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

[User] Output prescription as YAML.

[Assistant]
Approach:
1. Task: Create prescription 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:
rx_id: RX-3684509
patient_mrn: MRN-644382
prescriber: Chelsea Henson
date: '2026-01-04'
medications:
- name: Atorvastatin
  dosage: 10mg
  frequency: BID
  quantity: 60
- name: Metformin
  dosage: 20mg
  frequency: daily
  quantity: 60
- name: Metformin
  dosage: 10mg
  frequency: TID
  quantity: 60


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

[User]
Convert the following JSON to XML:
{
  "openapi": "3.0.0",
  "info": {
    "title": "Synchronized holistic archive API",
    "version": "1.0.0"
  },
  "paths": {
    "/policy": {
      "get": {
        "summary": "Red reason present loss yeah run.",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  }
}

[Assistant]
Approach:
1. Task: Convert api specification 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"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Synchronized holistic archive API</title>
<version>1.0.0</version>
</info>
<paths>
</policy>
<get>
<summary>Red reason present loss yeah run.</summary>
<parameters>
<name>param0</name>
<in>query</in>
<type>string</type>
</parameters>
<responses>
<200>
<description>Success</description>
</200>
<400>
<description>Bad Request</description>
</400>
</responses>
</get>
<//policy>
</paths>
</api_specification>


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

[User] Output sales analytics as CSV.

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

Output:
abstract,authors,channels,citations,funding_source,keywords,paper_id,period,publication_doi,publication_venue,publication_year,title,top_products,total_revenue,units_sold
,,"[{""name"": ""retail"", ""revenue"": 3840938, ""growth"": 18.52}, {""name"": ""wholesale"", ""revenue"": 1512471, ",,,,,February 2020,,,,,"[{""sku"": ""SKU-1744"", ""sales"": 276633}, {""sku"": ""SKU-5145"", ""sales"": 26445}, {""sku"": ""SKU-9218"", ""sal",2337421,23839
Green seek short necessary pull. Approach appear least town think order for. Let culture live baby s,"[{""name"": ""Jessica Franco"", ""affiliation"": ""Thompson, Kennedy and Reyes"", ""email"": ""vegarobin@exampl",,132,Kirk Inc,"[""adult"", ""heart"", ""begin"", ""exist""]",arXiv:2020.58288,,10.5262/envA,Cell,2022,Reactive optimal structure,,,
End couple seat. Research within two mother. Live continue keep point rate quickly yeah.,"[{""name"": ""Brian Adams"", ""affiliation"": ""Collins LLC"", ""email"": ""smccall@example.net""}, {""name"": ""Ch",,342,None,"[""avoid"", ""discuss"", ""use""]",arXiv:2020.95844,,10.3567/eSvp,Science,2020,Advanced secondary customer loyalty,,,


[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: medium - 5-8 fields, 2-3 levels
3. Format rules: header row, comma-separated, quoted fields with commas
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
content,engagement_comments,engagement_likes,engagement_shares,hashtags,platform,post_id,timestamp,user_id,username
Property political your form stand cup blood. Business later seem sea represent enough relationship ,39,8599,93,"[""#red"", ""#hotel"", ""#create""]",instagram,POST-94493547,2026-01-07T13:51:27.134920,ebddd714-2a63-4fd6-985c-fb7fe32db0b4,laura52
Son toward go throw among option. Continue fast imagine positive season democratic fast building. So,374,9762,712,"[""#board"", ""#outside"", ""#occur""]",instagram,POST-88077774,2026-01-07T13:51:27.136345,c504caad-2771-4a2f-9070-12ad3881a39a,ithomas
"Foreign first choose exactly model. Goal forward bag wait whose economic.
Stock record national prac",169,2403,949,"[""#enjoy"", ""#to"", ""#question"", ""#fact""]",twitter,POST-91980363,2026-01-07T13:51:27.136740,d7264e70-abe4-432b-8521-166eca52a6df,kendrahorton


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

[User]
Transform this YAML data into CSV format:
experiment_id: EXP-500587
title: Effect of seem on put
methodology:
  design: cohort
  sample_size: 806
  duration_days: 332
results:
- metric: safety
  baseline: 59.15
  endpoint: 80.7
  p_value: 0.0751
- metric: efficacy
  baseline: 25.67
  endpoint: 99.48
  p_value: 0.1142
- metric: safety
  baseline: 72.29
  endpoint: 18.69
  p_value: 0.2768
- metric: safety
  baseline: 16.24
  endpoint: 94.98
  p_value: 0.315
conclusion: significant

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

Output:
conclusion,experiment_id,methodology_design,methodology_duration_days,methodology_sample_size,results,title
significant,EXP-500587,cohort,332,806,"[{""metric"": ""safety"", ""baseline"": 59.15, ""endpoint"": 80.7, ""p_value"": 0.0751}, {""metric"": ""efficacy""",Effect of seem on put
significant,EXP-413544,RCT,206,224,"[{""metric"": ""efficacy"", ""baseline"": 72.74, ""endpoint"": 62.17, ""p_value"": 0.3628}, {""metric"": ""effica",Effect of city on from
significant,EXP-450693,cohort,259,260,"[{""metric"": ""safety"", ""baseline"": 11.94, ""endpoint"": 97.38, ""p_value"": 0.4345}, {""metric"": ""safety"",",Effect of value on force
non-significant,EXP-698621,observational,343,55,"[{""metric"": ""efficacy"", ""baseline"": 27.66, ""endpoint"": 27.34, ""p_value"": 0.4157}, {""metric"": ""effica",Effect of audience on subject
significant,EXP-141123,cohort,176,683,"[{""metric"": ""efficacy"", ""baseline"": 75.73, ""endpoint"": 64.46, ""p_value"": 0.0322}, {""metric"": ""safety",Effect of professional on good


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

[User] Create a XML representation of prescription.

[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-9036427</rx_id>
<patient_mrn>MRN-461250</patient_mrn>
<prescriber>Zachary Berry</prescriber>
<date>2026-01-01</date>
<medications>
<name>Atorvastatin</name>
<dosage>5mg</dosage>
<frequency>daily</frequency>
<quantity>30</quantity>
</medications>
</prescription>


[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-4911961
patient_mrn: MRN-250544
order_date: '2026-01-03'
panel: CBC
results:
- test: Hemoglobin
  value: 121.1
  unit: g/dL
  flag: normal
- test: Hemoglobin
  value: 77.4
  unit: mg/dL
  flag: high
- test: Glucose
  value: 107.3
  unit: g/dL
  flag: high
- test: Glucose
  value: 172.8
  unit: g/dL
  flag: normal
- test: Hemoglobin
  value: 166.2
  unit: mg/dL
  flag: normal
- test: Hemoglobin
  value: 140.6
  unit: g/dL
  flag: normal
- test: WBC
  value: 120.4
  unit: mg/dL
  flag: normal


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

[User]
Convert the following JSON to XML:
{
  "title": "Effect of main on stand",
  "results": [
    {
      "metric": "efficacy",
      "baseline": 50.39,
      "endpoint": 61.09,
      "p_value": 0.3936
    },
    {
      "metric": "safety",
      "baseline": 99.02,
      "endpoint": 82.38,
      "p_value": 0.0752
    },
    {
      "metric": "efficacy",
      "baseline": 94.16,
      "endpoint": 58.56,
      "p_value": 0.1239
    },
    {
      "metric": "safety",
      "baseline": 41.74,
      "endpoint": 45.99,
      "p_value": 0.0661
    }
  ],
  "experiment_id": "EXP-681166",
  "methodology": {
    "design": "RCT",
    "sample_size": 875,
    "duration_days": 212
  },
  "conclusion": "non-significant"
}

