[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:
{
  "error_id": "385c5830-2f90-42e3-ae2f-53faace4448a",
  "timestamp": "2026-01-07T13:51:26.292009",
  "level": "CRITICAL",
  "service": "almostService",
  "message": "People party agreement mother that investment approach.",
  "stack_trace": [
    "at fight.py:491",
    "at city.py:369",
    "at statement.py:378"
  ],
  "context": {
    "user_id": "264dfcb4-39aa-45b1-999f-d115795470f4",
    "request_id": "4c579c9e-314d-44f6-9e5a-9c3c95ea5e82"
  }
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<error_log>
<error_id>385c5830-2f90-42e3-ae2f-53faace4448a</error_id>
<timestamp>2026-01-07T13:51:26.292009</timestamp>
<level>CRITICAL</level>
<service>almostService</service>
<message>People party agreement mother that investment approach.</message>
<stack_trace>at fight.py:491</stack_trace>
<stack_trace>at city.py:369</stack_trace>
<stack_trace>at statement.py:378</stack_trace>
<context>
<user_id>264dfcb4-39aa-45b1-999f-d115795470f4</user_id>
<request_id>4c579c9e-314d-44f6-9e5a-9c3c95ea5e82</request_id>
</context>
</error_log>


[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: 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"?>
<prescription>
<rx_id>RX-5305677</rx_id>
<patient_mrn>MRN-215469</patient_mrn>
<prescriber>Jeremy Hatfield</prescriber>
<date>2026-01-03</date>
<medications>
<name>Metformin</name>
<dosage>10mg</dosage>
<frequency>daily</frequency>
<quantity>90</quantity>
</medications>
<medications>
<name>Metformin</name>
<dosage>5mg</dosage>
<frequency>daily</frequency>
<quantity>30</quantity>
</medications>
<medications>
<name>Atorvastatin</name>
<dosage>10mg</dosage>
<frequency>BID</frequency>
<quantity>90</quantity>
</medications>
</prescription>


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

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

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

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


[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-64636774",
  "platform": "instagram",
  "user_id": "180a1898-015f-483f-94a7-e771a6fb148e",
  "username": "melissa16",
  "content": "Use Mr only week. Crime form attention. Right world stand surface rate three.",
  "timestamp": "2026-01-07T13:51:26.942814",
  "hashtags": [
    "#economic",
    "#speak"
  ],
  "engagement": {
    "likes": 9998,
    "shares": 653,
    "comments": 4
  }
}


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

[User]
Transform this TOML data into CSV format:
period = "January 2024"
total_revenue = 3091656
units_sold = 63856
[[channels]]
name = "wholesale"
revenue = 2739604
growth = -0.52

[[channels]]
name = "online"
revenue = 247982
growth = 14.46

[[top_products]]
sku = "SKU-7268"
sales = 409348

[[top_products]]
sku = "SKU-4030"
sales = 70087

[[top_products]]
sku = "SKU-4380"
sales = 298376

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

Output:
abstract,authors,channels,citations,funding_source,keywords,paper_id,period,publication_doi,publication_venue,publication_year,title,top_products,total_revenue,units_sold
,,"[{""name"": ""wholesale"", ""revenue"": 2739604, ""growth"": -0.52}, {""name"": ""online"", ""revenue"": 247982, """,,,,,January 2024,,,,,"[{""sku"": ""SKU-7268"", ""sales"": 409348}, {""sku"": ""SKU-4030"", ""sales"": 70087}, {""sku"": ""SKU-4380"", ""sal",3091656,63856
Position hand charge activity sound decade machine another. Lawyer teach they everyone win day like ,"[{""name"": ""Ashley Wilkerson"", ""affiliation"": ""Watts, Green and Winters"", ""email"": ""katiebraun@exampl",,302,None,"[""forward"", ""side"", ""born""]",arXiv:2021.55299,,10.5334/HYky,Cell,2020,Phased multi-tasking time-frame,,,
Be manager live politics. Try debate study contain page local economic.,"[{""name"": ""Lisa David"", ""affiliation"": ""Green-Barr"", ""email"": ""fhayes@example.com""}, {""name"": ""Derri",,67,"Hood, Liu and Alexander","[""want"", ""tree"", ""institution"", ""class""]",arXiv:2020.79026,,10.9007/ZcHn,Science,2020,Compatible analyzing moderator,,,


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

[User]
Reformat the data below from XML to CSV:
<?xml version="1.0" encoding="UTF-8"?>
<lab_result>
<result_id>LAB-9047593</result_id>
<patient_mrn>MRN-478989</patient_mrn>
<order_date>2026-01-06</order_date>
<panel>CMP</panel>
<results>
<test>Hemoglobin</test>
<value>171.8</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>WBC</test>
<value>58.0</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>WBC</test>
<value>78.7</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Glucose</test>
<value>138.7</value>
<unit>mg/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>51.5</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>141.9</value>
<unit>mg/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>191.7</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
</lab_result>

[Assistant]
Approach:
1. Task: Convert lab result from XML to 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,CMP,MRN-478989,LAB-9047593,"[{""test"": ""Hemoglobin"", ""value"": 171.8, ""unit"": ""mg/dL"", ""flag"": ""normal""}, {""test"": ""WBC"", ""value"":"
2026-01-03,Lipid,MRN-622487,LAB-3048095,"[{""test"": ""Hemoglobin"", ""value"": 94.9, ""unit"": ""mg/dL"", ""flag"": ""high""}, {""test"": ""WBC"", ""value"": 10"
2026-01-01,CBC,MRN-703796,LAB-6971075,"[{""test"": ""WBC"", ""value"": 107.9, ""unit"": ""mg/dL"", ""flag"": ""high""}, {""test"": ""Hemoglobin"", ""value"": 1"


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<news_article>
<article_id>ART-5646798</article_id>
<headline>Switchable hybrid groupware</headline>
<author>Joshua Bell</author>
<published>2026-01-05T05:31:42.088007</published>

Business

<content>List road lay not year. Congress gas full particular according. Prevent hear century game friend civil live.
Possible option especially woman. Ahead down suffer doctor six traditional. Prove ready American star impact operation just. Difficult yourself difficult base of four letter.</content>
<tags>author</tags>
<tags>son</tags>
<tags>food</tags>
<views>74484</views>
<shares>596</shares>
</news_article>

[Assistant]
Approach:
1. Task: Convert news article 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:
{
  "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 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: 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:
{
  "medications": [
    {
      "name": "Atorvastatin",
      "dosage": "5mg",
      "frequency": "BID",
      "quantity": 30
    }
  ],
  "prescriber": "Isaac Howard",
  "date": "2026-01-03"
}


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


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

[User] Create a XML representation of error log.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<error_log>
<error_id>e01a43f8-d4eb-4ec7-a325-ad2b31726d0f</error_id>
<timestamp>2026-01-07T13:51:25.462522</timestamp>
<level>ERROR</level>
<service>winService</service>
<message>Western energy project push building.</message>
<stack_trace>at could.py:42</stack_trace>
<stack_trace>at seem.py:198</stack_trace>
<context>
<user_id>7197800d-0acd-4eee-b9ab-24b5158dfa0a</user_id>
<request_id>00c4c00d-dc22-4013-8495-1ed2381fc937</request_id>
</context>
</error_log>


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

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

[Assistant]
Approach:
1. Task: Convert financial report from JSON to 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>Thompson LLC</company>
<ticker>QQLN</ticker>
<quarter>Q2 2020</quarter>
<revenue>63838743</revenue>
<expenses>967762</expenses>
<net_income>16633381</net_income>
<eps>0.69</eps>
<metrics>
<profit_margin>22.56</profit_margin>
<roe>23.58</roe>
</metrics>
</financial_report>


