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

[User] Create a TOML representation of error log.

[Assistant]
Approach:
1. Task: Create error log in TOML
2. Complexity: 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 = "21bf982e-3e24-486f-a8ed-fe9e0227df3b"
timestamp = "2026-01-07T13:51:27.797574"
level = "CRITICAL"
service = "letService"
message = "Story quite another important."
stack_trace = [ "at decision.py:100", "at sing.py:289", "at long.py:325", "at special.py:174",]

[context]
user_id = "8c36ba55-183c-4481-9cd9-dc049447888c"
request_id = "089e0eaa-71d8-4f30-a2f1-bac42a6b74a3"


[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: 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
2026-01-05,"[{""name"": ""Atorvastatin"", ""dosage"": ""20mg"", ""frequency"": ""daily"", ""quantity"": 30}]",MRN-909141,Heather Stephens,RX-9719971
2026-01-06,"[{""name"": ""Atorvastatin"", ""dosage"": ""20mg"", ""frequency"": ""BID"", ""quantity"": 90}]",MRN-159791,Benjamin Hampton,RX-8081993
2026-01-04,"[{""name"": ""Atorvastatin"", ""dosage"": ""20mg"", ""frequency"": ""TID"", ""quantity"": 60}, {""name"": ""Metformin",MRN-520777,Tommy Marshall,RX-4460819
2026-01-02,"[{""name"": ""Atorvastatin"", ""dosage"": ""10mg"", ""frequency"": ""TID"", ""quantity"": 90}, {""name"": ""Lisinopri",MRN-183404,Kayla Rice,RX-3413963


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

[User] Create a JSON representation of prescription.

[Assistant]
Approach:
1. Task: Create prescription 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:
{
  "rx_id": "RX-6885629",
  "prescriber": "John Cook",
  "medications": [
    {
      "name": "Metformin",
      "dosage": "5mg",
      "frequency": "daily",
      "quantity": 30
    },
    {
      "name": "Atorvastatin",
      "dosage": "5mg",
      "frequency": "BID",
      "quantity": 90
    },
    {
      "name": "Lisinopril",
      "dosage": "5mg",
      "frequency": "TID",
      "quantity": 60
    }
  ],
  "date": "2026-01-02",
  "patient_mrn": "MRN-741538"
}


[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:
{
  "customer_id": "5642be10-2f96-4bf3-93bb-ea73b498db7e",
  "timestamp": "2026-01-07T13:51:27.704310",
  "total": 2159.3,
  "tax": 150.65,
  "items": [
    {
      "sku": "SKU-21107",
      "qty": 2,
      "price": 436.86
    },
    {
      "sku": "SKU-34269",
      "qty": 3,
      "price": 260.71
    },
    {
      "sku": "SKU-81249",
      "qty": 3,
      "price": 416.92
    },
    {
      "sku": "SKU-97216",
      "qty": 3,
      "price": 177.96
    }
  ]
}

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

Output:
abstract,authors,citations,customer_id,funding_source,items,keywords,paper_id,publication_doi,publication_venue,publication_year,tax,timestamp,title,total
,,,5642be10-2f96-4bf3-93bb-ea73b498db7e,,"[{""sku"": ""SKU-21107"", ""qty"": 2, ""price"": 436.86}, {""sku"": ""SKU-34269"", ""qty"": 3, ""price"": 260.71}, {",,,,,,150.65,2026-01-07T13:51:27.704310,,2159.3
"Yard apply high change speech boy. Floor already ahead PM drop real.
You then official suddenly. Thi","[{""name"": ""Sharon Mcdaniel"", ""affiliation"": ""Berry, Adams and Christensen"", ""email"": ""boyerdavid@exa",227,,None,,"[""land"", ""mission"", ""environmental"", ""could"", ""tonight""]",arXiv:2020.46946,10.4271/lenY,Cell,2023,,,Sharable background portal,
Be accept technology investment style. What past available certainly cause become form world.,"[{""name"": ""Shane Steele"", ""affiliation"": ""Lopez PLC"", ""email"": ""zmiller@example.net""}, {""name"": ""Rob",45,,Lloyd-Marshall,,"[""southern"", ""responsibility"", ""organization""]",arXiv:2021.62540,10.7067/TvwA,Cell,2021,,,Fully-configurable stable conglomeration,
Participant note third receive discussion. Television level rather scientist yeah government friend.,"[{""name"": ""Kelly Washington"", ""affiliation"": ""Martin Inc"", ""email"": ""wagnercourtney@example.org""}, {",219,,None,,"[""experience"", ""everything"", ""security"", ""factor""]",arXiv:2023.35056,10.1679/brVn,Science,2020,,,Seamless zero administration knowledgebase,


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

[User]
Reformat the data below from JSON to XML:
{
  "rx_id": "RX-5305677",
  "patient_mrn": "MRN-215469",
  "prescriber": "Jeremy Hatfield",
  "date": "2026-01-03",
  "medications": [
    {
      "name": "Metformin",
      "dosage": "10mg",
      "frequency": "daily",
      "quantity": 90
    },
    {
      "name": "Metformin",
      "dosage": "5mg",
      "frequency": "daily",
      "quantity": 30
    },
    {
      "name": "Atorvastatin",
      "dosage": "10mg",
      "frequency": "BID",
      "quantity": 90
    }
  ]
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<prescription>
<rx_id>RX-5305677</rx_id>
<patient_mrn>MRN-215469</patient_mrn>
<prescriber>Jeremy Hatfield</prescriber>
<date>2026-01-03</date>
<medications>
<name>Metformin</name>
<dosage>10mg</dosage>
<frequency>daily</frequency>
<quantity>90</quantity>
</medications>
<medications>
<name>Metformin</name>
<dosage>5mg</dosage>
<frequency>daily</frequency>
<quantity>30</quantity>
</medications>
<medications>
<name>Atorvastatin</name>
<dosage>10mg</dosage>
<frequency>BID</frequency>
<quantity>90</quantity>
</medications>
</prescription>


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

[User] Output error log as CSV.

[Assistant]
Approach:
1. Task: Create error log in CSV
2. Complexity: 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,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,
Environment without right pattern goal leave. Individual goal reason image heart among benefit. Less,"[{""name"": ""Amanda Fisher"", ""affiliation"": ""Davis-Torres"", ""email"": ""blakesheila@example.com""}, {""nam",37,,,,"Watson, Myers and Johnson","[""officer"", ""cold"", ""Mrs""]",,arXiv:2023.62976,10.5659/fmkj,Cell,2021,,,Focused hybrid strategy
Grow everything day camera cost in. As have especially interest. Behavior today throughout then side,"[{""name"": ""Vincent Collins"", ""affiliation"": ""Munoz, Peters and Downs"", ""email"": ""tranrachel@example.",470,,,,"Bell, Leonard and Hall","[""move"", ""summer"", ""culture"", ""identify""]",,arXiv:2024.65782,10.1406/etPb,Cell,2022,,,Customer-focused foreground framework
Whatever begin white discussion break go. Community six most business today.,"[{""name"": ""Timothy Morgan"", ""affiliation"": ""Brown-Harris"", ""email"": ""cball@example.com""}, {""name"": """,387,,,,Johnson and Sons,"[""about"", ""strong"", ""live""]",,arXiv:2022.71609,10.1121/RNkt,Cell,2024,,,Distributed foreground contingency


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

[User] Generate prescription data in JSON format.

[Assistant]
Approach:
1. Task: Create prescription 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:
{
  "rx_id": "RX-6036951",
  "patient_mrn": "MRN-440463",
  "prescriber": "Lisa Mathews",
  "date": "2026-01-05",
  "medications": [
    {
      "name": "Metformin",
      "dosage": "20mg",
      "frequency": "TID",
      "quantity": 90
    }
  ]
}


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

[User] Generate clinical note data in XML format.

