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

[User] Generate research paper data in TOML format.

[Assistant]
Approach:
1. Task: Create research paper 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:
paper_id = "arXiv:2020.69453"
title = "Assimilated needs-based portal"
abstract = "Economy instead thank kitchen. For pattern he purpose strong goal challenge."
keywords = [ "power", "main", "light", "form", "system",]
citations = 115
[[authors]]
name = "Evan Reed"
affiliation = "Orr, Wheeler and Johnson"
email = "cheryl05@example.net"

[[authors]]
name = "Amanda Mcmahon"
affiliation = "Maxwell-Price"
email = "mbowen@example.org"

[[authors]]
name = "Angel Vasquez"
affiliation = "Melendez, Osborne and Harris"
email = "timothysutton@example.com"

[publication]
venue = "Cell"
year = 2024
doi = "10.9550/gbOm"


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

[User] Generate error log data in CSV format.

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

Output:
abstract,authors,citations,context_request_id,context_user_id,error_id,funding_source,keywords,level,message,paper_id,publication_doi,publication_venue,publication_year,service,stack_trace,timestamp,title
,,,4c579c9e-314d-44f6-9e5a-9c3c95ea5e82,264dfcb4-39aa-45b1-999f-d115795470f4,385c5830-2f90-42e3-ae2f-53faace4448a,,,CRITICAL,People party agreement mother that investment approach.,,,,,almostService,"[""at fight.py:491"", ""at city.py:369"", ""at statement.py:378""]",2026-01-07T13:51:26.292009,
Democratic age whom its situation. That central bank none her. Produce lose member thousand.,"[{""name"": ""Donna Keller"", ""affiliation"": ""Greer, Ramirez and Carter"", ""email"": ""michelle76@example.n",72,,,,Beard-Roy,"[""if"", ""magazine"", ""health""]",,,arXiv:2022.49845,10.7432/PqzG,Nature,2020,,,,Profound logistical customer loyalty
Character interesting morning finish sense. Consider camera these risk. Memory others evidence relat,"[{""name"": ""Robert Wilkinson"", ""affiliation"": ""Santos, Clark and Patel"", ""email"": ""samuelbell@example",189,,,,Barnes LLC,"[""skin"", ""positive"", ""fight"", ""sister"", ""decide""]",,,arXiv:2022.79149,10.4023/PYtJ,Science,2023,,,,Customizable mission-critical middleware


[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:
{
  "note_id": "CN-4036732",
  "patient": {
    "mrn": "MRN-366942",
    "age": 79,
    "gender": "M"
  },
  "encounter_date": "2026-01-06",
  "chief_complaint": "headache",
  "vitals": {
    "bp": "102/96",
    "hr": 61,
    "temp_f": 97.1
  },
  "assessment": [
    {
      "problem": "hypertension",
      "icd10": "K52"
    }
  ]
}

[Assistant]
Approach:
1. Task: Convert clinical note from 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"?>
<clinical_note>
<note_id>CN-4036732</note_id>
<patient>
<mrn>MRN-366942</mrn>
<age>79</age>
<gender>M</gender>
</patient>
<encounter_date>2026-01-06</encounter_date>
<chief_complaint>headache</chief_complaint>
<vitals>
<bp>102/96</bp>

61

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


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

[User]
Convert the following XML to CSV:
<?xml version="1.0" encoding="UTF-8"?>
<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>

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

Output:
assessment,chief_complaint,encounter_date,note_id,patient_age,patient_gender,patient_mrn,vitals_bp,vitals_hr,vitals_temp_f
,,2026-01-06,CN-3823498,,,,131/104,84,99.9
"[{""problem"": ""hypertension"", ""icd10"": ""K48""}, {""problem"": ""hypertension"", ""icd10"": ""K13""}]",fever,2026-01-06,CN-5143623,45,F,MRN-821610,174/60,79,100.2
"[{""problem"": ""diabetes"", ""icd10"": ""I34""}, {""problem"": ""diabetes"", ""icd10"": ""K71""}]",fever,2026-01-04,CN-4602383,58,F,MRN-126591,156/110,79,98.7


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

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

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

Output:
openapi: 3.0.0
info:
  title: Secured well-modulated policy API
  version: 1.0.0
paths:
  /article:
    get:
      summary: During certainly full.
      parameters:
      - name: param0
        in: query
        type: string
      - name: param1
        in: query
        type: string
      - name: param2
        in: query
        type: string
      responses:
        '200':
          description: Success
        '400':
          description: Bad Request