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<sales_analytics>
<period>February 2020</period>
<total_revenue>2337421</total_revenue>
<units_sold>23839</units_sold>
<channels>
<name>retail</name>
<revenue>3840938</revenue>
<growth>18.52</growth>
</channels>
<channels>
<name>wholesale</name>
<revenue>1512471</revenue>
<growth>13.02</growth>
</channels>
<top_products>
<sku>SKU-1744</sku>
<sales>276633</sales>
</top_products>
<top_products>
<sku>SKU-5145</sku>
<sales>26445</sales>
</top_products>
<top_products>
<sku>SKU-9218</sku>
<sales>412054</sales>
</top_products>
</sales_analytics>

[Assistant]
Approach:
1. Task: Convert sales analytics 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:
{
  "period": "February 2020",
  "total_revenue": 2337421,
  "units_sold": 23839,
  "channels": [
    {
      "name": "retail",
      "revenue": 3840938,
      "growth": 18.52
    },
    {
      "name": "wholesale",
      "revenue": 1512471,
      "growth": 13.02
    }
  ],
  "top_products": [
    {
      "sku": "SKU-1744",
      "sales": 276633
    },
    {
      "sku": "SKU-5145",
      "sales": 26445
    },
    {
      "sku": "SKU-9218",
      "sales": 412054
    }
  ]
}


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

[User] Generate lab result data in YAML format.

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

Output:
result_id: LAB-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 CSV format. Think step-by-step, then generate syntactically perfect CSV.

[User] Create a CSV representation of news article.

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

Output:
article_id,author,content,headline,published,section,shares,tags,views
ART-8136358,Brian White,"Give model worry sense. Including reflect teacher near image.
Culture kitchen run first would. Agenc",Realigned multimedia paradigm,2026-01-02T14:21:25.908532,Sports,4175,"[""involve"", ""service"", ""along"", ""stand""]",7987
ART-1729821,Keith Hendricks,"Within wife start clearly million space. Example begin catch base take person remember.
Next certain",Adaptive zero administration standardization,2026-01-05T12:10:52.562102,Sports,2950,"[""analysis"", ""data"", ""small"", ""dream""]",59738
ART-8193413,Rebecca Davis,"Consumer run they.
Suggest same require technology. Film magazine top power very throughout despite.",Multi-channeled intangible implementation,2026-01-06T16:06:46.231980,Tech,1471,"[""likely"", ""imagine"", ""ready"", ""apply""]",45097
ART-9940568,Brooke Sandoval,"Receive computer check area allow. Small official civil in bring marriage.
Opportunity cold idea eff",Implemented explicit definition,2026-01-01T14:11:50.207239,Sports,2421,"[""region"", ""exist"", ""wide""]",76796
ART-2215239,Diane Summers,Ten idea everything magazine image condition. Explain ability chance. Thing identify money audience ,Digitized interactive artificial intelligence,2026-01-04T00:42:58.861774,Business,4315,"[""moment"", ""television"", ""series""]",86773


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

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

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

Output:
category,currency,is_available,name,price,product_id,rating,reviews,specs_dimensions,specs_weight_kg,stock
clothing,USD,True,Balanced demand-driven capacity,554.83,PROD-685161,3.32,212,86x88x63cm,39.83,872
books,USD,True,Enterprise-wide multimedia customer loyalty,964.77,PROD-238296,2.75,480,62x99x20cm,7.97,904
electronics,USD,True,Assimilated client-server circuit,58.72,PROD-359357,2.62,370,59x13x63cm,29.18,168


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<social_media_post>
<post_id>POST-54622203</post_id>
<platform>instagram</platform>
<user_id>1456e108-0a50-4482-8f1a-b1cb2398a121</user_id>
<username>fullersteven</username>
<content>Card these member kid western growth. Staff draw say early town general. Large break interesting ten against open.
Any fine power truth. Big like investment simple whatever education.</content>
<timestamp>2026-01-07T13:51:25.504049</timestamp>
<hashtags>#deep</hashtags>
<hashtags>#yes</hashtags>
<hashtags>#long</hashtags>
<hashtags>#including</hashtags>
<engagement>
<likes>464</likes>
<shares>699</shares>
<comments>294</comments>
</engagement>
</social_media_post>


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

[User] Output customer review as XML.

[Assistant]
Approach:
1. Task: Create customer review 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"?>
<customer_review>
<review_id>REV-4235678</review_id>
<product_id>PROD-754494</product_id>
<user_id>29638f7d-f697-4ae7-8fde-a1a70bcd6476</user_id>
<rating>5</rating>
<title>Help program law water necessary return clearly.</title>
<content>Team hold course throw center open enjoy old. Huge candidate still act decade civil. Safe middle indeed.</content>
<date>2026-01-03</date>
<verified_purchase>False</verified_purchase>
<helpful_votes>98</helpful_votes>
</customer_review>


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

[User] Generate clinical note data in XML format.

[Assistant]
Approach:
1. Task: Create clinical note in XML
2. Complexity: 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"?>
<clinical_note>
<vitals>
<bp>131/104</bp>

84

<temp_f>99.9</temp_f>
</vitals>
<note_id>CN-3823498</note_id>
<encounter_date>2026-01-06</encounter_date>
</clinical_note>


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

[User] Create a CSV representation of customer review.

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

Output:
abstract,authors,citations,date,funding_source,keywords,paper_id,publication_doi,publication_venue,publication_year,rating,title
,,,2026-01-05,,,,,,,4,Teach why painting per short.
Message city interesting Congress they small.,"[{""name"": ""Taylor Howard"", ""affiliation"": ""Arias Group"", ""email"": ""jill11@example.net""}, {""name"": ""S",32,,None,"[""five"", ""traditional"", ""manager"", ""myself""]",arXiv:2020.73036,10.5154/OGZj,Science,2023,,Switchable intangible complexity
Necessary such author her southern soldier sense. Reduce itself election special approach kitchen wi,"[{""name"": ""Kathleen Harris"", ""affiliation"": ""Stark, Thompson and Roberts"", ""email"": ""cindythomas@exa",120,,None,"[""some"", ""history"", ""financial"", ""energy""]",arXiv:2022.82681,10.1306/EolF,Nature,2024,,Intuitive methodical instruction set
Responsibility sometimes understand human long. Cost show cover prevent none truth.,"[{""name"": ""Katelyn Black"", ""affiliation"": ""Perez-King"", ""email"": ""curtisrivera@example.com""}, {""name",37,,None,"[""fine"", ""seat"", ""media"", ""box"", ""while""]",arXiv:2021.92430,10.7877/EkUT,Cell,2021,,Monitored zero tolerance approach
Challenge include son foot save. Show three similar outside page safe.,"[{""name"": ""Janice Diaz DVM"", ""affiliation"": ""Gonzalez, Davis and Green"", ""email"": ""qgallagher@exampl",79,,"Little, Miller and Lopez","[""until"", ""traditional"", ""make""]",arXiv:2021.34246,10.6713/gNjt,Cell,2020,,Virtual 4thgeneration conglomeration


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

[User] Create a JSON representation of prescription.

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

Output:
{
  "medications": [
    {
      "name": "Atorvastatin",
      "dosage": "10mg",
      "frequency": "BID",
      "quantity": 60
    }
  ],
  "rx_id": "RX-5523111",
  "date": "2026-01-01"
}


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

[User] Output course syllabus as CSV.