[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-4036732</note_id>
<patient>
<mrn>MRN-366942</mrn>
<age>79</age>
<gender>M</gender>
</patient>
<encounter_date>2026-01-06</encounter_date>
<chief_complaint>headache</chief_complaint>
<vitals>
<bp>102/96</bp>

61

<temp_f>97.1</temp_f>
</vitals>
<assessment>
<problem>hypertension</problem>
<icd10>K52</icd10>
</assessment>
</clinical_note>


[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:
{
  "instructor": "Rachel Moreno DVM",
  "credits": 4,
  "course_id": "CRS-8305",
  "title": "Open-architected even-keeled support 101",
  "term": "Spring 2023"
}


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

[User]
Transform this CSV data into TOML format:
article_id,author,content,headline,published,section,shares,tags,views
ART-8846154,Melanie Kennedy,"Edge wear coach whether dog sell respond. Claim feeling meeting somebody four real.
Indeed use send ",Phased bifurcated instruction set,2026-01-02T14:27:49.190328,Sports,4081,"[""memory"", ""score"", ""game"", ""join""]",47684
ART-3613315,Anna Knight,"Similar high have research crime bag table. Here attorney type true trial.
Economy word theory. Stay",Multi-channeled global leverage,2026-01-06T01:37:20.071841,Sports,3909,"[""listen"", ""report"", ""president"", ""talk"", ""party""]",41311
ART-2769854,Jeffrey Marshall,Popular town open. Top must budget water important prepare. Condition side performance policy board.,Realigned multimedia secured line,2026-01-04T10:17:55.709215,Politics,2383,"[""much"", ""democratic"", ""camera""]",51309
ART-3204910,Kim Griffith,"Reason today able police. Thus accept book rise measure manager international.
Everything developmen",Synchronized logistical Graphic Interface,2026-01-06T13:05:47.997886,Politics,1419,"[""recent"", ""man"", ""four"", ""authority"", ""though""]",46101

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

Output:
article_id = "ART-8846154"
headline = "Phased bifurcated instruction set"
author = "Melanie Kennedy"
published = "2026-01-02T14:27:49.190328"
section = "Sports"
content = "Edge wear coach whether dog sell respond. Claim feeling meeting somebody four real.\nIndeed use send represent leader require. Cup attack instead discuss. Plan with character rule.\nInformation mind company even serve. Experience pattern but certain she design speech."
tags = [ "memory", "score", "game", "join",]
views = 47684
shares = 4081


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

[User] Generate experiment result data in XML format.

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

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


[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 = "Distributed high-level website API"
version = "1.0.0"

[paths."/next".get]
summary = "Movie my movie common adult."
[[paths."/next".get.parameters]]
name = "param0"
in = "query"
type = "string"

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

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

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


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

[User]
Convert the following JSON to XML:
{
  "error_id": "2a52fc1b-775b-4f0d-9bad-8f4f44e2d81f",
  "timestamp": "2026-01-07T13:51:25.611338",
  "level": "ERROR",
  "service": "typeService",
  "message": "Suggest involve part skill write left participant.",
  "stack_trace": [
    "at risk.py:441",
    "at strategy.py:390",
    "at performance.py:267",
    "at kind.py:265"
  ],
  "context": {
    "user_id": "3651fff2-dc6a-4fe5-a964-ed26913f3e4b",
    "request_id": "f4fc48f0-6374-4e80-b666-89c2abac0904"
  }
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<error_log>
<error_id>2a52fc1b-775b-4f0d-9bad-8f4f44e2d81f</error_id>
<timestamp>2026-01-07T13:51:25.611338</timestamp>
<level>ERROR</level>
<service>typeService</service>
<message>Suggest involve part skill write left participant.</message>
<stack_trace>at risk.py:441</stack_trace>
<stack_trace>at strategy.py:390</stack_trace>
<stack_trace>at performance.py:267</stack_trace>
<stack_trace>at kind.py:265</stack_trace>
<context>
<user_id>3651fff2-dc6a-4fe5-a964-ed26913f3e4b</user_id>
<request_id>f4fc48f0-6374-4e80-b666-89c2abac0904</request_id>
</context>
</error_log>


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

[User] Output error log as XML.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<error_log>
<error_id>c6e14566-270a-4a5f-a250-5239ca9174ac</error_id>
<timestamp>2026-01-07T13:51:26.338486</timestamp>
<level>ERROR</level>
<service>humanService</service>
<message>Fear she east talk better central.</message>
<stack_trace>at college.py:218</stack_trace>
<stack_trace>at economy.py:209</stack_trace>
<stack_trace>at let.py:252</stack_trace>
<stack_trace>at whole.py:18</stack_trace>
<context>
<user_id>bda2bdb3-cc4e-4711-8927-aa42dc72d462</user_id>
<request_id>c7d51186-07ee-4743-a193-c5688ac0d6c5</request_id>
</context>
</error_log>


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

[User]
Transform this CSV data into XML format:
date,medications,patient_mrn,prescriber,rx_id
2026-01-01,"[{""name"": ""Lisinopril"", ""dosage"": ""10mg"", ""frequency"": ""BID"", ""quantity"": 60}, {""name"": ""Lisinopril""",MRN-412331,Tammy Adams,RX-2317847
2026-01-05,"[{""name"": ""Lisinopril"", ""dosage"": ""20mg"", ""frequency"": ""BID"", ""quantity"": 30}]",MRN-273903,Theresa Reyes,RX-7015507
2026-01-02,"[{""name"": ""Metformin"", ""dosage"": ""20mg"", ""frequency"": ""BID"", ""quantity"": 90}, {""name"": ""Lisinopril"",",MRN-457609,Daniel Greer,RX-2779694
2026-01-05,"[{""name"": ""Atorvastatin"", ""dosage"": ""20mg"", ""frequency"": ""daily"", ""quantity"": 90}]",MRN-534897,Stephanie Martinez,RX-4473562
2026-01-06,"[{""name"": ""Lisinopril"", ""dosage"": ""10mg"", ""frequency"": ""TID"", ""quantity"": 60}, {""name"": ""Metformin"",",MRN-481534,Anthony Elliott,RX-6283033

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<prescription>
<rx_id>RX-2317847</rx_id>
<patient_mrn>MRN-412331</patient_mrn>
<prescriber>Tammy Adams</prescriber>
<date>2026-01-01</date>
<medications>
<name>Lisinopril</name>
<dosage>10mg</dosage>
<frequency>BID</frequency>
<quantity>60</quantity>
</medications>
<medications>
<name>Lisinopril</name>
<dosage>10mg</dosage>
<frequency>BID</frequency>
<quantity>90</quantity>
</medications>
<medications>
<name>Atorvastatin</name>
<dosage>5mg</dosage>
<frequency>BID</frequency>
<quantity>30</quantity>
</medications>
</prescription>


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

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

[Assistant]
Approach:
1. Task: Create clinical note 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:
{
  "note_id": "CN-4493327",
  "patient": {
    "mrn": "MRN-934301",
    "age": 62,
    "gender": "F"
  },
  "encounter_date": "2026-01-06",
  "chief_complaint": "fever",
  "vitals": {
    "bp": "141/91",
    "hr": 100,
    "temp_f": 98.5
  },
  "assessment": [
    {
      "problem": "diabetes",
      "icd10": "I32"
    }
  ]
}


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

[User] Generate lab result data in YAML format.

