku: SKU-33525
  qty: 3
  price: 130.6
subtotal: 793.41
tax: 85.16
total: 1645.24
payment_method: apple_pay


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

[User] Create a CSV representation of prescription.

[Assistant]
Approach:
1. Task: Create prescription 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,date,funding_source,keywords,medications,paper_id,prescriber,publication_doi,publication_venue,publication_year,title
,,,2026-01-03,,,"[{""name"": ""Atorvastatin"", ""dosage"": ""5mg"", ""frequency"": ""BID"", ""quantity"": 30}]",,Isaac Howard,,,,
"Owner threat quite because kid force. Already minute fine effort.
Cell thing wife.","[{""name"": ""Ashley Leon"", ""affiliation"": ""Moore Group"", ""email"": ""zsmith@example.com""}, {""name"": ""Apr",343,,None,"[""system"", ""shake"", ""human"", ""without"", ""anyone""]",,arXiv:2021.63755,,10.4751/DMfb,Nature,2022,Inverse bifurcated solution
Return mission friend. Beautiful buy certainly body effort claim. Prevent land national military off,"[{""name"": ""Vickie Lara"", ""affiliation"": ""Fuller Inc"", ""email"": ""uperry@example.net""}, {""name"": ""Thom",306,,Lynn-James,"[""government"", ""ready"", ""conference"", ""more"", ""Republican""]",,arXiv:2021.91225,,10.8838/APmf,Cell,2022,Open-source solution-oriented open system


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

[User] Generate error log data in YAML format.

[Assistant]
Approach:
1. Task: Create error log in YAML
2. Complexity: 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:
error_id: c6e14566-270a-4a5f-a250-5239ca9174ac
timestamp: '2026-01-07T13:51:26.338486'
level: ERROR
service: humanService
message: Fear she east talk better central.
stack_trace:
- at college.py:218
- at economy.py:209
- at let.py:252
- at whole.py:18
context:
  user_id: bda2bdb3-cc4e-4711-8927-aa42dc72d462
  request_id: c7d51186-07ee-4743-a193-c5688ac0d6c5


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

[User] Generate student assessment data in CSV format.

[Assistant]
Approach:
1. Task: Create student assessment in CSV
2. Complexity: 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-852879,,CRS-9070,,2026-01-04,C,,,,,53.23,,"[{""question"": 1, ""points_earned"": 4, ""points_possible"": 10}, {""question"": 2, ""points_earned"": 10, ""p",STU-517758,,,58,exam
,PVU113,CRS-2544,4,,,40,30,30,Ashley Morris,,"[{""week"": 1, ""topic"": ""soon""}, {""week"": 2, ""topic"": ""long""}, {""week"": 3, ""topic"": ""own""}, {""week"": 4",,,Fall 2021,Versatile 5thgeneration application 101,,
,CYE324,CRS-2291,3,,,40,30,30,Joshua Johnson,,"[{""week"": 1, ""topic"": ""site""}, {""week"": 2, ""topic"": ""population""}, {""week"": 3, ""topic"": ""close""}, {""",,,Spring 2021,Universal global capacity 101,,


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

[User]
Reformat the data below from TOML to CSV:
txn_id = "TXN-13058367"
customer_id = "852e4544-1bd4-44f1-abf0-2ff01b4a4792"
timestamp = "2026-01-07T13:51:26.835091"
subtotal = 408.33
tax = 11.32
total = 1142.29
payment_method = "paypal"
[[items]]
sku = "SKU-47822"
qty = 3
price = 237.72

[[items]]
sku = "SKU-38430"
qty = 4
price = 285.9

[[items]]
sku = "SKU-22327"
qty = 1
price = 141.71

[Assistant]
Approach:
1. Task: Convert transaction record 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:
customer_id,items,payment_method,subtotal,tax,timestamp,total,txn_id
852e4544-1bd4-44f1-abf0-2ff01b4a4792,"[{""sku"": ""SKU-47822"", ""qty"": 3, ""price"": 237.72}, {""sku"": ""SKU-38430"", ""qty"": 4, ""price"": 285.9}, {""",paypal,408.33,11.32,2026-01-07T13:51:26.835091,1142.29,TXN-13058367
71aeac04-7023-4605-b6b3-0bb6ceecce85,"[{""sku"": ""SKU-42903"", ""qty"": 1, ""price"": 23.1}]",apple_pay,366.27,115.81,2026-01-07T13:51:26.837134,736.69,TXN-61906496
3fe3095c-7cf8-4dcb-b878-6803e1dad007,"[{""sku"": ""SKU-91221"", ""qty"": 4, ""price"": 349.85}, {""sku"": ""SKU-18747"", ""qty"": 2, ""price"": 439.71}, {",paypal,1687.63,22.51,2026-01-07T13:51:26.837216,753.99,TXN-62431039


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

[User] Generate error log data in TOML format.

[Assistant]
Approach:
1. Task: Create error log 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:
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 XML format. Think step-by-step, then generate syntactically perfect XML.

[User] Generate prescription data in XML format.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<prescription>
<date>2026-01-06</date>
<patient_mrn>MRN-259808</patient_mrn>
<rx_id>RX-8539167</rx_id>
<prescriber>Joseph Griffin</prescriber>
<medications>
<name>Atorvastatin</name>
<dosage>10mg</dosage>
<frequency>daily</frequency>
<quantity>90</quantity>
</medications>
<medications>
<name>Lisinopril</name>
<dosage>10mg</dosage>
<frequency>TID</frequency>
<quantity>30</quantity>
</medications>
<medications>
<name>Metformin</name>
<dosage>5mg</dosage>
<frequency>BID</frequency>
<quantity>30</quantity>
</medications>
</prescription>


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

[User] Create a CSV representation of news article.

[Assistant]
Approach:
1. Task: Create news article in CSV
2. Complexity: 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,author,authors,citations,funding_source,headline,keywords,paper_id,publication_doi,publication_venue,publication_year,published,tags,title
,Jenna Bryant,,,,Secured composite leverage,,,,,,2026-01-04T22:19:16.750289,"[""most"", ""off"", ""shoulder""]",
Find send compare professor now too site. Feeling order training keep enough wife.,,"[{""name"": ""Melvin Chavez"", ""affiliation"": ""Davis, Rodriguez and Strong"", ""email"": ""nancy81@example.n",159,Smith-Reynolds,,"[""choice"", ""name"", ""agent""]",arXiv:2022.34035,10.1840/qQXX,Science,2023,,,Managed maximized circuit
Tax ever pressure peace to cold. Position clear share even impact. Small collection artist military.,,"[{""name"": ""Nicole Choi"", ""affiliation"": ""Cross Inc"", ""email"": ""travisromero@example.org""}, {""name"": ",236,None,,"[""number"", ""class"", ""son"", ""water"", ""whom""]",arXiv:2023.14920,10.6351/SatP,Nature,2022,,,Monitored next generation throughput
Organization especially watch participant play rule world. Life worry relationship sit security can.,,"[{""name"": ""Kimberly Howard"", ""affiliation"": ""Carr, Bailey and Kerr"", ""email"": ""nlamb@example.com""}, ",132,None,,"[""fine"", ""growth"", ""meet"", ""example""]",arXiv:2024.81719,10.8535/nopw,Cell,2020,,,Multi-layered homogeneous moratorium
On laugh order ahead. Without against among hope discuss. Summer none community charge.,,"[{""name"": ""Joshua Cunningham"", ""affiliation"": ""Carrillo and Sons"", ""email"": ""zibarra@example.net""}, ",89,None,,"[""recently"", ""right"", ""poor""]",arXiv:2020.53133,10.6671/pBFP,Science,2023,,,Cross-platform bifurcated encoding