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

Output:
code,course_id,credits,grading_final,grading_homework,grading_midterm,instructor,schedule,term,title
QAA477,CRS-1797,4,40,30,30,Selena Walker,"[{""week"": 1, ""topic"": ""all""}, {""week"": 2, ""topic"": ""education""}, {""week"": 3, ""topic"": ""will""}, {""wee",Fall 2024,User-friendly composite interface 101
MTB149,CRS-1344,3,40,30,30,Gregory Beck,"[{""week"": 1, ""topic"": ""game""}, {""week"": 2, ""topic"": ""laugh""}, {""week"": 3, ""topic"": ""staff""}, {""week""",Spring 2024,Sharable optimizing success 101
ZQP362,CRS-9238,4,40,30,30,Linda Harding,"[{""week"": 1, ""topic"": ""economic""}, {""week"": 2, ""topic"": ""nearly""}, {""week"": 3, ""topic"": ""look""}, {""w",Fall 2023,Innovative cohesive customer loyalty 101
VMX308,CRS-3729,3,40,30,30,Brian Johnson,"[{""week"": 1, ""topic"": ""music""}, {""week"": 2, ""topic"": ""hit""}, {""week"": 3, ""topic"": ""career""}, {""week""",Spring 2023,Open-source exuding definition 101


[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: 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:
rx_id = "RX-6885629"
prescriber = "John Cook"
date = "2026-01-02"
patient_mrn = "MRN-741538"
[[medications]]
name = "Metformin"
dosage = "5mg"
frequency = "daily"
quantity = 30

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

[[medications]]
name = "Lisinopril"
dosage = "5mg"
frequency = "TID"
quantity = 60


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

[User] Output product listing as TOML.

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

Output:
product_id = "PROD-597223"
name = "Proactive tertiary database"
category = "books"
price = 435.77
currency = "USD"
stock = 111
is_available = true
rating = 1.73
reviews = 539

[specs]
weight_kg = 19.61
dimensions = "87x91x85cm"


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

[User]
Convert the following TOML to XML:
rx_id = "RX-6885629"
prescriber = "John Cook"
date = "2026-01-02"
patient_mrn = "MRN-741538"
[[medications]]
name = "Metformin"
dosage = "5mg"
frequency = "daily"
quantity = 30

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

[[medications]]
name = "Lisinopril"
dosage = "5mg"
frequency = "TID"
quantity = 60

[Assistant]
Approach:
1. Task: Convert prescription from TOML 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"?>
<prescription>
<rx_id>RX-6885629</rx_id>
<prescriber>John Cook</prescriber>
<medications>
<name>Metformin</name>
<dosage>5mg</dosage>
<frequency>daily</frequency>
<quantity>30</quantity>
</medications>
<medications>
<name>Atorvastatin</name>
<dosage>5mg</dosage>
<frequency>BID</frequency>
<quantity>90</quantity>
</medications>
<medications>
<name>Lisinopril</name>
<dosage>5mg</dosage>
<frequency>TID</frequency>
<quantity>60</quantity>
</medications>
<date>2026-01-02</date>
<patient_mrn>MRN-741538</patient_mrn>
</prescription>


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

[User] Generate product listing data in CSV format.

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

Output:
category,currency,is_available,name,price,product_id,rating,reviews,specs_dimensions,specs_weight_kg,stock
books,USD,True,Grass-roots methodical neural-net,156.58,PROD-361703,3.73,915,90x40x81cm,25.41,3
electronics,USD,True,Optional next generation array,484.35,PROD-358234,2.98,945,75x62x25cm,28.5,674
clothing,USD,True,Exclusive intermediate toolset,634.41,PROD-405955,4.62,410,26x68x76cm,21.4,885
electronics,USD,True,Networked next generation service-desk,98.8,PROD-648905,4.98,412,54x54x93cm,22.68,98
electronics,USD,True,Stand-alone uniform Internet solution,245.19,PROD-416796,1.1,881,56x31x29cm,21.83,526


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

[User] Output experiment result as XML.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<experiment_result>
<experiment_id>EXP-690622</experiment_id>
<title>Effect of drug on effect</title>
<methodology>
<design>RCT</design>
<sample_size>718</sample_size>
<duration_days>247</duration_days>
</methodology>
<results>
<metric>efficacy</metric>
<baseline>65.65</baseline>
<endpoint>47.19</endpoint>
<p_value>0.4009</p_value>
</results>
<results>
<metric>efficacy</metric>
<baseline>18.88</baseline>
<endpoint>49.79</endpoint>
<p_value>0.0184</p_value>
</results>
<results>
<metric>efficacy</metric>
<baseline>32.37</baseline>
<endpoint>97.44</endpoint>
<p_value>0.3919</p_value>
</results>
<conclusion>non-significant</conclusion>
</experiment_result>


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

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

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

Output:
code,course_id,credits,grading_final,grading_homework,grading_midterm,instructor,schedule,term,title
,CRS-8305,4,,,,Rachel Moreno DVM,,Spring 2023,Open-architected even-keeled support 101
CNK133,CRS-5922,3,40,30,30,Tammy Scott,"[{""week"": 1, ""topic"": ""team""}, {""week"": 2, ""topic"": ""much""}, {""week"": 3, ""topic"": ""executive""}, {""we",Fall 2022,Diverse homogeneous access 101
TDW280,CRS-9943,4,40,30,30,Christine Hamilton,"[{""week"": 1, ""topic"": ""matter""}, {""week"": 2, ""topic"": ""black""}, {""week"": 3, ""topic"": ""your""}, {""week",Fall 2021,Decentralized interactive project 101


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<student_assessment>
<total_score>65</total_score>
<percentage>51.02</percentage>
<assessment_id>ASMT-810488</assessment_id>
</student_assessment>

[Assistant]
Approach:
1. Task: Convert student assessment 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:
{
  "total_score": 65,
  "percentage": 51.02,
  "assessment_id": "ASMT-810488"
}


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<course_syllabus>
<course_id>CRS-3948</course_id>
CSZ142
<title>Intuitive foreground functionalities 101</title>
<instructor>Robert Carter</instructor>
<credits>4</credits>
<term>Fall 2022</term>
<schedule>
<week>1</week>
<topic>manage</topic>
</schedule>
<schedule>
<week>2</week>
<topic>catch</topic>
</schedule>
<schedule>
<week>3</week>
<topic>people</topic>
</schedule>
<schedule>
<week>4</week>
<topic>out</topic>
</schedule>
<schedule>
<week>5</week>
<topic>story</topic>
</schedule>
<schedule>
<week>6</week>
<topic>share</topic>
</schedule>
<schedule>
<week>7</week>
<topic>become</topic>
</schedule>
<schedule>
<week>8</week>
<topic>part</topic>
</schedule>
<schedule>
<week>9</week>
<topic>cell</topic>
</schedule>
<grading>
<homework>30</homework>
<midterm>30</midterm>
<final>40</final>
</grading>
</course_syllabus>

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

Output:
{
  "course_id": "CRS-3948",
  "code": "CSZ142",
  "title": "Intuitive foreground functionalities 101",
  "instructor": "Robert Carter",
  "credits": 4,
  "term": "Fall 2022",
  "schedule": [
    {
      "week": 1,
      "topic": "manage"
    },
    {
      "week": 2,
      "topic": "catch"
    },
    {
      "week": 3,
      "topic": "people"
    },
    {
      "week": 4,
      "topic": "out"
    },
    {
      "week": 5,
      "topic": "story"
    },
    {
      "week": 6,
      "topic": "share"
    },
    {
      "week": 7,
      "topic": "become"
    },
    {
      "week": 8,
      "topic": "part"
    },
    {
      "week": 9,
      "topic": "cell"
    }
  ],
  "grading": {
    "homework": 30,
    "midterm": 30,
    "final": 40
  }
}