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

Output:
result_id: LAB-9548003
patient_mrn: MRN-322322
order_date: '2026-01-03'
panel: CMP
results:
- test: Glucose
  value: 67.0
  unit: g/dL
  flag: high
- test: Hemoglobin
  value: 66.7
  unit: mg/dL
  flag: low
- test: Glucose
  value: 118.1
  unit: mg/dL
  flag: normal
- test: Hemoglobin
  value: 198.6
  unit: mg/dL
  flag: normal
- test: Glucose
  value: 167.9
  unit: mg/dL
  flag: low
- test: Hemoglobin
  value: 143.5
  unit: mg/dL
  flag: normal
- test: Glucose
  value: 150.3
  unit: g/dL
  flag: low


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Secured well-modulated policy API</title>
<version>1.0.0</version>
</info>
<paths>
</article>
<get>
<summary>During certainly full.</summary>
<parameters>
<name>param0</name>
<in>query</in>
<type>string</type>
</parameters>
<parameters>
<name>param1</name>
<in>query</in>
<type>string</type>
</parameters>
<parameters>
<name>param2</name>
<in>query</in>
<type>string</type>
</parameters>
<responses>
<200>
<description>Success</description>
</200>
<400>
<description>Bad Request</description>
</400>
</responses>
</get>
<//article>
</paths>
</api_specification>

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

Output:
{
  "openapi": "3.0.0",
  "info": {
    "title": "Secured well-modulated policy API",
    "version": "1.0.0"
  },
  "paths": {
    "/article": {
      "get": {
        "summary": "During certainly full.",
        "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]
Convert the following CSV to TOML:
category,currency,is_available,name,price,product_id,rating,reviews,specs_dimensions,specs_weight_kg,stock
books,USD,True,Focused background info-mediaries,16.4,PROD-891981,3.23,117,65x39x62cm,31.51,192
clothing,USD,True,Triple-buffered value-added utilization,636.7,PROD-453557,4.77,75,65x67x98cm,28.2,649
clothing,USD,True,Re-contextualized transitional emulation,808.49,PROD-253084,4.69,259,31x19x83cm,19.88,82

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

Output:
product_id = "PROD-891981"
name = "Focused background info-mediaries"
category = "books"
price = 16.4
currency = "USD"
stock = 192
is_available = true
rating = 3.23
reviews = 117

[specs]
weight_kg = 31.51
dimensions = "65x39x62cm"


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

[User] Output student assessment as TOML.

[Assistant]
Approach:
1. Task: Create student assessment in TOML
2. Complexity: 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:
assessment_id = "ASMT-350362"
student_id = "STU-421536"
course_id = "CRS-1231"
type = "exam"
date = "2026-01-01"
total_score = 51
percentage = 80.6
grade = "A"
[[scores]]
question = 1
points_earned = 2
points_possible = 10

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

[[scores]]
question = 3
points_earned = 8
points_possible = 10

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

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

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

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

[[scores]]
question = 8
points_earned = 2
points_possible = 10

[[scores]]
question = 9
points_earned = 1
points_possible = 10

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

[[scores]]
question = 11
points_earned = 9
points_possible = 10


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

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

[Assistant]
Approach:
1. Task: Create news article 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:
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 JSON format. Think step-by-step, then generate syntactically perfect JSON.

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<review_id>REV-5832770</review_id>
<product_id>PROD-688379</product_id>
<user_id>d5e035fb-55b8-4fae-85aa-504fb2b837bd</user_id>
<rating>3</rating>
<title>Investment great beat fear step Democrat treat.</title>
<content>Near season take foot decade hold some meet.
Pretty season exist old turn consumer particularly star. Step receive unit different.</content>
<date>2026-01-02</date>
<verified_purchase>False</verified_purchase>
<helpful_votes>62</helpful_votes>
</customer_review>

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

Output:
{
  "review_id": "REV-5832770",
  "product_id": "PROD-688379",
  "user_id": "d5e035fb-55b8-4fae-85aa-504fb2b837bd",
  "rating": 3,
  "title": "Investment great beat fear step Democrat treat.",
  "content": "Near season take foot decade hold some meet.\nPretty season exist old turn consumer particularly star. Step receive unit different.",
  "date": "2026-01-02",
  "verified_purchase": false,
  "helpful_votes": 62
}


[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-530397,,CRS-8191,,2026-01-01,A,,,,,61.03,,"[{""question"": 1, ""points_earned"": 3, ""points_possible"": 10}, {""question"": 2, ""points_earned"": 5, ""po",STU-509684,,,91,quiz
,EWU268,CRS-6528,3,,,40,30,30,Jeff Bennett,,"[{""week"": 1, ""topic"": ""represent""}, {""week"": 2, ""topic"": ""international""}, {""week"": 3, ""topic"": ""the",,,Spring 2023,Horizontal transitional extranet 101,,
,XEQ433,CRS-4620,3,,,40,30,30,Jonathan Cabrera,,"[{""week"": 1, ""topic"": ""report""}, {""week"": 2, ""topic"": ""begin""}, {""week"": 3, ""topic"": ""floor""}, {""wee",,,Fall 2021,Proactive executive definition 101,,
,JLC381,CRS-5661,3,,,40,30,30,Jenna Larson,,"[{""week"": 1, ""topic"": ""require""}, {""week"": 2, ""topic"": ""service""}, {""week"": 3, ""topic"": ""hope""}, {""w",,,Fall 2021,Business-focused systemic circuit 101,,


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

[User]
Convert the following JSON to XML:
{
  "helpful_votes": 39,
  "date": "2026-01-04",
  "rating": 5,
  "review_id": "REV-1864702",
  "title": "State standard bad message use."
}

[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>
<helpful_votes>39</helpful_votes>
<date>2026-01-04</date>
<rating>5</rating>
<review_id>REV-1864702</review_id>
<title>State standard bad message use.</title>
</customer_review>


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

[User] Generate news article data in TOML format.

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

Output:
article_id = "ART-6180455"
headline = "Grass-roots multi-tasking hub"
author = "David Espinoza"
published = "2026-01-07T13:20:10.771283"
section = "Politics"
content = "Either large lot east. Show everybody away city election happy my. Believe left sure mother.\nWhom game determine road little. Sing this character. Agent fill kitchen themselves agreement.\nWoman draw budget stage. Star cultural old president where national success."
tags = [ "size", "commercial", "president", "city", "expect",]
views = 43396
shares = 2564


[System] You are an expert in 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: medium - 5-8 fields, 2-3 levels
3. Format rules: proper braces/brackets, quoted keys, correct value types
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

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


[System] You are an expert in 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>
<result_id>LAB-5387789</result_id>
<patient_mrn>MRN-887521</patient_mrn>
<order_date>2026-01-05</order_date>
<panel>CBC</panel>
<results>
<test>WBC</test>
<value>66.6</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Glucose</test>
<value>111.4</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>168.1</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>136.7</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>WBC</test>
<value>148.7</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Glucose</test>
<value>86.9</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-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 CSV format. Think step-by-step, then generate syntactically perfect CSV.

[User] Output customer review as CSV.

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

Output:
category,content,currency,date,helpful_votes,is_available,name,price,product_id,rating,review_id,reviews,specs_dimensions,specs_weight_kg,stock,title,user_id,verified_purchase
,North describe old attention usually third. Important wish security ago somebody remain everyone mod,,2026-01-04,34,,,,PROD-452864,3,REV-9982202,,,,,Example center fill free.,015289de-7f3e-45e2-b1d0-7fe22aff92a9,False
books,,USD,,,True,Open-source uniform capability,301.27,PROD-318199,4.66,,24,81x14x96cm,40.6,54,,,
books,,USD,,,True,Reactive 4thgeneration contingency,189.15,PROD-546709,3.83,,865,33x54x28cm,22.27,209,,,
books,,USD,,,True,Cross-platform grid-enabled leverage,653.55,PROD-287286,3.19,,34,64x17x56cm,47.51,891,,,


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

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

[Assistant]
Approach:
1. Task: Create sales analytics 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:
period: March 2022
total_revenue: 7500818
units_sold: 73950
channels:
- name: retail
  revenue: 528123
  growth: 12.05
- name: online
  revenue: 1160273
  growth: 23.93
top_products:
- sku: SKU-6153
  sales: 328911
- sku: SKU-4483
  sales: 21251
- sku: SKU-5114
  sales: 21486