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

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

[Assistant]
Approach:
1. Task: Create product listing 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:
{
  "category": "electronics",
  "specs": {
    "weight_kg": 38.59,
    "dimensions": "23x92x45cm"
  },
  "stock": 596,
  "price": 218.58
}


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

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

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


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

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

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

Output:
{
  "result_id": "LAB-5387789",
  "patient_mrn": "MRN-887521",
  "order_date": "2026-01-05",
  "panel": "CBC",
  "results": [
    {
      "test": "WBC",
      "value": 66.6,
      "unit": "mg/dL",
      "flag": "normal"
    },
    {
      "test": "Glucose",
      "value": 111.4,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "Hemoglobin",
      "value": 168.1,
      "unit": "g/dL",
      "flag": "high"
    },
    {
      "test": "Hemoglobin",
      "value": 136.7,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "WBC",
      "value": 148.7,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "Glucose",
      "value": 86.9,
      "unit": "mg/dL",
      "flag": "normal"
    }
  ]
}


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

[User]
Reformat the data below from JSON to XML:
{
  "review_id": "REV-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 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"?>
<customer_review>
<review_id>REV-5911912</review_id>
<product_id>PROD-652506</product_id>
<user_id>e81c58cf-1a13-4302-a93a-5e1fbbfd28db</user_id>
<rating>3</rating>
<title>Their husband whole president threat argue.</title>
<content>Happen member step can deal animal fine. Like among study from book.
Democratic significant every sport next want. List religious computer rise wrong.</content>
<date>2026-01-02</date>
<verified_purchase>True</verified_purchase>
<helpful_votes>61</helpful_votes>
</customer_review>


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

[User] Generate clinical note data in CSV format.

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

Output:
assessment,chief_complaint,encounter_date,note_id,patient_age,patient_gender,patient_mrn,vitals_bp,vitals_hr,vitals_temp_f
"[{""problem"": ""hypertension"", ""icd10"": ""K41""}, {""problem"": ""hypertension"", ""icd10"": ""J91""}, {""problem",chest pain,,CN-6154695,67,F,MRN-705297,97/107,107,99.6
"[{""problem"": ""hypertension"", ""icd10"": ""I84""}, {""problem"": ""diabetes"", ""icd10"": ""J84""}, {""problem"": """,chest pain,2026-01-05,CN-6112020,31,M,MRN-385062,105/75,109,102.7
"[{""problem"": ""diabetes"", ""icd10"": ""K70""}]",fever,2026-01-01,CN-7729424,32,M,MRN-419634,157/86,69,99.2


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

[User] Generate research paper data in CSV format.

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

Output:
abstract,authors,citations,funding_source,keywords,paper_id,publication_doi,publication_venue,publication_year,title
Before today call network oil future. Admit itself catch song various rest. Personal worry quality d,"[{""name"": ""Keith Wilcox"", ""affiliation"": ""Ruiz-Torres"", ""email"": ""martinstephanie@example.org""}, {""n",274,None,"[""song"", ""TV"", ""southern""]",arXiv:2020.59386,10.1369/MikD,Nature,2020,Self-enabling demand-driven application
Never life mention fine authority perform but none. But speak above question bit recent.,"[{""name"": ""Pamela Stewart"", ""affiliation"": ""Lawson, James and Proctor"", ""email"": ""wrichards@example.",168,"Martinez, Waller and Campbell","[""number"", ""letter"", ""collection"", ""exactly"", ""sister""]",arXiv:2021.22947,10.2262/DCQg,Cell,2022,Sharable human-resource Graphical User Interface
Eat by tend hit. Mouth trouble visit pretty from single yet. Election very effort beyond beyond fine,"[{""name"": ""Eric Huff"", ""affiliation"": ""Lawson Ltd"", ""email"": ""quinnmichelle@example.com""}, {""name"": ",494,None,"[""but"", ""keep"", ""look""]",arXiv:2023.10174,10.1376/uMTP,Science,2020,Ergonomic full-range product
"Reveal almost no answer yard use special current.
Outside spend sometimes painting. House force up s","[{""name"": ""Gina Glover"", ""affiliation"": ""Grimes-Arnold"", ""email"": ""trussell@example.com""}, {""name"": ",267,Romero PLC,"[""reality"", ""set"", ""challenge"", ""fill"", ""partner""]",arXiv:2021.25152,10.8359/Htvs,Science,2023,Multi-tiered client-server website


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

[User] Output api specification as JSON.

[Assistant]
Approach:
1. Task: Create api specification in JSON
2. Complexity: 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:
{
  "openapi": "3.0.0",
  "info": {
    "title": "Synchronized holistic archive API",
    "version": "1.0.0"
  },
  "paths": {
    "/policy": {
      "get": {
        "summary": "Red reason present loss yeah run.",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  }
}


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

[User]
Convert the following JSON to TOML:
{
  "revenue": 65816825,
  "ticker": "IQTA",
  "expenses": 77578182,
  "company": "Ramos-Wallace"
}

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

Output:
revenue = 65816825
ticker = "IQTA"
expenses = 77578182
company = "Ramos-Wallace"


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

[User] Output customer review as CSV.

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

Output:
category,content,currency,date,helpful_votes,is_available,name,price,product_id,rating,review_id,reviews,specs_dimensions,specs_weight_kg,stock,title,user_id,verified_purchase
,Particularly myself court bring vote business boy lawyer. Economy name wonder thank a charge. Succes,,2026-01-04,17,,,,PROD-561113,2,REV-1417017,,,,,Miss entire student source like impact.,58368812-841f-4b65-a63f-bf59f81a4b62,False
electronics,,USD,,,True,Progressive explicit firmware,282.24,PROD-630832,1.82,,321,62x27x93cm,14.9,610,,,
clothing,,USD,,,True,Ergonomic intangible productivity,190.24,PROD-476742,4.2,,46,22x54x55cm,5.36,935,,,
books,,USD,,,True,Ameliorated next generation middleware,576.11,PROD-236753,1.21,,763,78x75x29cm,28.35,900,,,


[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"?>
<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>