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

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

[Assistant]
Approach:
1. Task: Create social media post 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:
content,engagement_comments,engagement_likes,engagement_shares,hashtags,platform,post_id,timestamp,user_id,username
"Might north politics.
Moment bad without change physical store call. Enjoy question state student po",18,9146,205,"[""#kid"", ""#off"", ""#school"", ""#fund""]",instagram,POST-86898750,2026-01-07T13:51:25.591017,a47ec401-ca4e-44b5-afc7-6c2b372f589e,dylan00
"Court enjoy light series new ask. Really reason visit far. Hour mean attorney necessary Congress.
Ha",194,4813,303,"[""#picture"", ""#bag"", ""#spend"", ""#purpose""]",twitter,POST-48909369,2026-01-07T13:51:25.592414,33da6354-ad99-4c72-b589-1f6513d550aa,aaronschwartz
"Character modern last arrive. National rise actually ready thank.
Far senior in. Condition happen ce",434,2507,359,"[""#put"", ""#product"", ""#your"", ""#court""]",facebook,POST-81769728,2026-01-07T13:51:25.592760,b8906363-4b49-413b-9a2b-2ea303a2135c,qbennett
"Thus spend push among. American response may relationship particular these.
Bad night candidate key.",425,3927,926,"[""#question"", ""#scene""]",twitter,POST-53283746,2026-01-07T13:51:25.593041,28328463-0c46-478d-a0cc-97d9ec90b90f,erin86
"Prevent nature moment animal. Woman pick end group.
Upon rule able these agent. Push professor a its",403,7742,2,"[""#rock"", ""#current"", ""#treatment""]",instagram,POST-81253092,2026-01-07T13:51:25.593520,cc87f2bb-8296-45b1-a66f-ff6063c8255a,myersnicole


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

[User] Create a TOML representation of error log.

[Assistant]
Approach:
1. Task: Create error log in TOML
2. Complexity: 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 = "424897c8-d97d-4bfb-9c1a-7b6e63fd6096"
timestamp = "2026-01-07T13:51:27.529237"
level = "ERROR"
service = "heartService"
message = "How these anyone stop indeed."
stack_trace = [ "at manage.py:289", "at thing.py:107", "at guy.py:172", "at seat.py:479",]

[context]
user_id = "082cc3eb-3997-4d99-990c-f696ca4ee534"
request_id = "0f3326d0-3afd-48c1-9c4d-32cc8b0c5920"


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

[User] Output research paper as TOML.

[Assistant]
Approach:
1. Task: Create research paper 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:
funding_source = "Kramer Ltd"
title = "Configurable bandwidth-monitored strategy"
[[authors]]
name = "James Brown"
affiliation = "Ward-Davidson"
email = "wilsonkristin@example.org"

[[authors]]
name = "Luke Liu"
affiliation = "Obrien-Huynh"
email = "jason08@example.org"

[[authors]]
name = "Paula Gonzalez"
affiliation = "Jones-Howell"
email = "brent41@example.org"

[publication]
venue = "Cell"
year = 2021
doi = "10.3653/hXNF"


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

[User] Generate student assessment data in JSON format.

[Assistant]
Approach:
1. Task: Create student assessment 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:
{
  "scores": [
    {
      "question": 1,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 10,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 0,
      "points_possible": 10
    }
  ],
  "grade": "C",
  "date": "2026-01-01"
}


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

[User] Generate prescription data in CSV format.

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

Output:
date,medications,patient_mrn,prescriber,rx_id
2026-01-01,"[{""name"": ""Metformin"", ""dosage"": ""20mg"", ""frequency"": ""daily"", ""quantity"": 90}]",MRN-355763,Henry Padilla,RX-1795504
2026-01-02,"[{""name"": ""Atorvastatin"", ""dosage"": ""5mg"", ""frequency"": ""BID"", ""quantity"": 90}]",MRN-757915,Eric Smith,RX-8656023
2026-01-05,"[{""name"": ""Metformin"", ""dosage"": ""20mg"", ""frequency"": ""daily"", ""quantity"": 90}, {""name"": ""Atorvastat",MRN-896890,Tara Palmer,RX-9397476


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

[User] Output error log as CSV.

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

Output:
abstract,authors,citations,error_id,funding_source,keywords,level,paper_id,publication_doi,publication_venue,publication_year,service,title
,,,85223c4c-4b76-4351-95ee-55a2460043f3,,,ERROR,,,,,writeService,
"Wall fast apply movie. World ok several no.
Crime less arm region network society until. Man include","[{""name"": ""Tasha Anderson"", ""affiliation"": ""Hoffman, Lopez and Middleton"", ""email"": ""garciasteven@ex",138,,None,"[""gas"", ""laugh"", ""step"", ""capital"", ""nation""]",,arXiv:2022.23734,10.9004/fnkj,Cell,2022,,Right-sized even-keeled core
Lay cell true do individual computer choose. Third art buy put beat.,"[{""name"": ""Joel Mccoy"", ""affiliation"": ""Maldonado PLC"", ""email"": ""molinazoe@example.net""}, {""name"": ",249,,None,"[""night"", ""range"", ""sense"", ""defense"", ""past""]",,arXiv:2024.17868,10.2051/hpCt,Science,2022,,Multi-layered mission-critical toolset


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<lab_result>
<result_id>LAB-4303735</result_id>
<patient_mrn>MRN-230243</patient_mrn>
<order_date>2026-01-02</order_date>
<panel>Lipid</panel>
<results>
<test>WBC</test>
<value>142.8</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>100.6</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>WBC</test>
<value>148.7</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>95.1</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
</lab_result>


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

[User] Generate course syllabus data in XML format.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<course_syllabus>
<course_id>CRS-6873</course_id>
GDK183
<title>Grass-roots 24/7 emulation 101</title>
<instructor>Melinda Thompson</instructor>
<credits>3</credits>
<term>Fall 2020</term>
<schedule>
<week>1</week>
<topic>girl</topic>
</schedule>
<schedule>
<week>2</week>
<topic>explain</topic>
</schedule>
<schedule>
<week>3</week>
<topic>center</topic>
</schedule>
<schedule>
<week>4</week>
<topic>almost</topic>
</schedule>
<schedule>
<week>5</week>
<topic>property</topic>
</schedule>
<schedule>
<week>6</week>
<topic>call</topic>
</schedule>
<schedule>
<week>7</week>
<topic>bad</topic>
</schedule>
<schedule>
<week>8</week>
<topic>study</topic>
</schedule>
<schedule>
<week>9</week>
<topic>campaign</topic>
</schedule>
<schedule>
<week>10</week>
<topic>performance</topic>
</schedule>
<schedule>
<week>11</week>
<topic>sport</topic>
</schedule>
<grading>
<homework>30</homework>
<midterm>30</midterm>
<final>40</final>
</grading>
</course_syllabus>


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

[User] Create a JSON representation of student assessment.

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

Output:
{
  "assessment_id": "ASMT-475777",
  "student_id": "STU-613124",
  "course_id": "CRS-2241",
  "type": "assignment",
  "date": "2026-01-06",
  "scores": [
    {
      "question": 1,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 6,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 3,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 0,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 9,
      "points_earned": 3,
      "points_possible": 10
    }
  ],
  "total_score": 75,
  "percentage": 81.54,
  "grade": "B"
}


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<lab_result>
<result_id>LAB-2441646</result_id>
<patient_mrn>MRN-228148</patient_mrn>
<order_date>2026-01-01</order_date>
<panel>Lipid</panel>
<results>
<test>Glucose</test>
<value>81.9</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
<results>
<test>WBC</test>
<value>107.7</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>101.6</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>197.9</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
</lab_result>


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

[User] Create a CSV representation of error log.

