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

[User]
Convert the following YAML to CSV:
openapi: 3.0.0
info:
  title: Grass-roots 6thgeneration ability API
  version: 1.0.0
paths:
  /million:
    get:
      summary: About little above investment already magazine.
      parameters:
      - name: param0
        in: query
        type: string
      responses:
        '200':
          description: Success
        '400':
          description: Bad Request

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

Output:
abstract,authors,citations,funding_source,info_title,info_version,keywords,openapi,paper_id,paths_/million_get_parameters,paths_/million_get_responses_200_description,paths_/million_get_responses_400_description,paths_/million_get_summary,publication_doi,publication_venue,publication_year,title
,,,,Grass-roots 6thgeneration ability API,1.0.0,,3.0.0,,"[{""name"": ""param0"", ""in"": ""query"", ""type"": ""string""}]",Success,Bad Request,About little above investment already magazine.,,,,
"Wear benefit here religious agency billion pull. Series write book.
Item participant instead suggest","[{""name"": ""Joyce Weber"", ""affiliation"": ""Glass LLC"", ""email"": ""jroy@example.org""}, {""name"": ""Theresa",496,"Daniels, Gallagher and Edwards",,,"[""fact"", ""trip"", ""community"", ""instead""]",,arXiv:2024.55589,,,,,10.8027/Zlsb,Science,2020,Persevering fresh-thinking monitoring
Attention century history stage myself edge. Prepare put right. College as any look western current ,"[{""name"": ""Adam Hays"", ""affiliation"": ""Moreno, Carlson and Murphy"", ""email"": ""smithdavid@example.com",237,"Blair, Robertson and Fowler",,,"[""experience"", ""assume"", ""administration"", ""consider""]",,arXiv:2022.35370,,,,,10.1825/egIQ,Cell,2023,Multi-tiered even-keeled access
Anything always these run certainly. Stock total share small production. Too service democratic comp,"[{""name"": ""Ann Garza"", ""affiliation"": ""Reilly-Woodard"", ""email"": ""vanessakim@example.org""}, {""name"":",491,None,,,"[""prove"", ""product"", ""understand"", ""life"", ""as""]",,arXiv:2020.98330,,,,,10.9954/eApv,Cell,2023,Customizable even-keeled access


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

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

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

Output:
article_id,author,content,headline,published,section,shares,tags,views
ART-5347545,Martha Brown,Have fall sing then fast research break. Bar ready eye medical school might recognize. Nice sometime,Triple-buffered zero administration algorithm,2026-01-05T16:28:34.342789,Sports,1479,"[""line"", ""true"", ""compare"", ""for""]",96946
ART-7509552,Victor Marshall,"Move suddenly week test music less run measure.
Foot deep minute nice reality I. Indicate century ra",Switchable fresh-thinking open architecture,2026-01-06T18:12:58.596935,Business,2114,"[""necessary"", ""phone"", ""available"", ""young""]",5200
ART-8238517,Kristin Jackson,"How agent responsibility line position consumer. Decision we boy similar body.
Fact arm no across gr",Distributed tertiary hardware,2026-01-04T18:49:58.900358,Politics,3538,"[""safe"", ""policy"", ""somebody"", ""prove"", ""significant""]",75429
ART-6334821,Stephanie Garcia,"Article lay history party must lead. Always look less big society. Who color else any their west.
Fo",Advanced analyzing capability,2026-01-02T09:17:37.931982,Business,4001,"[""mean"", ""continue"", ""rock"", ""no"", ""scientist""]",15310


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

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

[Assistant]
Approach:
1. Task: Convert api specification 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:
{
  "openapi": "3.0.0",
  "info": {
    "title": "Seamless disintermediate flexibility API",
    "version": "1.0.0"
  },
  "paths": {
    "/significant": {
      "get": {
        "summary": "Box project skin day catch.",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  }
}


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

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

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

Output:
customer_id,items,payment_method,subtotal,tax,timestamp,total,txn_id
d14101dd-b47b-4916-b7e5-0ad54eefbb55,"[{""sku"": ""SKU-29323"", ""qty"": 2, ""price"": 70.49}, {""sku"": ""SKU-65460"", ""qty"": 3, ""price"": 466.32}, {""",apple_pay,1301.16,124.54,2026-01-07T13:51:26.808008,239.49,TXN-72432123
3f608bf1-e93f-4755-b25d-9a6084693cad,"[{""sku"": ""SKU-48870"", ""qty"": 1, ""price"": 41.99}]",apple_pay,1654.4,67.27,2026-01-07T13:51:26.809541,213.65,TXN-11810608
cd939e4a-f1c0-41fe-bc47-309265928578,"[{""sku"": ""SKU-51679"", ""qty"": 4, ""price"": 371.41}, {""sku"": ""SKU-80144"", ""qty"": 3, ""price"": 484.86}]",credit_card,1946.61,154.79,2026-01-07T13:51:26.809584,2062.09,TXN-51453063


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

[User]
Convert the following JSON to XML:
{
  "experiment_id": "EXP-330074",
  "title": "Effect of politics on stop",
  "methodology": {
    "design": "RCT",
    "sample_size": 328,
    "duration_days": 247
  },
  "results": [
    {
      "metric": "efficacy",
      "baseline": 34.54,
      "endpoint": 53.32,
      "p_value": 0.0487
    },
    {
      "metric": "safety",
      "baseline": 10.4,
      "endpoint": 13.84,
      "p_value": 0.1164
    },
    {
      "metric": "efficacy",
      "baseline": 78.27,
      "endpoint": 47.78,
      "p_value": 0.0781
    }
  ],
  "conclusion": "non-significant"
}

[Assistant]
Approach:
1. Task: Convert experiment result 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"?>
<experiment_result>
<experiment_id>EXP-330074</experiment_id>
<title>Effect of politics on stop</title>
<methodology>
<design>RCT</design>
<sample_size>328</sample_size>
<duration_days>247</duration_days>
</methodology>
<results>
<metric>efficacy</metric>
<baseline>34.54</baseline>
<endpoint>53.32</endpoint>
<p_value>0.0487</p_value>
</results>
<results>
<metric>safety</metric>
<baseline>10.4</baseline>
<endpoint>13.84</endpoint>
<p_value>0.1164</p_value>
</results>
<results>
<metric>efficacy</metric>
<baseline>78.27</baseline>
<endpoint>47.78</endpoint>
<p_value>0.0781</p_value>
</results>
<conclusion>non-significant</conclusion>
</experiment_result>


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

[User]
Convert the following JSON to XML:
{
  "article_id": "ART-3366717",
  "headline": "Integrated bi-directional complexity",
  "author": "Linda Clark",
  "published": "2026-01-07T13:19:20.433040",
  "section": "Tech",
  "content": "Anything music blood how public to. Even student idea piece if. Whom phone rich long.\nLook memory help find reduce. Structure most tough realize ground.\nAround fear reduce ago. Thus moment letter evening stuff three.\nHer themselves campaign cup four catch as. Part turn leg.",
  "tags": [
    "necessary",
    "listen",
    "employee",
    "here"
  ],
  "views": 75939,
  "shares": 1143
}

[Assistant]
Approach:
1. Task: Convert news article 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"?>
<news_article>
<article_id>ART-3366717</article_id>
<headline>Integrated bi-directional complexity</headline>
<author>Linda Clark</author>
<published>2026-01-07T13:19:20.433040</published>

Tech

<content>Anything music blood how public to. Even student idea piece if. Whom phone rich long.
Look memory help find reduce. Structure most tough realize ground.
Around fear reduce ago. Thus moment letter evening stuff three.
Her themselves campaign cup four catch as. Part turn leg.</content>
<tags>necessary</tags>
<tags>listen</tags>
<tags>employee</tags>
<tags>here</tags>
<views>75939</views>
<shares>1143</shares>
</news_article>


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

[User] Generate prescription data in TOML format.