[Assistant]
Approach:
1. Task: Convert experiment result 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"?>
<experiment_result>
<title>Effect of main on stand</title>
<results>
<metric>efficacy</metric>
<baseline>50.39</baseline>
<endpoint>61.09</endpoint>
<p_value>0.3936</p_value>
</results>
<results>
<metric>safety</metric>
<baseline>99.02</baseline>
<endpoint>82.38</endpoint>
<p_value>0.0752</p_value>
</results>
<results>
<metric>efficacy</metric>
<baseline>94.16</baseline>
<endpoint>58.56</endpoint>
<p_value>0.1239</p_value>
</results>
<results>
<metric>safety</metric>
<baseline>41.74</baseline>
<endpoint>45.99</endpoint>
<p_value>0.0661</p_value>
</results>
<experiment_id>EXP-681166</experiment_id>
<methodology>
<design>RCT</design>
<sample_size>875</sample_size>
<duration_days>212</duration_days>
</methodology>
<conclusion>non-significant</conclusion>
</experiment_result>


[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"?>
<research_paper>
<paper_id>arXiv:2024.31964</paper_id>
<title>Optimized solution-oriented success</title>
<authors>
<name>Meagan Sutton</name>
<affiliation>Williamson, Mitchell and Smith</affiliation>
<email>davilabridget@example.com</email>
</authors>
<authors>
<name>William Gross</name>
<affiliation>Miller and Sons</affiliation>
<email>linda03@example.net</email>
</authors>
<abstract>Price while never. Night great must well remain. Share less reveal often.</abstract>
<keywords>less</keywords>
<keywords>radio</keywords>
<keywords>spend</keywords>
<keywords>which</keywords>
<publication>
<venue>Science</venue>
<year>2023</year>
<doi>10.4651/vEqE</doi>
</publication>
<citations>155</citations>
<funding_source />
</research_paper>

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

Output:
abstract,authors,citations,funding_source,keywords,paper_id,publication_doi,publication_venue,publication_year,title
Price while never. Night great must well remain. Share less reveal often.,"[{""name"": ""Meagan Sutton"", ""affiliation"": ""Williamson, Mitchell and Smith"", ""email"": ""davilabridget@",155,None,"[""less"", ""radio"", ""spend"", ""which""]",arXiv:2024.31964,10.4651/vEqE,Science,2023,Optimized solution-oriented success
Quite in when full within. Letter receive democratic picture seem perhaps show.,"[{""name"": ""Edward Barton"", ""affiliation"": ""Olson, Huang and Hancock"", ""email"": ""ybaxter@example.net""",401,Aguirre-Johnson,"[""around"", ""draw"", ""although"", ""lose""]",arXiv:2021.71677,10.8157/CqEG,Nature,2022,Multi-channeled optimizing standardization
Piece television of. Laugh run else suffer son minute region.,"[{""name"": ""Angela Nelson"", ""affiliation"": ""Cunningham-Young"", ""email"": ""yadams@example.net""}, {""name",394,Roberts-Snow,"[""up"", ""scientist"", ""chance"", ""any"", ""remember""]",arXiv:2024.64422,10.4775/JWrF,Cell,2022,Customizable systemic structure
May field ahead door tree. Partner east discussion kid sound ability.,"[{""name"": ""Jonathan Dunn"", ""affiliation"": ""Clark-Carney"", ""email"": ""johnbolton@example.org""}, {""name",456,Munoz-Carpenter,"[""away"", ""direction"", ""manage"", ""choose""]",arXiv:2021.28163,10.9551/zmQB,Cell,2022,Right-sized fault-tolerant workforce


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

[User] Create a YAML representation of sales analytics.

[Assistant]
Approach:
1. Task: Create sales analytics 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:
period: June 2022
total_revenue: 7287772
units_sold: 8566
channels:
- name: retail
  revenue: 931216
  growth: 10.96
- name: wholesale
  revenue: 1224016
  growth: 31.92
top_products:
- sku: SKU-1474
  sales: 19268
- sku: SKU-3289
  sales: 31397
- sku: SKU-4950
  sales: 322920


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

[User] Create a CSV representation of research paper.

[Assistant]
Approach:
1. Task: Create research paper 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,funding_source,keywords,paper_id,publication_doi,publication_venue,publication_year,title
Sort suffer stand purpose six resource. Forward hard officer film the word human first.,"[{""name"": ""Garrett Contreras"", ""affiliation"": ""Drake-Dunn"", ""email"": ""sandrapineda@example.net""}, {""",172,"Wood, Baldwin and Cain","[""attack"", ""not"", ""describe""]",arXiv:2023.67735,10.7544/lKSL,Nature,2024,Optimized even-keeled conglomeration
Professional former occur effect. Build born adult impact.,"[{""name"": ""Travis Strong"", ""affiliation"": ""White-Anthony"", ""email"": ""catherinebrown@example.net""}, {",156,None,"[""step"", ""almost"", ""much""]",arXiv:2022.32870,10.1089/xfux,Cell,2024,Virtual local workforce
Perform stop now floor federal phone around after. History prevent at start claim.,"[{""name"": ""Michele Johnson"", ""affiliation"": ""Brown, Dougherty and Chavez"", ""email"": ""heatherbaird@ex",348,None,"[""want"", ""west"", ""paper"", ""number""]",arXiv:2024.98280,10.5020/AQNh,Nature,2020,Synergistic logistical projection


[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-5336793",
  "patient_mrn": "MRN-644295",
  "prescriber": "Thomas Ponce",
  "date": "2026-01-03",
  "medications": [
    {
      "name": "Atorvastatin",
      "dosage": "5mg",
      "frequency": "BID",
      "quantity": 90
    },
    {
      "name": "Atorvastatin",
      "dosage": "5mg",
      "frequency": "daily",
      "quantity": 30
    },
    {
      "name": "Atorvastatin",
      "dosage": "10mg",
      "frequency": "BID",
      "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-5336793</rx_id>
<patient_mrn>MRN-644295</patient_mrn>
<prescriber>Thomas Ponce</prescriber>
<date>2026-01-03</date>
<medications>
<name>Atorvastatin</name>
<dosage>5mg</dosage>
<frequency>BID</frequency>
<quantity>90</quantity>
</medications>
<medications>
<name>Atorvastatin</name>
<dosage>5mg</dosage>
<frequency>daily</frequency>
<quantity>30</quantity>
</medications>
<medications>
<name>Atorvastatin</name>
<dosage>10mg</dosage>
<frequency>BID</frequency>
<quantity>30</quantity>
</medications>
</prescription>


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

[User] Output contract as TOML.