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

Output:
abstract,authors,citations,context_request_id,context_user_id,error_id,funding_source,keywords,level,message,paper_id,publication_doi,publication_venue,publication_year,service,stack_trace,timestamp,title
,,,089e0eaa-71d8-4f30-a2f1-bac42a6b74a3,8c36ba55-183c-4481-9cd9-dc049447888c,21bf982e-3e24-486f-a8ed-fe9e0227df3b,,,CRITICAL,Story quite another important.,,,,,letService,"[""at decision.py:100"", ""at sing.py:289"", ""at long.py:325"", ""at special.py:174""]",2026-01-07T13:51:27.797574,
Determine story prove central. Family after right growth probably. Necessary good center note.,"[{""name"": ""Joseph Sanchez"", ""affiliation"": ""Moore Ltd"", ""email"": ""sarahesparza@example.com""}, {""name",46,,,,None,"[""story"", ""prove"", ""skill""]",,,arXiv:2022.62801,10.7977/oXlN,Cell,2023,,,,Secured logistical application
Office inside son role big degree cause. Avoid anything join reality play.,"[{""name"": ""Marie Welch"", ""affiliation"": ""Gamble Inc"", ""email"": ""weaverryan@example.net""}, {""name"": """,288,,,,None,"[""itself"", ""maintain"", ""high""]",,,arXiv:2020.44648,10.5898/yoNc,Cell,2020,,,,Multi-layered asymmetric info-mediaries


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


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

[User] Output lab result as TOML.

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

Output:
result_id = "LAB-4827299"
patient_mrn = "MRN-871984"
order_date = "2026-01-06"
panel = "Lipid"
[[results]]
test = "WBC"
value = 156.4
unit = "g/dL"
flag = "high"

[[results]]
test = "WBC"
value = 186.0
unit = "mg/dL"
flag = "low"

[[results]]
test = "WBC"
value = 134.8
unit = "mg/dL"
flag = "normal"

[[results]]
test = "WBC"
value = 64.1
unit = "mg/dL"
flag = "normal"


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<contract>
<contract_id>CTR-457828</contract_id>
<effective_date>2026-01-01</effective_date>
<term_months>32</term_months>
</contract>

[Assistant]
Approach:
1. Task: Convert contract 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:
{
  "contract_id": "CTR-457828",
  "effective_date": "2026-01-01",
  "term_months": 32
}


[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:
paper_id = "arXiv:2023.67735"
title = "Optimized even-keeled conglomeration"
abstract = "Sort suffer stand purpose six resource. Forward hard officer film the word human first."
keywords = [ "attack", "not", "describe",]
citations = 172
funding_source = "Wood, Baldwin and Cain"
[[authors]]
name = "Garrett Contreras"
affiliation = "Drake-Dunn"
email = "sandrapineda@example.net"

[[authors]]
name = "Ryan Bell"
affiliation = "Ramos, Gates and Reed"
email = "kdavis@example.net"

[[authors]]
name = "Cindy Silva"
affiliation = "Bryant, Pratt and Henderson"
email = "fmiller@example.net"

[publication]
venue = "Nature"
year = 2024
doi = "10.7544/lKSL"

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<research_paper>
<paper_id>arXiv:2023.67735</paper_id>
<title>Optimized even-keeled conglomeration</title>
<authors>
<name>Garrett Contreras</name>
<affiliation>Drake-Dunn</affiliation>
<email>sandrapineda@example.net</email>
</authors>
<authors>
<name>Ryan Bell</name>
<affiliation>Ramos, Gates and Reed</affiliation>
<email>kdavis@example.net</email>
</authors>
<authors>
<name>Cindy Silva</name>
<affiliation>Bryant, Pratt and Henderson</affiliation>
<email>fmiller@example.net</email>
</authors>
<abstract>Sort suffer stand purpose six resource. Forward hard officer film the word human first.</abstract>
<keywords>attack</keywords>
<keywords>not</keywords>
<keywords>describe</keywords>
<publication>
<venue>Nature</venue>
<year>2024</year>
<doi>10.7544/lKSL</doi>
</publication>
<citations>172</citations>
<funding_source>Wood, Baldwin and Cain</funding_source>
</research_paper>


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

[User]
Reformat the data below from YAML to TOML:
period: April 2020
total_revenue: 1914989
units_sold: 47758
channels:
- name: wholesale
  revenue: 3617590
  growth: 20.48
- name: online
  revenue: 654207
  growth: 24.4
top_products:
- sku: SKU-4328
  sales: 466200
- sku: SKU-2589
  sales: 244105
- sku: SKU-7725
  sales: 25778

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

Output:
period = "April 2020"
total_revenue = 1914989
units_sold = 47758
[[channels]]
name = "wholesale"
revenue = 3617590
growth = 20.48

[[channels]]
name = "online"
revenue = 654207
growth = 24.4

[[top_products]]
sku = "SKU-4328"
sales = 466200

[[top_products]]
sku = "SKU-2589"
sales = 244105

[[top_products]]
sku = "SKU-7725"
sales = 25778


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

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

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

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


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

[User] Create a YAML representation of course syllabus.

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

Output:
course_id: CRS-1797
code: QAA477
title: User-friendly composite interface 101
instructor: Selena Walker
credits: 4
term: Fall 2024
schedule:
- week: 1
  topic: all
- week: 2
  topic: education
- week: 3
  topic: will
- week: 4
  topic: operation
- week: 5
  topic: western
- week: 6
  topic: plan
- week: 7
  topic: allow
grading:
  homework: 30
  midterm: 30
  final: 40


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

[User]
Reformat the data below from JSON to XML:
{
  "rx_id": "RX-8246470",
  "patient_mrn": "MRN-256913",
  "prescriber": "Victor Valentine",
  "date": "2026-01-01",
  "medications": [
    {
      "name": "Lisinopril",
      "dosage": "20mg",
      "frequency": "daily",
      "quantity": 30
    },
    {
      "name": "Lisinopril",
      "dosage": "10mg",
      "frequency": "BID",
      "quantity": 60
    },
    {
      "name": "Lisinopril",
      "dosage": "5mg",
      "frequency": "TID",
      "quantity": 30
    }
  ]
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<prescription>
<rx_id>RX-8246470</rx_id>
<patient_mrn>MRN-256913</patient_mrn>
<prescriber>Victor Valentine</prescriber>
<date>2026-01-01</date>
<medications>
<name>Lisinopril</name>
<dosage>20mg</dosage>
<frequency>daily</frequency>
<quantity>30</quantity>
</medications>
<medications>
<name>Lisinopril</name>
<dosage>10mg</dosage>
<frequency>BID</frequency>
<quantity>60</quantity>
</medications>
<medications>
<name>Lisinopril</name>
<dosage>5mg</dosage>
<frequency>TID</frequency>
<quantity>30</quantity>
</medications>
</prescription>


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<lab_result>
<result_id>LAB-5956795</result_id>
<patient_mrn>MRN-953048</patient_mrn>
<order_date>2026-01-05</order_date>
<panel>CBC</panel>
<results>
<test>Glucose</test>
<value>138.6</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>69.4</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>89.7</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>191.9</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>WBC</test>
<value>169.5</value>
<unit>mg/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Glucose</test>
<value>187.7</value>
<unit>mg/dL</unit>
<flag>low</flag>
</results>
<results>
<test>WBC</test>
<value>120.0</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
</lab_result>

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

Output:
{
  "result_id": "LAB-5956795",
  "patient_mrn": "MRN-953048",
  "order_date": "2026-01-05",
  "panel": "CBC",
  "results": [
    {
      "test": "Glucose",
      "value": 138.6,
      "unit": "g/dL",
      "flag": "high"
    },
    {
      "test": "Hemoglobin",
      "value": 69.4,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 89.7,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 191.9,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "WBC",
      "value": 169.5,
      "unit": "mg/dL",
      "flag": "low"
    },
    {
      "test": "Glucose",
      "value": 187.7,
      "unit": "mg/dL",
      "flag": "low"
    },
    {
      "test": "WBC",
      "value": 120.0,
      "unit": "mg/dL",
      "flag": "high"
    }
  ]
}


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

[User] Create a TOML representation of experiment result.

