[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-3472120",
  "patient_mrn": "MRN-972429",
  "prescriber": "Matthew Bennett",
  "date": "2026-01-06",
  "medications": [
    {
      "name": "Atorvastatin",
      "dosage": "10mg",
      "frequency": "daily",
      "quantity": 60
    }
  ]
}


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

[User]
Reformat the data below from XML to YAML:
<?xml version="1.0" encoding="UTF-8"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Implemented leadingedge groupware API</title>
<version>1.0.0</version>
</info>
<paths>
</reveal>
<get>
<summary>Parent dark five.</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>
<//reveal>
</paths>
</api_specification>

[Assistant]
Approach:
1. Task: Convert api specification from XML 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:
openapi: 3.0.0
info:
  title: Implemented leadingedge groupware API
  version: 1.0.0
paths:
  /reveal:
    get:
      summary: Parent dark five.
      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] Create a YAML representation of experiment result.

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

Output:
experiment_id: EXP-574681
title: Effect of anyone on society
methodology:
  design: cohort
  sample_size: 560
  duration_days: 320
results:
- metric: efficacy
  baseline: 50.77
  endpoint: 70.83
  p_value: 0.3046
- metric: efficacy
  baseline: 96.52
  endpoint: 82.25
  p_value: 0.0326
- metric: safety
  baseline: 43.38
  endpoint: 72.88
  p_value: 0.2787
- metric: safety
  baseline: 17.71
  endpoint: 95.37
  p_value: 0.4542
conclusion: non-significant


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

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

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

Output:
assessment,chief_complaint,encounter_date,note_id,patient_age,patient_gender,patient_mrn,vitals_bp,vitals_hr,vitals_temp_f
"[{""problem"": ""hypertension"", ""icd10"": ""I52""}, {""problem"": ""diabetes"", ""icd10"": ""J76""}]",chest pain,2026-01-06,CN-7937835,66,M,MRN-749785,179/85,81,101.7
"[{""problem"": ""hypertension"", ""icd10"": ""I19""}]",headache,2026-01-05,CN-9948063,38,F,MRN-347636,164/72,78,98.4
"[{""problem"": ""diabetes"", ""icd10"": ""K48""}, {""problem"": ""diabetes"", ""icd10"": ""K48""}, {""problem"": ""hype",chest pain,2026-01-06,CN-1747586,42,F,MRN-982188,170/90,119,97.2
"[{""problem"": ""diabetes"", ""icd10"": ""J24""}, {""problem"": ""diabetes"", ""icd10"": ""K82""}]",fever,2026-01-06,CN-5100366,51,M,MRN-408390,106/98,80,101.0


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

[Assistant]
Approach:
1. Task: Convert error log 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:
{
  "error_id": "bcec7cd1-70fc-42ba-97dd-2c6e2159fc7d",
  "timestamp": "2026-01-07T13:51:27.288021",
  "level": "CRITICAL",
  "service": "reasonService",
  "message": "Recent security meet three Congress find seat.",
  "stack_trace": [
    "at current.py:236",
    "at your.py:146",
    "at without.py:194"
  ],
  "context": {
    "user_id": "fc408ea4-9df4-4d81-87da-9d63d4bc8744",
    "request_id": "d8c95012-b6bb-42d7-8cb4-e57e77353a5b"
  }
}


[System] You are an expert in 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: medium - 5-8 fields, 2-3 levels
3. Format rules: consistent indentation, colon-space syntax, hyphen lists
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
rx_id: RX-9458448
patient_mrn: MRN-362998
prescriber: Courtney Hansen
date: '2026-01-02'
medications:
- name: Lisinopril
  dosage: 10mg
  frequency: BID
  quantity: 30


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

[User] Output course syllabus as XML.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<course_syllabus>
<instructor>Rachel Moreno DVM</instructor>
<credits>4</credits>
<course_id>CRS-8305</course_id>
<title>Open-architected even-keeled support 101</title>
<term>Spring 2023</term>
</course_syllabus>


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

[User] Output lab result as CSV.

[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
2026-01-03,CBC,MRN-247204,LAB-3793814,"[{""test"": ""Hemoglobin"", ""value"": 188.2, ""unit"": ""g/dL"", ""flag"": ""low""}, {""test"": ""WBC"", ""value"": 197"
2026-01-01,Lipid,MRN-509855,LAB-9065382,"[{""test"": ""WBC"", ""value"": 64.9, ""unit"": ""mg/dL"", ""flag"": ""low""}, {""test"": ""Hemoglobin"", ""value"": 111"
2026-01-05,Lipid,MRN-726592,LAB-2590959,"[{""test"": ""Glucose"", ""value"": 90.5, ""unit"": ""g/dL"", ""flag"": ""high""}, {""test"": ""Glucose"", ""value"": 17"


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

[User] Create a TOML representation of financial report.

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

Output:
company = "Smith-Glover"
ticker = "JROI"
quarter = "Q3 2023"
revenue = 95238846
expenses = 30652579
net_income = 5856951
eps = 7.31

[metrics]
profit_margin = 9.94
roe = 10.91


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Upgradable 4thgeneration middleware API</title>
<version>1.0.0</version>
</info>
<paths>
</pass>
<get>
<summary>Story amount nor bed night get message.</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>
<//pass>
</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": "Upgradable 4thgeneration middleware API",
    "version": "1.0.0"
  },
  "paths": {
    "/pass": {
      "get": {
        "summary": "Story amount nor bed night get message.",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  }
}


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

[User] Create a CSV representation of clinical note.

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

Output:
assessment,chief_complaint,encounter_date,note_id,patient_age,patient_gender,patient_mrn,vitals_bp,vitals_hr,vitals_temp_f
"[{""problem"": ""hypertension"", ""icd10"": ""K44""}]",fever,2026-01-04,CN-2804449,73,F,MRN-394213,162/64,70,102.7
"[{""problem"": ""diabetes"", ""icd10"": ""I19""}, {""problem"": ""diabetes"", ""icd10"": ""J99""}, {""problem"": ""hype",chest pain,2026-01-06,CN-5991540,37,F,MRN-684447,149/75,67,100.9
"[{""problem"": ""hypertension"", ""icd10"": ""K43""}]",fever,2026-01-06,CN-3041214,41,M,MRN-644865,148/69,62,98.0
"[{""problem"": ""diabetes"", ""icd10"": ""J46""}]",fever,2026-01-02,CN-4797120,65,M,MRN-730283,173/73,66,98.9


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

[User] Generate product listing data in TOML format.

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

Output:
product_id = "PROD-791864"
name = "Decentralized heuristic migration"
category = "books"
price = 124.58
currency = "USD"
stock = 601
is_available = true
rating = 3.59
reviews = 538

[specs]
weight_kg = 9.83
dimensions = "30x16x25cm"


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

[User] Output customer review as TOML.

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

Output:
rating = 5
review_id = "REV-2205395"
content = "Respond order far story by area affect. Important also catch down choice office necessary political. Firm along bar.\nStuff create including star question traditional reflect. Share fast thought."


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

[User] Create a CSV representation of api specification.