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

[User] Output student assessment as XML.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<student_assessment>
<assessment_id>ASMT-482875</assessment_id>
<student_id>STU-646713</student_id>
<course_id>CRS-2679</course_id>
<type>assignment</type>
<date>2026-01-01</date>
<scores>
<question>1</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>3</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>7</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>3</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>8</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>9</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>10</question>
<points_earned>8</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>62</total_score>
<percentage>98.87</percentage>
<grade>C</grade>
</student_assessment>


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

[User]
Reformat the data below from JSON to YAML:
{
  "paper_id": "arXiv:2020.69453",
  "title": "Assimilated needs-based portal",
  "authors": [
    {
      "name": "Evan Reed",
      "affiliation": "Orr, Wheeler and Johnson",
      "email": "cheryl05@example.net"
    },
    {
      "name": "Amanda Mcmahon",
      "affiliation": "Maxwell-Price",
      "email": "mbowen@example.org"
    },
    {
      "name": "Angel Vasquez",
      "affiliation": "Melendez, Osborne and Harris",
      "email": "timothysutton@example.com"
    }
  ],
  "abstract": "Economy instead thank kitchen. For pattern he purpose strong goal challenge.",
  "keywords": [
    "power",
    "main",
    "light",
    "form",
    "system"
  ],
  "publication": {
    "venue": "Cell",
    "year": 2024,
    "doi": "10.9550/gbOm"
  },
  "citations": 115,
  "funding_source": null
}

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

Output:
paper_id: arXiv:2020.69453
title: Assimilated needs-based portal
authors:
- name: Evan Reed
  affiliation: Orr, Wheeler and Johnson
  email: cheryl05@example.net
- name: Amanda Mcmahon
  affiliation: Maxwell-Price
  email: mbowen@example.org
- name: Angel Vasquez
  affiliation: Melendez, Osborne and Harris
  email: timothysutton@example.com
abstract: Economy instead thank kitchen. For pattern he purpose strong goal challenge.
keywords:
- power
- main
- light
- form
- system
publication:
  venue: Cell
  year: 2024
  doi: 10.9550/gbOm
citations: 115
funding_source: null


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

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

[Assistant]
Approach:
1. Task: Create social media post in XML
2. Complexity: 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"?>
<social_media_post>
<engagement>
<likes>6676</likes>
<shares>196</shares>
<comments>84</comments>
</engagement>
<username>nicholasalvarez</username>
<post_id>POST-61351209</post_id>
<hashtags>#pretty</hashtags>
<hashtags>#admit</hashtags>
<hashtags>#available</hashtags>
<user_id>5e546096-8461-4a3f-84e6-813e9e89a39c</user_id>
</social_media_post>


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<student_assessment>
<assessment_id>ASMT-549878</assessment_id>
<student_id>STU-264168</student_id>
<course_id>CRS-6692</course_id>
<type>assignment</type>
<date>2026-01-01</date>
<scores>
<question>1</question>
<points_earned>7</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>3</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>4</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>70</total_score>
<percentage>54.38</percentage>
<grade>C</grade>
</student_assessment>

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

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


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<review_id>REV-2575466</review_id>
<product_id>PROD-346187</product_id>
<user_id>320eb87e-12bd-44ab-bb47-6fec45bd5144</user_id>
<rating>1</rating>
<title>Possible modern last rate memory fight conference </title>
<content>Character walk loss rock me social gun.
Center choice either push. Push stop yourself.</content>
<date>2026-01-01</date>
<verified_purchase>False</verified_purchase>
<helpful_votes>26</helpful_votes>
</customer_review>

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

Output:
{
  "review_id": "REV-2575466",
  "product_id": "PROD-346187",
  "user_id": "320eb87e-12bd-44ab-bb47-6fec45bd5144",
  "rating": 1,
  "title": "Possible modern last rate memory fight conference ",
  "content": "Character walk loss rock me social gun.\nCenter choice either push. Push stop yourself.",
  "date": "2026-01-01",
  "verified_purchase": false,
  "helpful_votes": 26
}


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

[User]
Convert the following TOML to CSV:
date = "2026-01-05"
title = "Teach why painting per short."
rating = 4

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

Output:
abstract,authors,citations,date,funding_source,keywords,paper_id,publication_doi,publication_venue,publication_year,rating,title
,,,2026-01-05,,,,,,,4,Teach why painting per short.
City standard hit Republican specific win. Foot fast media everything drive and. West question mean ,"[{""name"": ""Daniel Torres"", ""affiliation"": ""Greene, Herrera and Lewis"", ""email"": ""sandy50@example.com",486,,None,"[""woman"", ""building"", ""population""]",arXiv:2020.88512,10.6688/TNnX,Cell,2024,,Persistent multimedia Graphical User Interface
"None chair suffer. Modern dog forward nation.
Send field order pay suffer.","[{""name"": ""Richard Fernandez"", ""affiliation"": ""Meza-Nguyen"", ""email"": ""megan29@example.com""}, {""name",387,,None,"[""worker"", ""family"", ""deal""]",arXiv:2024.40576,10.4368/nAhv,Nature,2024,,Switchable scalable data-warehouse


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

[User]
Reformat the data below from CSV to TOML:
abstract,authors,channels,citations,funding_source,keywords,paper_id,period,publication_doi,publication_venue,publication_year,title,top_products,total_revenue,units_sold
,,"[{""name"": ""wholesale"", ""revenue"": 2780960, ""growth"": 22.76}, {""name"": ""retail"", ""revenue"": 4140341, ",,,,,June 2021,,,,,"[{""sku"": ""SKU-8636"", ""sales"": 261407}, {""sku"": ""SKU-9950"", ""sales"": 107242}, {""sku"": ""SKU-8311"", ""sa",4317671,11582
Offer for day fact. Candidate both political painting left charge. Resource movement take serve red.,"[{""name"": ""Robert Khan"", ""affiliation"": ""Johnson, Faulkner and Young"", ""email"": ""lorianderson@exampl",,402,None,"[""great"", ""meet"", ""by""]",arXiv:2021.49528,,10.8172/rcFR,Cell,2024,Organized web-enabled Local Area Network,,,
Of once listen relationship director page name various. Before new foreign always.,"[{""name"": ""Jennifer Brown"", ""affiliation"": ""Gordon, Bullock and Hall"", ""email"": ""michaelramirez@exam",,193,None,"[""challenge"", ""on"", ""once"", ""fast"", ""view""]",arXiv:2023.72181,,10.8817/kYRi,Nature,2021,Upgradable asymmetric function,,,

[Assistant]
Approach:
1. Task: Convert sales analytics from CSV 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:
period = "June 2021"
total_revenue = 4317671
units_sold = 11582
[[channels]]
name = "wholesale"
revenue = 2780960
growth = 22.76

[[channels]]
name = "retail"
revenue = 4140341
growth = -9.84

[[top_products]]
sku = "SKU-8636"
sales = 261407

[[top_products]]
sku = "SKU-9950"
sales = 107242

[[top_products]]
sku = "SKU-8311"
sales = 494004


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

[User] Create a TOML representation of contract.

[Assistant]
Approach:
1. Task: Create contract 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:
contract_id = "CTR-449984"
effective_date = "2026-01-04"
term_months = 49
value = 694475
status = "pending"
[[parties]]
name = "Garcia-Henson"
role = "party_a"

[[parties]]
name = "Moore LLC"
role = "party_b"


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

[User] Output error log as YAML.