[Assistant]
Approach:
1. Task: Create experiment result 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:
experiment_id = "EXP-574681"
title = "Effect of anyone on society"
conclusion = "non-significant"
[[results]]
metric = "efficacy"
baseline = 50.77
endpoint = 70.83
p_value = 0.3046

[[results]]
metric = "efficacy"
baseline = 96.52
endpoint = 82.25
p_value = 0.0326

[[results]]
metric = "safety"
baseline = 43.38
endpoint = 72.88
p_value = 0.2787

[[results]]
metric = "safety"
baseline = 17.71
endpoint = 95.37
p_value = 0.4542

[methodology]
design = "cohort"
sample_size = 560
duration_days = 320


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

[User] Create a YAML representation of student assessment.

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

Output:
assessment_id: ASMT-475777
student_id: STU-613124
course_id: CRS-2241
type: assignment
date: '2026-01-06'
scores:
- question: 1
  points_earned: 8
  points_possible: 10
- question: 2
  points_earned: 6
  points_possible: 10
- question: 3
  points_earned: 3
  points_possible: 10
- question: 4
  points_earned: 1
  points_possible: 10
- question: 5
  points_earned: 9
  points_possible: 10
- question: 6
  points_earned: 7
  points_possible: 10
- question: 7
  points_earned: 0
  points_possible: 10
- question: 8
  points_earned: 9
  points_possible: 10
- question: 9
  points_earned: 3
  points_possible: 10
total_score: 75
percentage: 81.54
grade: B


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

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

[Assistant]
Approach:
1. Task: Create social media post 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:
content,engagement_comments,engagement_likes,engagement_shares,hashtags,platform,post_id,timestamp,user_id,username
About industry woman size. Available box return camera public time. Establish outside ability sport ,28,3129,891,"[""#share"", ""#prevent"", ""#entire"", ""#owner""]",instagram,POST-20150897,2026-01-07T13:51:25.995017,ace3958f-4578-4576-9236-9cbfc1f62953,spatrick
"Whom sit continue. General reduce sport structure.
New stand relationship that parent.
Kitchen call ",393,4802,465,"[""#name"", ""#treatment"", ""#sea"", ""#list""]",facebook,POST-16327890,2026-01-07T13:51:25.996341,4735f81d-1ca4-460b-9315-e316db1689ef,pjackson
"Term new bar bar. Treatment statement somebody court loss ok.
Party rule author laugh. Somebody nati",479,4320,182,"[""#another"", ""#like"", ""#fact""]",facebook,POST-87820652,2026-01-07T13:51:25.996792,d52f0d2e-b741-4d68-9ad3-e7a07f4ccfc3,wilsonvalerie
"Year unit organization to get later fact. Cover money fact perform can goal through oil.
Player to m",222,4373,292,"[""#south"", ""#nor"", ""#anything""]",twitter,POST-95316210,2026-01-07T13:51:25.997088,38d453e4-1609-46dd-b252-e74e671c7af4,tlynch
Assume lot hand drive space me level do. Purpose interesting lose drive course bill ask movie.,168,2853,8,"[""#family"", ""#through"", ""#risk""]",facebook,POST-30279072,2026-01-07T13:51:25.997425,5ecd9e63-749f-4666-aeed-f80fe1a76477,greenjennifer


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

[User]
Reformat the data below from JSON to XML:
{
  "review_id": "REV-1274071",
  "product_id": "PROD-300785",
  "user_id": "c183a72e-4d6f-40ac-92b0-2d1073039571",
  "rating": 5,
  "title": "Follow large high gas clear drug pretty else.",
  "content": "Recent cause family writer. Old less control he woman. Coach quickly will.\nRelationship same against one stand agreement. Be fine occur ten energy resource wall. Nation ten continue.",
  "date": "2026-01-06",
  "verified_purchase": true,
  "helpful_votes": 37
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<review_id>REV-1274071</review_id>
<product_id>PROD-300785</product_id>
<user_id>c183a72e-4d6f-40ac-92b0-2d1073039571</user_id>
<rating>5</rating>
<title>Follow large high gas clear drug pretty else.</title>
<content>Recent cause family writer. Old less control he woman. Coach quickly will.
Relationship same against one stand agreement. Be fine occur ten energy resource wall. Nation ten continue.</content>
<date>2026-01-06</date>
<verified_purchase>True</verified_purchase>
<helpful_votes>37</helpful_votes>
</customer_review>


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

[User]
Convert the following JSON to XML:
{
  "result_id": "LAB-2441646",
  "patient_mrn": "MRN-228148",
  "order_date": "2026-01-01",
  "panel": "Lipid",
  "results": [
    {
      "test": "Glucose",
      "value": 81.9,
      "unit": "g/dL",
      "flag": "high"
    },
    {
      "test": "WBC",
      "value": 107.7,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "Hemoglobin",
      "value": 101.6,
      "unit": "mg/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 197.9,
      "unit": "g/dL",
      "flag": "low"
    }
  ]
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<lab_result>
<result_id>LAB-2441646</result_id>
<patient_mrn>MRN-228148</patient_mrn>
<order_date>2026-01-01</order_date>
<panel>Lipid</panel>
<results>
<test>Glucose</test>
<value>81.9</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
<results>
<test>WBC</test>
<value>107.7</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>101.6</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>197.9</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
</lab_result>


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<research_paper>
<paper_id>arXiv:2023.87771</paper_id>
<title>User-centric stable ability</title>
<authors>
<name>Todd Hall MD</name>
<affiliation>Nunez-Nguyen</affiliation>
<email>grhodes@example.net</email>
</authors>
<authors>
<name>Makayla Long</name>
<affiliation>Stanley, Sellers and Jones</affiliation>
<email>johnsontammy@example.net</email>
</authors>
<abstract>Behavior skin nation pay behind remain. Then put again. Process participant current all.</abstract>
<keywords>design</keywords>
<keywords>him</keywords>
<keywords>blue</keywords>
<keywords>less</keywords>
<keywords>fine</keywords>
<publication>
<venue>Nature</venue>
<year>2020</year>
<doi>10.6248/yEgY</doi>
</publication>
<citations>194</citations>
<funding_source />
</research_paper>

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

Output:
{
  "paper_id": "arXiv:2023.87771",
  "title": "User-centric stable ability",
  "authors": [
    {
      "name": "Todd Hall MD",
      "affiliation": "Nunez-Nguyen",
      "email": "grhodes@example.net"
    },
    {
      "name": "Makayla Long",
      "affiliation": "Stanley, Sellers and Jones",
      "email": "johnsontammy@example.net"
    }
  ],
  "abstract": "Behavior skin nation pay behind remain. Then put again. Process participant current all.",
  "keywords": [
    "design",
    "him",
    "blue",
    "less",
    "fine"
  ],
  "publication": {
    "venue": "Nature",
    "year": 2020,
    "doi": "10.6248/yEgY"
  },
  "citations": 194,
  "funding_source": null
}


[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:
{
  "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
  }
}

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

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


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

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

[Assistant]
Approach:
1. Task: Create clinical note in JSON
2. Complexity: 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:
{
  "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 TOML format. Think step-by-step, then generate syntactically perfect TOML.

[User] Produce a TOML document for a prescription.

[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-7328466"
patient_mrn = "MRN-740510"
prescriber = "William Hebert"
date = "2026-01-04"
[[medications]]
name = "Lisinopril"
dosage = "20mg"
frequency = "TID"
quantity = 30

[[medications]]
name = "Metformin"
dosage = "20mg"
frequency = "BID"
quantity = 60


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

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

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

Output:
note_id = "CN-3508494"
encounter_date = "2026-01-06"
chief_complaint = "chest pain"
[[assessment]]
problem = "hypertension"
icd10 = "K96"

[[assessment]]
problem = "diabetes"
icd10 = "K86"

[patient]
mrn = "MRN-721804"
age = 51
gender = "F"

[vitals]
bp = "130/109"
hr = 78
temp_f = 100.6


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

[User] Generate api specification data in YAML format.

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

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


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

[User] Output clinical note as XML.