[Assistant]
Approach:
1. Task: Create prescription 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:
rx_id = "RX-3022361"
patient_mrn = "MRN-726192"
prescriber = "Jessica Warner"
date = "2026-01-02"
[[medications]]
name = "Atorvastatin"
dosage = "20mg"
frequency = "BID"
quantity = 90

[[medications]]
name = "Atorvastatin"
dosage = "20mg"
frequency = "daily"
quantity = 30


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

[User] Produce a JSON document for a prescription.

[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-7328466",
  "patient_mrn": "MRN-740510",
  "prescriber": "William Hebert",
  "date": "2026-01-04",
  "medications": [
    {
      "name": "Lisinopril",
      "dosage": "20mg",
      "frequency": "TID",
      "quantity": 30
    },
    {
      "name": "Metformin",
      "dosage": "20mg",
      "frequency": "BID",
      "quantity": 60
    }
  ]
}


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

[User] Produce a JSON document for a contract.

[Assistant]
Approach:
1. Task: Create contract 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:
{
  "contract_id": "CTR-619223",
  "parties": [
    {
      "name": "Mcdaniel LLC",
      "role": "party_a"
    },
    {
      "name": "Hunt-Bowman",
      "role": "party_b"
    }
  ],
  "effective_date": "2026-01-03",
  "term_months": 21,
  "value": 87478,
  "status": "pending"
}


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

[User]
Convert the following CSV to JSON:
code,course_id,credits,grading_final,grading_homework,grading_midterm,instructor,schedule,term,title
NOO384,CRS-7514,4,40,30,30,Lori Martinez,"[{""week"": 1, ""topic"": ""bar""}, {""week"": 2, ""topic"": ""population""}, {""week"": 3, ""topic"": ""thus""}, {""we",Fall 2024,Fundamental encompassing database 101
BPH239,CRS-3376,3,40,30,30,James Cross,"[{""week"": 1, ""topic"": ""of""}, {""week"": 2, ""topic"": ""wear""}, {""week"": 3, ""topic"": ""push""}, {""week"": 4,",Fall 2024,Focused reciprocal methodology 101
WXD364,CRS-1003,3,40,30,30,Laura Atkinson,"[{""week"": 1, ""topic"": ""that""}, {""week"": 2, ""topic"": ""personal""}, {""week"": 3, ""topic"": ""road""}, {""wee",Fall 2024,Multi-lateral holistic protocol 101
OWI460,CRS-8162,3,40,30,30,Jeremy Navarro,"[{""week"": 1, ""topic"": ""field""}, {""week"": 2, ""topic"": ""throughout""}, {""week"": 3, ""topic"": ""line""}, {""",Fall 2023,Monitored leadingedge synergy 101
VBS127,CRS-4685,4,40,30,30,Charles Smith,"[{""week"": 1, ""topic"": ""public""}, {""week"": 2, ""topic"": ""fight""}, {""week"": 3, ""topic"": ""main""}, {""week",Spring 2023,Optimized encompassing groupware 101

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

Output:
{
  "course_id": "CRS-7514",
  "code": "NOO384",
  "title": "Fundamental encompassing database 101",
  "instructor": "Lori Martinez",
  "credits": 4,
  "term": "Fall 2024",
  "schedule": [
    {
      "week": 1,
      "topic": "bar"
    },
    {
      "week": 2,
      "topic": "population"
    },
    {
      "week": 3,
      "topic": "thus"
    },
    {
      "week": 4,
      "topic": "manage"
    },
    {
      "week": 5,
      "topic": "purpose"
    },
    {
      "week": 6,
      "topic": "look"
    },
    {
      "week": 7,
      "topic": "nothing"
    },
    {
      "week": 8,
      "topic": "remember"
    },
    {
      "week": 9,
      "topic": "song"
    },
    {
      "week": 10,
      "topic": "ahead"
    },
    {
      "week": 11,
      "topic": "pass"
    }
  ],
  "grading": {
    "homework": 30,
    "midterm": 30,
    "final": 40
  }
}


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

[User] Generate contract data in TOML format.

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

Output:
effective_date = "2026-01-03"
value = 837359
term_months = 24
status = "executed"


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

[User]
Convert the following TOML to JSON:
note_id = "CN-3759937"

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

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

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

Output:
{
  "patient": {
    "mrn": "MRN-802088",
    "age": 30,
    "gender": "M"
  },
  "note_id": "CN-3759937",
  "vitals": {
    "bp": "119/74",
    "hr": 67,
    "temp_f": 100.9
  }
}


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

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

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

Output:
openapi = "3.0.0"

[info]
title = "Upgradable 4thgeneration middleware API"
version = "1.0.0"

[paths."/pass".get]
summary = "Story amount nor bed night get message."
[[paths."/pass".get.parameters]]
name = "param0"
in = "query"
type = "string"

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

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


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

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

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

Output:
experiment_id: EXP-168652
title: Effect of green on from
methodology:
  design: cohort
  sample_size: 797
  duration_days: 186
results:
- metric: safety
  baseline: 24.16
  endpoint: 44.82
  p_value: 0.0559
- metric: efficacy
  baseline: 16.54
  endpoint: 28.48
  p_value: 0.2997
conclusion: non-significant


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

[User]
Transform this JSON data into XML format:
{
  "experiment_id": "EXP-883806",
  "title": "Effect of there on wife",
  "methodology": {
    "design": "observational",
    "sample_size": 200,
    "duration_days": 32
  },
  "results": [
    {
      "metric": "efficacy",
      "baseline": 15.64,
      "endpoint": 83.3,
      "p_value": 0.4248
    },
    {
      "metric": "efficacy",
      "baseline": 36.36,
      "endpoint": 63.05,
      "p_value": 0.0775
    }
  ],
  "conclusion": "significant"
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<experiment_result>
<experiment_id>EXP-883806</experiment_id>
<title>Effect of there on wife</title>
<methodology>
<design>observational</design>
<sample_size>200</sample_size>
<duration_days>32</duration_days>
</methodology>
<results>
<metric>efficacy</metric>
<baseline>15.64</baseline>
<endpoint>83.3</endpoint>
<p_value>0.4248</p_value>
</results>
<results>
<metric>efficacy</metric>
<baseline>36.36</baseline>
<endpoint>63.05</endpoint>
<p_value>0.0775</p_value>
</results>
<conclusion>significant</conclusion>
</experiment_result>


[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: 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:
{
  "eps": 6.0,
  "company": "Richardson-Gonzalez",
  "quarter": "Q3 2020",
  "net_income": 13953656
}


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

[User] Generate course syllabus data in CSV format.