[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: 91d16731-5e7b-4a47-8285-7a54d79d3b76
timestamp: '2026-01-07T13:51:25.635487'
level: WARNING
service: AmericanService
message: Drug sell certainly major total.
stack_trace:
- at although.py:151
- at mission.py:443
context:
  user_id: 11d85442-7276-4e30-9249-06df8089bd39
  request_id: f3cc0b9c-f4db-4c9d-bea8-f49774b1a7e6


[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: 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:
article_id,author,content,headline,published,section,shares,tags,views
ART-3682408,Thomas Acevedo,"Cold trial recognize improve nice between these. Happy herself suggest impact tell easy.
Start movie",Decentralized stable neural-net,2026-01-01T11:30:40.673887,Business,1329,"[""movie"", ""it"", ""chance""]",12438
ART-4889709,Deanna Mann,Catch Mr blue soldier. Mr try line between lawyer store. Information open reveal choose piece base y,Integrated transitional instruction set,2026-01-05T15:50:35.466776,Business,745,"[""table"", ""leave"", ""kitchen"", ""statement"", ""kitchen""]",16714
ART-2876040,Michael Allen,"Blue strong team two war scene nice. Hundred deal goal will section.
Base analysis determine much si",Profound bandwidth-monitored architecture,2026-01-03T05:09:14.625194,Sports,2956,"[""base"", ""economic"", ""offer"", ""movie""]",68794


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

[User] Create a TOML representation of customer review.

[Assistant]
Approach:
1. Task: Create customer review in TOML
2. Complexity: 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:
review_id = "REV-7122533"
content = "Expert difficult hot radio mission. Throw southern he book way media particular."
rating = 1
date = "2026-01-06"
verified_purchase = false


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

[User]
Transform this JSON data into XML format:
{
  "product_id": "PROD-723394",
  "name": "Streamlined full-range ability",
  "category": "clothing",
  "price": 959.9,
  "currency": "USD",
  "stock": 28,
  "is_available": true,
  "rating": 3.7,
  "reviews": 332,
  "specs": {
    "weight_kg": 9.93,
    "dimensions": "53x67x45cm"
  }
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<product_listing>
<product_id>PROD-723394</product_id>
<name>Streamlined full-range ability</name>
<category>clothing</category>
<price>959.9</price>
<currency>USD</currency>
<stock>28</stock>
<is_available>True</is_available>
<rating>3.7</rating>
<reviews>332</reviews>
<specs>
<weight_kg>9.93</weight_kg>
<dimensions>53x67x45cm</dimensions>
</specs>
</product_listing>


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

[User]
Transform this CSV data into YAML format:
abstract,authors,citations,context_request_id,context_user_id,error_id,funding_source,keywords,level,message,paper_id,publication_doi,publication_venue,publication_year,service,stack_trace,timestamp,title
,,,cc597ab0-ad26-419a-8cbb-1facc38a2f79,dc348ded-7e54-44aa-bfc8-75caf977ffdf,7af25ba6-3e63-43d5-89e6-c5a6b377b923,,,CRITICAL,Prevent true movie stop.,,,,,downService,"[""at hand.py:436"", ""at whose.py:275"", ""at information.py:57"", ""at central.py:306""]",2026-01-07T13:51:26.975438,
Office seat military low watch than message. Less career open task sister. Listen black single colle,"[{""name"": ""Michael Harrell"", ""affiliation"": ""Garrison, Jones and Carter"", ""email"": ""hawkinsscott@exa",2,,,,"Morse, Wallace and Chaney","[""yet"", ""friend"", ""window"", ""hotel"", ""hour""]",,,arXiv:2020.65137,10.4037/HCtk,Nature,2022,,,,Configurable disintermediate analyzer
Concern develop institution at while development very. Rock PM view sea.,"[{""name"": ""Jennifer Parker"", ""affiliation"": ""Howe-Gray"", ""email"": ""nathan31@example.net""}, {""name"": ",328,,,,None,"[""talk"", ""new"", ""window"", ""ground"", ""team""]",,,arXiv:2024.76212,10.8353/sGCQ,Science,2023,,,,Front-line solution-oriented customer loyalty

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

Output:
error_id: 7af25ba6-3e63-43d5-89e6-c5a6b377b923
timestamp: '2026-01-07T13:51:26.975438'
level: CRITICAL
service: downService
message: Prevent true movie stop.
stack_trace:
- at hand.py:436
- at whose.py:275
- at information.py:57
- at central.py:306
context:
  user_id: dc348ded-7e54-44aa-bfc8-75caf977ffdf
  request_id: cc597ab0-ad26-419a-8cbb-1facc38a2f79


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

[User] Generate news article data in CSV format.

[Assistant]
Approach:
1. Task: Create news article 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:
article_id,author,content,headline,published,section,shares,tags,views
ART-6180455,David Espinoza,"Either large lot east. Show everybody away city election happy my. Believe left sure mother.
Whom ga",Grass-roots multi-tasking hub,2026-01-07T13:20:10.771283,Politics,2564,"[""size"", ""commercial"", ""president"", ""city"", ""expect""]",43396
ART-2182419,Robert Marshall,Occur activity camera reach management fall. Early machine direction mouth girl condition challenge.,Public-key motivating methodology,2026-01-01T04:17:08.457393,Politics,4721,"[""feel"", ""stay"", ""do"", ""student"", ""music""]",77224
ART-5298594,Theodore Brady,There professor party cover fly study radio. Process those all word hotel at perhaps. Strategy ask t,Future-proofed bifurcated standardization,2026-01-05T16:49:21.984657,Sports,967,"[""maintain"", ""human"", ""but""]",91827
ART-9171860,Stephanie Valenzuela,Main whatever it field. Pull himself trouble themselves officer Republican. Everybody address guy fi,Quality-focused scalable protocol,2026-01-01T09:23:05.902795,Tech,2188,"[""anything"", ""year"", ""since""]",92753
ART-4473583,Daniel Thomas,"Improve four position natural. Thought medical camera. Prevent although happen.
Difference six avail",Innovative transitional instruction set,2026-01-04T12:02:18.215147,Business,1990,"[""standard"", ""reach"", ""no"", ""glass"", ""outside""]",55011


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<clinical_note>
<note_id>CN-9595817</note_id>
<patient>
<mrn>MRN-972408</mrn>
<age>32</age>
<gender>F</gender>
</patient>
<encounter_date>2026-01-02</encounter_date>
<chief_complaint>chest pain</chief_complaint>
<vitals>
<bp>102/103</bp>

113

<temp_f>102.5</temp_f>
</vitals>
<assessment>
<problem>hypertension</problem>
<icd10>K99</icd10>
</assessment>
</clinical_note>

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

Output:
{
  "note_id": "CN-9595817",
  "patient": {
    "mrn": "MRN-972408",
    "age": 32,
    "gender": "F"
  },
  "encounter_date": "2026-01-02",
  "chief_complaint": "chest pain",
  "vitals": {
    "bp": "102/103",
    "hr": 113,
    "temp_f": 102.5
  },
  "assessment": [
    {
      "problem": "hypertension",
      "icd10": "K99"
    }
  ]
}


[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"?>
<customer_review>
<helpful_votes>39</helpful_votes>
<date>2026-01-04</date>
<rating>5</rating>
<review_id>REV-1864702</review_id>
<title>State standard bad message use.</title>
</customer_review>

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

Output:
{
  "helpful_votes": 39,
  "date": "2026-01-04",
  "rating": 5,
  "review_id": "REV-1864702",
  "title": "State standard bad message use."
}


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

[User] Output course syllabus as XML.

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


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

[User] Generate clinical note data in YAML format.

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

Output:
note_id: CN-4315709
patient:
  mrn: MRN-534874
  age: 89
  gender: M
encounter_date: '2026-01-02'
chief_complaint: chest pain
vitals:
  bp: 165/61
  hr: 112
  temp_f: 99.4
assessment:
- problem: diabetes
  icd10: I12
- problem: diabetes
  icd10: K62


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

[User] Output course syllabus as YAML.

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

Output:
course_id: CRS-6496
code: TMG245
instructor: Maria Bowers
schedule:
- week: 1
  topic: situation
- week: 2
  topic: firm
- week: 3
  topic: involve
- week: 4
  topic: change
- week: 5
  topic: yard
- week: 6
  topic: morning
- week: 7
  topic: other
- week: 8
  topic: left


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

[User] Output api specification as CSV.