[Assistant]
Approach:
1. Task: Create contract 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:
contract_id = "CTR-784600"
effective_date = "2026-01-06"
term_months = 16
value = 53888
status = "active"
[[parties]]
name = "Snyder-Thornton"
role = "party_a"

[[parties]]
name = "Oliver Group"
role = "party_b"


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


[System] You are an expert in 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"?>
<transaction_record>
<txn_id>TXN-30876983</txn_id>
<customer_id>b5aca191-66fe-49e0-85ce-2d363d5ef454</customer_id>
<timestamp>2026-01-07T13:51:26.163076</timestamp>
<items>
<sku>SKU-56664</sku>
<qty>2</qty>
<price>285.83</price>
</items>
<items>
<sku>SKU-25305</sku>
<qty>1</qty>
<price>45.15</price>
</items>
<items>
<sku>SKU-78820</sku>
<qty>4</qty>
<price>47.49</price>
</items>
<subtotal>199.93</subtotal>
<tax>118.13</tax>
<total>913.78</total>
<payment_method>apple_pay</payment_method>
</transaction_record>

[Assistant]
Approach:
1. Task: Convert transaction record 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:
{
  "txn_id": "TXN-30876983",
  "customer_id": "b5aca191-66fe-49e0-85ce-2d363d5ef454",
  "timestamp": "2026-01-07T13:51:26.163076",
  "items": [
    {
      "sku": "SKU-56664",
      "qty": 2,
      "price": 285.83
    },
    {
      "sku": "SKU-25305",
      "qty": 1,
      "price": 45.15
    },
    {
      "sku": "SKU-78820",
      "qty": 4,
      "price": 47.49
    }
  ],
  "subtotal": 199.93,
  "tax": 118.13,
  "total": 913.78,
  "payment_method": "apple_pay"
}


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

[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-1417017</review_id>
<product_id>PROD-561113</product_id>
<user_id>58368812-841f-4b65-a63f-bf59f81a4b62</user_id>
<rating>2</rating>
<title>Miss entire student source like impact.</title>
<content>Particularly myself court bring vote business boy lawyer. Economy name wonder thank a charge. Successful value site thus. Exist election about task reason.</content>
<date>2026-01-04</date>
<verified_purchase>False</verified_purchase>
<helpful_votes>17</helpful_votes>
</customer_review>


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

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

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

Output:
order_date,panel,patient_mrn,result_id,results
2026-01-05,CBC,MRN-953048,LAB-5956795,"[{""test"": ""Glucose"", ""value"": 138.6, ""unit"": ""g/dL"", ""flag"": ""high""}, {""test"": ""Hemoglobin"", ""value"""
2026-01-02,CBC,MRN-454328,LAB-3153618,"[{""test"": ""WBC"", ""value"": 194.7, ""unit"": ""mg/dL"", ""flag"": ""low""}, {""test"": ""Hemoglobin"", ""value"": 69"
2026-01-02,Lipid,MRN-894393,LAB-4367493,"[{""test"": ""Glucose"", ""value"": 95.9, ""unit"": ""mg/dL"", ""flag"": ""low""}, {""test"": ""Glucose"", ""value"": 16"
2026-01-06,Lipid,MRN-485637,LAB-6936282,"[{""test"": ""Glucose"", ""value"": 124.8, ""unit"": ""g/dL"", ""flag"": ""high""}, {""test"": ""WBC"", ""value"": 183.8"


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

[User]
Reformat the data below from YAML to JSON:
rx_id: RX-3305496
patient_mrn: MRN-551064
prescriber: Eric Jackson
date: '2026-01-03'
medications:
- name: Atorvastatin
  dosage: 20mg
  frequency: daily
  quantity: 90

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

Output:
{
  "rx_id": "RX-3305496",
  "patient_mrn": "MRN-551064",
  "prescriber": "Eric Jackson",
  "date": "2026-01-03",
  "medications": [
    {
      "name": "Atorvastatin",
      "dosage": "20mg",
      "frequency": "daily",
      "quantity": 90
    }
  ]
}


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

[User] Create a JSON representation of error log.

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


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

[User] Create a XML representation of course syllabus.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<course_syllabus>
<instructor>Tamara Stark</instructor>
<term>Spring 2022</term>
VMA483
<grading>
<homework>30</homework>
<midterm>30</midterm>
<final>40</final>
</grading>
</course_syllabus>


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

[User] Generate experiment result data in YAML format.

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

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


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

[User] Output experiment result as YAML.

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

Output:
title: Effect of main on stand
results:
- metric: efficacy
  baseline: 50.39
  endpoint: 61.09
  p_value: 0.3936
- metric: safety
  baseline: 99.02
  endpoint: 82.38
  p_value: 0.0752
- metric: efficacy
  baseline: 94.16
  endpoint: 58.56
  p_value: 0.1239
- metric: safety
  baseline: 41.74
  endpoint: 45.99
  p_value: 0.0661
experiment_id: EXP-681166
methodology:
  design: RCT
  sample_size: 875
  duration_days: 212
conclusion: non-significant


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

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

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

Output:
{
  "items": [
    {
      "sku": "SKU-89816",
      "qty": 1,
      "price": 437.44
    },
    {
      "sku": "SKU-65650",
      "qty": 1,
      "price": 455.72
    },
    {
      "sku": "SKU-98183",
      "qty": 3,
      "price": 337.62
    }
  ],
  "total": 1900.4,
  "payment_method": "apple_pay"
}


[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:
assessment_id: ASMT-672485
student_id: STU-183204
course_id: CRS-8704
type: quiz
date: '2026-01-01'
scores:
- question: 1
  points_earned: 0
  points_possible: 10
- question: 2
  points_earned: 9
  points_possible: 10
- question: 3
  points_earned: 1
  points_possible: 10
- question: 4
  points_earned: 10
  points_possible: 10
- question: 5
  points_earned: 1
  points_possible: 10
- question: 6
  points_earned: 8
  points_possible: 10
- question: 7
  points_earned: 7
  points_possible: 10
- question: 8
  points_earned: 7
  points_possible: 10
- question: 9
  points_earned: 0
  points_possible: 10
- question: 10
  points_earned: 5
  points_possible: 10
- question: 11
  points_earned: 5
  points_possible: 10
- question: 12
  points_earned: 0
  points_possible: 10
total_score: 82
percentage: 72.48
grade: A

[Assistant]
Approach:
1. Task: Convert student assessment 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:
assessment_id = "ASMT-672485"
student_id = "STU-183204"
course_id = "CRS-8704"
type = "quiz"
date = "2026-01-01"
total_score = 82
percentage = 72.48
grade = "A"
[[scores]]
question = 1
points_earned = 0
points_possible = 10

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

[[scores]]
question = 3
points_earned = 1
points_possible = 10

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

[[scores]]
question = 5
points_earned = 1
points_possible = 10

[[scores]]
question = 6
points_earned = 8
points_possible = 10

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

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

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

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

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

[[scores]]
question = 12
points_earned = 0
points_possible = 10


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

[User] Generate news article data in JSON format.

[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-4067367",
  "headline": "Polarized human-resource adapter",
  "author": "Kristin Larson",
  "published": "2026-01-07T00:05:34.405255",
  "section": "Business",
  "content": "Ahead effort author use. Unit together series provide arrive country off. Whether let thought down.\nEight audience power analysis. Age hope leader yeah without. Experience kitchen heart city.",
  "tags": [
    "program",
    "final",
    "computer",
    "live"
  ],
  "views": 74807,
  "shares": 3986
}


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

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

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

Output:
paper_id: arXiv:2020.93852
title: Reactive solution-oriented circuit
authors:
- name: Jennifer Gray
  affiliation: Bryant, Lewis and Wells
  email: spalmer@example.com
- name: David Brown
  affiliation: Cortez, Cook and Ross
  email: melvin21@example.com
abstract: 'Law fund huge better or. Federal forward north law. Work available call
  never.

  Carry cultural day front resource write. Southern white pattern fear.'
keywords:
- wind
- wife
- report
- financial
publication:
  venue: Cell
  year: 2023
  doi: 10.1277/DPuH
citations: 45
funding_source: null


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

[User] Create a TOML representation of product listing.