[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
GDK183,CRS-6873,3,40,30,30,Melinda Thompson,"[{""week"": 1, ""topic"": ""girl""}, {""week"": 2, ""topic"": ""explain""}, {""week"": 3, ""topic"": ""center""}, {""we",Fall 2020,Grass-roots 24/7 emulation 101
GNF274,CRS-5383,3,40,30,30,Debra Kane,"[{""week"": 1, ""topic"": ""support""}, {""week"": 2, ""topic"": ""society""}, {""week"": 3, ""topic"": ""environment",Spring 2024,Realigned tertiary data-warehouse 101
FDD462,CRS-5811,4,40,30,30,Sarah Anderson,"[{""week"": 1, ""topic"": ""capital""}, {""week"": 2, ""topic"": ""off""}, {""week"": 3, ""topic"": ""final""}, {""week",Spring 2020,Reverse-engineered grid-enabled monitoring 101


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

[User] Generate product listing data in JSON format.

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

Output:
{
  "product_id": "PROD-428311",
  "name": "Object-based value-added workforce",
  "category": "books",
  "price": 802.3,
  "currency": "USD",
  "stock": 719,
  "is_available": true,
  "rating": 1.5,
  "reviews": 81,
  "specs": {
    "weight_kg": 27.85,
    "dimensions": "99x87x32cm"
  }
}


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

[User] Output error log as TOML.

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

Output:
error_id = "e78ff1cc-d984-499d-9fcf-126ccada9355"
timestamp = "2026-01-07T13:51:26.607679"
level = "WARNING"
service = "generationService"
message = "Bag difference growth have leader yeah him."
stack_trace = [ "at teach.py:30", "at poor.py:409",]

[context]
user_id = "e8daac99-0bad-4fb0-ae26-78525528db85"
request_id = "a6fe9e0f-a1a6-42b2-ab77-98b8bb662a52"


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

[User] Create a XML representation of news article.

[Assistant]
Approach:
1. Task: Create news article 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"?>
<news_article>
<article_id>ART-3366717</article_id>
<headline>Integrated bi-directional complexity</headline>
<author>Linda Clark</author>
<published>2026-01-07T13:19:20.433040</published>

Tech

<content>Anything music blood how public to. Even student idea piece if. Whom phone rich long.
Look memory help find reduce. Structure most tough realize ground.
Around fear reduce ago. Thus moment letter evening stuff three.
Her themselves campaign cup four catch as. Part turn leg.</content>
<tags>necessary</tags>
<tags>listen</tags>
<tags>employee</tags>
<tags>here</tags>
<views>75939</views>
<shares>1143</shares>
</news_article>


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

[User]
Convert the following JSON to YAML:
{
  "eps": 6.0,
  "company": "Richardson-Gonzalez",
  "quarter": "Q3 2020",
  "net_income": 13953656
}

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

Output:
eps: 6.0
company: Richardson-Gonzalez
quarter: Q3 2020
net_income: 13953656


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<product_listing>
<product_id>PROD-428311</product_id>
<name>Object-based value-added workforce</name>
<category>books</category>
<price>802.3</price>
<currency>USD</currency>
<stock>719</stock>
<is_available>True</is_available>
<rating>1.5</rating>
<reviews>81</reviews>
<specs>
<weight_kg>27.85</weight_kg>
<dimensions>99x87x32cm</dimensions>
</specs>
</product_listing>

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

Output:
{
  "product_id": "PROD-428311",
  "name": "Object-based value-added workforce",
  "category": "books",
  "price": 802.3,
  "currency": "USD",
  "stock": 719,
  "is_available": true,
  "rating": 1.5,
  "reviews": 81,
  "specs": {
    "weight_kg": 27.85,
    "dimensions": "99x87x32cm"
  }
}


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

[User]
Convert the following JSON to TOML:
{
  "product_id": "PROD-110536",
  "name": "Organized didactic parallelism",
  "category": "clothing",
  "price": 68.12,
  "currency": "USD",
  "stock": 153,
  "is_available": true,
  "rating": 1.45,
  "reviews": 277,
  "specs": {
    "weight_kg": 1.85,
    "dimensions": "33x70x14cm"
  }
}

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

Output:
product_id = "PROD-110536"
name = "Organized didactic parallelism"
category = "clothing"
price = 68.12
currency = "USD"
stock = 153
is_available = true
rating = 1.45
reviews = 277

[specs]
weight_kg = 1.85
dimensions = "33x70x14cm"


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<experiment_result>
<experiment_id>EXP-942720</experiment_id>
<title>Effect of edge on when</title>
<methodology>
<design>cohort</design>
<sample_size>645</sample_size>
<duration_days>54</duration_days>
</methodology>
<results>
<metric>safety</metric>
<baseline>79.64</baseline>
<endpoint>26.86</endpoint>
<p_value>0.2863</p_value>
</results>
<results>
<metric>safety</metric>
<baseline>55.57</baseline>
<endpoint>59.78</endpoint>
<p_value>0.1705</p_value>
</results>
<results>
<metric>efficacy</metric>
<baseline>30.69</baseline>
<endpoint>27.4</endpoint>
<p_value>0.1116</p_value>
</results>
<results>
<metric>efficacy</metric>
<baseline>32.07</baseline>
<endpoint>35.79</endpoint>
<p_value>0.1946</p_value>
</results>
<conclusion>non-significant</conclusion>
</experiment_result>

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

Output:
{
  "experiment_id": "EXP-942720",
  "title": "Effect of edge on when",
  "methodology": {
    "design": "cohort",
    "sample_size": 645,
    "duration_days": 54
  },
  "results": [
    {
      "metric": "safety",
      "baseline": 79.64,
      "endpoint": 26.86,
      "p_value": 0.2863
    },
    {
      "metric": "safety",
      "baseline": 55.57,
      "endpoint": 59.78,
      "p_value": 0.1705
    },
    {
      "metric": "efficacy",
      "baseline": 30.69,
      "endpoint": 27.4,
      "p_value": 0.1116
    },
    {
      "metric": "efficacy",
      "baseline": 32.07,
      "endpoint": 35.79,
      "p_value": 0.1946
    }
  ],
  "conclusion": "non-significant"
}


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

[User] Create a YAML representation of news article.

[Assistant]
Approach:
1. Task: Create news article in YAML
2. Complexity: 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:
content: 'Capital way what customer unit skill. Arm bar occur article mouth enjoy.
  Exactly approach mention single.

  Strong who against entire.

  Kid television artist dream back agency. Need main ago investment job behavior.'
published: '2026-01-03T04:54:27.964292'
views: 73181
headline: Vision-oriented analyzing groupware
section: Business


[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"?>
<clinical_note>
<assessment>
<problem>diabetes</problem>
<icd10>I24</icd10>
</assessment>
<encounter_date>2026-01-06</encounter_date>
<patient>
<mrn>MRN-470382</mrn>
<age>61</age>
<gender>F</gender>
</patient>
<note_id>CN-3244099</note_id>
<vitals>
<bp>158/77</bp>

112

<temp_f>99.5</temp_f>
</vitals>
</clinical_note>

[Assistant]
Approach:
1. Task: Convert clinical note 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:
{
  "assessment": [
    {
      "problem": "diabetes",
      "icd10": "I24"
    }
  ],
  "encounter_date": "2026-01-06",
  "patient": {
    "mrn": "MRN-470382",
    "age": 61,
    "gender": "F"
  },
  "note_id": "CN-3244099",
  "vitals": {
    "bp": "158/77",
    "hr": 112,
    "temp_f": 99.5
  }
}


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

[User] Output product listing as CSV.

[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
electronics,USD,True,Profound logistical array,299.46,PROD-852387,2.95,519,16x47x36cm,6.22,505
books,USD,True,Monitored methodical software,307.65,PROD-881491,5.0,377,46x45x31cm,2.59,45
clothing,USD,True,Distributed regional function,294.8,PROD-724042,1.03,967,17x90x55cm,3.53,666


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

[User] Generate error log data in XML format.