[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_/sea_get_parameters,paths_/sea_get_responses_200_description,paths_/sea_get_responses_400_description,paths_/sea_get_summary,publication_doi,publication_venue,publication_year,title
,,,,Assimilated neutral archive API,1.0.0,,3.0.0,,"[{""name"": ""param0"", ""in"": ""query"", ""type"": ""string""}, {""name"": ""param1"", ""in"": ""query"", ""type"": ""str",Success,Bad Request,Team happen challenge address expert manage beyond,,,,
People begin standard church month.,"[{""name"": ""Wesley Griffith"", ""affiliation"": ""Gomez, Rogers and Erickson"", ""email"": ""stevensilva@exam",56,None,,,"[""sometimes"", ""task"", ""none"", ""animal"", ""Republican""]",,arXiv:2021.98399,,,,,10.5743/MbeJ,Nature,2022,Devolved secondary artificial intelligence
Old if wife open recognize establish. Whether hair personal check able name. Car reality later playe,"[{""name"": ""Tiffany Hardy"", ""affiliation"": ""Anderson, Ortega and Murphy"", ""email"": ""lucasbenson@examp",141,None,,,"[""foot"", ""hour"", ""bit"", ""positive"", ""your""]",,arXiv:2021.14017,,,,,10.3231/ZsJR,Nature,2021,Balanced uniform product


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

[User]
Convert the following JSON to XML:
{
  "period": "September 2023",
  "total_revenue": 9732569,
  "units_sold": 38507,
  "channels": [
    {
      "name": "retail",
      "revenue": 4979277,
      "growth": 36.06
    },
    {
      "name": "wholesale",
      "revenue": 4800863,
      "growth": 8.87
    }
  ],
  "top_products": [
    {
      "sku": "SKU-5649",
      "sales": 311811
    },
    {
      "sku": "SKU-1879",
      "sales": 391924
    },
    {
      "sku": "SKU-4665",
      "sales": 317392
    }
  ]
}

[Assistant]
Approach:
1. Task: Convert sales analytics 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"?>
<sales_analytics>
<period>September 2023</period>
<total_revenue>9732569</total_revenue>
<units_sold>38507</units_sold>
<channels>
<name>retail</name>
<revenue>4979277</revenue>
<growth>36.06</growth>
</channels>
<channels>
<name>wholesale</name>
<revenue>4800863</revenue>
<growth>8.87</growth>
</channels>
<top_products>
<sku>SKU-5649</sku>
<sales>311811</sales>
</top_products>
<top_products>
<sku>SKU-1879</sku>
<sales>391924</sales>
</top_products>
<top_products>
<sku>SKU-4665</sku>
<sales>317392</sales>
</top_products>
</sales_analytics>


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

[User] Output experiment result as YAML.

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

Output:
experiment_id: EXP-393268
title: Effect of themselves on time
methodology:
  design: RCT
  sample_size: 237
  duration_days: 116
results:
- metric: efficacy
  baseline: 34.76
  endpoint: 73.98
  p_value: 0.4055
- metric: safety
  baseline: 70.26
  endpoint: 84.17
  p_value: 0.253
- metric: safety
  baseline: 22.1
  endpoint: 56.91
  p_value: 0.1172
conclusion: significant


[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"?>
<research_paper>
<paper_id>arXiv:2020.69453</paper_id>
<title>Assimilated needs-based portal</title>
<authors>
<name>Evan Reed</name>
<affiliation>Orr, Wheeler and Johnson</affiliation>
<email>cheryl05@example.net</email>
</authors>
<authors>
<name>Amanda Mcmahon</name>
<affiliation>Maxwell-Price</affiliation>
<email>mbowen@example.org</email>
</authors>
<authors>
<name>Angel Vasquez</name>
<affiliation>Melendez, Osborne and Harris</affiliation>
<email>timothysutton@example.com</email>
</authors>
<abstract>Economy instead thank kitchen. For pattern he purpose strong goal challenge.</abstract>
<keywords>power</keywords>
<keywords>main</keywords>
<keywords>light</keywords>
<keywords>form</keywords>
<keywords>system</keywords>
<publication>
<venue>Cell</venue>
<year>2024</year>
<doi>10.9550/gbOm</doi>
</publication>
<citations>115</citations>
<funding_source />
</research_paper>

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

Output:
{
  "paper_id": "arXiv:2020.69453",
  "title": "Assimilated needs-based portal",
  "authors": [
    {
      "name": "Evan Reed",
      "affiliation": "Orr, Wheeler and Johnson",
      "email": "cheryl05@example.net"
    },
    {
      "name": "Amanda Mcmahon",
      "affiliation": "Maxwell-Price",
      "email": "mbowen@example.org"
    },
    {
      "name": "Angel Vasquez",
      "affiliation": "Melendez, Osborne and Harris",
      "email": "timothysutton@example.com"
    }
  ],
  "abstract": "Economy instead thank kitchen. For pattern he purpose strong goal challenge.",
  "keywords": [
    "power",
    "main",
    "light",
    "form",
    "system"
  ],
  "publication": {
    "venue": "Cell",
    "year": 2024,
    "doi": "10.9550/gbOm"
  },
  "citations": 115,
  "funding_source": null
}


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

[User] Generate customer review data in JSON format.

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

Output:
{
  "review_id": "REV-7122533",
  "content": "Expert difficult hot radio mission. Throw southern he book way media particular.",
  "rating": 1,
  "date": "2026-01-06",
  "verified_purchase": false
}


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

[User] Generate experiment result data in TOML format.

[Assistant]
Approach:
1. Task: Create experiment 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:
experiment_id = "EXP-734376"
title = "Effect of probably on skin"
conclusion = "significant"
[[results]]
metric = "efficacy"
baseline = 94.92
endpoint = 99.12
p_value = 0.3163

[[results]]
metric = "safety"
baseline = 43.8
endpoint = 81.58
p_value = 0.1627

[[results]]
metric = "efficacy"
baseline = 31.59
endpoint = 36.02
p_value = 0.4619

[[results]]
metric = "efficacy"
baseline = 82.54
endpoint = 59.85
p_value = 0.3654

[methodology]
design = "cohort"
sample_size = 800
duration_days = 273


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

[User] Output product listing as YAML.

[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:
rating: 4.54
stock: 843
specs:
  weight_kg: 34.7
  dimensions: 61x86x65cm
currency: USD


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

[User]
Reformat the data below from JSON to XML:
{
  "post_id": "POST-59844758",
  "timestamp": "2026-01-07T13:51:27.358144",
  "hashtags": [
    "#population",
    "#during",
    "#executive",
    "#house"
  ]
}

[Assistant]
Approach:
1. Task: Convert social media post 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"?>
<social_media_post>
<post_id>POST-59844758</post_id>
<timestamp>2026-01-07T13:51:27.358144</timestamp>
<hashtags>#population</hashtags>
<hashtags>#during</hashtags>
<hashtags>#executive</hashtags>
<hashtags>#house</hashtags>
</social_media_post>


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

[User] Output prescription as TOML.

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

Output:
rx_id = "RX-5305677"
patient_mrn = "MRN-215469"
prescriber = "Jeremy Hatfield"
date = "2026-01-03"
[[medications]]
name = "Metformin"
dosage = "10mg"
frequency = "daily"
quantity = 90

[[medications]]
name = "Metformin"
dosage = "5mg"
frequency = "daily"
quantity = 30

[[medications]]
name = "Atorvastatin"
dosage = "10mg"
frequency = "BID"
quantity = 90


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

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

[Assistant]
Approach:
1. Task: Create product listing in CSV
2. Complexity: 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
clothing,USD,True,Streamlined full-range ability,959.9,PROD-723394,3.7,332,53x67x45cm,9.93,28
electronics,USD,True,Expanded bottom-line model,840.7,PROD-698040,4.22,190,74x95x57cm,3.34,783
books,USD,True,De-engineered 5thgeneration complexity,615.54,PROD-690887,3.16,360,17x21x44cm,25.36,224


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

[User] Generate experiment result data in JSON format.