[Assistant]
Approach:
1. Task: Create api specification in CSV
2. Complexity: 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,info_title,info_version,keywords,openapi,paper_id,paths_/traditional_get_parameters,paths_/traditional_get_responses_200_description,paths_/traditional_get_responses_400_description,paths_/traditional_get_summary,publication_doi,publication_venue,publication_year,title
,,,,Optional bottom-line complexity API,1.0.0,,3.0.0,,"[{""name"": ""param0"", ""in"": ""query"", ""type"": ""string""}, {""name"": ""param1"", ""in"": ""query"", ""type"": ""str",Success,Bad Request,Discussion then kind hair.,,,,
Two professor clearly and. Throughout financial during if truth involve change husband.,"[{""name"": ""Patrick Johnson"", ""affiliation"": ""Finley PLC"", ""email"": ""kmurray@example.org""}, {""name"": ",320,None,,,"[""learn"", ""leg"", ""two""]",,arXiv:2024.27870,,,,,10.7781/mzuv,Cell,2020,Centralized grid-enabled ability
Value treat size keep. Country marriage one though there moment. Local sure likely generation medica,"[{""name"": ""Julia Jackson"", ""affiliation"": ""Richard Group"", ""email"": ""fernandorichard@example.com""}, ",226,"Campbell, Garcia and Gonzalez",,,"[""name"", ""discuss"", ""fill"", ""quickly"", ""process""]",,arXiv:2024.34171,,,,,10.3922/iAWM,Cell,2022,Polarized non-volatile software


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

[User] Generate prescription data in CSV format.

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

Output:
date,medications,patient_mrn,prescriber,rx_id
2026-01-03,"[{""name"": ""Metformin"", ""dosage"": ""20mg"", ""frequency"": ""daily"", ""quantity"": 30}]",MRN-389849,Briana Dickerson,RX-7309915
2026-01-03,"[{""name"": ""Atorvastatin"", ""dosage"": ""5mg"", ""frequency"": ""BID"", ""quantity"": 60}, {""name"": ""Metformin""",MRN-730090,Corey Perkins,RX-9670781
2026-01-02,"[{""name"": ""Lisinopril"", ""dosage"": ""20mg"", ""frequency"": ""TID"", ""quantity"": 90}]",MRN-179545,Amanda Knox,RX-4182969
2026-01-02,"[{""name"": ""Lisinopril"", ""dosage"": ""10mg"", ""frequency"": ""daily"", ""quantity"": 30}]",MRN-664070,Adam Greene,RX-7404878
2026-01-06,"[{""name"": ""Metformin"", ""dosage"": ""5mg"", ""frequency"": ""TID"", ""quantity"": 60}, {""name"": ""Metformin"", """,MRN-237840,Dale Martin,RX-6274396


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

[User] Generate financial report data in YAML format.

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

Output:
company: 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 JSON format. Think step-by-step, then generate syntactically perfect JSON.

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

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

Output:
{
  "post_id": "POST-39452168",
  "platform": "twitter",
  "user_id": "ca270bc8-d443-4389-880a-6fc8dd3e9fa5",
  "username": "robertowens",
  "content": "With writer dinner any kitchen add well. Floor image speech charge rate manager vote. Worry involve benefit there nothing rock.\nFactor even apply how three box light.",
  "timestamp": "2026-01-07T13:51:25.425211",
  "hashtags": [
    "#training",
    "#Democrat",
    "#pattern",
    "#discover"
  ],
  "engagement": {
    "likes": 5319,
    "shares": 573,
    "comments": 283
  }
}


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

[User]
Reformat the data below from CSV to JSON:
abstract,authors,channels,citations,funding_source,keywords,paper_id,period,publication_doi,publication_venue,publication_year,title,top_products,total_revenue,units_sold
,,"[{""name"": ""online"", ""revenue"": 1867975, ""growth"": -2.95}, {""name"": ""retail"", ""revenue"": 1947932, ""gr",,,,,February 2024,,,,,"[{""sku"": ""SKU-5409"", ""sales"": 492017}, {""sku"": ""SKU-4816"", ""sales"": 486050}, {""sku"": ""SKU-9957"", ""sa",3108970,70292
Relate social everything. Among against statement between happen coach already. Bill meet lead oppor,"[{""name"": ""Andres Spence DVM"", ""affiliation"": ""Anderson-King"", ""email"": ""vdavis@example.net""}, {""nam",,386,Newman-Wise,"[""we"", ""born"", ""often""]",arXiv:2023.45556,,10.8714/UhpU,Cell,2023,Extended uniform workforce,,,
Behavior fight any require Congress age party. Later seat woman western seek.,"[{""name"": ""Susan Harris"", ""affiliation"": ""Lowery LLC"", ""email"": ""rcallahan@example.net""}, {""name"": """,,267,None,"[""action"", ""man"", ""save"", ""expert""]",arXiv:2023.46683,,10.8261/YEYc,Science,2020,Realigned even-keeled array,,,
Win today with water full thank. Radio choose help detail strategy two bit.,"[{""name"": ""William Clarke DDS"", ""affiliation"": ""Mitchell PLC"", ""email"": ""cindyhoffman@example.com""},",,319,"Duncan, Morales and Erickson","[""time"", ""painting"", ""body"", ""second""]",arXiv:2024.66945,,10.3675/GkFi,Science,2022,Fundamental 5thgeneration emulation,,,

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

Output:
{
  "period": "February 2024",
  "total_revenue": 3108970,
  "units_sold": 70292,
  "channels": [
    {
      "name": "online",
      "revenue": 1867975,
      "growth": -2.95
    },
    {
      "name": "retail",
      "revenue": 1947932,
      "growth": 22.54
    }
  ],
  "top_products": [
    {
      "sku": "SKU-5409",
      "sales": 492017
    },
    {
      "sku": "SKU-4816",
      "sales": 486050
    },
    {
      "sku": "SKU-9957",
      "sales": 44038
    }
  ]
}


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Sharable solution-oriented migration API</title>
<version>1.0.0</version>
</info>
<paths>
</anything>
<get>
<summary>Those all evidence respond she listen.</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>
<//anything>
</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": "Sharable solution-oriented migration API",
    "version": "1.0.0"
  },
  "paths": {
    "/anything": {
      "get": {
        "summary": "Those all evidence respond she listen.",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          },
          {
            "name": "param1",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  }
}


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

[User] Generate course syllabus data in CSV format.

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

Output:
code,course_id,credits,grading_final,grading_homework,grading_midterm,instructor,schedule,term,title
RVR286,CRS-4164,3,40,30,30,Shannon Miller,"[{""week"": 1, ""topic"": ""stuff""}, {""week"": 2, ""topic"": ""professional""}, {""week"": 3, ""topic"": ""hard""}, ",Fall 2023,Team-oriented incremental info-mediaries 101
SFZ181,CRS-2568,3,40,30,30,Susan Morgan,"[{""week"": 1, ""topic"": ""government""}, {""week"": 2, ""topic"": ""certain""}, {""week"": 3, ""topic"": ""consider",Fall 2024,Quality-focused user-facing migration 101
EUK344,CRS-5941,4,40,30,30,Connie Williams,"[{""week"": 1, ""topic"": ""some""}, {""week"": 2, ""topic"": ""site""}, {""week"": 3, ""topic"": ""list""}, {""week"": ",Spring 2023,Fundamental human-resource throughput 101
GSN319,CRS-4019,3,40,30,30,Melissa Neal,"[{""week"": 1, ""topic"": ""nice""}, {""week"": 2, ""topic"": ""however""}, {""week"": 3, ""topic"": ""field""}, {""wee",Spring 2021,Switchable clear-thinking solution 101


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

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

[Assistant]
Approach:
1. Task: Create social media post in TOML
2. Complexity: 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:
post_id = "POST-58883169"
user_id = "9fc1586a-703b-4459-a18b-2f5e0582ab64"
username = "alexandra57"


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<contract>
<effective_date>2026-01-02</effective_date>
<term_months>54</term_months>
<status>pending</status>
</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:
{
  "effective_date": "2026-01-02",
  "term_months": 54,
  "status": "pending"
}


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

[User] Create a CSV representation of contract.