[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>19a033e5-3ad7-4877-8a96-e38503174031</error_id>
<timestamp>2026-01-07T13:51:26.139508</timestamp>
<level>ERROR</level>
<service>offService</service>
<message>Light method real rich option.</message>
<stack_trace>at very.py:253</stack_trace>
<stack_trace>at piece.py:469</stack_trace>
<stack_trace>at home.py:259</stack_trace>
<context>
<user_id>45de80c2-9a4d-4d83-abf9-651f235bf4e8</user_id>
<request_id>53b4884a-375f-459c-a303-838dd3a8411e</request_id>
</context>
</error_log>


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

[User] Output transaction record as JSON.

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

Output:
{
  "payment_method": "paypal",
  "customer_id": "fe237049-a4a1-4a5c-af14-940bbb31d0e7",
  "total": 1227.54
}


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

[User]
Convert the following JSON to XML:
{
  "grade": "A",
  "course_id": "CRS-4519",
  "total_score": 75
}

[Assistant]
Approach:
1. Task: Convert student assessment 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"?>
<student_assessment>
<grade>A</grade>
<course_id>CRS-4519</course_id>
<total_score>75</total_score>
</student_assessment>


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

[User] Generate lab result data in CSV format.

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

Output:
order_date,panel,patient_mrn,result_id,results
2026-01-04,Lipid,MRN-508219,LAB-3990665,"[{""test"": ""Hemoglobin"", ""value"": 80.7, ""unit"": ""g/dL"", ""flag"": ""low""}, {""test"": ""Glucose"", ""value"": "
2026-01-04,CBC,MRN-987678,LAB-1799113,"[{""test"": ""Glucose"", ""value"": 106.5, ""unit"": ""mg/dL"", ""flag"": ""normal""}, {""test"": ""Hemoglobin"", ""val"
2026-01-01,Lipid,MRN-961454,LAB-2592224,"[{""test"": ""WBC"", ""value"": 55.1, ""unit"": ""mg/dL"", ""flag"": ""normal""}, {""test"": ""WBC"", ""value"": 56.9, """
2026-01-01,Lipid,MRN-690566,LAB-8897495,"[{""test"": ""Glucose"", ""value"": 160.9, ""unit"": ""g/dL"", ""flag"": ""low""}, {""test"": ""Hemoglobin"", ""value"":"
2026-01-03,CMP,MRN-711587,LAB-1684835,"[{""test"": ""WBC"", ""value"": 106.1, ""unit"": ""mg/dL"", ""flag"": ""normal""}, {""test"": ""WBC"", ""value"": 99.8, "


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

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

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

Output:
post_id: POST-20150897
platform: instagram
user_id: ace3958f-4578-4576-9236-9cbfc1f62953
username: spatrick
content: 'About industry woman size. Available box return camera public time. Establish
  outside ability sport describe air who.

  Certain miss girl different both wife. Blood relationship if model.'
timestamp: '2026-01-07T13:51:25.995017'
hashtags:
- '#share'
- '#prevent'
- '#entire'
- '#owner'
engagement:
  likes: 3129
  shares: 891
  comments: 28


[System] You are an expert in 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
info:
  title: Visionary eco-centric methodology API
  version: 1.0.0
paths:
  /edge:
    get:
      summary: Simple really social range.
      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 XML format. Think step-by-step, then generate syntactically perfect XML.

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<research_paper>
<paper_id>arXiv:2020.65510</paper_id>
<title>Mandatory solution-oriented groupware</title>
<authors>
<name>Jared Fuller</name>
<affiliation>Robinson, Crawford and Johnson</affiliation>
<email>jenna58@example.net</email>
</authors>
<authors>
<name>Nancy Anderson</name>
<affiliation>Shannon-Johnson</affiliation>
<email>richdonald@example.net</email>
</authors>
<authors>
<name>Julia Neal</name>
<affiliation>Roach, Harper and Cameron</affiliation>
<email>gillcory@example.com</email>
</authors>
<abstract>Along its pressure yeah. Artist pattern nearly rich realize available skill. Month beyond rate make kid painting.</abstract>
<keywords>surface</keywords>
<keywords>consumer</keywords>
<keywords>despite</keywords>
<keywords>compare</keywords>
<keywords>protect</keywords>
<publication>
<venue>Nature</venue>
<year>2022</year>
<doi>10.8909/Qnkv</doi>
</publication>
<citations>488</citations>
<funding_source>Johnson LLC</funding_source>
</research_paper>


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

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

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

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


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

[User] Create a YAML representation of lab result.

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

Output:
result_id: LAB-6812810
patient_mrn: MRN-631747
order_date: '2026-01-04'
panel: Lipid
results:
- test: WBC
  value: 54.3
  unit: mg/dL
  flag: high
- test: WBC
  value: 70.8
  unit: mg/dL
  flag: low
- test: Glucose
  value: 59.6
  unit: mg/dL
  flag: low
- test: WBC
  value: 140.8
  unit: mg/dL
  flag: high


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<research_paper>
<authors>
<name>Emily Davis</name>
<affiliation>Nelson, Diaz and Humphrey</affiliation>
<email>jpalmer@example.org</email>
</authors>
<authors>
<name>Robert Clark</name>
<affiliation>James Inc</affiliation>
<email>dennis02@example.net</email>
</authors>
<publication>
<venue>Science</venue>
<year>2022</year>
<doi>10.6797/tlMT</doi>
</publication>
<keywords>lead</keywords>
<keywords>list</keywords>
<keywords>she</keywords>
<funding_source />
<paper_id>arXiv:2022.72917</paper_id>
</research_paper>

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

Output:
{
  "authors": [
    {
      "name": "Emily Davis",
      "affiliation": "Nelson, Diaz and Humphrey",
      "email": "jpalmer@example.org"
    },
    {
      "name": "Robert Clark",
      "affiliation": "James Inc",
      "email": "dennis02@example.net"
    }
  ],
  "publication": {
    "venue": "Science",
    "year": 2022,
    "doi": "10.6797/tlMT"
  },
  "keywords": [
    "lead",
    "list",
    "she"
  ],
  "funding_source": null,
  "paper_id": "arXiv:2022.72917"
}


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

[User]
Transform this TOML data into YAML format:
course_id = "CRS-3741"
code = "XMJ312"
title = "Managed incremental focus group 101"
instructor = "Rachel Diaz"
credits = 4
term = "Fall 2021"
[[schedule]]
week = 1
topic = "body"

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

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

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

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

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

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

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

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

Output:
course_id: CRS-3741
code: XMJ312
title: Managed incremental focus group 101
instructor: Rachel Diaz
credits: 4
term: Fall 2021
schedule:
- week: 1
  topic: body
- week: 2
  topic: rather
- week: 3
  topic: song
- week: 4
  topic: child
- week: 5
  topic: born
- week: 6
  topic: beyond
- week: 7
  topic: there
grading:
  homework: 30
  midterm: 30
  final: 40


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

[User] Generate lab result data in JSON format.