[Assistant]
Approach:
1. Task: Create experiment result in JSON
2. Complexity: 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:
{
  "experiment_id": "EXP-139463",
  "title": "Effect of quite on arm",
  "methodology": {
    "design": "RCT",
    "sample_size": 371,
    "duration_days": 284
  },
  "results": [
    {
      "metric": "safety",
      "baseline": 91.61,
      "endpoint": 76.9,
      "p_value": 0.4003
    },
    {
      "metric": "safety",
      "baseline": 58.96,
      "endpoint": 23.83,
      "p_value": 0.3437
    },
    {
      "metric": "safety",
      "baseline": 23.31,
      "endpoint": 88.63,
      "p_value": 0.3018
    }
  ],
  "conclusion": "non-significant"
}


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

[User] Output social media post as JSON.

[Assistant]
Approach:
1. Task: Create social media post 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:
{
  "post_id": "POST-46905875",
  "platform": "instagram",
  "user_id": "2079b341-d50b-4860-ba15-aa28bbe0f5b3",
  "username": "xhernandez",
  "content": "Serious degree upon late.\nPainting throughout direction indicate night. Political business voice street child. Across between ready. Majority red mission prepare state.",
  "timestamp": "2026-01-07T13:51:26.735117",
  "hashtags": [
    "#easy",
    "#miss"
  ],
  "engagement": {
    "likes": 6808,
    "shares": 9,
    "comments": 24
  }
}


[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: 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-1521978</review_id>
<product_id>PROD-894495</product_id>
<user_id>0e93d4dc-0d39-4af2-8ec3-d8d1250011b9</user_id>
<rating>4</rating>
<title>Great how data open such.</title>
<content>City not either situation all along might. Under could expect build member. Fish ready onto white majority.</content>
<date>2026-01-05</date>
<verified_purchase>False</verified_purchase>
<helpful_votes>57</helpful_votes>
</customer_review>


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

[User]
Reformat the data below from JSON to YAML:
{
  "company": "Thompson LLC",
  "ticker": "QQLN",
  "quarter": "Q2 2020",
  "revenue": 63838743,
  "expenses": 967762,
  "net_income": 16633381,
  "eps": 0.69,
  "metrics": {
    "profit_margin": 22.56,
    "roe": 23.58
  }
}

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

Output:
company: Thompson LLC
ticker: QQLN
quarter: Q2 2020
revenue: 63838743
expenses: 967762
net_income: 16633381
eps: 0.69
metrics:
  profit_margin: 22.56
  roe: 23.58


[System] You are an expert in 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-94493547"
platform = "instagram"
user_id = "ebddd714-2a63-4fd6-985c-fb7fe32db0b4"
username = "laura52"
content = "Property political your form stand cup blood. Business later seem sea represent enough relationship memory.\nWhat ok that look past. Budget understand mouth during brother pull type spring."
timestamp = "2026-01-07T13:51:27.134920"
hashtags = [ "#red", "#hotel", "#create",]

[engagement]
likes = 8599
shares = 93
comments = 39


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

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

[Assistant]
Approach:
1. Task: Create social media post 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:
{
  "post_id": "POST-58559815",
  "platform": "instagram",
  "user_id": "0fae79ab-dabb-47f5-823b-f22743181c7c",
  "username": "ortizkristina",
  "content": "Speech can sea play. Season near story animal remain.\nOff present vote wall. Society know family build. Certain thing live rise.",
  "timestamp": "2026-01-07T13:51:26.463560",
  "hashtags": [
    "#once",
    "#it",
    "#rich",
    "#keep"
  ],
  "engagement": {
    "likes": 248,
    "shares": 32,
    "comments": 161
  }
}


[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"?>
<sales_analytics>
<period>February 2020</period>
<total_revenue>2007174</total_revenue>
<units_sold>24558</units_sold>
<channels>
<name>online</name>
<revenue>235807</revenue>
<growth>46.03</growth>
</channels>
<channels>
<name>wholesale</name>
<revenue>4419318</revenue>
<growth>24.35</growth>
</channels>
<top_products>
<sku>SKU-6554</sku>
<sales>258652</sales>
</top_products>
<top_products>
<sku>SKU-8652</sku>
<sales>200091</sales>
</top_products>
<top_products>
<sku>SKU-9581</sku>
<sales>65110</sales>
</top_products>
</sales_analytics>

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

Output:
{
  "period": "February 2020",
  "total_revenue": 2007174,
  "units_sold": 24558,
  "channels": [
    {
      "name": "online",
      "revenue": 235807,
      "growth": 46.03
    },
    {
      "name": "wholesale",
      "revenue": 4419318,
      "growth": 24.35
    }
  ],
  "top_products": [
    {
      "sku": "SKU-6554",
      "sales": 258652
    },
    {
      "sku": "SKU-8652",
      "sales": 200091
    },
    {
      "sku": "SKU-9581",
      "sales": 65110
    }
  ]
}


[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:
openapi: 3.0.0
paths:
  /sense:
    get:
      summary: Pay yes agree executive year ahead program.
      parameters:
      - name: param0
        in: query
        type: string
      responses:
        '200':
          description: Success
        '400':
          description: Bad Request
info:
  title: Customer-focused zero-defect array API
  version: 1.0.0


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

[User] Create a JSON representation of transaction record.

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

Output:
{
  "txn_id": "TXN-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: 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
2026-01-03,"[{""name"": ""Metformin"", ""dosage"": ""20mg"", ""frequency"": ""TID"", ""quantity"": 60}, {""name"": ""Atorvastatin",MRN-226686,Regina Martin,RX-1565761
2026-01-05,"[{""name"": ""Metformin"", ""dosage"": ""10mg"", ""frequency"": ""TID"", ""quantity"": 90}, {""name"": ""Lisinopril"",",MRN-596334,Faith Jackson,RX-7485145
2026-01-01,"[{""name"": ""Lisinopril"", ""dosage"": ""10mg"", ""frequency"": ""daily"", ""quantity"": 60}]",MRN-336641,Jon Hogan,RX-6914611
2026-01-02,"[{""name"": ""Lisinopril"", ""dosage"": ""20mg"", ""frequency"": ""TID"", ""quantity"": 90}]",MRN-628797,Michael Price,RX-9410524
2026-01-02,"[{""name"": ""Metformin"", ""dosage"": ""20mg"", ""frequency"": ""TID"", ""quantity"": 60}, {""name"": ""Lisinopril"",",MRN-585011,Luis Harrison,RX-4229300


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

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

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

Output:
{
  "company": "Moore-Thompson",
  "ticker": "XFVE",
  "quarter": "Q2 2022",
  "revenue": 73324772,
  "expenses": 43130054,
  "net_income": 18329728,
  "eps": 9.88,
  "metrics": {
    "profit_margin": 22.03,
    "roe": 10.54
  }
}


[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>Moore-Thompson</company>
<ticker>XFVE</ticker>
<quarter>Q2 2022</quarter>
<revenue>73324772</revenue>
<expenses>43130054</expenses>
<net_income>18329728</net_income>
<eps>9.88</eps>
<metrics>
<profit_margin>22.03</profit_margin>
<roe>10.54</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 YAML to XML:
paper_id: arXiv:2021.53732
title: De-engineered exuding monitoring
authors:
- name: Joseph Johnson
  affiliation: Mccann, Romero and Ortiz
  email: wcook@example.org
- name: Mr. Henry Thomas
  affiliation: Clarke-Williams
  email: mlittle@example.com
abstract: Cut happen you after talk trial accept she. Country church development card.
  Learn support son service.
keywords:
- positive
- American
- hand
- sure
publication:
  venue: Science
  year: 2024
  doi: 10.3815/gTFt
citations: 88
funding_source: Kim LLC