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

Output:
{
  "post_id": "POST-18209344",
  "platform": "facebook",
  "user_id": "8880ae5d-22ce-466e-ac5d-224201417b5e",
  "username": "xmcbride",
  "content": "Determine live compare center as direction. Eye experience low wear. If south level.\nWorry expect style camera. Scene majority pay voice television professor.",
  "timestamp": "2026-01-07T13:51:27.602464",
  "hashtags": [
    "#culture",
    "#whole",
    "#central"
  ],
  "engagement": {
    "likes": 2214,
    "shares": 878,
    "comments": 146
  }
}


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

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

[Assistant]
Approach:
1. Task: Create api specification 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:
paths:
  /population:
    get:
      summary: Lead room develop man according street century.
      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
info:
  title: Ameliorated radical initiative API
  version: 1.0.0
openapi: 3.0.0


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

[User] Generate product listing data in XML format.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<product_listing>
<product_id>PROD-524008</product_id>
<name>Implemented multimedia focus group</name>
<category>electronics</category>
<price>524.9</price>
<currency>USD</currency>
<stock>714</stock>
<is_available>True</is_available>
<rating>2.56</rating>
<reviews>633</reviews>
<specs>
<weight_kg>40.1</weight_kg>
<dimensions>80x44x77cm</dimensions>
</specs>
</product_listing>


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

[User] Output contract as YAML.

[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-324198
parties:
- name: Alvarado-Barnes
  role: party_a
- name: Lopez, Price and Melendez
  role: party_b
effective_date: '2026-01-06'
term_months: 34
value: 725205
status: pending


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

[User] Output lab result as TOML.

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

Output:
result_id = "LAB-3941350"
patient_mrn = "MRN-739958"
order_date = "2026-01-01"
panel = "CBC"
[[results]]
test = "Glucose"
value = 134.1
unit = "mg/dL"
flag = "high"

[[results]]
test = "WBC"
value = 188.7
unit = "g/dL"
flag = "low"

[[results]]
test = "Hemoglobin"
value = 142.9
unit = "mg/dL"
flag = "high"

[[results]]
test = "Hemoglobin"
value = 117.3
unit = "g/dL"
flag = "normal"

[[results]]
test = "Glucose"
value = 159.8
unit = "g/dL"
flag = "normal"

[[results]]
test = "WBC"
value = 131.5
unit = "g/dL"
flag = "normal"


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

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

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

Output:
txn_id = "TXN-38439045"
customer_id = "39de4165-2950-403a-b7cf-252ec7bafdcc"
timestamp = "2026-01-07T13:51:25.757679"
subtotal = 964.6
tax = 142.48
total = 1270.74
payment_method = "credit_card"
[[items]]
sku = "SKU-68017"
qty = 5
price = 287.63

[[items]]
sku = "SKU-13598"
qty = 1
price = 397.9

[[items]]
sku = "SKU-25253"
qty = 4
price = 226.78

[[items]]
sku = "SKU-92380"
qty = 1
price = 318.47


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

[User] Output financial report as YAML.

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

Output:
company: Rodriguez, Sanchez and French
ticker: TOPI
quarter: Q3 2022
revenue: 30596216
expenses: 79425858
net_income: 10739155
eps: 9.27
metrics:
  profit_margin: 21.79
  roe: 22.32


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

[User]
Convert the following TOML to CSV:
period = "May 2020"
total_revenue = 534039
units_sold = 34851
[[channels]]
name = "retail"
revenue = 707158
growth = 43.16

[[channels]]
name = "wholesale"
revenue = 2548868
growth = 26.24

[[top_products]]
sku = "SKU-6020"
sales = 18280

[[top_products]]
sku = "SKU-3349"
sales = 458703

[[top_products]]
sku = "SKU-8781"
sales = 265385

[Assistant]
Approach:
1. Task: Convert sales analytics 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:
abstract,authors,channels,citations,funding_source,keywords,paper_id,period,publication_doi,publication_venue,publication_year,title,top_products,total_revenue,units_sold
,,"[{""name"": ""retail"", ""revenue"": 707158, ""growth"": 43.16}, {""name"": ""wholesale"", ""revenue"": 2548868, """,,,,,May 2020,,,,,"[{""sku"": ""SKU-6020"", ""sales"": 18280}, {""sku"": ""SKU-3349"", ""sales"": 458703}, {""sku"": ""SKU-8781"", ""sal",534039,34851
According film TV answer religious weight. Drug very provide too work so admit. Word common trade es,"[{""name"": ""Kelly Lowe"", ""affiliation"": ""Mckenzie, Martin and Neal"", ""email"": ""jasminestevenson@examp",,233,Osborne Ltd,"[""current"", ""program"", ""well"", ""could""]",arXiv:2024.19244,,10.2728/EPaQ,Nature,2020,Adaptive high-level matrix,,,
Main father interest. Team risk whether relationship act. Site professor writer side.,"[{""name"": ""Jessica Cooper"", ""affiliation"": ""Perkins, Hughes and Carpenter"", ""email"": ""huntjohn@examp",,403,Adams Inc,"[""agree"", ""serious"", ""phone"", ""performance"", ""last""]",arXiv:2020.96015,,10.8764/DyLh,Cell,2024,Streamlined impactful info-mediaries,,,


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

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

[Assistant]
Approach:
1. Task: Convert clinical note from JSON to 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:
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]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<lab_result>
<result_id>LAB-2309770</result_id>
<patient_mrn>MRN-380513</patient_mrn>
<order_date>2026-01-02</order_date>
<panel>CMP</panel>
<results>
<test>Glucose</test>
<value>62.8</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>141.2</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>WBC</test>
<value>75.4</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Glucose</test>
<value>174.6</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Glucose</test>
<value>170.1</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
</lab_result>

[Assistant]
Approach:
1. Task: Convert lab 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:
{
  "result_id": "LAB-2309770",
  "patient_mrn": "MRN-380513",
  "order_date": "2026-01-02",
  "panel": "CMP",
  "results": [
    {
      "test": "Glucose",
      "value": 62.8,
      "unit": "mg/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 141.2,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "WBC",
      "value": 75.4,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "Glucose",
      "value": 174.6,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "Glucose",
      "value": 170.1,
      "unit": "g/dL",
      "flag": "low"
    }
  ]
}


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

[User] Create a JSON representation of course syllabus.

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

Output:
{
  "title": "Stand-alone empowering functionalities 101",
  "schedule": [
    {
      "week": 1,
      "topic": "class"
    },
    {
      "week": 2,
      "topic": "leave"
    },
    {
      "week": 3,
      "topic": "develop"
    },
    {
      "week": 4,
      "topic": "style"
    },
    {
      "week": 5,
      "topic": "again"
    },
    {
      "week": 6,
      "topic": "man"
    },
    {
      "week": 7,
      "topic": "list"
    }
  ],
  "grading": {
    "homework": 30,
    "midterm": 30,
    "final": 40
  }
}


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

[User] Create a XML representation of customer review.

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

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


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

[User] Generate transaction record data in TOML format.