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

[User]
Transform this XML data into CSV format:
<?xml version="1.0" encoding="UTF-8"?>
<social_media_post>
<post_id>POST-94493547</post_id>
<platform>instagram</platform>
<user_id>ebddd714-2a63-4fd6-985c-fb7fe32db0b4</user_id>
<username>laura52</username>
<content>Property political your form stand cup blood. Business later seem sea represent enough relationship memory.
What ok that look past. Budget understand mouth during brother pull type spring.</content>
<timestamp>2026-01-07T13:51:27.134920</timestamp>
<hashtags>#red</hashtags>
<hashtags>#hotel</hashtags>
<hashtags>#create</hashtags>
<engagement>
<likes>8599</likes>
<shares>93</shares>
<comments>39</comments>
</engagement>
</social_media_post>

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

Output:
content,engagement_comments,engagement_likes,engagement_shares,hashtags,platform,post_id,timestamp,user_id,username
Property political your form stand cup blood. Business later seem sea represent enough relationship ,39,8599,93,"[""#red"", ""#hotel"", ""#create""]",instagram,POST-94493547,2026-01-07T13:51:27.134920,ebddd714-2a63-4fd6-985c-fb7fe32db0b4,laura52
Mind continue week full degree all. Range stuff firm national system myself any. Night effect expect,294,4957,278,"[""#well"", ""#that""]",instagram,POST-87670653,2026-01-07T13:51:27.137327,ff49d413-4fa9-4998-83a7-d890a3a11265,katiedurham
"Minute sure commercial surface what enter glass. Democrat training lawyer red weight.
Her stage secu",325,9984,554,"[""#identify"", ""#bad""]",facebook,POST-24638744,2026-01-07T13:51:27.137610,2e3170f4-9d5c-4162-af15-4739f6dff5af,xhahn
"Kid interview PM market. Life theory real baby operation experience.
Staff until control news song b",106,6541,770,"[""#compare"", ""#option"", ""#attention""]",instagram,POST-32951188,2026-01-07T13:51:27.137912,37b47f13-44bc-4729-a176-829c5c0a9e33,brittany00


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<research_paper>
<paper_id>arXiv:2021.87801</paper_id>
<title>Cross-group 24/7 methodology</title>
<authors>
<name>Scott Webb</name>
<affiliation>Chapman LLC</affiliation>
<email>juanbooth@example.com</email>
</authors>
<authors>
<name>Robert Mullins</name>
<affiliation>Robbins, Adkins and Rogers</affiliation>
<email>michaeldunn@example.org</email>
</authors>
<abstract>Reality maybe court material response cell. Middle instead husband win thousand collection.</abstract>
<keywords>girl</keywords>
<keywords>face</keywords>
<keywords>protect</keywords>
<publication>
<venue>Cell</venue>
<year>2023</year>
<doi>10.4960/byWV</doi>
</publication>
<citations>193</citations>
<funding_source>Williams Ltd</funding_source>
</research_paper>


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<research_paper>
<paper_id>arXiv:2024.67669</paper_id>
<title>Triple-buffered dedicated knowledgebase</title>
<authors>
<name>Julie Mclaughlin</name>
<affiliation>Andrews Group</affiliation>
<email>brianna81@example.org</email>
</authors>
<authors>
<name>Peggy Kramer</name>
<affiliation>Beasley, Edwards and Webb</affiliation>
<email>susan35@example.com</email>
</authors>
<abstract>Account fish possible democratic ok no. Accept short mention guy.
Place finish religious mean end success. Travel into music they.</abstract>
<keywords>thank</keywords>
<keywords>far</keywords>
<keywords>fund</keywords>
<keywords>get</keywords>
<keywords>role</keywords>
<publication>
<venue>Nature</venue>
<year>2023</year>
<doi>10.1349/JgWc</doi>
</publication>
<citations>60</citations>
<funding_source>Diaz-Salinas</funding_source>
</research_paper>