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<research_paper>
<paper_id>arXiv:2021.53732</paper_id>
<title>De-engineered exuding monitoring</title>
<authors>
<name>Joseph Johnson</name>
<affiliation>Mccann, Romero and Ortiz</affiliation>
<email>wcook@example.org</email>
</authors>
<authors>
<name>Mr. Henry Thomas</name>
<affiliation>Clarke-Williams</affiliation>
<email>mlittle@example.com</email>
</authors>
<abstract>Cut happen you after talk trial accept she. Country church development card. Learn support son service.</abstract>
<keywords>positive</keywords>
<keywords>American</keywords>
<keywords>hand</keywords>
<keywords>sure</keywords>
<publication>
<venue>Science</venue>
<year>2024</year>
<doi>10.3815/gTFt</doi>
</publication>
<citations>88</citations>
<funding_source>Kim LLC</funding_source>
</research_paper>


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


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

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

[Assistant]
Approach:
1. Task: Create course syllabus 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:
code,course_id,credits,grading_final,grading_homework,grading_midterm,instructor,schedule,term,title
NHA456,CRS-2281,3,40,30,30,Natalie Middleton,"[{""week"": 1, ""topic"": ""its""}, {""week"": 2, ""topic"": ""attorney""}, {""week"": 3, ""topic"": ""decision""}, {""",Spring 2024,Profit-focused mission-critical hardware 101
NMW222,CRS-2495,3,40,30,30,Kylie Davis,"[{""week"": 1, ""topic"": ""trial""}, {""week"": 2, ""topic"": ""night""}, {""week"": 3, ""topic"": ""financial""}, {""",Spring 2020,Ergonomic intangible product 101
UMT270,CRS-2420,3,40,30,30,Katrina Jensen,"[{""week"": 1, ""topic"": ""national""}, {""week"": 2, ""topic"": ""through""}, {""week"": 3, ""topic"": ""seat""}, {""",Spring 2020,Programmable national migration 101
OFO453,CRS-6448,4,40,30,30,Jeffrey Nunez MD,"[{""week"": 1, ""topic"": ""above""}, {""week"": 2, ""topic"": ""nation""}, {""week"": 3, ""topic"": ""present""}, {""w",Fall 2024,Team-oriented transitional success 101


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

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

[Assistant]
Approach:
1. Task: Create error log in TOML
2. Complexity: 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 = "91d16731-5e7b-4a47-8285-7a54d79d3b76"
timestamp = "2026-01-07T13:51:25.635487"
level = "WARNING"
service = "AmericanService"
message = "Drug sell certainly major total."
stack_trace = [ "at although.py:151", "at mission.py:443",]

[context]
user_id = "11d85442-7276-4e30-9249-06df8089bd39"
request_id = "f3cc0b9c-f4db-4c9d-bea8-f49774b1a7e6"


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

[User] Create a YAML representation of prescription.

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

Output:
rx_id: RX-8706225
patient_mrn: MRN-970748
prescriber: Brady Keller
date: '2026-01-01'
medications:
- name: Lisinopril
  dosage: 5mg
  frequency: TID
  quantity: 30


[System] You are an expert in 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: 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-2691236</review_id>
<product_id>PROD-245093</product_id>
<user_id>98b0ec97-f0e6-4eda-907b-c1488d5de2f5</user_id>
<rating>1</rating>
<title>Now new sell exist just.</title>
<content>Issue suddenly such maybe. Military they second staff end agreement.
Close that speech alone know wish matter. Finally adult statement method.</content>
<date>2026-01-02</date>
<verified_purchase>False</verified_purchase>
<helpful_votes>34</helpful_votes>
</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"?>
<course_syllabus>
<course_id>CRS-9141</course_id>
ESH384
<title>Inverse real-time hardware 101</title>
<instructor>Matthew Boyd</instructor>
<credits>4</credits>
<term>Fall 2022</term>
<schedule>
<week>1</week>
<topic>western</topic>
</schedule>
<schedule>
<week>2</week>
<topic>since</topic>
</schedule>
<schedule>
<week>3</week>
<topic>later</topic>
</schedule>
<schedule>
<week>4</week>
<topic>next</topic>
</schedule>
<schedule>
<week>5</week>
<topic>tree</topic>
</schedule>
<schedule>
<week>6</week>
<topic>until</topic>
</schedule>
<schedule>
<week>7</week>
<topic>everything</topic>
</schedule>
<schedule>
<week>8</week>
<topic>until</topic>
</schedule>
<schedule>
<week>9</week>
<topic>how</topic>
</schedule>
<schedule>
<week>10</week>
<topic>test</topic>
</schedule>
<schedule>
<week>11</week>
<topic>half</topic>
</schedule>
<grading>
<homework>30</homework>
<midterm>30</midterm>
<final>40</final>
</grading>
</course_syllabus>

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


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

[User] Output news article as CSV.

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

Output:
article_id,author,content,headline,published,section,shares,tags,views
ART-9178511,Gabrielle Daugherty,Lawyer might home mouth end so science. Hope attention strong public teach person beautiful though. ,Fully-configurable secondary access,2026-01-05T07:34:40.744934,Tech,778,"[""maybe"", ""glass"", ""election"", ""moment""]",24250
ART-5510591,Aaron West,Not probably ask attorney win whose mind. Stay reflect dream energy create opportunity. Fly knowledg,Intuitive actuating firmware,2026-01-06T02:25:18.496242,Tech,2289,"[""attention"", ""line"", ""above"", ""own""]",89480
ART-5889047,Natasha Foster,Various hold if series opportunity professor there. Minute toward Republican would. Including teach ,Upgradable contextually-based projection,2026-01-02T19:16:57.233655,Tech,3105,"[""particularly"", ""movement"", ""performance"", ""fire""]",51297
ART-4927455,David Jackson,Become decide institution exactly this ability war. Fight new ability himself language fear nor life,Phased dedicated analyzer,2026-01-07T03:12:14.114582,Politics,1717,"[""control"", ""firm"", ""animal"", ""strategy"", ""huge""]",70765


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

[User] Output api specification as YAML.

[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:
info:
  title: Object-based multimedia secured line API
  version: 1.0.0
openapi: 3.0.0
paths:
  /party:
    get:
      summary: Discussion partner stay wear again.
      parameters:
      - name: param0
        in: query
        type: string
      - name: param1
        in: query
        type: string
      responses:
        '200':
          description: Success
        '400':
          description: Bad Request


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

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

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

Output:
product_id = "PROD-308726"
name = "Cross-platform client-server attitude"
category = "electronics"
price = 875.12
currency = "USD"
stock = 161
is_available = true
rating = 1.18
reviews = 705

[specs]
weight_kg = 37.34
dimensions = "78x81x41cm"


[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: complex - 8-10 fields, 3-4 levels
3. Format rules: proper braces/brackets, quoted keys, correct value types
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
{
  "result_id": "LAB-2983714",
  "patient_mrn": "MRN-369371",
  "order_date": "2026-01-04",
  "panel": "CMP",
  "results": [
    {
      "test": "Hemoglobin",
      "value": 97.6,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "WBC",
      "value": 60.0,
      "unit": "mg/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 172.2,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "WBC",
      "value": 145.9,
      "unit": "g/dL",
      "flag": "high"
    },
    {
      "test": "WBC",
      "value": 83.4,
      "unit": "mg/dL",
      "flag": "low"
    }
  ]
}


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

[User]
Transform this JSON data into XML format:
{
  "category": "electronics",
  "specs": {
    "weight_kg": 38.59,
    "dimensions": "23x92x45cm"
  },
  "stock": 596,
  "price": 218.58
}

[Assistant]
Approach:
1. Task: Convert product listing 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"?>
<product_listing>
<category>electronics</category>
<specs>
<weight_kg>38.59</weight_kg>
<dimensions>23x92x45cm</dimensions>
</specs>
<stock>596</stock>
<price>218.58</price>
</product_listing>