[Assistant]
Approach:
1. Task: Create lab result 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:
{
  "order_date": "2026-01-01",
  "panel": "Lipid",
  "patient_mrn": "MRN-952425",
  "result_id": "LAB-8958063",
  "results": [
    {
      "test": "Glucose",
      "value": 142.4,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 196.3,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 74.4,
      "unit": "mg/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 119.9,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "WBC",
      "value": 99.2,
      "unit": "mg/dL",
      "flag": "normal"
    },
    {
      "test": "Glucose",
      "value": 51.3,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "Glucose",
      "value": 186.5,
      "unit": "mg/dL",
      "flag": "low"
    }
  ]
}


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

[User]
Reformat the data below from CSV to YAML:
contract_id,effective_date,parties,status,term_months,value
CTR-760727,2026-01-04,"[{""name"": ""King, Moore and Vazquez"", ""role"": ""party_a""}, {""name"": ""Brown, Henry and Craig"", ""role"": ",active,15,170545
CTR-547536,2026-01-05,"[{""name"": ""Sharp Group"", ""role"": ""party_a""}, {""name"": ""Wilson, Holt and West"", ""role"": ""party_b""}]",executed,20,668248
CTR-742271,2026-01-04,"[{""name"": ""Pena, Boyd and Maddox"", ""role"": ""party_a""}, {""name"": ""Hernandez, Choi and Vargas"", ""role""",pending,32,703590
CTR-874419,2026-01-06,"[{""name"": ""Orozco Ltd"", ""role"": ""party_a""}, {""name"": ""Holland, Wood and Hill"", ""role"": ""party_b""}]",pending,51,284408

[Assistant]
Approach:
1. Task: Convert contract 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:
contract_id: CTR-760727
parties:
- name: King, Moore and Vazquez
  role: party_a
- name: Brown, Henry and Craig
  role: party_b
effective_date: '2026-01-04'
term_months: 15
value: 170545
status: active


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

[User] Generate research paper data in YAML format.

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

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


[System] You are an expert in 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"?>
<lab_result>
<order_date>2026-01-01</order_date>
<panel>Lipid</panel>
<patient_mrn>MRN-952425</patient_mrn>
<result_id>LAB-8958063</result_id>
<results>
<test>Glucose</test>
<value>142.4</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>196.3</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>74.4</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>119.9</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>WBC</test>
<value>99.2</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Glucose</test>
<value>51.3</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Glucose</test>
<value>186.5</value>
<unit>mg/dL</unit>
<flag>low</flag>
</results>
</lab_result>

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

Output:
{
  "order_date": "2026-01-01",
  "panel": "Lipid",
  "patient_mrn": "MRN-952425",
  "result_id": "LAB-8958063",
  "results": [
    {
      "test": "Glucose",
      "value": 142.4,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 196.3,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 74.4,
      "unit": "mg/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 119.9,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "WBC",
      "value": 99.2,
      "unit": "mg/dL",
      "flag": "normal"
    },
    {
      "test": "Glucose",
      "value": 51.3,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "Glucose",
      "value": 186.5,
      "unit": "mg/dL",
      "flag": "low"
    }
  ]
}


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

[User] Create a CSV representation of financial report.

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

Output:
company,eps,expenses,metrics_profit_margin,metrics_roe,net_income,quarter,revenue,ticker
"Snow, Shelton and Parsons",3.41,3428077,11.21,5.99,8543670,Q3 2022,49988929,LYEH
Banks-Smith,9.64,68319717,19.03,14.01,18208702,Q2 2024,91532444,DPCJ
"Alexander, Thornton and Kent",5.5,14925320,12.8,17.55,18357640,Q3 2020,2193726,ETLI
Allen and Sons,5.08,6947789,29.14,20.84,17582508,Q2 2023,8077658,NWDY
Miller Group,2.92,30244581,6.27,13.83,6204115,Q3 2022,52960865,LHZE


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

[User] Create a TOML representation of student assessment.

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

Output:
assessment_id = "ASMT-554535"
student_id = "STU-693793"
course_id = "CRS-9992"
type = "exam"
date = "2026-01-03"
total_score = 86
percentage = 63.99
grade = "B"
[[scores]]
question = 1
points_earned = 9
points_possible = 10

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

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

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

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

[[scores]]
question = 6
points_earned = 1
points_possible = 10

[[scores]]
question = 7
points_earned = 4
points_possible = 10

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

[[scores]]
question = 9
points_earned = 2
points_possible = 10

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


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

[User] Create a YAML representation of clinical note.

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

Output:
vitals:
  bp: 97/107
  hr: 107
  temp_f: 99.6
patient:
  mrn: MRN-705297
  age: 67
  gender: F
chief_complaint: chest pain
assessment:
- problem: hypertension
  icd10: K41
- problem: hypertension
  icd10: J91
- problem: hypertension
  icd10: J64
note_id: CN-6154695


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

[User]
Transform this TOML data into XML format:
course_id = "CRS-1689"
code = "NZW166"
title = "Operative modular system engine 101"
instructor = "David Chen"
credits = 4
term = "Fall 2021"
[[schedule]]
week = 1
topic = "in"

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

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

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

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

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

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

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

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

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

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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<course_syllabus>
<course_id>CRS-1689</course_id>
NZW166
<title>Operative modular system engine 101</title>
<instructor>David Chen</instructor>
<credits>4</credits>
<term>Fall 2021</term>
<schedule>
<week>1</week>
<topic>in</topic>
</schedule>
<schedule>
<week>2</week>
<topic>summer</topic>
</schedule>
<schedule>
<week>3</week>
<topic>unit</topic>
</schedule>
<schedule>
<week>4</week>
<topic>wind</topic>
</schedule>
<schedule>
<week>5</week>
<topic>act</topic>
</schedule>
<schedule>
<week>6</week>
<topic>itself</topic>
</schedule>
<schedule>
<week>7</week>
<topic>would</topic>
</schedule>
<schedule>
<week>8</week>
<topic>itself</topic>
</schedule>
<schedule>
<week>9</week>
<topic>tell</topic>
</schedule>
<schedule>
<week>10</week>
<topic>money</topic>
</schedule>
<schedule>
<week>11</week>
<topic>long</topic>
</schedule>
<grading>
<homework>30</homework>
<midterm>30</midterm>
<final>40</final>
</grading>
</course_syllabus>


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

[User] Output news article as XML.

[Assistant]
Approach:
1. Task: Create news article 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"?>
<news_article>
<article_id>ART-9801838</article_id>
<headline>Multi-lateral didactic encryption</headline>
<author>Jeffrey Gordon</author>
<published>2026-01-04T05:36:27.140251</published>

Business

<content>Partner energy whose simply half because long. Pattern include thousand care four against.
Scene center certainly letter already rate among. Do amount account court term same.
Step usually ground onto study myself.</content>
<tags>word</tags>
<tags>public</tags>
<tags>near</tags>
<views>26731</views>
<shares>4423</shares>
</news_article>


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

[User] Create a YAML representation of research paper.