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

Output:
subtotal = 205.31
payment_method = "apple_pay"
total = 1732.06


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

[User]
Reformat the data below from TOML to CSV:
txn_id = "TXN-28879814"
customer_id = "b13e97b5-e84b-41ec-9dea-05b4809cdd35"
timestamp = "2026-01-07T13:51:25.895711"
subtotal = 994.66
tax = 143.59
total = 1762.36
payment_method = "apple_pay"
[[items]]
sku = "SKU-36351"
qty = 1
price = 310.41

[[items]]
sku = "SKU-26629"
qty = 2
price = 119.44

[[items]]
sku = "SKU-75447"
qty = 3
price = 127.79

[[items]]
sku = "SKU-81003"
qty = 3
price = 336.59

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

Output:
customer_id,items,payment_method,subtotal,tax,timestamp,total,txn_id
b13e97b5-e84b-41ec-9dea-05b4809cdd35,"[{""sku"": ""SKU-36351"", ""qty"": 1, ""price"": 310.41}, {""sku"": ""SKU-26629"", ""qty"": 2, ""price"": 119.44}, {",apple_pay,994.66,143.59,2026-01-07T13:51:25.895711,1762.36,TXN-28879814
c93f99c2-d211-4f6d-8231-adba2e350118,"[{""sku"": ""SKU-59987"", ""qty"": 1, ""price"": 398.01}, {""sku"": ""SKU-37174"", ""qty"": 2, ""price"": 438.11}]",credit_card,764.36,62.6,2026-01-07T13:51:25.897218,1150.3,TXN-92489527
c3ea38bf-03e9-4073-97fa-f3481c6bae2f,"[{""sku"": ""SKU-50902"", ""qty"": 2, ""price"": 219.88}]",apple_pay,1899.29,68.58,2026-01-07T13:51:25.897263,686.74,TXN-67821163
385bc0d9-95fb-4a89-9bf9-28fc41191668,"[{""sku"": ""SKU-76207"", ""qty"": 5, ""price"": 413.24}]",credit_card,463.37,93.53,2026-01-07T13:51:25.897296,1568.53,TXN-12140069
c5e6225f-e73d-411c-9457-5eca15f773f0,"[{""sku"": ""SKU-63996"", ""qty"": 2, ""price"": 362.36}, {""sku"": ""SKU-54253"", ""qty"": 2, ""price"": 37.65}, {""",paypal,1501.55,49.59,2026-01-07T13:51:25.897325,2068.34,TXN-43814480


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

[User] Generate product listing data in CSV format.

[Assistant]
Approach:
1. Task: Create product listing in CSV
2. Complexity: 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,Object-based value-added workforce,802.3,PROD-428311,1.5,81,99x87x32cm,27.85,719
clothing,USD,True,Decentralized attitude-oriented encryption,117.83,PROD-763826,4.43,842,12x44x40cm,34.29,370
clothing,USD,True,Optional responsive pricing structure,724.95,PROD-545923,4.55,113,44x58x15cm,46.48,211


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

[User] Generate customer review data in XML format.

[Assistant]
Approach:
1. Task: Create customer review 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"?>
<customer_review>
<review_id>REV-9546377</review_id>
<product_id>PROD-108034</product_id>
<user_id>d01ac4e1-ccd9-4273-9fe0-9ca6afc6af77</user_id>
<rating>4</rating>
<title>Appear speak sure list.</title>
<content>Today offer none role certain reach. Second Mr official enjoy movement turn city. Name employee early much first sit.</content>
<date>2026-01-01</date>
<verified_purchase>True</verified_purchase>
<helpful_votes>43</helpful_votes>
</customer_review>


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

[User] Generate error log data in YAML format.

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

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


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

[User] Produce a YAML document for a prescription.

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

Output:
rx_id: RX-3472120
patient_mrn: MRN-972429
prescriber: Matthew Bennett
date: '2026-01-06'
medications:
- name: Atorvastatin
  dosage: 10mg
  frequency: daily
  quantity: 60


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<lab_result>
<order_date>2026-01-05</order_date>
<results>
<test>Hemoglobin</test>
<value>95.5</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>52.7</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Glucose</test>
<value>142.9</value>
<unit>mg/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Glucose</test>
<value>146.5</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<panel>Lipid</panel>
</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:
{
  "order_date": "2026-01-05",
  "results": [
    {
      "test": "Hemoglobin",
      "value": 95.5,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "Hemoglobin",
      "value": 52.7,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "Glucose",
      "value": 142.9,
      "unit": "mg/dL",
      "flag": "low"
    },
    {
      "test": "Glucose",
      "value": 146.5,
      "unit": "mg/dL",
      "flag": "high"
    }
  ],
  "panel": "Lipid"
}


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

[User] Create a CSV representation of course syllabus.

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

Output:
code,course_id,credits,grading_final,grading_homework,grading_midterm,instructor,schedule,term,title
OMY437,CRS-8422,3,40,30,30,Rodney Anderson,"[{""week"": 1, ""topic"": ""answer""}, {""week"": 2, ""topic"": ""best""}, {""week"": 3, ""topic"": ""meet""}, {""week""",Spring 2023,Optimized upward-trending conglomeration 101
FCH329,CRS-9108,4,40,30,30,Brad Nixon,"[{""week"": 1, ""topic"": ""concern""}, {""week"": 2, ""topic"": ""guy""}, {""week"": 3, ""topic"": ""society""}, {""we",Fall 2021,Focused 4thgeneration artificial intelligence 101
CCM268,CRS-6240,4,40,30,30,Michele Harris,"[{""week"": 1, ""topic"": ""thus""}, {""week"": 2, ""topic"": ""south""}, {""week"": 3, ""topic"": ""dream""}, {""week""",Fall 2023,Diverse object-oriented process improvement 101


[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:
{
  "note_id": "CN-5751204",
  "patient": {
    "mrn": "MRN-566004",
    "age": 47,
    "gender": "M"
  },
  "encounter_date": "2026-01-05",
  "chief_complaint": "headache",
  "vitals": {
    "bp": "160/96",
    "hr": 75,
    "temp_f": 102.4
  },
  "assessment": [
    {
      "problem": "diabetes",
      "icd10": "I93"
    }
  ]
}

[Assistant]
Approach:
1. Task: Convert clinical note 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"?>
<clinical_note>
<note_id>CN-5751204</note_id>
<patient>
<mrn>MRN-566004</mrn>
<age>47</age>
<gender>M</gender>
</patient>
<encounter_date>2026-01-05</encounter_date>
<chief_complaint>headache</chief_complaint>
<vitals>
<bp>160/96</bp>

75

<temp_f>102.4</temp_f>
</vitals>
<assessment>
<problem>diabetes</problem>
<icd10>I93</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:
{
  "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
}

[Assistant]
Approach:
1. Task: Convert transaction record 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"?>
<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>


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

[User] Produce a XML document for a clinical note.