[Assistant]
Approach:
1. Task: Create contract 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:
contract_id,effective_date,parties,status,term_months,value
CTR-784600,2026-01-06,"[{""name"": ""Snyder-Thornton"", ""role"": ""party_a""}, {""name"": ""Oliver Group"", ""role"": ""party_b""}]",active,16,53888
CTR-362699,2026-01-03,"[{""name"": ""Griffith-Francis"", ""role"": ""party_a""}, {""name"": ""Carter Group"", ""role"": ""party_b""}]",executed,36,172336
CTR-792296,2026-01-06,"[{""name"": ""Stewart-Smith"", ""role"": ""party_a""}, {""name"": ""Hicks-Smith"", ""role"": ""party_b""}]",active,20,187054
CTR-975508,2026-01-03,"[{""name"": ""Smith-Smith"", ""role"": ""party_a""}, {""name"": ""Small, Holden and Choi"", ""role"": ""party_b""}]",executed,49,95085
CTR-109779,2026-01-04,"[{""name"": ""Barnes, Ochoa and Reyes"", ""role"": ""party_a""}, {""name"": ""Garrett and Sons"", ""role"": ""party",active,58,398292


[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"?>
<financial_report>
<company>Williams Ltd</company>
<ticker>IHFM</ticker>
<quarter>Q3 2022</quarter>
<revenue>93368790</revenue>
<expenses>48847964</expenses>
<net_income>12028281</net_income>
<eps>9.18</eps>
<metrics>
<profit_margin>7.56</profit_margin>
<roe>13.89</roe>
</metrics>
</financial_report>

[Assistant]
Approach:
1. Task: Convert financial report 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:
{
  "company": "Williams Ltd",
  "ticker": "IHFM",
  "quarter": "Q3 2022",
  "revenue": 93368790,
  "expenses": 48847964,
  "net_income": 12028281,
  "eps": 9.18,
  "metrics": {
    "profit_margin": 7.56,
    "roe": 13.89
  }
}


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

[User] Output course syllabus as YAML.

[Assistant]
Approach:
1. Task: Create course syllabus in YAML
2. Complexity: 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:
course_id: CRS-5570
code: ZMD258
title: Mandatory leadingedge superstructure 101
instructor: Gregory Dunn
credits: 3
term: Spring 2021
schedule:
- week: 1
  topic: guess
- week: 2
  topic: forget
- week: 3
  topic: technology
- week: 4
  topic: nothing
- week: 5
  topic: sea
- week: 6
  topic: other
- week: 7
  topic: new
- week: 8
  topic: report
- week: 9
  topic: guy
- week: 10
  topic: can
- week: 11
  topic: inside
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]
Transform this CSV data into XML 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
,Today offer none role certain reach. Second Mr official enjoy movement turn city. Name employee earl,,2026-01-01,43,,,,PROD-108034,4,REV-9546377,,,,,Appear speak sure list.,d01ac4e1-ccd9-4273-9fe0-9ca6afc6af77,True
clothing,,USD,,,True,Automated client-server portal,352.79,PROD-380389,2.4,,158,23x95x25cm,28.8,636,,,
electronics,,USD,,,True,Digitized didactic open architecture,898.93,PROD-621897,3.27,,511,30x90x78cm,3.02,812,,,
books,,USD,,,True,Proactive incremental database,907.47,PROD-569756,2.23,,248,88x84x99cm,33.43,807,,,
clothing,,USD,,,True,Progressive disintermediate portal,97.71,PROD-262804,4.91,,943,40x79x15cm,47.43,400,,,

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<review_id>REV-9546377</review_id>
<product_id>PROD-108034</product_id>
<user_id>d01ac4e1-ccd9-4273-9fe0-9ca6afc6af77</user_id>
<rating>4</rating>
<title>Appear speak sure list.</title>
<content>Today offer none role certain reach. Second Mr official enjoy movement turn city. Name employee early much first sit.</content>
<date>2026-01-01</date>
<verified_purchase>True</verified_purchase>
<helpful_votes>43</helpful_votes>
</customer_review>


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

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

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

Output:
abstract,authors,citations,context_request_id,context_user_id,error_id,funding_source,keywords,level,message,paper_id,publication_doi,publication_venue,publication_year,service,stack_trace,timestamp,title
,,,0f3326d0-3afd-48c1-9c4d-32cc8b0c5920,082cc3eb-3997-4d99-990c-f696ca4ee534,424897c8-d97d-4bfb-9c1a-7b6e63fd6096,,,ERROR,How these anyone stop indeed.,,,,,heartService,"[""at manage.py:289"", ""at thing.py:107"", ""at guy.py:172"", ""at seat.py:479""]",2026-01-07T13:51:27.529237,
Alone animal loss base our. It tax seat against talk. Manager trial always education hospital.,"[{""name"": ""Brittany Myers"", ""affiliation"": ""Alexander-Terry"", ""email"": ""vargasneil@example.com""}, {""",58,,,,None,"[""test"", ""improve"", ""mention""]",,,arXiv:2021.53040,10.4561/YdvP,Nature,2023,,,,Synchronized uniform superstructure
Lay and go young successful themselves. Area plant carry hard team. Investment clearly prove red wil,"[{""name"": ""James Moss"", ""affiliation"": ""Hill LLC"", ""email"": ""zpratt@example.com""}, {""name"": ""Laura S",89,,,,None,"[""physical"", ""bad"", ""medical""]",,,arXiv:2020.68814,10.2583/uXtA,Science,2024,,,,Operative high-level installation


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

[User] Output social media post as YAML.

[Assistant]
Approach:
1. Task: Create social media post 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:
post_id: POST-59844758
timestamp: '2026-01-07T13:51:27.358144'
hashtags:
- '#population'
- '#during'
- '#executive'
- '#house'


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

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

Output:
{
  "experiment_id": "EXP-725280",
  "title": "Effect of city on expert",
  "methodology": {
    "design": "observational",
    "sample_size": 907,
    "duration_days": 166
  },
  "results": [
    {
      "metric": "safety",
      "baseline": 43.19,
      "endpoint": 64.81,
      "p_value": 0.4813
    },
    {
      "metric": "safety",
      "baseline": 71.73,
      "endpoint": 68.14,
      "p_value": 0.0851
    },
    {
      "metric": "safety",
      "baseline": 77.12,
      "endpoint": 63.9,
      "p_value": 0.1154
    }
  ],
  "conclusion": "significant"
}


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

[User] Produce a CSV document for a student assessment.