[Assistant]
Approach:
1. Task: Create clinical note 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"?>
<clinical_note>
<encounter_date>2026-01-03</encounter_date>
<note_id>CN-2646438</note_id>
<patient>
<mrn>MRN-771263</mrn>
<age>41</age>
<gender>M</gender>
</patient>
</clinical_note>


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

[User]
Reformat the data below from TOML to JSON:
total_score = 97
percentage = 78.32
course_id = "CRS-4089"
[[scores]]
question = 1
points_earned = 0
points_possible = 10

[[scores]]
question = 2
points_earned = 4
points_possible = 10

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

[[scores]]
question = 4
points_earned = 5
points_possible = 10

[[scores]]
question = 5
points_earned = 4
points_possible = 10

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

[[scores]]
question = 7
points_earned = 1
points_possible = 10

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

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

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

[[scores]]
question = 11
points_earned = 5
points_possible = 10

[Assistant]
Approach:
1. Task: Convert student assessment 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:
{
  "total_score": 97,
  "scores": [
    {
      "question": 1,
      "points_earned": 0,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 10,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 5,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 5,
      "points_possible": 10
    },
    {
      "question": 9,
      "points_earned": 3,
      "points_possible": 10
    },
    {
      "question": 10,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 11,
      "points_earned": 5,
      "points_possible": 10
    }
  ],
  "percentage": 78.32,
  "course_id": "CRS-4089"
}


[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"?>
<prescription>
<rx_id>RX-9001624</rx_id>
<patient_mrn>MRN-695608</patient_mrn>
<prescriber>Stephen Davis</prescriber>
<date>2026-01-05</date>
<medications>
<name>Lisinopril</name>
<dosage>20mg</dosage>
<frequency>daily</frequency>
<quantity>90</quantity>
</medications>
</prescription>

[Assistant]
Approach:
1. Task: Convert prescription 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:
rx_id: RX-9001624
patient_mrn: MRN-695608
prescriber: Stephen Davis
date: '2026-01-05'
medications:
- name: Lisinopril
  dosage: 20mg
  frequency: daily
  quantity: 90


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

[User] Generate customer review data in YAML format.

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

Output:
review_id: REV-1681251
product_id: PROD-380005
user_id: 6ee75bbe-7aec-42b2-b8ce-db908c5fbc3a
rating: 3
title: Floor measure may hear dark at.
content: 'Us board wonder trouble. Up as inside party growth seat. College late direction
  amount best team.

  Fish gas end appear mother assume. Anyone major game miss similar argue. Moment
  describe require.'
date: '2026-01-05'
verified_purchase: true
helpful_votes: 21


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

[User] Create a YAML representation of error log.

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

Output:
error_id: e01a43f8-d4eb-4ec7-a325-ad2b31726d0f
timestamp: '2026-01-07T13:51:25.462522'
level: ERROR
service: winService
message: Western energy project push building.
stack_trace:
- at could.py:42
- at seem.py:198
context:
  user_id: 7197800d-0acd-4eee-b9ab-24b5158dfa0a
  request_id: 00c4c00d-dc22-4013-8495-1ed2381fc937


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

[User] Output api specification as JSON.

[Assistant]
Approach:
1. Task: Create api specification in JSON
2. Complexity: 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:
{
  "openapi": "3.0.0",
  "info": {
    "title": "Intuitive disintermediate website API",
    "version": "1.0.0"
  },
  "paths": {
    "/reality": {
      "get": {
        "summary": "Activity public whole paper there relationship tas",
        "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 JSON format. Think step-by-step, then generate syntactically perfect JSON.

[User] Create a JSON representation of news article.

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

Output:
{
  "article_id": "ART-8668047",
  "headline": "Seamless local alliance",
  "author": "Alyssa Moore",
  "published": "2026-01-02T06:22:52.413807",
  "section": "Business",
  "content": "Billion up year window similar. Oil two resource next. If this tough pattern.\nRule year push international.\nReceive charge movie remember hear theory stuff explain. Century animal decide everyone direction rather. Month property rock environment fine such hand remain.",
  "tags": [
    "traditional",
    "wish",
    "little",
    "inside",
    "year"
  ],
  "views": 55093,
  "shares": 3713
}


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

[User] Create a CSV representation of clinical note.

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

Output:
assessment,chief_complaint,encounter_date,note_id,patient_age,patient_gender,patient_mrn,vitals_bp,vitals_hr,vitals_temp_f
"[{""problem"": ""diabetes"", ""icd10"": ""K25""}]",headache,2026-01-02,CN-4466987,87,F,MRN-766590,147/66,72,101.1
"[{""problem"": ""diabetes"", ""icd10"": ""I70""}, {""problem"": ""hypertension"", ""icd10"": ""I54""}, {""problem"": """,fever,2026-01-05,CN-3827373,22,M,MRN-202785,137/100,74,99.0
"[{""problem"": ""diabetes"", ""icd10"": ""J96""}, {""problem"": ""diabetes"", ""icd10"": ""I73""}]",fever,2026-01-04,CN-2431018,88,F,MRN-324204,180/92,106,97.7


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<social_media_post>
<post_id>POST-54622203</post_id>
<platform>instagram</platform>
<user_id>1456e108-0a50-4482-8f1a-b1cb2398a121</user_id>
<username>fullersteven</username>
<content>Card these member kid western growth. Staff draw say early town general. Large break interesting ten against open.
Any fine power truth. Big like investment simple whatever education.</content>
<timestamp>2026-01-07T13:51:25.504049</timestamp>
<hashtags>#deep</hashtags>
<hashtags>#yes</hashtags>
<hashtags>#long</hashtags>
<hashtags>#including</hashtags>
<engagement>
<likes>464</likes>
<shares>699</shares>
<comments>294</comments>
</engagement>
</social_media_post>

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


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

[User] Create a CSV representation of prescription.

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

Output:
date,medications,patient_mrn,prescriber,rx_id
2026-01-04,,,Melinda Black,RX-8618237
2026-01-01,"[{""name"": ""Lisinopril"", ""dosage"": ""5mg"", ""frequency"": ""BID"", ""quantity"": 90}]",MRN-426730,David Murphy,RX-7640117
2026-01-04,"[{""name"": ""Atorvastatin"", ""dosage"": ""20mg"", ""frequency"": ""TID"", ""quantity"": 30}, {""name"": ""Metformin",MRN-381721,Brandi Ellis,RX-6112301


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

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

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

Output:
{
  "verified_purchase": true,
  "date": "2026-01-05",
  "rating": 1
}


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

[User] Produce a YAML document for a contract.

[Assistant]
Approach:
1. Task: Create contract in YAML
2. Complexity: 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:
term_months: 34
parties:
- name: Garza-Henson
  role: party_a
- name: Griffin-Weaver
  role: party_b
status: executed
effective_date: '2026-01-01'


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


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

[User]
Reformat the data below from CSV to JSON:
abstract,authors,citations,funding_source,keywords,paper_id,publication_doi,publication_venue,publication_year,title
List son shake understand food. Up no police friend factor. Support company yes push argue.,"[{""name"": ""Heather Lee"", ""affiliation"": ""Garcia, Ellison and Kim"", ""email"": ""kimberlysimpson@example",36,"Guerra, Richards and Schaefer","[""fact"", ""guess"", ""truth""]",arXiv:2022.73738,10.7028/ttmb,Cell,2024,Switchable maximized Local Area Network
Big recognize discussion minute particular popular play.,"[{""name"": ""Cassie Davis"", ""affiliation"": ""Lee Inc"", ""email"": ""michelletran@example.org""}, {""name"": """,106,"Walton, Turner and Lee","[""class"", ""popular"", ""service""]",arXiv:2020.13480,10.3582/qRyJ,Cell,2021,Organized logistical capability
"Society table pay others. Reach candidate possible authority.
As left although read successful. Woul","[{""name"": ""Joel Cortez"", ""affiliation"": ""Jennings-Mcconnell"", ""email"": ""andrewwarner@example.com""}, ",38,Rivera-Parks,"[""ready"", ""next"", ""study"", ""method"", ""carry""]",arXiv:2023.41767,10.2532/yYHl,Cell,2023,Ergonomic client-driven portal
"Grow former sell evidence eat human. Garden field black some shoulder whether join.
Before could no ","[{""name"": ""Sue Hughes"", ""affiliation"": ""Sanders, Castro and Poole"", ""email"": ""doylerobert@example.or",170,"Boyer, Chan and Chapman","[""summer"", ""man"", ""gun""]",arXiv:2022.74130,10.4843/ITBH,Cell,2020,Exclusive logistical approach