[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-6952117</note_id>
<patient>
<mrn>MRN-227055</mrn>
<age>50</age>
<gender>F</gender>
</patient>
<encounter_date>2026-01-03</encounter_date>
<chief_complaint>headache</chief_complaint>
<vitals>
<bp>146/78</bp>

63

<temp_f>97.9</temp_f>
</vitals>
<assessment>
<problem>hypertension</problem>
<icd10>J35</icd10>
</assessment>
<assessment>
<problem>hypertension</problem>
<icd10>K44</icd10>
</assessment>
<assessment>
<problem>hypertension</problem>
<icd10>I58</icd10>
</assessment>
</clinical_note>


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

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

[Assistant]
Approach:
1. Task: Convert api specification from JSON to 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:
info:
  title: Multi-tiered directional knowledge user API
  version: 1.0.0
openapi: 3.0.0
paths:
  /require:
    get:
      summary: Suffer kid pull bed decision rest.
      parameters:
      - name: param0
        in: query
        type: string
      - name: param1
        in: query
        type: string
      - name: param2
        in: query
        type: string
      responses:
        '200':
          description: Success
        '400':
          description: Bad Request


[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,context_request_id,context_user_id,error_id,funding_source,keywords,message,paper_id,publication_doi,publication_venue,publication_year,stack_trace,timestamp,title
,,,ab94fb1e-d258-4626-9686-12f860249c41,97fc14e5-867d-4c23-9d2e-00b538b50acf,ddf52566-8f32-4c90-8477-d7f45504f7db,,,Computer so cold feeling huge reason reach.,,,,,"[""at their.py:436"", ""at activity.py:81"", ""at test.py:46""]",2026-01-07T13:51:26.578554,
Size late draw with authority fight over. Money eat find cut back appear.,"[{""name"": ""Kimberly Hernandez"", ""affiliation"": ""Harrington PLC"", ""email"": ""amylevine@example.net""}, ",56,,,,None,"[""people"", ""pull"", ""heart"", ""majority""]",,arXiv:2024.77377,10.7816/OqBr,Science,2022,,,Visionary scalable info-mediaries
Score take financial reflect same about. Who thousand site before fill color exactly leave. Next con,"[{""name"": ""Stephen Washington"", ""affiliation"": ""Walker-Sanchez"", ""email"": ""moralestodd@example.net""}",180,,,,Ward Group,"[""final"", ""research"", ""effect"", ""camera""]",,arXiv:2023.89584,10.5916/Yrbo,Science,2024,,,Sharable bi-directional methodology
May sing institution eat. Affect save almost goal former. Nation article born lay enter sport call d,"[{""name"": ""Alexandra White"", ""affiliation"": ""Jackson-White"", ""email"": ""randall75@example.com""}, {""na",460,,,,None,"[""between"", ""understand"", ""less"", ""country""]",,arXiv:2020.39701,10.2162/Dqnk,Cell,2023,,,Monitored upward-trending extranet
Sometimes thing according build own ready. World large past sing.,"[{""name"": ""Anthony Blake"", ""affiliation"": ""Allen-Roman"", ""email"": ""brett38@example.org""}, {""name"": """,79,,,,Williams and Sons,"[""star"", ""police"", ""well""]",,arXiv:2024.33190,10.3599/fPBN,Science,2024,,,Upgradable background synergy

[Assistant]
Approach:
1. Task: Convert error log from CSV 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:
{
  "message": "Computer so cold feeling huge reason reach.",
  "error_id": "ddf52566-8f32-4c90-8477-d7f45504f7db",
  "stack_trace": [
    "at their.py:436",
    "at activity.py:81",
    "at test.py:46"
  ],
  "timestamp": "2026-01-07T13:51:26.578554",
  "context": {
    "user_id": "97fc14e5-867d-4c23-9d2e-00b538b50acf",
    "request_id": "ab94fb1e-d258-4626-9686-12f860249c41"
  }
}


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

[User] Generate api specification data in JSON format.

[Assistant]
Approach:
1. Task: Create api specification 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:
{
  "info": {
    "title": "Multi-tiered directional knowledge user API",
    "version": "1.0.0"
  },
  "openapi": "3.0.0",
  "paths": {
    "/require": {
      "get": {
        "summary": "Suffer kid pull bed decision rest.",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          },
          {
            "name": "param1",
            "in": "query",
            "type": "string"
          },
          {
            "name": "param2",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  }
}


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

[User] Generate transaction record data in TOML format.

[Assistant]
Approach:
1. Task: Create transaction record in TOML
2. Complexity: 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:
txn_id = "TXN-79156891"
customer_id = "5450ecc9-30b8-498f-a527-04ec3de16dd8"
timestamp = "2026-01-07T13:51:26.258900"
subtotal = 258.62
tax = 22.79
total = 1713.37
payment_method = "paypal"
[[items]]
sku = "SKU-81880"
qty = 4
price = 401.7

[[items]]
sku = "SKU-99718"
qty = 5
price = 334.37

[[items]]
sku = "SKU-65882"
qty = 3
price = 292.8

[[items]]
sku = "SKU-88201"
qty = 2
price = 114.91


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

[User] Output product listing as TOML.

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

Output:
product_id = "PROD-141484"
name = "Managed bandwidth-monitored focus group"
category = "books"
price = 751.35
currency = "USD"
stock = 108
is_available = true
rating = 2.94
reviews = 250

[specs]
weight_kg = 6.41
dimensions = "15x82x35cm"


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

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

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

Output:
{
  "product_id": "PROD-852387",
  "name": "Profound logistical array",
  "category": "electronics",
  "price": 299.46,
  "currency": "USD",
  "stock": 505,
  "is_available": true,
  "rating": 2.95,
  "reviews": 519,
  "specs": {
    "weight_kg": 6.22,
    "dimensions": "16x47x36cm"
  }
}


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

[User]
Reformat the data below from YAML to TOML:
paper_id: arXiv:2023.57642
title: Organized clear-thinking projection
authors:
- name: Thomas Harrison
  affiliation: Benjamin, Peterson and James
  email: martinjoseph@example.com
- name: Samantha Phillips
  affiliation: Carpenter Ltd
  email: hawkinssarah@example.com
abstract: 'Leg third those over. Almost state money hear condition little.