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

Output:
abstract,authors,citations,date,funding_source,grade,keywords,paper_id,publication_doi,publication_venue,publication_year,scores,title
,,,2026-01-01,,C,,,,,,"[{""question"": 1, ""points_earned"": 8, ""points_possible"": 10}, {""question"": 2, ""points_earned"": 4, ""po",
Plan pay order become. Brother ability admit wait.,"[{""name"": ""Brandi Day"", ""affiliation"": ""Sanders Inc"", ""email"": ""bglass@example.org""}, {""name"": ""Anth",162,,"Parker, Mclean and Guerrero",,"[""full"", ""perform"", ""by""]",arXiv:2020.26273,10.8485/LHjX,Nature,2024,,Enterprise-wide grid-enabled frame
Imagine magazine name. Song against rock need pretty chair less.,"[{""name"": ""Michael Figueroa"", ""affiliation"": ""Johnson-Robinson"", ""email"": ""melissaelliott@example.co",188,,Smith and Sons,,"[""particularly"", ""both"", ""sport"", ""part"", ""land""]",arXiv:2022.48709,10.9934/emLb,Nature,2022,,Face-to-face didactic moderator
"Hour partner option hit war nearly employee.
Training data issue hard both board minute present. Mee","[{""name"": ""Jacqueline Weaver"", ""affiliation"": ""Zhang, Morris and Burns"", ""email"": ""wellsronald@examp",310,,None,,"[""rest"", ""prepare"", ""alone"", ""art""]",arXiv:2020.76549,10.2680/rmAS,Nature,2021,,Proactive dynamic function
Red huge fact send peace partner before. Walk herself particular sell political get medical feel. Re,"[{""name"": ""Lisa Powell"", ""affiliation"": ""Williamson Inc"", ""email"": ""kaufmanamber@example.com""}, {""na",279,,None,,"[""house"", ""production"", ""author"", ""they""]",arXiv:2024.14291,10.2421/TidE,Cell,2024,,Devolved multi-tasking contingency


[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:
{
  "vitals": {
    "bp": "131/104",
    "hr": 84,
    "temp_f": 99.9
  },
  "note_id": "CN-3823498",
  "encounter_date": "2026-01-06"
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<clinical_note>
<vitals>
<bp>131/104</bp>

84

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


[System] You are an expert in 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-449984</contract_id>
<parties>
<name>Garcia-Henson</name>
<role>party_a</role>
</parties>
<parties>
<name>Moore LLC</name>
<role>party_b</role>
</parties>
<effective_date>2026-01-04</effective_date>
<term_months>49</term_months>
<value>694475</value>
<status>pending</status>
</contract>


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

[User] Create a CSV representation of financial report.

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

Output:
company,eps,expenses,metrics_profit_margin,metrics_roe,net_income,quarter,revenue,ticker
Ramos-Wallace,,77578182,,,,,65816825,IQTA
"Tran, Harvey and Pearson",8.74,16500516,20.12,18.5,18056562,Q2 2020,69167252,IEQC
"Morris, Mckenzie and Evans",2.05,53009964,21.04,15.17,14598376,Q2 2023,43265955,MJDA
"Schneider, Benson and Gonzalez",7.54,29832540,25.45,12.03,3701601,Q1 2021,34460683,JILZ
Henson-Cooke,4.41,20152341,7.21,23.01,9658169,Q1 2021,54756904,SNYQ


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

[User] Produce a TOML document for a student assessment.

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

Output:
assessment_id = "ASMT-485879"
student_id = "STU-284737"
course_id = "CRS-1053"
type = "exam"
date = "2026-01-03"
total_score = 89
percentage = 64.04
grade = "A"
[[scores]]
question = 1
points_earned = 0
points_possible = 10

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

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

[[scores]]
question = 4
points_earned = 9
points_possible = 10

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

[[scores]]
question = 6
points_earned = 9
points_possible = 10

[[scores]]
question = 7
points_earned = 2
points_possible = 10


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

[User] Create a XML representation of clinical note.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<clinical_note>
<note_id>CN-8348908</note_id>
<patient>
<mrn>MRN-109351</mrn>
<age>84</age>
<gender>F</gender>
</patient>
<encounter_date>2026-01-06</encounter_date>
<chief_complaint>fever</chief_complaint>
<vitals>
<bp>157/81</bp>

101

<temp_f>97.1</temp_f>
</vitals>
<assessment>
<problem>diabetes</problem>
<icd10>J60</icd10>
</assessment>
<assessment>
<problem>diabetes</problem>
<icd10>K69</icd10>
</assessment>
<assessment>
<problem>hypertension</problem>
<icd10>J80</icd10>
</assessment>
</clinical_note>


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

[User]
Transform this JSON data into XML format:
{
  "assessment_id": "ASMT-893180",
  "student_id": "STU-881633",
  "course_id": "CRS-6394",
  "type": "quiz",
  "date": "2026-01-03",
  "scores": [
    {
      "question": 1,
      "points_earned": 10,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 10,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 6,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 6,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 0,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 10,
      "points_possible": 10
    },
    {
      "question": 9,
      "points_earned": 5,
      "points_possible": 10
    }
  ],
  "total_score": 98,
  "percentage": 73.06,
  "grade": "A"
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<student_assessment>
<assessment_id>ASMT-893180</assessment_id>
<student_id>STU-881633</student_id>
<course_id>CRS-6394</course_id>
<type>quiz</type>
<date>2026-01-03</date>
<scores>
<question>1</question>
<points_earned>10</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>8</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>3</question>
<points_earned>10</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>4</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>6</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>0</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>10</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>9</question>
<points_earned>5</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>98</total_score>
<percentage>73.06</percentage>
<grade>A</grade>
</student_assessment>


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

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

[Assistant]
Approach:
1. Task: Create sales analytics 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:
period = "March 2022"
total_revenue = 6503980
units_sold = 7670
[[channels]]
name = "retail"
revenue = 3279241
growth = 22.76

[[channels]]
name = "wholesale"
revenue = 1469640
growth = 16.07

[[top_products]]
sku = "SKU-8081"
sales = 71747

[[top_products]]
sku = "SKU-8211"
sales = 475825

[[top_products]]
sku = "SKU-4565"
sales = 485553


[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-7317178",
  "headline": "Sharable 5thgeneration framework",
  "author": "Judy Garner",
  "published": "2026-01-07T07:35:28.380949",
  "section": "Politics",
  "content": "Cover whole myself late last month authority. Make away choose difficult.\nShoulder so support like let increase improve movie. Gun career hair necessary improve operation detail.",
  "tags": [
    "cover",
    "people",
    "available",
    "above",
    "service"
  ],
  "views": 84087,
  "shares": 2480
}

[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-7317178</article_id>
<headline>Sharable 5thgeneration framework</headline>
<author>Judy Garner</author>
<published>2026-01-07T07:35:28.380949</published>

Politics

<content>Cover whole myself late last month authority. Make away choose difficult.
Shoulder so support like let increase improve movie. Gun career hair necessary improve operation detail.</content>
<tags>cover</tags>
<tags>people</tags>
<tags>available</tags>
<tags>above</tags>
<tags>service</tags>
<views>84087</views>
<shares>2480</shares>
</news_article>


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

[Assistant]
Approach:
1. Task: Convert error log 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:
{
  "error_id": "91d16731-5e7b-4a47-8285-7a54d79d3b76",
  "timestamp": "2026-01-07T13:51:25.635487",
  "level": "WARNING",
  "service": "AmericanService",
  "message": "Drug sell certainly major total.",
  "stack_trace": [
    "at although.py:151",
    "at mission.py:443"
  ],
  "context": {
    "user_id": "11d85442-7276-4e30-9249-06df8089bd39",
    "request_id": "f3cc0b9c-f4db-4c9d-bea8-f49774b1a7e6"
  }
}


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

[User]
Reformat the data below from JSON to XML:
{
  "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 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-3305496</rx_id>
<patient_mrn>MRN-551064</patient_mrn>
<prescriber>Eric Jackson</prescriber>
<date>2026-01-03</date>
<medications>
<name>Atorvastatin</name>
<dosage>20mg</dosage>
<frequency>daily</frequency>
<quantity>90</quantity>
</medications>
</prescription>


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

[User]
Transform this TOML data into XML format:
product_id = "PROD-325945"
name = "Universal bottom-line system engine"
category = "electronics"
price = 225.75
currency = "USD"
stock = 955
is_available = true
rating = 3.31
reviews = 802

[specs]
weight_kg = 22.25
dimensions = "77x29x32cm"

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<product_listing>
<product_id>PROD-325945</product_id>
<name>Universal bottom-line system engine</name>
<category>electronics</category>
<price>225.75</price>
<currency>USD</currency>
<stock>955</stock>
<is_available>True</is_available>
<rating>3.31</rating>
<reviews>802</reviews>
<specs>
<weight_kg>22.25</weight_kg>
<dimensions>77x29x32cm</dimensions>
</specs>
</product_listing>


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

[User] Create a CSV representation of financial report.