[Assistant]
Approach:
1. Task: Create product listing in TOML
2. Complexity: 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-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"


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

[User]
Reformat the data below from JSON to XML:
{
  "assessment_id": "ASMT-577861",
  "student_id": "STU-664280",
  "course_id": "CRS-8099",
  "type": "exam",
  "date": "2026-01-06",
  "scores": [
    {
      "question": 1,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 0,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 5,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 6,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 3,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 0,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 1,
      "points_possible": 10
    }
  ],
  "total_score": 52,
  "percentage": 81.98,
  "grade": "B"
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<student_assessment>
<assessment_id>ASMT-577861</assessment_id>
<student_id>STU-664280</student_id>
<course_id>CRS-8099</course_id>
<type>exam</type>
<date>2026-01-06</date>
<scores>
<question>1</question>
<points_earned>7</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>0</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>3</question>
<points_earned>5</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>6</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>3</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>0</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>52</total_score>
<percentage>81.98</percentage>
<grade>B</grade>
</student_assessment>


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

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

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

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

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

Output:
{
  "txn_id": "TXN-38439045",
  "customer_id": "39de4165-2950-403a-b7cf-252ec7bafdcc",
  "timestamp": "2026-01-07T13:51:25.757679",
  "items": [
    {
      "sku": "SKU-68017",
      "qty": 5,
      "price": 287.63
    },
    {
      "sku": "SKU-13598",
      "qty": 1,
      "price": 397.9
    },
    {
      "sku": "SKU-25253",
      "qty": 4,
      "price": 226.78
    },
    {
      "sku": "SKU-92380",
      "qty": 1,
      "price": 318.47
    }
  ],
  "subtotal": 964.6,
  "tax": 142.48,
  "total": 1270.74,
  "payment_method": "credit_card"
}


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

[User] Output api specification as TOML.

[Assistant]
Approach:
1. Task: Create api specification 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:
openapi = "3.0.0"

[info]
title = "Synchronized holistic archive API"
version = "1.0.0"

[paths."/policy".get]
summary = "Red reason present loss yeah run."
[[paths."/policy".get.parameters]]
name = "param0"
in = "query"
type = "string"

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

[paths."/policy".get.responses.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 research paper.

[Assistant]
Approach:
1. Task: Create research paper 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:
{
  "paper_id": "arXiv:2022.79764",
  "title": "Progressive exuding adapter",
  "authors": [
    {
      "name": "Gary Johnson",
      "affiliation": "Wolf Group",
      "email": "jamie40@example.org"
    },
    {
      "name": "Lisa Ortega",
      "affiliation": "Wells, Flores and Cooper",
      "email": "nicholas25@example.com"
    },
    {
      "name": "Kimberly Alvarez",
      "affiliation": "Lewis-Hunt",
      "email": "bookersteven@example.com"
    }
  ],
  "abstract": "Win both purpose hour professor table.",
  "keywords": [
    "office",
    "during",
    "more",
    "apply",
    "program"
  ],
  "publication": {
    "venue": "Nature",
    "year": 2023,
    "doi": "10.1780/NyHo"
  },
  "citations": 258,
  "funding_source": "Espinoza, Khan and Lowe"
}


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<contract>
<term_months>34</term_months>
<parties>
<name>Garza-Henson</name>
<role>party_a</role>
</parties>
<parties>
<name>Griffin-Weaver</name>
<role>party_b</role>
</parties>
<status>executed</status>
<effective_date>2026-01-01</effective_date>
</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:
{
  "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 CSV format. Think step-by-step, then generate syntactically perfect CSV.

[User]
Convert the following TOML to CSV:
encounter_date = "2026-01-06"
note_id = "CN-3244099"
[[assessment]]
problem = "diabetes"
icd10 = "I24"

[patient]
mrn = "MRN-470382"
age = 61
gender = "F"

[vitals]
bp = "158/77"
hr = 112
temp_f = 99.5

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

Output:
assessment,chief_complaint,encounter_date,note_id,patient_age,patient_gender,patient_mrn,vitals_bp,vitals_hr,vitals_temp_f
"[{""problem"": ""diabetes"", ""icd10"": ""I24""}]",,2026-01-06,CN-3244099,61,F,MRN-470382,158/77,112,99.5
"[{""problem"": ""hypertension"", ""icd10"": ""J96""}, {""problem"": ""diabetes"", ""icd10"": ""I27""}, {""problem"": """,headache,2026-01-03,CN-6346853,54,F,MRN-619925,130/81,93,97.7
"[{""problem"": ""hypertension"", ""icd10"": ""K78""}]",headache,2026-01-03,CN-5182973,24,M,MRN-706108,104/95,95,101.4
"[{""problem"": ""hypertension"", ""icd10"": ""J68""}, {""problem"": ""diabetes"", ""icd10"": ""I12""}, {""problem"": """,chest pain,2026-01-06,CN-5391034,41,F,MRN-882784,102/64,85,99.3
"[{""problem"": ""diabetes"", ""icd10"": ""K57""}, {""problem"": ""diabetes"", ""icd10"": ""K84""}, {""problem"": ""diab",headache,2026-01-05,CN-9245534,31,F,MRN-763226,109/61,112,99.0


[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-7937835"
encounter_date = "2026-01-06"
chief_complaint = "chest pain"
[[assessment]]
problem = "hypertension"
icd10 = "I52"

[[assessment]]
problem = "diabetes"
icd10 = "J76"

[patient]
mrn = "MRN-749785"
age = 66
gender = "M"

[vitals]
bp = "179/85"
hr = 81
temp_f = 101.7


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

[User] Output contract as JSON.

[Assistant]
Approach:
1. Task: Create contract 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:
{
  "contract_id": "CTR-464030",
  "parties": [
    {
      "name": "Morales, Williams and Williams",
      "role": "party_a"
    },
    {
      "name": "Ward-Miller",
      "role": "party_b"
    }
  ],
  "effective_date": "2026-01-06",
  "term_months": 35,
  "value": 994957,
  "status": "active"
}


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

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

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


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

[User] Generate research paper data in YAML format.

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

Output:
paper_id: arXiv:2024.40808
title: Versatile systematic infrastructure
authors:
- name: Andres Compton
  affiliation: Knight, Wyatt and Mccarty
  email: lawsontammy@example.org
- name: Michael Mcgrath
  affiliation: Garcia, Davis and Caldwell
  email: madison05@example.net
abstract: Face direction whom party go follow. According meet pick hit environmental
  resource glass.
keywords:
- service
- walk
- although
- several
- against
publication:
  venue: Cell
  year: 2021
  doi: 10.1740/TuDe
citations: 172
funding_source: Bautista, Saunders and Delgado


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

[User]
Transform this JSON data into XML format:
{
  "openapi": "3.0.0",
  "info": {
    "title": "Reactive exuding frame API",
    "version": "1.0.0"
  },
  "paths": {
    "/second": {
      "get": {
        "summary": "Life century work throughout however miss another.",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  }
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Reactive exuding frame API</title>
<version>1.0.0</version>
</info>
<paths>
</second>
<get>
<summary>Life century work throughout however miss another.</summary>
<parameters>
<name>param0</name>
<in>query</in>
<type>string</type>
</parameters>
<responses>
<200>
<description>Success</description>
</200>
<400>
<description>Bad Request</description>
</400>
</responses>
</get>
<//second>
</paths>
</api_specification>


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

[User] Output prescription as JSON.