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

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


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

[User]
Reformat the data below from XML to YAML:
<?xml version="1.0" encoding="UTF-8"?>
<error_log>
<error_id>8332f894-7969-41dc-b41e-1d31b796cba0</error_id>
<timestamp>2026-01-07T13:51:27.125156</timestamp>
<level>CRITICAL</level>
<service>imageService</service>
<message>Bad prepare able heavy morning.</message>
<stack_trace>at property.py:50</stack_trace>
<stack_trace>at short.py:272</stack_trace>
<context>
<user_id>a3de195f-baae-4936-bd72-230b1e266327</user_id>
<request_id>35eb846c-1e2f-4451-a60f-b8ee42943a10</request_id>
</context>
</error_log>

[Assistant]
Approach:
1. Task: Convert error log from XML 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:
error_id: 8332f894-7969-41dc-b41e-1d31b796cba0
timestamp: '2026-01-07T13:51:27.125156'
level: CRITICAL
service: imageService
message: Bad prepare able heavy morning.
stack_trace:
- at property.py:50
- at short.py:272
context:
  user_id: a3de195f-baae-4936-bd72-230b1e266327
  request_id: 35eb846c-1e2f-4451-a60f-b8ee42943a10


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

[User]
Convert the following JSON to XML:
{
  "assessment_id": "ASMT-350362",
  "student_id": "STU-421536",
  "course_id": "CRS-1231",
  "type": "exam",
  "date": "2026-01-01",
  "scores": [
    {
      "question": 1,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 6,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 5,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 9,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 10,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 11,
      "points_earned": 9,
      "points_possible": 10
    }
  ],
  "total_score": 51,
  "percentage": 80.6,
  "grade": "A"
}

[Assistant]
Approach:
1. Task: Convert student assessment 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"?>
<student_assessment>
<assessment_id>ASMT-350362</assessment_id>
<student_id>STU-421536</student_id>
<course_id>CRS-1231</course_id>
<type>exam</type>
<date>2026-01-01</date>
<scores>
<question>1</question>
<points_earned>2</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>8</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>8</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>8</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>6</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>5</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>9</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>10</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>11</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>51</total_score>
<percentage>80.6</percentage>
<grade>A</grade>
</student_assessment>


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

[User]
Convert the following JSON to XML:
{
  "paper_id": "arXiv:2023.54834",
  "title": "Profit-focused radical throughput",
  "authors": [
    {
      "name": "Scott Dunlap",
      "affiliation": "Daniels PLC",
      "email": "williamssheri@example.com"
    },
    {
      "name": "Shawn Payne",
      "affiliation": "Dorsey, Price and Burns",
      "email": "smoyer@example.net"
    },
    {
      "name": "Chase Lee",
      "affiliation": "Garcia Inc",
      "email": "burgesssarah@example.org"
    }
  ],
  "abstract": "Read deal buy final thus. Sure home game rest lose.\nThose any reality if teach.\nMain never still little study clearly today.",
  "keywords": [
    "measure",
    "stage",
    "scene",
    "reason"
  ],
  "publication": {
    "venue": "Science",
    "year": 2020,
    "doi": "10.8776/UhOT"
  },
  "citations": 388,
  "funding_source": "Reese-Perez"
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<research_paper>
<paper_id>arXiv:2023.54834</paper_id>
<title>Profit-focused radical throughput</title>
<authors>
<name>Scott Dunlap</name>
<affiliation>Daniels PLC</affiliation>
<email>williamssheri@example.com</email>
</authors>
<authors>
<name>Shawn Payne</name>
<affiliation>Dorsey, Price and Burns</affiliation>
<email>smoyer@example.net</email>
</authors>
<authors>
<name>Chase Lee</name>
<affiliation>Garcia Inc</affiliation>
<email>burgesssarah@example.org</email>
</authors>
<abstract>Read deal buy final thus. Sure home game rest lose.
Those any reality if teach.
Main never still little study clearly today.</abstract>
<keywords>measure</keywords>
<keywords>stage</keywords>
<keywords>scene</keywords>
<keywords>reason</keywords>
<publication>
<venue>Science</venue>
<year>2020</year>
<doi>10.8776/UhOT</doi>
</publication>
<citations>388</citations>
<funding_source>Reese-Perez</funding_source>
</research_paper>


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

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

[Assistant]
Approach:
1. Task: Create social media post in JSON
2. Complexity: 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-19357850",
  "platform": "twitter",
  "user_id": "664b960b-1331-492f-addd-e9b37d21656f",
  "username": "mbaldwin",
  "content": "Forward front agreement cover hour we remember ask. Read glass few word mother deep TV.",
  "timestamp": "2026-01-07T13:51:27.605837",
  "hashtags": [
    "#cost",
    "#he",
    "#relationship"
  ],
  "engagement": {
    "likes": 304,
    "shares": 796,
    "comments": 124
  }
}


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

[User] Create a YAML representation of lab result.

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

Output:
result_id: LAB-4303735
patient_mrn: MRN-230243
order_date: '2026-01-02'
panel: Lipid
results:
- test: WBC
  value: 142.8
  unit: g/dL
  flag: high
- test: Hemoglobin
  value: 100.6
  unit: mg/dL
  flag: high
- test: WBC
  value: 148.7
  unit: mg/dL
  flag: high
- test: Hemoglobin
  value: 95.1
  unit: g/dL
  flag: normal


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

[User] Output social media post as XML.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<social_media_post>
<post_id>POST-61935008</post_id>
<platform>instagram</platform>
<user_id>ecd9585e-2adb-45f4-adda-e91c5f4f7ebe</user_id>
<username>halezachary</username>
<content>Treat second sing development scientist particularly their. Like question recently line top. Resource movie enter involve order stop region.</content>
<timestamp>2026-01-07T13:51:25.597395</timestamp>
<hashtags>#box</hashtags>
<hashtags>#speak</hashtags>
<hashtags>#reason</hashtags>
<engagement>
<likes>4027</likes>
<shares>604</shares>
<comments>194</comments>
</engagement>
</social_media_post>


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

[User] Generate customer review data in CSV format.

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

Output:
content,date,helpful_votes,product_id,rating,review_id,title,user_id,verified_purchase
Expert difficult hot radio mission. Throw southern he book way media particular.,2026-01-06,,,1,REV-7122533,,,False
"News point thousand physical. Heavy argue physical great area interesting clearly.
Behavior issue in",2026-01-04,35,PROD-313091,2,REV-7797216,Consumer until note everyone environment.,fe66d16e-8562-4e3f-94f8-c7c3b137b8c5,True
Nature couple lawyer too media shoulder situation. Miss recent baby television within. Call wide beh,2026-01-01,27,PROD-491844,2,REV-5911588,World catch magazine use case seven.,fd696c18-b176-41c5-8572-2912d48deff8,True


[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-3041313
patient:
  mrn: MRN-164256
  age: 45
  gender: F
encounter_date: '2026-01-04'
chief_complaint: fever
vitals:
  bp: 153/76
  hr: 98
  temp_f: 102.6
assessment:
- problem: hypertension
  icd10: I84
- problem: hypertension
  icd10: J93


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

Output:
{
  "post_id": "POST-25055870",
  "platform": "twitter",
  "user_id": "28837af0-4898-41b2-8a38-faf0e2d7f431",
  "username": "khahn",
  "content": "Serve student science today general. Tell risk ball quickly technology.\nDrive because generation support gun message majority. Though do old.",
  "timestamp": "2026-01-07T13:51:27.403909",
  "hashtags": [
    "#conference",
    "#body"
  ],
  "engagement": {
    "likes": 9394,
    "shares": 444,
    "comments": 203
  }
}


[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: 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-8172649"
headline = "Triple-buffered responsive model"
author = "Rachel Clark"
published = "2026-01-03T00:35:22.551008"
section = "Business"
content = "Pattern capital time compare include night top. Large than important morning.\nCard authority protect present return while middle. Development miss write five."
tags = [ "consider", "whatever", "part", "however", "special",]
views = 49705
shares = 392


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

[User] Generate product listing data in CSV format.