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

Output:
company,eps,expenses,metrics_profit_margin,metrics_roe,net_income,quarter,revenue,ticker
"Rodriguez, Sanchez and French",9.27,79425858,21.79,22.32,10739155,Q3 2022,30596216,TOPI
"Johnson, Carroll and Winters",7.15,67877427,20.04,10.53,2730470,Q2 2024,70738897,HHLB
Lopez Ltd,4.75,9610850,21.06,13.52,9464205,Q4 2020,21402752,AVQR


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

[User] Generate api specification data in YAML format.

[Assistant]
Approach:
1. Task: Create api specification in YAML
2. Complexity: 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:
openapi: 3.0.0
info:
  title: Face-to-face zero administration application API
  version: 1.0.0
paths:
  /peace:
    get:
      summary: Feel piece low way effort action bag.
      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 XML format. Think step-by-step, then generate syntactically perfect XML.

[User]
Transform this JSON data into XML format:
{
  "product_id": "PROD-852387",
  "name": "Profound logistical array",
  "category": "electronics",
  "price": 299.46,
  "currency": "USD",
  "stock": 505,
  "is_available": true,
  "rating": 2.95,
  "reviews": 519,
  "specs": {
    "weight_kg": 6.22,
    "dimensions": "16x47x36cm"
  }
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<product_listing>
<product_id>PROD-852387</product_id>
<name>Profound logistical array</name>
<category>electronics</category>
<price>299.46</price>
<currency>USD</currency>
<stock>505</stock>
<is_available>True</is_available>
<rating>2.95</rating>
<reviews>519</reviews>
<specs>
<weight_kg>6.22</weight_kg>
<dimensions>16x47x36cm</dimensions>
</specs>
</product_listing>


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

[User] Output contract as XML.

[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-464030</contract_id>
<parties>
<name>Morales, Williams and Williams</name>
<role>party_a</role>
</parties>
<parties>
<name>Ward-Miller</name>
<role>party_b</role>
</parties>
<effective_date>2026-01-06</effective_date>
<term_months>35</term_months>
<value>994957</value>
<status>active</status>
</contract>


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

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

Output:
conclusion,experiment_id,methodology_design,methodology_duration_days,methodology_sample_size,results,title
non-significant,EXP-168652,cohort,186,797,"[{""metric"": ""safety"", ""baseline"": 24.16, ""endpoint"": 44.82, ""p_value"": 0.0559}, {""metric"": ""efficacy",Effect of green on from
significant,EXP-215495,RCT,265,796,"[{""metric"": ""safety"", ""baseline"": 19.54, ""endpoint"": 85.98, ""p_value"": 0.1172}, {""metric"": ""safety"",",Effect of amount on address
non-significant,EXP-166400,observational,105,394,"[{""metric"": ""safety"", ""baseline"": 14.58, ""endpoint"": 96.74, ""p_value"": 0.2699}, {""metric"": ""efficacy",Effect of grow on hundred
non-significant,EXP-252360,observational,303,939,"[{""metric"": ""efficacy"", ""baseline"": 37.17, ""endpoint"": 21.23, ""p_value"": 0.023}, {""metric"": ""safety""",Effect of possible on suggest


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

[User] Output prescription as CSV.

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

Output:
date,medications,patient_mrn,prescriber,rx_id
2026-01-06,"[{""name"": ""Atorvastatin"", ""dosage"": ""10mg"", ""frequency"": ""daily"", ""quantity"": 90}, {""name"": ""Lisinop",MRN-259808,Joseph Griffin,RX-8539167
2026-01-05,"[{""name"": ""Atorvastatin"", ""dosage"": ""20mg"", ""frequency"": ""daily"", ""quantity"": 60}]",MRN-776198,Herbert Herman,RX-2228905
2026-01-06,"[{""name"": ""Lisinopril"", ""dosage"": ""20mg"", ""frequency"": ""daily"", ""quantity"": 90}, {""name"": ""Metformin",MRN-299069,Andrea Khan,RX-2333776


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

[User] Create a XML representation of financial report.

[Assistant]
Approach:
1. Task: Create financial report in XML
2. Complexity: 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"?>
<financial_report>
<net_income>16280737</net_income>
<revenue>93235840</revenue>
<metrics>
<profit_margin>9.67</profit_margin>
<roe>5.79</roe>
</metrics>
<expenses>6835352</expenses>
</financial_report>


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

[User] Generate course syllabus data in TOML format.

[Assistant]
Approach:
1. Task: Create course syllabus 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:
course_id = "CRS-7514"
code = "NOO384"
title = "Fundamental encompassing database 101"
instructor = "Lori Martinez"
credits = 4
term = "Fall 2024"
[[schedule]]
week = 1
topic = "bar"

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

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

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

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

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

[[schedule]]
week = 7
topic = "nothing"

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

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

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

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

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


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

[User] Generate product listing data in YAML format.

[Assistant]
Approach:
1. Task: Create product listing 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:
product_id: PROD-852387
name: Profound logistical array
category: electronics
price: 299.46
currency: USD
stock: 505
is_available: true
rating: 2.95
reviews: 519
specs:
  weight_kg: 6.22
  dimensions: 16x47x36cm


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

[User] Create a YAML representation of prescription.

[Assistant]
Approach:
1. Task: Create prescription in YAML
2. Complexity: 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:
prescriber: Melinda Black
date: '2026-01-04'
rx_id: RX-8618237


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

[User] Output error log as JSON.

[Assistant]
Approach:
1. Task: Create error log 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:
{
  "error_id": "234c0781-6e40-4e46-8b0d-ad1b39309eb0",
  "timestamp": "2026-01-07T13:51:25.659911",
  "level": "WARNING",
  "service": "beyondService",
  "message": "Section material entire top community.",
  "stack_trace": [
    "at reason.py:320",
    "at always.py:365",
    "at red.py:27"
  ],
  "context": {
    "user_id": "6765bd92-f82e-426f-a383-fa0a088a0752",
    "request_id": "4ccfb0b5-8185-4d26-902a-0379b3534400"
  }
}


[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: complex - 8-10 fields, 3-4 levels
3. Format rules: header row, comma-separated, quoted fields with commas
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
category,content,currency,date,helpful_votes,is_available,name,price,product_id,rating,review_id,reviews,specs_dimensions,specs_weight_kg,stock,title,user_id,verified_purchase
,Official police serve past already. Number down similar senior head amount. Focus reality really hol,,2026-01-03,99,,,,PROD-853148,3,REV-9723622,,,,,Risk tell team series house.,44919496-69de-498e-922c-5ea4230c00fa,False
electronics,,USD,,,True,Ergonomic explicit portal,500.69,PROD-863871,4.89,,345,29x24x72cm,0.91,341,,,
electronics,,USD,,,True,Future-proofed zero-defect database,342.1,PROD-397434,2.25,,232,82x47x38cm,19.21,260,,,
clothing,,USD,,,True,Object-based solution-oriented help-desk,859.24,PROD-206909,1.36,,812,49x31x72cm,0.46,258,,,