[Assistant]
Approach:
1. Task: Create prescription 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:
{
  "rx_id": "RX-1565761",
  "patient_mrn": "MRN-226686",
  "prescriber": "Regina Martin",
  "date": "2026-01-03",
  "medications": [
    {
      "name": "Metformin",
      "dosage": "20mg",
      "frequency": "TID",
      "quantity": 60
    },
    {
      "name": "Atorvastatin",
      "dosage": "20mg",
      "frequency": "BID",
      "quantity": 90
    }
  ]
}


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<review_id>REV-1521978</review_id>
<product_id>PROD-894495</product_id>
<user_id>0e93d4dc-0d39-4af2-8ec3-d8d1250011b9</user_id>
<rating>4</rating>
<title>Great how data open such.</title>
<content>City not either situation all along might. Under could expect build member. Fish ready onto white majority.</content>
<date>2026-01-05</date>
<verified_purchase>False</verified_purchase>
<helpful_votes>57</helpful_votes>
</customer_review>

[Assistant]
Approach:
1. Task: Convert customer review 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:
{
  "review_id": "REV-1521978",
  "product_id": "PROD-894495",
  "user_id": "0e93d4dc-0d39-4af2-8ec3-d8d1250011b9",
  "rating": 4,
  "title": "Great how data open such.",
  "content": "City not either situation all along might. Under could expect build member. Fish ready onto white majority.",
  "date": "2026-01-05",
  "verified_purchase": false,
  "helpful_votes": 57
}


[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"?>
<prescription>
<rx_id>RX-5336793</rx_id>
<patient_mrn>MRN-644295</patient_mrn>
<prescriber>Thomas Ponce</prescriber>
<date>2026-01-03</date>
<medications>
<name>Atorvastatin</name>
<dosage>5mg</dosage>
<frequency>BID</frequency>
<quantity>90</quantity>
</medications>
<medications>
<name>Atorvastatin</name>
<dosage>5mg</dosage>
<frequency>daily</frequency>
<quantity>30</quantity>
</medications>
<medications>
<name>Atorvastatin</name>
<dosage>10mg</dosage>
<frequency>BID</frequency>
<quantity>30</quantity>
</medications>
</prescription>

[Assistant]
Approach:
1. Task: Convert prescription 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:
{
  "rx_id": "RX-5336793",
  "patient_mrn": "MRN-644295",
  "prescriber": "Thomas Ponce",
  "date": "2026-01-03",
  "medications": [
    {
      "name": "Atorvastatin",
      "dosage": "5mg",
      "frequency": "BID",
      "quantity": 90
    },
    {
      "name": "Atorvastatin",
      "dosage": "5mg",
      "frequency": "daily",
      "quantity": 30
    },
    {
      "name": "Atorvastatin",
      "dosage": "10mg",
      "frequency": "BID",
      "quantity": 30
    }
  ]
}


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

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

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

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


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

[User] Create a XML representation of contract.

[Assistant]
Approach:
1. Task: Create contract 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"?>
<contract>
<contract_id>CTR-926700</contract_id>
<parties>
<name>Kelly-Jackson</name>
<role>party_a</role>
</parties>
<parties>
<name>Ramos, Hampton and Hartman</name>
<role>party_b</role>
</parties>
<effective_date>2026-01-04</effective_date>
<term_months>36</term_months>
<value>178791</value>
<status>pending</status>
</contract>


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

[User]
Transform this YAML data into JSON format:
contract_id: CTR-449984
parties:
- name: Garcia-Henson
  role: party_a
- name: Moore LLC
  role: party_b
effective_date: '2026-01-04'
term_months: 49
value: 694475
status: pending

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

Output:
{
  "contract_id": "CTR-449984",
  "parties": [
    {
      "name": "Garcia-Henson",
      "role": "party_a"
    },
    {
      "name": "Moore LLC",
      "role": "party_b"
    }
  ],
  "effective_date": "2026-01-04",
  "term_months": 49,
  "value": 694475,
  "status": "pending"
}


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

[User] Create a TOML representation of financial report.

[Assistant]
Approach:
1. Task: Create financial report in TOML
2. Complexity: 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:
quarter = "Q3 2022"
company = "Dunn-Byrd"
expenses = 58548919
eps = 9.56
ticker = "ATGQ"


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

[User]
Convert the following YAML to XML:
quarter: Q3 2022
company: Dunn-Byrd
expenses: 58548919
eps: 9.56
ticker: ATGQ

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<financial_report>
<quarter>Q3 2022</quarter>
<company>Dunn-Byrd</company>
<expenses>58548919</expenses>
<eps>9.56</eps>
<ticker>ATGQ</ticker>
</financial_report>


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

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

[Assistant]
Approach:
1. Task: Create customer review in YAML
2. Complexity: 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:
review_id: REV-9723622
product_id: PROD-853148
user_id: 44919496-69de-498e-922c-5ea4230c00fa
rating: 3
title: Risk tell team series house.
content: Official police serve past already. Number down similar senior head amount.
  Focus reality really hold lose.
date: '2026-01-03'
verified_purchase: false
helpful_votes: 99


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

[User] Generate customer review data in TOML format.

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

Output:
review_id = "REV-2691236"
product_id = "PROD-245093"
user_id = "98b0ec97-f0e6-4eda-907b-c1488d5de2f5"
rating = 1
title = "Now new sell exist just."
content = "Issue suddenly such maybe. Military they second staff end agreement.\nClose that speech alone know wish matter. Finally adult statement method."
date = "2026-01-02"
verified_purchase = false
helpful_votes = 34


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

[User] Create a TOML representation of product listing.

[Assistant]
Approach:
1. Task: Create product listing in TOML
2. Complexity: 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:
is_available = true
rating = 1.03
category = "electronics"
price = 302.74


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

[User] Produce a YAML document for a 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-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 XML format. Think step-by-step, then generate syntactically perfect XML.

[User]
Convert the following JSON to XML:
{
  "schedule": [
    {
      "week": 1,
      "topic": "table"
    },
    {
      "week": 2,
      "topic": "team"
    },
    {
      "week": 3,
      "topic": "miss"
    },
    {
      "week": 4,
      "topic": "face"
    },
    {
      "week": 5,
      "topic": "sort"
    },
    {
      "week": 6,
      "topic": "board"
    },
    {
      "week": 7,
      "topic": "effect"
    },
    {
      "week": 8,
      "topic": "still"
    },
    {
      "week": 9,
      "topic": "training"
    },
    {
      "week": 10,
      "topic": "different"
    }
  ],
  "code": "GHC481",
  "grading": {
    "homework": 30,
    "midterm": 30,
    "final": 40
  },
  "term": "Spring 2020",
  "credits": 4
}

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


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

[User]
Convert the following JSON to TOML:
{
  "article_id": "ART-6846954",
  "headline": "Triple-buffered intangible knowledgebase",
  "author": "Steven Burgess",
  "published": "2026-01-02T13:52:55.283034",
  "section": "Politics",
  "content": "Police report arm sense find civil during. New avoid old future quality finally bad. Meeting child effect go play issue.\nThousand security article two color early. Avoid commercial science. Low method cultural personal night often.",
  "tags": [
    "couple",
    "specific",
    "him"
  ],
  "views": 35509,
  "shares": 3662
}

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

Output:
article_id = "ART-6846954"
headline = "Triple-buffered intangible knowledgebase"
author = "Steven Burgess"
published = "2026-01-02T13:52:55.283034"
section = "Politics"
content = "Police report arm sense find civil during. New avoid old future quality finally bad. Meeting child effect go play issue.\nThousand security article two color early. Avoid commercial science. Low method cultural personal night often."
tags = [ "couple", "specific", "him",]
views = 35509
shares = 3662


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

[User] Output student assessment as JSON.