  Manager minute writer manager. Walk hand situation similar media back fill huge.'
keywords:
- decade
- kitchen
- discover
- wide
publication:
  venue: Cell
  year: 2023
  doi: 10.5371/HWME
citations: 306
funding_source: null

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

Output:
paper_id = "arXiv:2023.57642"
title = "Organized clear-thinking projection"
abstract = "Leg third those over. Almost state money hear condition little.\nManager minute writer manager. Walk hand situation similar media back fill huge."
keywords = [ "decade", "kitchen", "discover", "wide",]
citations = 306
[[authors]]
name = "Thomas Harrison"
affiliation = "Benjamin, Peterson and James"
email = "martinjoseph@example.com"

[[authors]]
name = "Samantha Phillips"
affiliation = "Carpenter Ltd"
email = "hawkinssarah@example.com"

[publication]
venue = "Cell"
year = 2023
doi = "10.5371/HWME"


[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:
{
  "verified_purchase": false,
  "rating": 2,
  "date": "2026-01-02",
  "user_id": "ccea0611-b57c-4ee0-9ab6-48c5cb4c2b4c",
  "title": "Nature prepare style hit cell feeling start societ"
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<verified_purchase>False</verified_purchase>
<rating>2</rating>
<date>2026-01-02</date>
<user_id>ccea0611-b57c-4ee0-9ab6-48c5cb4c2b4c</user_id>
<title>Nature prepare style hit cell feeling start societ</title>
</customer_review>


[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"?>
<experiment_result>
<experiment_id>EXP-318732</experiment_id>
<title>Effect of produce on stock</title>
<methodology>
<design>observational</design>
<sample_size>303</sample_size>
<duration_days>155</duration_days>
</methodology>
<results>
<metric>safety</metric>
<baseline>20.77</baseline>
<endpoint>67.03</endpoint>
<p_value>0.1826</p_value>
</results>
<results>
<metric>safety</metric>
<baseline>69.69</baseline>
<endpoint>32.04</endpoint>
<p_value>0.1176</p_value>
</results>
<conclusion>non-significant</conclusion>
</experiment_result>

[Assistant]
Approach:
1. Task: Convert experiment 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:
{
  "experiment_id": "EXP-318732",
  "title": "Effect of produce on stock",
  "methodology": {
    "design": "observational",
    "sample_size": 303,
    "duration_days": 155
  },
  "results": [
    {
      "metric": "safety",
      "baseline": 20.77,
      "endpoint": 67.03,
      "p_value": 0.1826
    },
    {
      "metric": "safety",
      "baseline": 69.69,
      "endpoint": 32.04,
      "p_value": 0.1176
    }
  ],
  "conclusion": "non-significant"
}


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

[User] Create a YAML representation of financial report.

[Assistant]
Approach:
1. Task: Create financial report 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:
expenses: 54498119
ticker: OKCY
company: Clark-Pearson


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

[User] Create a TOML representation of 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-986141"
name = "Focused neutral encoding"
category = "books"
price = 14.45
currency = "USD"
stock = 826
is_available = true
rating = 4.59
reviews = 564

[specs]
weight_kg = 27.7
dimensions = "42x99x90cm"


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<review_id>REV-7169946</review_id>
<product_id>PROD-908355</product_id>
<user_id>109a43ce-0a9d-47ca-b5cc-5940dcb3a5c0</user_id>
<rating>3</rating>
<title>Suffer kid daughter race still baby.</title>
<content>Young lot card leave book. Thank agency tree shake. Manage organization reduce from sort soldier.
Run rich marriage parent discover kitchen. Positive person baby list positive really range.</content>
<date>2026-01-05</date>
<verified_purchase>True</verified_purchase>
<helpful_votes>3</helpful_votes>
</customer_review>


[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-353280
student_id: STU-259399
course_id: CRS-9241
type: quiz
date: '2026-01-05'
scores:
- question: 1
  points_earned: 4
  points_possible: 10
- question: 2
  points_earned: 6
  points_possible: 10
- question: 3
  points_earned: 0
  points_possible: 10
- question: 4
  points_earned: 2
  points_possible: 10
- question: 5
  points_earned: 4
  points_possible: 10
- question: 6
  points_earned: 9
  points_possible: 10
- question: 7
  points_earned: 7
  points_possible: 10
- question: 8
  points_earned: 4
  points_possible: 10
- question: 9
  points_earned: 3
  points_possible: 10
- question: 10
  points_earned: 7
  points_possible: 10
- question: 11
  points_earned: 7
  points_possible: 10
- question: 12
  points_earned: 0
  points_possible: 10
- question: 13
  points_earned: 2
  points_possible: 10
total_score: 68
percentage: 88.23
grade: C


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

[User] Create a JSON representation of news article.

[Assistant]
Approach:
1. Task: Create news article 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:
{
  "article_id": "ART-2650245",
  "headline": "Enhanced multimedia hub",
  "author": "Jennifer Davis",
  "published": "2026-01-02T17:44:08.333575",
  "section": "Tech",
  "content": "Late situation both data share market. These foot health box.\nPay me together western ever story cup. Game production million happy reveal. Attorney bill shake crime eat finally drive.\nChoice four concern cold test. Road executive policy official season increase.",
  "tags": [
    "future",
    "here",
    "new"
  ],
  "views": 46115,
  "shares": 2819
}


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

[User] Output experiment result as XML.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<experiment_result>
<experiment_id>EXP-725280</experiment_id>
<title>Effect of city on expert</title>
<methodology>
<design>observational</design>
<sample_size>907</sample_size>
<duration_days>166</duration_days>
</methodology>
<results>
<metric>safety</metric>
<baseline>43.19</baseline>
<endpoint>64.81</endpoint>
<p_value>0.4813</p_value>
</results>
<results>
<metric>safety</metric>
<baseline>71.73</baseline>
<endpoint>68.14</endpoint>
<p_value>0.0851</p_value>
</results>
<results>
<metric>safety</metric>
<baseline>77.12</baseline>
<endpoint>63.9</endpoint>
<p_value>0.1154</p_value>
</results>
<conclusion>significant</conclusion>
</experiment_result>


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

[User] Create a CSV representation of lab result.

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

Output:
order_date,panel,patient_mrn,result_id,results
2026-01-03,CBC,MRN-709917,LAB-5490961,"[{""test"": ""Glucose"", ""value"": 146.9, ""unit"": ""mg/dL"", ""flag"": ""high""}, {""test"": ""Hemoglobin"", ""value"
2026-01-01,Lipid,MRN-733525,LAB-9915150,"[{""test"": ""WBC"", ""value"": 63.9, ""unit"": ""mg/dL"", ""flag"": ""high""}, {""test"": ""WBC"", ""value"": 98.3, ""un"
2026-01-02,CBC,MRN-978406,LAB-6499515,"[{""test"": ""Glucose"", ""value"": 187.5, ""unit"": ""mg/dL"", ""flag"": ""normal""}, {""test"": ""WBC"", ""value"": 13"
2026-01-03,Lipid,MRN-799074,LAB-8972745,"[{""test"": ""WBC"", ""value"": 186.5, ""unit"": ""mg/dL"", ""flag"": ""low""}, {""test"": ""Glucose"", ""value"": 91.7,"
2026-01-02,CMP,MRN-129084,LAB-2001145,"[{""test"": ""WBC"", ""value"": 134.4, ""unit"": ""g/dL"", ""flag"": ""low""}, {""test"": ""Glucose"", ""value"": 120.0,"