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

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

[Assistant]
Approach:
1. Task: Create news article in TOML
2. Complexity: 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:
section = "Politics"
tags = [ "machine", "fund", "station", "our",]
published = "2026-01-05T17:58:55.100855"
views = 86295


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

[User]
Reformat the data below from XML to TOML:
<?xml version="1.0" encoding="UTF-8"?>
<social_media_post>
<post_id>POST-32645861</post_id>
<platform>facebook</platform>
<user_id>b5521d05-1410-43ee-b828-2c240f95461c</user_id>
<username>yanderson</username>
<content>Example suggest around pattern small everybody. Rate watch blue walk test camera. Partner decide leave really.</content>
<timestamp>2026-01-07T13:51:27.526455</timestamp>
<hashtags>#door</hashtags>
<hashtags>#relate</hashtags>
<engagement>
<likes>5828</likes>
<shares>957</shares>
<comments>117</comments>
</engagement>
</social_media_post>

[Assistant]
Approach:
1. Task: Convert social media post from XML 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:
post_id = "POST-32645861"
platform = "facebook"
user_id = "b5521d05-1410-43ee-b828-2c240f95461c"
username = "yanderson"
content = "Example suggest around pattern small everybody. Rate watch blue walk test camera. Partner decide leave really."
timestamp = "2026-01-07T13:51:27.526455"
hashtags = [ "#door", "#relate",]

[engagement]
likes = 5828
shares = 957
comments = 117


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

[User] Produce a TOML document for a 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:
eps = 6.0
company = "Richardson-Gonzalez"
quarter = "Q3 2020"
net_income = 13953656


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

[User] Create a TOML representation of clinical note.

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

Output:
note_id = "CN-7237025"
encounter_date = "2026-01-06"
chief_complaint = "fever"
[[assessment]]
problem = "diabetes"
icd10 = "J46"

[patient]
mrn = "MRN-276187"
age = 53
gender = "F"

[vitals]
bp = "95/82"
hr = 103
temp_f = 102.9


[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
,"Near season take foot decade hold some meet.
Pretty season exist old turn consumer particularly star",,2026-01-02,62,,,,PROD-688379,3,REV-5832770,,,,,Investment great beat fear step Democrat treat.,d5e035fb-55b8-4fae-85aa-504fb2b837bd,False
clothing,,USD,,,True,Grass-roots empowering hub,720.42,PROD-752099,3.56,,247,40x38x18cm,25.66,7,,,
clothing,,USD,,,True,Automated web-enabled capacity,473.59,PROD-186243,2.7,,417,36x14x89cm,3.65,664,,,
books,,USD,,,True,User-centric 4thgeneration database,313.73,PROD-339117,2.66,,224,82x60x65cm,0.8,446,,,


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

[User] Generate research paper data in JSON format.

[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:2021.48279",
  "title": "Operative systemic definition",
  "authors": [
    {
      "name": "Patricia Owens",
      "affiliation": "Pearson, Quinn and Owens",
      "email": "christopher41@example.net"
    },
    {
      "name": "Wayne Boyd",
      "affiliation": "Delacruz-Weaver",
      "email": "powens@example.net"
    },
    {
      "name": "Christopher Castillo",
      "affiliation": "Lawrence-Caldwell",
      "email": "amandacarey@example.com"
    }
  ],
  "abstract": "Tv wear teacher under doctor. Eight mention month argue amount how voice.",
  "keywords": [
    "month",
    "southern",
    "administration"
  ],
  "publication": {
    "venue": "Cell",
    "year": 2021,
    "doi": "10.1648/XIrv"
  },
  "citations": 167,
  "funding_source": null
}


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

[User] Output social media post as YAML.

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

Output:
post_id: POST-58559815
platform: instagram
user_id: 0fae79ab-dabb-47f5-823b-f22743181c7c
username: ortizkristina
content: 'Speech can sea play. Season near story animal remain.

  Off present vote wall. Society know family build. Certain thing live rise.'
timestamp: '2026-01-07T13:51:26.463560'
hashtags:
- '#once'
- '#it'
- '#rich'
- '#keep'
engagement:
  likes: 248
  shares: 32
  comments: 161


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

[User] Create a TOML representation of error log.

[Assistant]
Approach:
1. Task: Create error log in TOML
2. Complexity: 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:
message = "Computer so cold feeling huge reason reach."
error_id = "ddf52566-8f32-4c90-8477-d7f45504f7db"
stack_trace = [ "at their.py:436", "at activity.py:81", "at test.py:46",]
timestamp = "2026-01-07T13:51:26.578554"

[context]
user_id = "97fc14e5-867d-4c23-9d2e-00b538b50acf"
request_id = "ab94fb1e-d258-4626-9686-12f860249c41"


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

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

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

Output:
abstract,authors,channels,citations,funding_source,keywords,paper_id,period,publication_doi,publication_venue,publication_year,title,top_products,total_revenue,units_sold
,,"[{""name"": ""retail"", ""revenue"": 1926384, ""growth"": 34.29}, {""name"": ""online"", ""revenue"": 1062444, ""gr",,,,,June 2020,,,,,"[{""sku"": ""SKU-3818"", ""sales"": 48786}, {""sku"": ""SKU-7605"", ""sales"": 408187}, {""sku"": ""SKU-6728"", ""sal",2603625,51574
"Human sound likely individual. Know within subject protect. Pattern talk by.
Agent attack alone budg","[{""name"": ""Chad Garrison"", ""affiliation"": ""Coleman, Hamilton and Rivera"", ""email"": ""salazarsheryl@ex",,161,None,"[""building"", ""now"", ""deep"", ""popular""]",arXiv:2021.58212,,10.3793/LXDF,Nature,2024,Optional fault-tolerant task-force,,,
Ahead PM really president surface. Than reach performance direction. Research skin onto painting.,"[{""name"": ""Angela Martin"", ""affiliation"": ""Robinson LLC"", ""email"": ""anorton@example.net""}, {""name"": ",,288,Brown-Coleman,"[""thousand"", ""career"", ""between"", ""significant""]",arXiv:2020.84927,,10.1961/HYhq,Cell,2023,Multi-tiered foreground support,,,
"Lead think year book. Subject space need. Yes grow nearly consider style.
Party than from informatio","[{""name"": ""Jeffrey Howard"", ""affiliation"": ""Huff Ltd"", ""email"": ""james25@example.org""}, {""name"": ""An",,273,"Phillips, Flores and Sanchez","[""today"", ""entire"", ""address""]",arXiv:2020.82362,,10.6264/VoDO,Science,2024,Reactive scalable open architecture,,,


[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
Card these member kid western growth. Staff draw say early town general. Large break interesting ten,294,464,699,"[""#deep"", ""#yes"", ""#long"", ""#including""]",instagram,POST-54622203,2026-01-07T13:51:25.504049,1456e108-0a50-4482-8f1a-b1cb2398a121,fullersteven
"Available same impact modern research high bring where. Crime art walk meet early kid detail.
Boy ta",406,1745,944,"[""#tonight"", ""#day""]",twitter,POST-63151603,2026-01-07T13:51:25.505558,8eab6869-cfb5-44f4-b22a-e766ef53cd85,lrobbins
"Camera either green phone type natural color. Wide positive report view list.
Way important study ge",412,5027,586,"[""#stop"", ""#impact"", ""#hot""]",twitter,POST-53467523,2026-01-07T13:51:25.505853,310c991c-0db8-40d4-9ac3-f76edf194e51,michael87
Relationship late wide rest. Turn how by hold detail scientist war. Shake yourself forget floor try ,252,988,945,"[""#support"", ""#accept"", ""#policy""]",facebook,POST-83879779,2026-01-07T13:51:25.506108,c0658898-82a5-4ca8-829d-035bd723f496,donald76
Many friend feeling worker hot listen I crime. Including help fine born tonight certainly suddenly. ,97,8792,910,"[""#side"", ""#billion"", ""#product"", ""#will""]",instagram,POST-39983849,2026-01-07T13:51:25.506459,72bd7eaa-0370-4c56-afb1-93f31cd2fa41,eddiedavis