[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-672485",
  "student_id": "STU-183204",
  "course_id": "CRS-8704",
  "type": "quiz",
  "date": "2026-01-01",
  "scores": [
    {
      "question": 1,
      "points_earned": 0,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 10,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 9,
      "points_earned": 0,
      "points_possible": 10
    },
    {
      "question": 10,
      "points_earned": 5,
      "points_possible": 10
    },
    {
      "question": 11,
      "points_earned": 5,
      "points_possible": 10
    },
    {
      "question": 12,
      "points_earned": 0,
      "points_possible": 10
    }
  ],
  "total_score": 82,
  "percentage": 72.48,
  "grade": "A"
}


[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:
{
  "contract_id": "CTR-123472",
  "parties": [
    {
      "name": "Palmer-White",
      "role": "party_a"
    },
    {
      "name": "Rodriguez-Moore",
      "role": "party_b"
    }
  ],
  "effective_date": "2026-01-06",
  "term_months": 59,
  "value": 388976,
  "status": "pending"
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<contract>
<contract_id>CTR-123472</contract_id>
<parties>
<name>Palmer-White</name>
<role>party_a</role>
</parties>
<parties>
<name>Rodriguez-Moore</name>
<role>party_b</role>
</parties>
<effective_date>2026-01-06</effective_date>
<term_months>59</term_months>
<value>388976</value>
<status>pending</status>
</contract>


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

[User] Generate financial report data in JSON format.

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

Output:
{
  "company": "Scott-Campbell",
  "ticker": "SZQB",
  "quarter": "Q2 2021",
  "revenue": 15063505,
  "expenses": 40738667,
  "net_income": 16626814,
  "eps": 6.47,
  "metrics": {
    "profit_margin": 15.92,
    "roe": 8.35
  }
}


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

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

[Assistant]
Approach:
1. Task: Create api specification 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"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Organic analyzing strategy API</title>
<version>1.0.0</version>
</info>
<paths>
</similar>
<get>
<summary>Natural see lot recently.</summary>
<parameters>
<name>param0</name>
<in>query</in>
<type>string</type>
</parameters>
<parameters>
<name>param1</name>
<in>query</in>
<type>string</type>
</parameters>
<responses>
<200>
<description>Success</description>
</200>
<400>
<description>Bad Request</description>
</400>
</responses>
</get>
<//similar>
</paths>
</api_specification>


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

[User]
Transform this JSON data into XML format:
{
  "experiment_id": "EXP-168652",
  "title": "Effect of green on from",
  "methodology": {
    "design": "cohort",
    "sample_size": 797,
    "duration_days": 186
  },
  "results": [
    {
      "metric": "safety",
      "baseline": 24.16,
      "endpoint": 44.82,
      "p_value": 0.0559
    },
    {
      "metric": "efficacy",
      "baseline": 16.54,
      "endpoint": 28.48,
      "p_value": 0.2997
    }
  ],
  "conclusion": "non-significant"
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<experiment_result>
<experiment_id>EXP-168652</experiment_id>
<title>Effect of green on from</title>
<methodology>
<design>cohort</design>
<sample_size>797</sample_size>
<duration_days>186</duration_days>
</methodology>
<results>
<metric>safety</metric>
<baseline>24.16</baseline>
<endpoint>44.82</endpoint>
<p_value>0.0559</p_value>
</results>
<results>
<metric>efficacy</metric>
<baseline>16.54</baseline>
<endpoint>28.48</endpoint>
<p_value>0.2997</p_value>
</results>
<conclusion>non-significant</conclusion>
</experiment_result>


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

[User] Output product listing as YAML.

[Assistant]
Approach:
1. Task: Create product listing in YAML
2. Complexity: 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:
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


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

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


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

[User] Create a TOML representation of student assessment.

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

Output:
assessment_id = "ASMT-482875"
student_id = "STU-646713"
course_id = "CRS-2679"
type = "assignment"
date = "2026-01-01"
total_score = 62
percentage = 98.87
grade = "C"
[[scores]]
question = 1
points_earned = 1
points_possible = 10

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

[[scores]]
question = 3
points_earned = 1
points_possible = 10

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

[[scores]]
question = 5
points_earned = 3
points_possible = 10

[[scores]]
question = 6
points_earned = 8
points_possible = 10

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

[[scores]]
question = 8
points_earned = 1
points_possible = 10

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

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


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

[User] Create a TOML representation of news article.

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

Output:
article_id = "ART-1823437"
headline = "Integrated content-based throughput"
author = "Anna Ortiz"
published = "2026-01-05T06:32:59.977242"
section = "Politics"
content = "Success off activity him process hot whose pay. Most probably including at arm avoid media finally.\nFilm traditional together still member. Culture let serve home.\nChoose free minute in rich after image. Family meet health offer total leave media. Education enter against foreign."
tags = [ "base", "fight", "test",]
views = 75522
shares = 3070


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

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

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

Output:
{
  "company": "Taylor Ltd",
  "ticker": "AOED",
  "quarter": "Q1 2024",
  "revenue": 69752271,
  "expenses": 52626087,
  "net_income": 18580243,
  "eps": 1.63,
  "metrics": {
    "profit_margin": 23.4,
    "roe": 21.22
  }
}


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

[User] Output contract as JSON.

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

Output:
{
  "contract_id": "CTR-784600",
  "parties": [
    {
      "name": "Snyder-Thornton",
      "role": "party_a"
    },
    {
      "name": "Oliver Group",
      "role": "party_b"
    }
  ],
  "effective_date": "2026-01-06",
  "term_months": 16,
  "value": 53888,
  "status": "active"
}


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<social_media_post>
<post_id>POST-52722833</post_id>
<platform>facebook</platform>
<user_id>d42576ea-a78d-4261-852d-cbcc2fd55da5</user_id>
<username>justin96</username>
<content>Southern write three operation throw interest whether.
Decade quality training employee. Financial out position catch finish author. Past over in create.
Nice reduce try contain future back customer.</content>
<timestamp>2026-01-07T13:51:26.716888</timestamp>
<hashtags>#report</hashtags>
<hashtags>#newspaper</hashtags>
<engagement>
<likes>8106</likes>
<shares>850</shares>
<comments>244</comments>
</engagement>
</social_media_post>


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<review_id>REV-5008217</review_id>
<product_id>PROD-173271</product_id>
<user_id>11121b86-b60c-4ea2-b83a-cbb727cd7a24</user_id>
<rating>2</rating>
<title>Lay lead it politics brother.</title>
<content>Camera left hope prevent inside real. Whether trouble their always manager cultural majority popular. Song condition entire security concern science. Run number firm listen serious.</content>
<date>2026-01-01</date>
<verified_purchase>True</verified_purchase>
<helpful_votes>23</helpful_votes>
</customer_review>

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

Output:
{
  "review_id": "REV-5008217",
  "product_id": "PROD-173271",
  "user_id": "11121b86-b60c-4ea2-b83a-cbb727cd7a24",
  "rating": 2,
  "title": "Lay lead it politics brother.",
  "content": "Camera left hope prevent inside real. Whether trouble their always manager cultural majority popular. Song condition entire security concern science. Run number firm listen serious.",
  "date": "2026-01-01",
  "verified_purchase": true,
  "helpful_votes": 23
}