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

Output:
abstract,authors,citations,funding_source,is_available,keywords,paper_id,price,publication_doi,publication_venue,publication_year,rating,specs_dimensions,specs_weight_kg,stock,title
,,,,True,,,743.81,,,,2.69,19x24x69cm,41.33,485,
Reduce number argue yeah produce. Source film go make. Nature nothing here conference meet various l,"[{""name"": ""Christina Williams"", ""affiliation"": ""Roberts-Johnson"", ""email"": ""nicholas17@example.net""}",23,None,,"[""require"", ""plan"", ""defense"", ""resource"", ""policy""]",arXiv:2020.69832,,10.3255/smIw,Cell,2020,,,,,Secured demand-driven concept
Identify baby national scene happy account. Within character firm. Marriage guess science win police,"[{""name"": ""Jacob Dean"", ""affiliation"": ""Nguyen LLC"", ""email"": ""alexanderkim@example.org""}, {""name"": ",281,None,,"[""accept"", ""exactly"", ""TV""]",arXiv:2024.85912,,10.3622/xxlQ,Science,2023,,,,,Optimized 6thgeneration data-warehouse


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

[User] Generate research paper data in YAML format.

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

Output:
paper_id: arXiv:2020.57295
title: Persevering global groupware
authors:
- name: Edwin Moore
  affiliation: Smith-Jones
  email: bowenzachary@example.net
- name: Anna Collins
  affiliation: Thomas, Rogers and Baldwin
  email: thill@example.com
- name: Mrs. Mary Delacruz MD
  affiliation: French, Rodriguez and Johnson
  email: amywest@example.org
abstract: Stand season mind indicate either. Buy gas keep skin.
keywords:
- stock
- member
- laugh
- language
- right
publication:
  venue: Cell
  year: 2022
  doi: 10.9461/HDZk
citations: 204
funding_source: null


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

[User] Generate financial report data in JSON format.

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

Output:
{
  "company": "Nichols, Ferguson and Butler",
  "ticker": "NDVN",
  "quarter": "Q1 2022",
  "revenue": 39470251,
  "expenses": 26562838,
  "net_income": 16784469,
  "eps": 3.2,
  "metrics": {
    "profit_margin": 27.93,
    "roe": 5.96
  }
}


[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"": ""Lisinopril"", ""dosage"": ""20mg"", ""frequency"": ""daily"", ""quantity"": 90}]",MRN-695608,Stephen Davis,RX-9001624
2026-01-01,"[{""name"": ""Metformin"", ""dosage"": ""20mg"", ""frequency"": ""TID"", ""quantity"": 90}]",MRN-625378,Brian Wilson,RX-6170949
2026-01-03,"[{""name"": ""Metformin"", ""dosage"": ""20mg"", ""frequency"": ""BID"", ""quantity"": 30}, {""name"": ""Atorvastatin",MRN-504595,Brandon Baxter,RX-3308638
2026-01-01,"[{""name"": ""Metformin"", ""dosage"": ""20mg"", ""frequency"": ""TID"", ""quantity"": 90}, {""name"": ""Atorvastatin",MRN-515082,Peggy Collins,RX-8253884
2026-01-04,"[{""name"": ""Lisinopril"", ""dosage"": ""5mg"", ""frequency"": ""BID"", ""quantity"": 30}, {""name"": ""Atorvastatin",MRN-774792,Todd Erickson,RX-8837484


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

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

[Assistant]
Approach:
1. Task: Convert financial report 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"?>
<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] Output prescription as XML.

[Assistant]
Approach:
1. Task: Create prescription 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"?>
<prescription>
<rx_id>RX-3022361</rx_id>
<patient_mrn>MRN-726192</patient_mrn>
<prescriber>Jessica Warner</prescriber>
<date>2026-01-02</date>
<medications>
<name>Atorvastatin</name>
<dosage>20mg</dosage>
<frequency>BID</frequency>
<quantity>90</quantity>
</medications>
<medications>
<name>Atorvastatin</name>
<dosage>20mg</dosage>
<frequency>daily</frequency>
<quantity>30</quantity>
</medications>
</prescription>


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

[User] Create a TOML representation of financial report.

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

Output:
company = "Snow, Shelton and Parsons"
ticker = "LYEH"
quarter = "Q3 2022"
revenue = 49988929
expenses = 3428077
net_income = 8543670
eps = 3.41

[metrics]
profit_margin = 11.21
roe = 5.99


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

[User]
Transform this JSON data into XML format:
{
  "period": "February 2022",
  "total_revenue": 6033804,
  "units_sold": 27183,
  "channels": [
    {
      "name": "wholesale",
      "revenue": 4147239,
      "growth": 40.37
    },
    {
      "name": "online",
      "revenue": 2663137,
      "growth": 9.96
    }
  ],
  "top_products": [
    {
      "sku": "SKU-2538",
      "sales": 420940
    },
    {
      "sku": "SKU-8680",
      "sales": 364206
    },
    {
      "sku": "SKU-2062",
      "sales": 350623
    }
  ]
}

[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>February 2022</period>
<total_revenue>6033804</total_revenue>
<units_sold>27183</units_sold>
<channels>
<name>wholesale</name>
<revenue>4147239</revenue>
<growth>40.37</growth>
</channels>
<channels>
<name>online</name>
<revenue>2663137</revenue>
<growth>9.96</growth>
</channels>
<top_products>
<sku>SKU-2538</sku>
<sales>420940</sales>
</top_products>
<top_products>
<sku>SKU-8680</sku>
<sales>364206</sales>
</top_products>
<top_products>
<sku>SKU-2062</sku>
<sales>350623</sales>
</top_products>
</sales_analytics>


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

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

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


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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<experiment_result>
<experiment_id>EXP-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 CSV format. Think step-by-step, then generate syntactically perfect CSV.

[User] Create a CSV representation of sales analytics.

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

Output:
abstract,authors,channels,citations,funding_source,keywords,paper_id,period,publication_doi,publication_venue,publication_year,title,top_products,total_revenue,units_sold
,,"[{""name"": ""retail"", ""revenue"": 528123, ""growth"": 12.05}, {""name"": ""online"", ""revenue"": 1160273, ""gro",,,,,March 2022,,,,,"[{""sku"": ""SKU-6153"", ""sales"": 328911}, {""sku"": ""SKU-4483"", ""sales"": 21251}, {""sku"": ""SKU-5114"", ""sal",7500818,73950
Well parent lot speak. Magazine training federal pull second. Describe cause bank speak father well ,"[{""name"": ""Brian Robertson"", ""affiliation"": ""Maldonado, Reyes and Brown"", ""email"": ""huntmatthew@exam",,57,None,"[""most"", ""truth"", ""design""]",arXiv:2020.25220,,10.1757/sdZs,Nature,2024,Decentralized full-range focus group,,,
I across anyone opportunity. Gas drive role black seat in blue. Region best foot onto development fa,"[{""name"": ""Jessica Ochoa"", ""affiliation"": ""Patterson, Garcia and Calhoun"", ""email"": ""linda79@example",,47,Vega-Ruiz,"[""us"", ""account"", ""suffer""]",arXiv:2023.57935,,10.3312/ZnRh,Cell,2020,Function-based didactic project,,,
"Something support run political.
Throw political clear general. Have all material color end.
Kind th","[{""name"": ""Kevin Morris"", ""affiliation"": ""Hunter, Bautista and Mitchell"", ""email"": ""derek13@example.",,296,Johnson-Banks,"[""news"", ""strategy"", ""bed"", ""full""]",arXiv:2021.42052,,10.1671/EjkG,Science,2024,Grass-roots logistical moratorium,,,


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

[User] Output lab result as JSON.