[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"?>
<contract>
<effective_date>2026-01-03</effective_date>
<value>837359</value>
<term_months>24</term_months>
<status>executed</status>
</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:
{
  "effective_date": "2026-01-03",
  "value": 837359,
  "term_months": 24,
  "status": "executed"
}


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<transaction_record>
<txn_id>TXN-13058367</txn_id>
<customer_id>852e4544-1bd4-44f1-abf0-2ff01b4a4792</customer_id>
<timestamp>2026-01-07T13:51:26.835091</timestamp>
<items>
<sku>SKU-47822</sku>
<qty>3</qty>
<price>237.72</price>
</items>
<items>
<sku>SKU-38430</sku>
<qty>4</qty>
<price>285.9</price>
</items>
<items>
<sku>SKU-22327</sku>
<qty>1</qty>
<price>141.71</price>
</items>
<subtotal>408.33</subtotal>
<tax>11.32</tax>
<total>1142.29</total>
<payment_method>paypal</payment_method>
</transaction_record>

[Assistant]
Approach:
1. Task: Convert transaction record 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:
{
  "txn_id": "TXN-13058367",
  "customer_id": "852e4544-1bd4-44f1-abf0-2ff01b4a4792",
  "timestamp": "2026-01-07T13:51:26.835091",
  "items": [
    {
      "sku": "SKU-47822",
      "qty": 3,
      "price": 237.72
    },
    {
      "sku": "SKU-38430",
      "qty": 4,
      "price": 285.9
    },
    {
      "sku": "SKU-22327",
      "qty": 1,
      "price": 141.71
    }
  ],
  "subtotal": 408.33,
  "tax": 11.32,
  "total": 1142.29,
  "payment_method": "paypal"
}


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

[User]
Reformat the data below from JSON to YAML:
{
  "product_id": "PROD-141484",
  "name": "Managed bandwidth-monitored focus group",
  "category": "books",
  "price": 751.35,
  "currency": "USD",
  "stock": 108,
  "is_available": true,
  "rating": 2.94,
  "reviews": 250,
  "specs": {
    "weight_kg": 6.41,
    "dimensions": "15x82x35cm"
  }
}

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

Output:
product_id: PROD-141484
name: Managed bandwidth-monitored focus group
category: books
price: 751.35
currency: USD
stock: 108
is_available: true
rating: 2.94
reviews: 250
specs:
  weight_kg: 6.41
  dimensions: 15x82x35cm


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<clinical_note>
<note_id>CN-2341842</note_id>
<patient>
<mrn>MRN-739833</mrn>
<age>85</age>
<gender>F</gender>
</patient>
<encounter_date>2026-01-01</encounter_date>
<chief_complaint>fever</chief_complaint>
<vitals>
<bp>174/60</bp>

60

<temp_f>98.7</temp_f>
</vitals>
<assessment>
<problem>diabetes</problem>
<icd10>I65</icd10>
</assessment>
<assessment>
<problem>diabetes</problem>
<icd10>J29</icd10>
</assessment>
</clinical_note>

[Assistant]
Approach:
1. Task: Convert clinical note 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:
{
  "note_id": "CN-2341842",
  "patient": {
    "mrn": "MRN-739833",
    "age": 85,
    "gender": "F"
  },
  "encounter_date": "2026-01-01",
  "chief_complaint": "fever",
  "vitals": {
    "bp": "174/60",
    "hr": 60,
    "temp_f": 98.7
  },
  "assessment": [
    {
      "problem": "diabetes",
      "icd10": "I65"
    },
    {
      "problem": "diabetes",
      "icd10": "J29"
    }
  ]
}


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

[User]
Reformat the data below from JSON to YAML:
{
  "contract_id": "CTR-457828",
  "effective_date": "2026-01-01",
  "term_months": 32
}

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

Output:
contract_id: CTR-457828
effective_date: '2026-01-01'
term_months: 32


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

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

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

Output:
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.

  Eight 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] Create a YAML representation of contract.

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

Output:
contract_id: CTR-457828
effective_date: '2026-01-01'
term_months: 32


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

[User] Output prescription as CSV.

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

Output:
date,medications,patient_mrn,prescriber,rx_id
2026-01-02,"[{""name"": ""Metformin"", ""dosage"": ""5mg"", ""frequency"": ""daily"", ""quantity"": 30}, {""name"": ""Atorvastati",MRN-741538,John Cook,RX-6885629
2026-01-04,"[{""name"": ""Atorvastatin"", ""dosage"": ""5mg"", ""frequency"": ""daily"", ""quantity"": 30}, {""name"": ""Atorvast",MRN-171495,Lauren French,RX-9982935
2026-01-01,"[{""name"": ""Metformin"", ""dosage"": ""10mg"", ""frequency"": ""daily"", ""quantity"": 30}, {""name"": ""Metformin""",MRN-848360,Patrick Gutierrez,RX-2710259
2026-01-01,"[{""name"": ""Lisinopril"", ""dosage"": ""5mg"", ""frequency"": ""BID"", ""quantity"": 30}, {""name"": ""Metformin"", ",MRN-320817,Daniel Hunt,RX-3410176


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

[User]
Reformat the data below from JSON to XML:
{
  "verified_purchase": true,
  "date": "2026-01-05",
  "rating": 1
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<verified_purchase>True</verified_purchase>
<date>2026-01-05</date>
<rating>1</rating>
</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
2026-01-02,CMP,MRN-977601,LAB-1056021,"[{""test"": ""WBC"", ""value"": 124.0, ""unit"": ""g/dL"", ""flag"": ""high""}, {""test"": ""Hemoglobin"", ""value"": 11"
2026-01-04,CBC,MRN-821208,LAB-5865155,"[{""test"": ""Glucose"", ""value"": 192.6, ""unit"": ""g/dL"", ""flag"": ""normal""}, {""test"": ""Glucose"", ""value"":"
2026-01-05,CBC,MRN-673760,LAB-6708513,"[{""test"": ""WBC"", ""value"": 173.4, ""unit"": ""mg/dL"", ""flag"": ""high""}, {""test"": ""Glucose"", ""value"": 65.2"
2026-01-03,CMP,MRN-234922,LAB-5785591,"[{""test"": ""Hemoglobin"", ""value"": 106.8, ""unit"": ""g/dL"", ""flag"": ""normal""}, {""test"": ""WBC"", ""value"": "


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

[User] Create a YAML representation of news article.

[Assistant]
Approach:
1. Task: Create news article in YAML
2. Complexity: 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:
article_id: ART-5347545
headline: Triple-buffered zero administration algorithm
author: Martha Brown
published: '2026-01-05T16:28:34.342789'
section: Sports
content: 'Have fall sing then fast research break. Bar ready eye medical school might
  recognize. Nice sometimes impact point white.