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

[User]
Convert the following JSON to XML:
{
  "article_id": "ART-1823437",
  "headline": "Integrated content-based throughput",
  "author": "Anna Ortiz",
  "published": "2026-01-05T06:32:59.977242",
  "section": "Politics",
  "content": "Success off activity him process hot whose pay. Most probably including at arm avoid media finally.\nFilm traditional together still member. Culture let serve home.\nChoose free minute in rich after image. Family meet health offer total leave media. Education enter against foreign.",
  "tags": [
    "base",
    "fight",
    "test"
  ],
  "views": 75522,
  "shares": 3070
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<news_article>
<article_id>ART-1823437</article_id>
<headline>Integrated content-based throughput</headline>
<author>Anna Ortiz</author>
<published>2026-01-05T06:32:59.977242</published>

Politics

<content>Success off activity him process hot whose pay. Most probably including at arm avoid media finally.
Film traditional together still member. Culture let serve home.
Choose free minute in rich after image. Family meet health offer total leave media. Education enter against foreign.</content>
<tags>base</tags>
<tags>fight</tags>
<tags>test</tags>
<views>75522</views>
<shares>3070</shares>
</news_article>


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

[User]
Convert the following JSON to CSV:
{
  "course_id": "CRS-8855",
  "code": "DBP130",
  "title": "Team-oriented 3rdgeneration implementation 101",
  "instructor": "Carl Davis",
  "credits": 3,
  "term": "Fall 2024",
  "schedule": [
    {
      "week": 1,
      "topic": "manage"
    },
    {
      "week": 2,
      "topic": "someone"
    },
    {
      "week": 3,
      "topic": "bring"
    },
    {
      "week": 4,
      "topic": "board"
    },
    {
      "week": 5,
      "topic": "important"
    },
    {
      "week": 6,
      "topic": "he"
    },
    {
      "week": 7,
      "topic": "possible"
    },
    {
      "week": 8,
      "topic": "office"
    },
    {
      "week": 9,
      "topic": "board"
    },
    {
      "week": 10,
      "topic": "drive"
    },
    {
      "week": 11,
      "topic": "Mrs"
    }
  ],
  "grading": {
    "homework": 30,
    "midterm": 30,
    "final": 40
  }
}

[Assistant]
Approach:
1. Task: Convert course syllabus from JSON 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:
code,course_id,credits,grading_final,grading_homework,grading_midterm,instructor,schedule,term,title
DBP130,CRS-8855,3,40,30,30,Carl Davis,"[{""week"": 1, ""topic"": ""manage""}, {""week"": 2, ""topic"": ""someone""}, {""week"": 3, ""topic"": ""bring""}, {""w",Fall 2024,Team-oriented 3rdgeneration implementation 101
TNY170,CRS-8221,3,40,30,30,Nancy Willis,"[{""week"": 1, ""topic"": ""discuss""}, {""week"": 2, ""topic"": ""above""}, {""week"": 3, ""topic"": ""adult""}, {""we",Spring 2020,Virtual value-added migration 101
EEF374,CRS-6073,4,40,30,30,Charles Reynolds,"[{""week"": 1, ""topic"": ""drive""}, {""week"": 2, ""topic"": ""article""}, {""week"": 3, ""topic"": ""fly""}, {""week",Spring 2023,Managed fresh-thinking flexibility 101


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

[User] Create a TOML representation of customer review.

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

Output:
review_id = "REV-9723622"
product_id = "PROD-853148"
user_id = "44919496-69de-498e-922c-5ea4230c00fa"
rating = 3
title = "Risk tell team series house."
content = "Official police serve past already. Number down similar senior head amount. Focus reality really hold lose."
date = "2026-01-03"
verified_purchase = false
helpful_votes = 99


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

[User] Create a TOML representation of contract.

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

Output:
contract_id = "CTR-926700"
effective_date = "2026-01-04"
term_months = 36
value = 178791
status = "pending"
[[parties]]
name = "Kelly-Jackson"
role = "party_a"

[[parties]]
name = "Ramos, Hampton and Hartman"
role = "party_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 financial report.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<financial_report>
<company>Martinez, Patterson and Hunter</company>
<ticker>PPOB</ticker>
<quarter>Q1 2023</quarter>
<revenue>66694743</revenue>
<expenses>21448775</expenses>
<net_income>421192</net_income>
<eps>2.32</eps>
<metrics>
<profit_margin>7.89</profit_margin>
<roe>9.32</roe>
</metrics>
</financial_report>


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

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

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

Output:
{
  "article_id": "ART-6846954",
  "headline": "Triple-buffered intangible knowledgebase",
  "author": "Steven Burgess",
  "published": "2026-01-02T13:52:55.283034",
  "section": "Politics",
  "content": "Police report arm sense find civil during. New avoid old future quality finally bad. Meeting child effect go play issue.\nThousand security article two color early. Avoid commercial science. Low method cultural personal night often.",
  "tags": [
    "couple",
    "specific",
    "him"
  ],
  "views": 35509,
  "shares": 3662
}


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<research_paper>
<paper_id>arXiv:2020.57295</paper_id>
<title>Persevering global groupware</title>
<authors>
<name>Edwin Moore</name>
<affiliation>Smith-Jones</affiliation>
<email>bowenzachary@example.net</email>
</authors>
<authors>
<name>Anna Collins</name>
<affiliation>Thomas, Rogers and Baldwin</affiliation>
<email>thill@example.com</email>
</authors>
<authors>
<name>Mrs. Mary Delacruz MD</name>
<affiliation>French, Rodriguez and Johnson</affiliation>
<email>amywest@example.org</email>
</authors>
<abstract>Stand season mind indicate either. Buy gas keep skin.</abstract>
<keywords>stock</keywords>
<keywords>member</keywords>
<keywords>laugh</keywords>
<keywords>language</keywords>
<keywords>right</keywords>
<publication>
<venue>Cell</venue>
<year>2022</year>
<doi>10.9461/HDZk</doi>
</publication>
<citations>204</citations>
<funding_source />
</research_paper>

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

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


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<clinical_note>
<note_id>CN-4466987</note_id>
<patient>
<mrn>MRN-766590</mrn>
<age>87</age>
<gender>F</gender>
</patient>
<encounter_date>2026-01-02</encounter_date>
<chief_complaint>headache</chief_complaint>
<vitals>
<bp>147/66</bp>

72

<temp_f>101.1</temp_f>
</vitals>
<assessment>
<problem>diabetes</problem>
<icd10>K25</icd10>
</assessment>
</clinical_note>

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

Output:
{
  "note_id": "CN-4466987",
  "patient": {
    "mrn": "MRN-766590",
    "age": 87,
    "gender": "F"
  },
  "encounter_date": "2026-01-02",
  "chief_complaint": "headache",
  "vitals": {
    "bp": "147/66",
    "hr": 72,
    "temp_f": 101.1
  },
  "assessment": [
    {
      "problem": "diabetes",
      "icd10": "K25"
    }
  ]
}


[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: 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:
{
  "rx_id": "RX-5336793",
  "patient_mrn": "MRN-644295",
  "prescriber": "Thomas Ponce",
  "date": "2026-01-03",
  "medications": [
    {
      "name": "Atorvastatin",
      "dosage": "5mg",
      "frequency": "BID",
      "quantity": 90
    },
    {
      "name": "Atorvastatin",
      "dosage": "5mg",
      "frequency": "daily",
      "quantity": 30
    },
    {
      "name": "Atorvastatin",
      "dosage": "10mg",
      "frequency": "BID",
      "quantity": 30
    }
  ]
}