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<social_media_post>
<post_id>POST-20150897</post_id>
<platform>instagram</platform>
<user_id>ace3958f-4578-4576-9236-9cbfc1f62953</user_id>
<username>spatrick</username>
<content>About industry woman size. Available box return camera public time. Establish outside ability sport describe air who.
Certain miss girl different both wife. Blood relationship if model.</content>
<timestamp>2026-01-07T13:51:25.995017</timestamp>
<hashtags>#share</hashtags>
<hashtags>#prevent</hashtags>
<hashtags>#entire</hashtags>
<hashtags>#owner</hashtags>
<engagement>
<likes>3129</likes>
<shares>891</shares>
<comments>28</comments>
</engagement>
</social_media_post>

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

Output:
{
  "post_id": "POST-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"?>
<research_paper>
<paper_id>arXiv:2020.10600</paper_id>
<title>Reactive bi-directional middleware</title>
<authors>
<name>Sarah Rose</name>
<affiliation>Martin, Taylor and Mills</affiliation>
<email>adrianporter@example.com</email>
</authors>
<authors>
<name>Samantha Garcia</name>
<affiliation>Santiago LLC</affiliation>
<email>cbrewer@example.net</email>
</authors>
<abstract>Carry prove certain tell event break. Thus not actually teacher girl perhaps.</abstract>
<keywords>public</keywords>
<keywords>stock</keywords>
<keywords>student</keywords>
<keywords>hair</keywords>
<keywords>hard</keywords>
<publication>
<venue>Cell</venue>
<year>2022</year>
<doi>10.6112/KodW</doi>
</publication>
<citations>273</citations>
<funding_source>Salazar, Mullen and Johnson</funding_source>
</research_paper>

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

Output:
{
  "paper_id": "arXiv:2020.10600",
  "title": "Reactive bi-directional middleware",
  "authors": [
    {
      "name": "Sarah Rose",
      "affiliation": "Martin, Taylor and Mills",
      "email": "adrianporter@example.com"
    },
    {
      "name": "Samantha Garcia",
      "affiliation": "Santiago LLC",
      "email": "cbrewer@example.net"
    }
  ],
  "abstract": "Carry prove certain tell event break. Thus not actually teacher girl perhaps.",
  "keywords": [
    "public",
    "stock",
    "student",
    "hair",
    "hard"
  ],
  "publication": {
    "venue": "Cell",
    "year": 2022,
    "doi": "10.6112/KodW"
  },
  "citations": 273,
  "funding_source": "Salazar, Mullen and Johnson"
}


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

[User] Output transaction record as TOML.

[Assistant]
Approach:
1. Task: Create transaction record 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:
txn_id = "TXN-28879814"
customer_id = "b13e97b5-e84b-41ec-9dea-05b4809cdd35"
timestamp = "2026-01-07T13:51:25.895711"
subtotal = 994.66
tax = 143.59
total = 1762.36
payment_method = "apple_pay"
[[items]]
sku = "SKU-36351"
qty = 1
price = 310.41

[[items]]
sku = "SKU-26629"
qty = 2
price = 119.44

[[items]]
sku = "SKU-75447"
qty = 3
price = 127.79

[[items]]
sku = "SKU-81003"
qty = 3
price = 336.59


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

[User] Create a TOML representation of clinical note.

[Assistant]
Approach:
1. Task: Create clinical note 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:
note_id = "CN-4466987"
encounter_date = "2026-01-02"
chief_complaint = "headache"
[[assessment]]
problem = "diabetes"
icd10 = "K25"

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

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


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

[User] Generate research paper data in CSV format.

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

Output:
abstract,authors,citations,funding_source,keywords,paper_id,publication_doi,publication_venue,publication_year,title
,"[{""name"": ""Emily Davis"", ""affiliation"": ""Nelson, Diaz and Humphrey"", ""email"": ""jpalmer@example.org""}",,None,"[""lead"", ""list"", ""she""]",arXiv:2022.72917,10.6797/tlMT,Science,2022,
Least away hear financial. Push wrong top also bring mean thing. Mouth number language rich produce ,"[{""name"": ""Brian Rice"", ""affiliation"": ""Kent, Thomas and Thomas"", ""email"": ""natalie00@example.com""},",86,Mason Group,"[""win"", ""agent"", ""whom"", ""century""]",arXiv:2021.74901,10.4219/DOyW,Cell,2022,Up-sized leadingedge matrices
"Together clearly view. Sing learn agreement blood until popular.
Environment physical peace option a","[{""name"": ""Elizabeth Simmons"", ""affiliation"": ""Pennington LLC"", ""email"": ""francobarry@example.com""},",274,Brown-Powell,"[""man"", ""citizen"", ""street""]",arXiv:2021.67414,10.7758/nwWK,Nature,2021,User-friendly neutral secured line


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

[User] Create a CSV representation of prescription.

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

Output:
date,medications,patient_mrn,prescriber,rx_id
2026-01-01,"[{""name"": ""Lisinopril"", ""dosage"": ""5mg"", ""frequency"": ""TID"", ""quantity"": 30}]",MRN-970748,Brady Keller,RX-8706225
2026-01-02,"[{""name"": ""Metformin"", ""dosage"": ""5mg"", ""frequency"": ""TID"", ""quantity"": 90}, {""name"": ""Metformin"", """,MRN-491362,Bradley Wilkerson,RX-1251418
2026-01-05,"[{""name"": ""Lisinopril"", ""dosage"": ""5mg"", ""frequency"": ""TID"", ""quantity"": 30}]",MRN-345152,Heather Jones,RX-3570251


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

[User]
Transform this JSON data into CSV format:
{
  "article_id": "ART-5646798",
  "headline": "Switchable hybrid groupware",
  "author": "Joshua Bell",
  "published": "2026-01-05T05:31:42.088007",
  "section": "Business",
  "content": "List road lay not year. Congress gas full particular according. Prevent hear century game friend civil live.\nPossible option especially woman. Ahead down suffer doctor six traditional. Prove ready American star impact operation just. Difficult yourself difficult base of four letter.",
  "tags": [
    "author",
    "son",
    "food"
  ],
  "views": 74484,
  "shares": 596
}

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

Output:
article_id,author,content,headline,published,section,shares,tags,views
ART-5646798,Joshua Bell,List road lay not year. Congress gas full particular according. Prevent hear century game friend civ,Switchable hybrid groupware,2026-01-05T05:31:42.088007,Business,596,"[""author"", ""son"", ""food""]",74484
ART-6165396,Ellen Hamilton,"Move yet fight lawyer him. Then size threat commercial month writer. Plan need mission.
Certain conc",Cross-platform secondary paradigm,2026-01-04T06:59:23.942438,Politics,3991,"[""attorney"", ""act"", ""movie""]",31541
ART-5224027,Sabrina Turner,"Reveal find check. Indeed protect tell catch art ball buy.
Agency development carry cultural forward",Programmable encompassing database,2026-01-02T07:03:14.355228,Tech,4412,"[""face"", ""door"", ""near"", ""federal"", ""officer""]",68992
ART-6474915,Sarah Thompson,Leg management half little party. Also offer owner. Three window involve surface middle own budget t,Monitored mission-critical data-warehouse,2026-01-03T07:41:01.430013,Sports,1882,"[""image"", ""field"", ""must""]",96897
ART-5325044,Sean Riley,"Tax never early year structure stop sport thing. Fish southern day president theory smile.
Pick sit ",Enhanced client-driven Graphical User Interface,2026-01-05T00:14:01.350446,Tech,2542,"[""reality"", ""civil"", ""sound""]",51972


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

[User]
Transform this YAML data into JSON format:
post_id: POST-54622203
platform: instagram
user_id: 1456e108-0a50-4482-8f1a-b1cb2398a121
username: fullersteven
content: 'Card these member kid western growth. Staff draw say early town general.
  Large break interesting ten against open.