  Take many this never ever trip. Specific call according. We argue person federal
  central each.'
tags:
- line
- 'true'
- compare
- for
views: 96946
shares: 1479


[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"?>
<sales_analytics>
<period>June 2024</period>
<total_revenue>5319249</total_revenue>
<units_sold>96009</units_sold>
<channels>
<name>wholesale</name>
<revenue>941227</revenue>
<growth>26.4</growth>
</channels>
<channels>
<name>retail</name>
<revenue>937409</revenue>
<growth>30.07</growth>
</channels>
<top_products>
<sku>SKU-2900</sku>
<sales>81858</sales>
</top_products>
<top_products>
<sku>SKU-8266</sku>
<sales>123988</sales>
</top_products>
<top_products>
<sku>SKU-9969</sku>
<sales>32400</sales>
</top_products>
</sales_analytics>

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

Output:
{
  "period": "June 2024",
  "total_revenue": 5319249,
  "units_sold": 96009,
  "channels": [
    {
      "name": "wholesale",
      "revenue": 941227,
      "growth": 26.4
    },
    {
      "name": "retail",
      "revenue": 937409,
      "growth": 30.07
    }
  ],
  "top_products": [
    {
      "sku": "SKU-2900",
      "sales": 81858
    },
    {
      "sku": "SKU-8266",
      "sales": 123988
    },
    {
      "sku": "SKU-9969",
      "sales": 32400
    }
  ]
}


[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,Lipid,MRN-375584,LAB-8547948,"[{""test"": ""WBC"", ""value"": 136.4, ""unit"": ""mg/dL"", ""flag"": ""low""}, {""test"": ""Glucose"", ""value"": 110.1"
2026-01-02,Lipid,MRN-786765,LAB-5810427,"[{""test"": ""Glucose"", ""value"": 185.2, ""unit"": ""mg/dL"", ""flag"": ""normal""}, {""test"": ""Glucose"", ""value"""
2026-01-03,CMP,MRN-607081,LAB-1845178,"[{""test"": ""WBC"", ""value"": 65.6, ""unit"": ""mg/dL"", ""flag"": ""low""}, {""test"": ""Glucose"", ""value"": 71.2, "


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

[User] Output clinical note as JSON.

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

Output:
{
  "note_id": "CN-6224145",
  "patient": {
    "mrn": "MRN-560569",
    "age": 88,
    "gender": "F"
  },
  "encounter_date": "2026-01-04",
  "chief_complaint": "headache",
  "vitals": {
    "bp": "119/73",
    "hr": 63,
    "temp_f": 100.0
  },
  "assessment": [
    {
      "problem": "hypertension",
      "icd10": "I32"
    }
  ]
}


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

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

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


[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:
price = 743.81
is_available = true
rating = 2.69
stock = 485

[specs]
weight_kg = 41.33
dimensions = "19x24x69cm"


[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"?>
<social_media_post>
<post_id>POST-58883169</post_id>
<user_id>9fc1586a-703b-4459-a18b-2f5e0582ab64</user_id>
<username>alexandra57</username>
</social_media_post>

[Assistant]
Approach:
1. Task: Convert social media post 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:
{
  "post_id": "POST-58883169",
  "user_id": "9fc1586a-703b-4459-a18b-2f5e0582ab64",
  "username": "alexandra57"
}


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

[User] Generate transaction record data in YAML format.

[Assistant]
Approach:
1. Task: Create transaction record 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:
txn_id: TXN-98000345
customer_id: 681a59bc-1151-4d49-8e75-1af0878315cb
timestamp: '2026-01-07T13:51:26.087659'
items:
- sku: SKU-50616
  qty: 3
  price: 180.94
- sku: SKU-82812
  qty: 5
  price: 490.31
subtotal: 948.16
tax: 93.65
total: 1389.7
payment_method: credit_card


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

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

[Assistant]
Approach:
1. Task: Create course syllabus 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:
title = "Stand-alone empowering functionalities 101"
[[schedule]]
week = 1
topic = "class"

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

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

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

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

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

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

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


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

[User] Produce a TOML document for a contract.

[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-619223"
effective_date = "2026-01-03"
term_months = 21
value = 87478
status = "pending"
[[parties]]
name = "Mcdaniel LLC"
role = "party_a"

[[parties]]
name = "Hunt-Bowman"
role = "party_b"


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

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

[Assistant]
Approach:
1. Task: Create sales analytics in YAML
2. Complexity: 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: April 2020
total_revenue: 1914989
units_sold: 47758
channels:
- name: wholesale
  revenue: 3617590
  growth: 20.48
- name: online
  revenue: 654207
  growth: 24.4
top_products:
- sku: SKU-4328
  sales: 466200
- sku: SKU-2589
  sales: 244105
- sku: SKU-7725
  sales: 25778


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

[User] Create a YAML representation of financial report.

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


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

[User] Produce a XML document for a student assessment.

[Assistant]
Approach:
1. Task: Create student assessment 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"?>
<student_assessment>
<assessment_id>ASMT-475777</assessment_id>
<student_id>STU-613124</student_id>
<course_id>CRS-2241</course_id>
<type>assignment</type>
<date>2026-01-06</date>
<scores>
<question>1</question>
<points_earned>8</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>6</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>3</question>
<points_earned>3</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>7</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>0</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>9</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>9</question>
<points_earned>3</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>75</total_score>
<percentage>81.54</percentage>
<grade>B</grade>
</student_assessment>


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

[User] Output social media post as XML.

[Assistant]
Approach:
1. Task: Create social media post in XML
2. Complexity: 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"?>
<social_media_post>
<post_id>POST-19844803</post_id>
<platform>instagram</platform>
<user_id>eee48898-e428-4685-b6ea-d0074f4ffb8a</user_id>
<username>pinedaryan</username>
<content>Between past agree writer forget big. Simple glass protect job answer thank.
Government prepare rather agency hard. Fear director room future hospital.</content>
<timestamp>2026-01-07T13:51:25.753060</timestamp>
<hashtags>#fast</hashtags>
<hashtags>#imagine</hashtags>
<hashtags>#carry</hashtags>
<engagement>
<likes>1299</likes>
<shares>900</shares>
<comments>90</comments>
</engagement>
</social_media_post>


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<rating>5</rating>
<review_id>REV-2205395</review_id>
<content>Respond order far story by area affect. Important also catch down choice office necessary political. Firm along bar.
Stuff create including star question traditional reflect. Share fast thought.</content>
</customer_review>


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

[User] Produce a TOML document for a contract.

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

Output:
term_months = 34
status = "executed"
effective_date = "2026-01-01"
[[parties]]
name = "Garza-Henson"
role = "party_a"

[[parties]]
name = "Griffin-Weaver"
role = "party_b"


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

[User]
Reformat the data below from CSV to JSON:
order_date,panel,patient_mrn,result_id,results
2026-01-04,CMP,MRN-369371,LAB-2983714,"[{""test"": ""Hemoglobin"", ""value"": 97.6, ""unit"": ""g/dL"", ""flag"": ""normal""}, {""test"": ""WBC"", ""value"": 6"
2026-01-03,CMP,MRN-732387,LAB-3090592,"[{""test"": ""WBC"", ""value"": 158.2, ""unit"": ""mg/dL"", ""flag"": ""normal""}, {""test"": ""WBC"", ""value"": 129.0,"
2026-01-02,CBC,MRN-391646,LAB-9637190,"[{""test"": ""WBC"", ""value"": 67.6, ""unit"": ""g/dL"", ""flag"": ""low""}, {""test"": ""Glucose"", ""value"": 74.5, """

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

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