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

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


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

[User]
Convert the following TOML to YAML:
period = "February 2020"
total_revenue = 5010605
units_sold = 4486
[[channels]]
name = "online"
revenue = 4865933
growth = 41.22

[[channels]]
name = "wholesale"
revenue = 4636446
growth = 21.68

[[top_products]]
sku = "SKU-3361"
sales = 360256

[[top_products]]
sku = "SKU-1576"
sales = 355717

[[top_products]]
sku = "SKU-8891"
sales = 396344

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

Output:
period: February 2020
total_revenue: 5010605
units_sold: 4486
channels:
- name: online
  revenue: 4865933
  growth: 41.22
- name: wholesale
  revenue: 4636446
  growth: 21.68
top_products:
- sku: SKU-3361
  sales: 360256
- sku: SKU-1576
  sales: 355717
- sku: SKU-8891
  sales: 396344


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

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

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

Output:
{
  "article_id": "ART-2388619",
  "headline": "Switchable tertiary collaboration",
  "author": "Paula Martinez",
  "published": "2026-01-07T02:15:35.006278",
  "section": "Politics",
  "content": "Choice list strong let reason. Education class ok front impact successful. Huge professor happen data image stop. Notice movie reduce everyone among ask already company.\nDoor president he always capital.\nBlack democratic heart read name. Professional billion prepare executive meeting sport.",
  "tags": [
    "hair",
    "democratic",
    "financial",
    "huge",
    "available"
  ],
  "views": 74003,
  "shares": 1794
}


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

[User] Output news article as TOML.

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


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

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

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

Output:
review_id = "REV-9546377"
product_id = "PROD-108034"
user_id = "d01ac4e1-ccd9-4273-9fe0-9ca6afc6af77"
rating = 4
title = "Appear speak sure list."
content = "Today offer none role certain reach. Second Mr official enjoy movement turn city. Name employee early much first sit."
date = "2026-01-01"
verified_purchase = true
helpful_votes = 43


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

[User]
Convert the following YAML to CSV:
result_id: LAB-5796495
patient_mrn: MRN-496025
order_date: '2026-01-06'
panel: Lipid
results:
- test: Hemoglobin
  value: 74.9
  unit: g/dL
  flag: low
- test: Hemoglobin
  value: 68.3
  unit: mg/dL
  flag: low
- test: WBC
  value: 121.2
  unit: mg/dL
  flag: normal
- test: Hemoglobin
  value: 142.6
  unit: g/dL
  flag: normal

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

Output:
order_date,panel,patient_mrn,result_id,results
2026-01-06,Lipid,MRN-496025,LAB-5796495,"[{""test"": ""Hemoglobin"", ""value"": 74.9, ""unit"": ""g/dL"", ""flag"": ""low""}, {""test"": ""Hemoglobin"", ""value"
2026-01-01,CBC,MRN-219986,LAB-5822541,"[{""test"": ""WBC"", ""value"": 106.6, ""unit"": ""g/dL"", ""flag"": ""normal""}, {""test"": ""WBC"", ""value"": 170.6, "
2026-01-04,Lipid,MRN-895724,LAB-5047000,"[{""test"": ""Hemoglobin"", ""value"": 120.6, ""unit"": ""mg/dL"", ""flag"": ""high""}, {""test"": ""WBC"", ""value"": 1"


[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:
{
  "openapi": "3.0.0",
  "info": {
    "title": "Centralized web-enabled hardware API",
    "version": "1.0.0"
  },
  "paths": {
    "/improve": {
      "get": {
        "summary": "Act attention yes herself significant recent.",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          },
          {
            "name": "param1",
            "in": "query",
            "type": "string"
          },
          {
            "name": "param2",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  }
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Centralized web-enabled hardware API</title>
<version>1.0.0</version>
</info>
<paths>
</improve>
<get>
<summary>Act attention yes herself significant recent.</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>
<//improve>
</paths>
</api_specification>


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

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

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

Output:
post_id: POST-32645861
platform: facebook
user_id: b5521d05-1410-43ee-b828-2c240f95461c
username: yanderson
content: Example suggest around pattern small everybody. Rate watch blue walk test
  camera. Partner decide leave really.
timestamp: '2026-01-07T13:51:27.526455'
hashtags:
- '#door'
- '#relate'
engagement:
  likes: 5828
  shares: 957
  comments: 117


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

[User] Generate product listing data in CSV format.

[Assistant]
Approach:
1. Task: Create product listing in CSV
2. Complexity: 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,category,citations,funding_source,is_available,keywords,paper_id,price,publication_doi,publication_venue,publication_year,rating,title
,,electronics,,,True,,,302.74,,,,1.03,
Else open relate late specific gas. Type factor work include pressure easy available. Against allow ,"[{""name"": ""Warren Craig"", ""affiliation"": ""Young LLC"", ""email"": ""osmith@example.org""}, {""name"": ""Anne",,92,None,,"[""green"", ""product"", ""turn"", ""imagine""]",arXiv:2024.40999,,10.6125/SevR,Cell,2020,,Ameliorated analyzing pricing structure
Happen cut war case have long interest police. Serve perhaps direction leg human meeting authority p,"[{""name"": ""Mark Gregory"", ""affiliation"": ""Reynolds-Jones"", ""email"": ""nicoleherman@example.org""}, {""n",,414,None,,"[""allow"", ""outside"", ""body"", ""effort"", ""everything""]",arXiv:2022.43669,,10.8067/vqkZ,Nature,2022,,Versatile 24hour encoding
Born quickly toward reach edge through result. Entire sound within general dog.,"[{""name"": ""Brian Ingram"", ""affiliation"": ""Doyle-Todd"", ""email"": ""smithronald@example.com""}, {""name"":",,205,Tate-Black,,"[""record"", ""draw"", ""east"", ""along""]",arXiv:2022.30341,,10.2984/CLia,Cell,2022,,Distributed intangible application
Trial little history call think federal. Person manager care.,"[{""name"": ""Tonya Maldonado"", ""affiliation"": ""Collins Ltd"", ""email"": ""foxangela@example.net""}, {""name",,186,None,,"[""small"", ""record"", ""night"", ""center"", ""without""]",arXiv:2023.91437,,10.4058/aKyJ,Science,2020,,Diverse stable artificial intelligence


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

[User] Generate sales analytics data in TOML format.

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

Output:
units_sold = 11543
period = "June 2021"
total_revenue = 8223229
[[channels]]
name = "online"
revenue = 1417680
growth = 41.94

[[channels]]
name = "wholesale"
revenue = 3176166
growth = 26.78

[[top_products]]
sku = "SKU-9002"
sales = 412560

[[top_products]]
sku = "SKU-3918"
sales = 426996

[[top_products]]
sku = "SKU-1618"
sales = 496165


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

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

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

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


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

[User] Produce a YAML document for a prescription.

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

Output:
rx_id: RX-2317847
patient_mrn: MRN-412331
prescriber: Tammy Adams
date: '2026-01-01'
medications:
- name: Lisinopril
  dosage: 10mg
  frequency: BID
  quantity: 60
- name: Lisinopril
  dosage: 10mg
  frequency: BID
  quantity: 90
- name: Atorvastatin
  dosage: 5mg
  frequency: BID
  quantity: 30