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

Output:
{
  "paper_id": "arXiv:2022.73738",
  "title": "Switchable maximized Local Area Network",
  "authors": [
    {
      "name": "Heather Lee",
      "affiliation": "Garcia, Ellison and Kim",
      "email": "kimberlysimpson@example.com"
    },
    {
      "name": "Jeremy Gonzalez",
      "affiliation": "Wilson, Sanchez and Copeland",
      "email": "michelle83@example.com"
    },
    {
      "name": "Brianna Hart",
      "affiliation": "Shannon, Tran and Taylor",
      "email": "penatyler@example.net"
    }
  ],
  "abstract": "List son shake understand food. Up no police friend factor. Support company yes push argue.",
  "keywords": [
    "fact",
    "guess",
    "truth"
  ],
  "publication": {
    "venue": "Cell",
    "year": 2024,
    "doi": "10.7028/ttmb"
  },
  "citations": 36,
  "funding_source": "Guerra, Richards and Schaefer"
}


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

[User] Generate financial report data in TOML format.

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

Output:
company = "Brooks LLC"
ticker = "HFOB"
quarter = "Q1 2020"
revenue = 30917299
expenses = 61265128
net_income = 10426094
eps = 3.56

[metrics]
profit_margin = 26.89
roe = 20.49


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

[User]
Convert the following JSON to XML:
{
  "txn_id": "TXN-15638187",
  "customer_id": "242fd3fb-d1fb-4e06-b998-4ca6fd25c6b7",
  "timestamp": "2026-01-07T13:51:27.047573",
  "items": [
    {
      "sku": "SKU-16950",
      "qty": 3,
      "price": 120.22
    },
    {
      "sku": "SKU-76122",
      "qty": 1,
      "price": 377.76
    },
    {
      "sku": "SKU-41194",
      "qty": 3,
      "price": 254.19
    },
    {
      "sku": "SKU-75246",
      "qty": 2,
      "price": 418.85
    }
  ],
  "subtotal": 1338.06,
  "tax": 172.92,
  "total": 2048.81,
  "payment_method": "apple_pay"
}

[Assistant]
Approach:
1. Task: Convert transaction record 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"?>
<transaction_record>
<txn_id>TXN-15638187</txn_id>
<customer_id>242fd3fb-d1fb-4e06-b998-4ca6fd25c6b7</customer_id>
<timestamp>2026-01-07T13:51:27.047573</timestamp>
<items>
<sku>SKU-16950</sku>
<qty>3</qty>
<price>120.22</price>
</items>
<items>
<sku>SKU-76122</sku>
<qty>1</qty>
<price>377.76</price>
</items>
<items>
<sku>SKU-41194</sku>
<qty>3</qty>
<price>254.19</price>
</items>
<items>
<sku>SKU-75246</sku>
<qty>2</qty>
<price>418.85</price>
</items>
<subtotal>1338.06</subtotal>
<tax>172.92</tax>
<total>2048.81</total>
<payment_method>apple_pay</payment_method>
</transaction_record>


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

[User]
Reformat the data below from TOML to YAML:
error_id = "bcec7cd1-70fc-42ba-97dd-2c6e2159fc7d"
timestamp = "2026-01-07T13:51:27.288021"
level = "CRITICAL"
service = "reasonService"
message = "Recent security meet three Congress find seat."
stack_trace = [ "at current.py:236", "at your.py:146", "at without.py:194",]

[context]
user_id = "fc408ea4-9df4-4d81-87da-9d63d4bc8744"
request_id = "d8c95012-b6bb-42d7-8cb4-e57e77353a5b"

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

Output:
error_id: bcec7cd1-70fc-42ba-97dd-2c6e2159fc7d
timestamp: '2026-01-07T13:51:27.288021'
level: CRITICAL
service: reasonService
message: Recent security meet three Congress find seat.
stack_trace:
- at current.py:236
- at your.py:146
- at without.py:194
context:
  user_id: fc408ea4-9df4-4d81-87da-9d63d4bc8744
  request_id: d8c95012-b6bb-42d7-8cb4-e57e77353a5b


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<sales_analytics>
<period>March 2022</period>
<total_revenue>7500818</total_revenue>
<units_sold>73950</units_sold>
<channels>
<name>retail</name>
<revenue>528123</revenue>
<growth>12.05</growth>
</channels>
<channels>
<name>online</name>
<revenue>1160273</revenue>
<growth>23.93</growth>
</channels>
<top_products>
<sku>SKU-6153</sku>
<sales>328911</sales>
</top_products>
<top_products>
<sku>SKU-4483</sku>
<sales>21251</sales>
</top_products>
<top_products>
<sku>SKU-5114</sku>
<sales>21486</sales>
</top_products>
</sales_analytics>


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

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

[Assistant]
Approach:
1. Task: Create financial report 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:
company,eps,expenses,metrics_profit_margin,metrics_roe,net_income,quarter,revenue,ticker
"Martinez, Patterson and Hunter",2.32,21448775,7.89,9.32,421192,Q1 2023,66694743,PPOB
"Daniels, Humphrey and Wilson",6.72,67513369,11.83,15.06,6655281,Q4 2023,13528417,DUFZ
Melendez Ltd,5.67,54117053,11.29,23.82,4872391,Q2 2020,35275291,RMWB
Ross-Hester,8.68,62810583,15.96,19.18,9661146,Q3 2023,72500076,SFJX


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

[User] Create a YAML representation of product listing.

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

Output:
reviews: 730
category: books
stock: 824
is_available: true
specs:
  weight_kg: 7.36
  dimensions: 46x21x76cm


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

[User]
Reformat the data below from YAML to TOML:
note_id: CN-4036732
patient:
  mrn: MRN-366942
  age: 79
  gender: M
encounter_date: '2026-01-06'
chief_complaint: headache
vitals:
  bp: 102/96
  hr: 61
  temp_f: 97.1
assessment:
- problem: hypertension
  icd10: K52

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

Output:
note_id = "CN-4036732"
encounter_date = "2026-01-06"
chief_complaint = "headache"
[[assessment]]
problem = "hypertension"
icd10 = "K52"

[patient]
mrn = "MRN-366942"
age = 79
gender = "M"

[vitals]
bp = "102/96"
hr = 61
temp_f = 97.1


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

[User]
Convert the following JSON to XML:
{
  "product_id": "PROD-685161",
  "name": "Balanced demand-driven capacity",
  "category": "clothing",
  "price": 554.83,
  "currency": "USD",
  "stock": 872,
  "is_available": true,
  "rating": 3.32,
  "reviews": 212,
  "specs": {
    "weight_kg": 39.83,
    "dimensions": "86x88x63cm"
  }
}

[Assistant]
Approach:
1. Task: Convert product listing 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"?>
<product_listing>
<product_id>PROD-685161</product_id>
<name>Balanced demand-driven capacity</name>
<category>clothing</category>
<price>554.83</price>
<currency>USD</currency>
<stock>872</stock>
<is_available>True</is_available>
<rating>3.32</rating>
<reviews>212</reviews>
<specs>
<weight_kg>39.83</weight_kg>
<dimensions>86x88x63cm</dimensions>
</specs>
</product_listing>