  Any fine power truth. Big like investment simple whatever education.'
timestamp: '2026-01-07T13:51:25.504049'
hashtags:
- '#deep'
- '#yes'
- '#long'
- '#including'
engagement:
  likes: 464
  shares: 699
  comments: 294

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

Output:
{
  "post_id": "POST-54622203",
  "platform": "instagram",
  "user_id": "1456e108-0a50-4482-8f1a-b1cb2398a121",
  "username": "fullersteven",
  "content": "Card these member kid western growth. Staff draw say early town general. Large break interesting ten against open.\nAny fine power truth. Big like investment simple whatever education.",
  "timestamp": "2026-01-07T13:51:25.504049",
  "hashtags": [
    "#deep",
    "#yes",
    "#long",
    "#including"
  ],
  "engagement": {
    "likes": 464,
    "shares": 699,
    "comments": 294
  }
}


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

[User]
Transform this TOML data into JSON format:
result_id = "LAB-4504067"
patient_mrn = "MRN-266543"
order_date = "2026-01-05"
panel = "Lipid"
[[results]]
test = "Glucose"
value = 181.1
unit = "g/dL"
flag = "normal"

[[results]]
test = "Hemoglobin"
value = 164.3
unit = "mg/dL"
flag = "low"

[[results]]
test = "Glucose"
value = 140.0
unit = "g/dL"
flag = "normal"

[[results]]
test = "Hemoglobin"
value = 113.0
unit = "mg/dL"
flag = "high"

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

Output:
{
  "result_id": "LAB-4504067",
  "patient_mrn": "MRN-266543",
  "order_date": "2026-01-05",
  "panel": "Lipid",
  "results": [
    {
      "test": "Glucose",
      "value": 181.1,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 164.3,
      "unit": "mg/dL",
      "flag": "low"
    },
    {
      "test": "Glucose",
      "value": 140.0,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 113.0,
      "unit": "mg/dL",
      "flag": "high"
    }
  ]
}


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

[User] Create a CSV representation of api specification.

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

Output:
abstract,authors,citations,funding_source,info_title,info_version,keywords,openapi,paper_id,paths_/teach_get_parameters,paths_/teach_get_responses_200_description,paths_/teach_get_responses_400_description,paths_/teach_get_summary,publication_doi,publication_venue,publication_year,title
,,,,Business-focused zero administration encryption API,1.0.0,,3.0.0,,"[{""name"": ""param0"", ""in"": ""query"", ""type"": ""string""}, {""name"": ""param1"", ""in"": ""query"", ""type"": ""str",Success,Bad Request,Government trade direction personal reason hundred,,,,
Affect today establish arm foot skin agent. Statement increase local candidate help meet.,"[{""name"": ""Eric Rose"", ""affiliation"": ""Cruz-Cannon"", ""email"": ""robin15@example.com""}, {""name"": ""Mand",367,None,,,"[""do"", ""matter"", ""serious"", ""official"", ""technology""]",,arXiv:2024.39689,,,,,10.3018/UBBT,Science,2024,Distributed radical implementation
Cold late national drive write. Loss break debate interview why manage new.,"[{""name"": ""Lisa Williams"", ""affiliation"": ""Maldonado-Mills"", ""email"": ""christopher76@example.org""}, ",207,None,,,"[""expert"", ""college"", ""drug""]",,arXiv:2021.88361,,,,,10.1907/lKeu,Nature,2024,Re-contextualized well-modulated protocol


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

[User] Generate api specification data in TOML format.

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

Output:
openapi = "3.0.0"

[info]
title = "Re-engineered mobile superstructure API"
version = "1.0.0"

[paths."/benefit".get]
summary = "Chair media space recognize doctor would second me"
[[paths."/benefit".get.parameters]]
name = "param0"
in = "query"
type = "string"

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

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

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

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


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

[User] Create a YAML representation of lab result.

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

Output:
result_id: LAB-5387789
patient_mrn: MRN-887521
order_date: '2026-01-05'
panel: CBC
results:
- test: WBC
  value: 66.6
  unit: mg/dL
  flag: normal
- test: Glucose
  value: 111.4
  unit: mg/dL
  flag: high
- test: Hemoglobin
  value: 168.1
  unit: g/dL
  flag: high
- test: Hemoglobin
  value: 136.7
  unit: g/dL
  flag: low
- test: WBC
  value: 148.7
  unit: g/dL
  flag: low
- test: Glucose
  value: 86.9
  unit: mg/dL
  flag: normal


[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-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>


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

[User] Output financial report as JSON.

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

Output:
{
  "company": "Eaton, Mccarty and Lopez",
  "ticker": "OWKB",
  "quarter": "Q3 2021",
  "revenue": 46227283,
  "expenses": 75330506,
  "net_income": 13309525,
  "eps": 4.82,
  "metrics": {
    "profit_margin": 29.61,
    "roe": 8.93
  }
}


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

[User] Output financial report as XML.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<financial_report>
<company>Woods and Sons</company>
<ticker>ZCNM</ticker>
<quarter>Q1 2020</quarter>
<revenue>42196406</revenue>
<expenses>48284794</expenses>
<net_income>2937548</net_income>
<eps>8.84</eps>
<metrics>
<profit_margin>12.42</profit_margin>
<roe>23.86</roe>
</metrics>
</financial_report>


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

[User]
Convert the following TOML to XML:
openapi = "3.0.0"

[info]
title = "Seamless disintermediate flexibility API"
version = "1.0.0"

[paths."/significant".get]
summary = "Box project skin day catch."
[[paths."/significant".get.parameters]]
name = "param0"
in = "query"
type = "string"

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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Seamless disintermediate flexibility API</title>
<version>1.0.0</version>
</info>
<paths>
</significant>
<get>
<summary>Box project skin day catch.</summary>
<parameters>
<name>param0</name>
<in>query</in>
<type>string</type>
</parameters>
<responses>
<200>
<description>Success</description>
</200>
<400>
<description>Bad Request</description>
</400>
</responses>
</get>
<//significant>
</paths>
</api_specification>


[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: 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:
category: electronics
specs:
  weight_kg: 38.59
  dimensions: 23x92x45cm
stock: 596
price: 218.58


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

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

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

Output:
paper_id: arXiv: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.

  Place 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