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

[User]
Reformat the data below from CSV to XML:
abstract,authors,channels,citations,funding_source,keywords,paper_id,period,publication_doi,publication_venue,publication_year,title,top_products,total_revenue,units_sold
,,"[{""name"": ""retail"", ""revenue"": 931216, ""growth"": 10.96}, {""name"": ""wholesale"", ""revenue"": 1224016, """,,,,,June 2022,,,,,"[{""sku"": ""SKU-1474"", ""sales"": 19268}, {""sku"": ""SKU-3289"", ""sales"": 31397}, {""sku"": ""SKU-4950"", ""sale",7287772,8566
Author pattern successful better current. Believe both education customer unit from. During conditio,"[{""name"": ""Tyler Anderson"", ""affiliation"": ""Martinez-Garcia"", ""email"": ""sharon14@example.org""}, {""na",,268,Morrison-Velasquez,"[""note"", ""economic"", ""offer"", ""nearly"", ""present""]",arXiv:2024.24675,,10.8087/wqIN,Science,2024,Organized high-level service-desk,,,
Well identify past home. Continue throw authority property star role study. True once always out.,"[{""name"": ""Jacqueline Castaneda"", ""affiliation"": ""Howard, Allen and Mckee"", ""email"": ""hudsonkathleen",,389,"Swanson, Martin and Garcia","[""section"", ""training"", ""entire""]",arXiv:2024.53707,,10.7036/sokD,Science,2021,Reactive demand-driven success,,,
"Prevent article price international language sister trial. Deal do attorney your set.
Strong offer s","[{""name"": ""Stephanie Ryan"", ""affiliation"": ""Thomas-Smith"", ""email"": ""thomas95@example.net""}, {""name""",,58,None,"[""pressure"", ""consumer"", ""capital"", ""social"", ""off""]",arXiv:2024.57510,,10.2618/iyDm,Cell,2024,Switchable local website,,,
Ok reveal meeting large recently term. Pressure base rule expert west enter.,"[{""name"": ""John Dorsey"", ""affiliation"": ""Hubbard-Murphy"", ""email"": ""gbrown@example.net""}, {""name"": """,,314,None,"[""choose"", ""knowledge"", ""no""]",arXiv:2023.95513,,10.4574/ulcy,Nature,2020,Streamlined demand-driven encryption,,,

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<sales_analytics>
<period>June 2022</period>
<total_revenue>7287772</total_revenue>
<units_sold>8566</units_sold>
<channels>
<name>retail</name>
<revenue>931216</revenue>
<growth>10.96</growth>
</channels>
<channels>
<name>wholesale</name>
<revenue>1224016</revenue>
<growth>31.92</growth>
</channels>
<top_products>
<sku>SKU-1474</sku>
<sales>19268</sales>
</top_products>
<top_products>
<sku>SKU-3289</sku>
<sales>31397</sales>
</top_products>
<top_products>
<sku>SKU-4950</sku>
<sales>322920</sales>
</top_products>
</sales_analytics>


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

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

[Assistant]
Approach:
1. Task: Create research paper in XML
2. Complexity: 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"?>
<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>


[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-66277640</post_id>
<platform>instagram</platform>
<user_id>7e83a029-16e2-49ad-a855-906c882abe46</user_id>
<username>reynoldstaylor</username>
<content>Thousand book animal myself wear beautiful. Room rock couple reality her.
Join town travel agency value improve way. Heavy late science mind develop consider ability.</content>
<timestamp>2026-01-07T13:51:26.676406</timestamp>
<hashtags>#case</hashtags>
<hashtags>#along</hashtags>
<hashtags>#only</hashtags>
<hashtags>#have</hashtags>
<engagement>
<likes>9942</likes>
<shares>119</shares>
<comments>368</comments>
</engagement>
</social_media_post>

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

Output:
{
  "post_id": "POST-66277640",
  "platform": "instagram",
  "user_id": "7e83a029-16e2-49ad-a855-906c882abe46",
  "username": "reynoldstaylor",
  "content": "Thousand book animal myself wear beautiful. Room rock couple reality her.\nJoin town travel agency value improve way. Heavy late science mind develop consider ability.",
  "timestamp": "2026-01-07T13:51:26.676406",
  "hashtags": [
    "#case",
    "#along",
    "#only",
    "#have"
  ],
  "engagement": {
    "likes": 9942,
    "shares": 119,
    "comments": 368
  }
}


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

[User]
Transform this CSV data into YAML format:
category,content,currency,date,helpful_votes,is_available,name,price,product_id,rating,review_id,reviews,specs_dimensions,specs_weight_kg,stock,title,user_id,verified_purchase
,Brother agent radio might own development. Too strong minute building why. Cell so amount imagine si,,2026-01-03,14,,,,PROD-380257,4,REV-1132090,,,,,Young race true property less government.,251dc214-da1e-4fb5-8ea5-d107ad43f82c,False
electronics,,USD,,,True,Grass-roots incremental utilization,959.71,PROD-324946,3.78,,14,60x96x69cm,42.4,575,,,
books,,USD,,,True,Synergistic interactive Local Area Network,326.43,PROD-224633,2.79,,246,32x33x47cm,42.9,442,,,
clothing,,USD,,,True,Progressive coherent adapter,387.29,PROD-912802,1.68,,31,23x13x93cm,47.74,150,,,

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

Output:
review_id: REV-1132090
product_id: PROD-380257
user_id: 251dc214-da1e-4fb5-8ea5-d107ad43f82c
rating: 4
title: Young race true property less government.
content: 'Brother agent radio might own development. Too strong minute building why.
  Cell so amount imagine simple.

  Court every deal change allow last practice. Western far thus.'
date: '2026-01-03'
verified_purchase: false
helpful_votes: 14


[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: medium - 5-8 fields, 2-3 levels
3. Format rules: header row, comma-separated, quoted fields with commas
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
category,content,currency,date,helpful_votes,is_available,name,price,product_id,rating,review_id,reviews,specs_dimensions,specs_weight_kg,stock,title,user_id,verified_purchase
,"Us board wonder trouble. Up as inside party growth seat. College late direction amount best team.
Fi",,2026-01-05,21,,,,PROD-380005,3,REV-1681251,,,,,Floor measure may hear dark at.,6ee75bbe-7aec-42b2-b8ce-db908c5fbc3a,True
clothing,,USD,,,True,Expanded responsive secured line,288.5,PROD-674851,1.22,,357,48x49x46cm,48.28,977,,,
electronics,,USD,,,True,Focused encompassing product,536.72,PROD-770304,4.69,,892,16x37x25cm,13.32,427,,,


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

[User] Output product listing as CSV.

[Assistant]
Approach:
1. Task: Create product listing in CSV
2. Complexity: 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,Diverse 6thgeneration solution,48.12,PROD-421885,3.7,717,87x57x81cm,20.82,460
clothing,USD,True,Ameliorated dynamic standardization,577.48,PROD-665509,4.43,787,23x12x72cm,19.54,956
clothing,USD,True,Innovative composite challenge,759.74,PROD-472050,3.05,346,91x27x82cm,34.58,445
electronics,USD,True,Right-sized needs-based hierarchy,716.79,PROD-105580,1.29,743,76x43x52cm,48.89,410


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

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

[Assistant]
Approach:
1. Task: Create transaction record 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:
subtotal: 205.31
payment_method: apple_pay
total: 1732.06