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

Output:
{
  "paper_id": "arXiv:2024.67669",
  "title": "Triple-buffered dedicated knowledgebase",
  "authors": [
    {
      "name": "Julie Mclaughlin",
      "affiliation": "Andrews Group",
      "email": "brianna81@example.org"
    },
    {
      "name": "Peggy Kramer",
      "affiliation": "Beasley, Edwards and Webb",
      "email": "susan35@example.com"
    }
  ],
  "abstract": "Account fish possible democratic ok no. Accept short mention guy.\nPlace finish religious mean end success. Travel into music they.",
  "keywords": [
    "thank",
    "far",
    "fund",
    "get",
    "role"
  ],
  "publication": {
    "venue": "Nature",
    "year": 2023,
    "doi": "10.1349/JgWc"
  },
  "citations": 60,
  "funding_source": "Diaz-Salinas"
}


[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>e78ff1cc-d984-499d-9fcf-126ccada9355</error_id>
<timestamp>2026-01-07T13:51:26.607679</timestamp>
<level>WARNING</level>
<service>generationService</service>
<message>Bag difference growth have leader yeah him.</message>
<stack_trace>at teach.py:30</stack_trace>
<stack_trace>at poor.py:409</stack_trace>
<context>
<user_id>e8daac99-0bad-4fb0-ae26-78525528db85</user_id>
<request_id>a6fe9e0f-a1a6-42b2-ab77-98b8bb662a52</request_id>
</context>
</error_log>

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

Output:
{
  "error_id": "e78ff1cc-d984-499d-9fcf-126ccada9355",
  "timestamp": "2026-01-07T13:51:26.607679",
  "level": "WARNING",
  "service": "generationService",
  "message": "Bag difference growth have leader yeah him.",
  "stack_trace": [
    "at teach.py:30",
    "at poor.py:409"
  ],
  "context": {
    "user_id": "e8daac99-0bad-4fb0-ae26-78525528db85",
    "request_id": "a6fe9e0f-a1a6-42b2-ab77-98b8bb662a52"
  }
}


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

[User] Create a CSV representation of experiment result.

[Assistant]
Approach:
1. Task: Create experiment result 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:
conclusion,experiment_id,methodology_design,methodology_duration_days,methodology_sample_size,results,title
significant,EXP-956799,RCT,355,962,"[{""metric"": ""efficacy"", ""baseline"": 84.98, ""endpoint"": 18.54, ""p_value"": 0.3765}, {""metric"": ""safety",Effect of town on start
significant,EXP-580673,cohort,88,909,"[{""metric"": ""safety"", ""baseline"": 60.21, ""endpoint"": 37.02, ""p_value"": 0.4775}, {""metric"": ""safety"",",Effect of onto on send
significant,EXP-106016,cohort,61,918,"[{""metric"": ""safety"", ""baseline"": 89.45, ""endpoint"": 82.29, ""p_value"": 0.1138}, {""metric"": ""safety"",",Effect of quickly on fight
non-significant,EXP-748392,observational,266,290,"[{""metric"": ""safety"", ""baseline"": 54.86, ""endpoint"": 10.85, ""p_value"": 0.4488}, {""metric"": ""efficacy",Effect of probably on everything


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

[User] Create a XML representation of research paper.

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

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


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<student_assessment>
<assessment_id>ASMT-766800</assessment_id>
<student_id>STU-927295</student_id>
<course_id>CRS-8819</course_id>
<type>assignment</type>
<date>2026-01-03</date>
<scores>
<question>1</question>
<points_earned>8</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>3</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>3</question>
<points_earned>8</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>5</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>2</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>4</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>99</total_score>
<percentage>71.71</percentage>
<grade>A</grade>
</student_assessment>

[Assistant]
Approach:
1. Task: Convert student assessment 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:
{
  "assessment_id": "ASMT-766800",
  "student_id": "STU-927295",
  "course_id": "CRS-8819",
  "type": "assignment",
  "date": "2026-01-03",
  "scores": [
    {
      "question": 1,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 3,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 5,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 0,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 9,
      "points_earned": 3,
      "points_possible": 10
    }
  ],
  "total_score": 99,
  "percentage": 71.71,
  "grade": "A"
}


[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
2026-01-01,"[{""name"": ""Lisinopril"", ""dosage"": ""20mg"", ""frequency"": ""daily"", ""quantity"": 30}, {""name"": ""Lisinopri",MRN-256913,Victor Valentine,RX-8246470
2026-01-05,"[{""name"": ""Metformin"", ""dosage"": ""10mg"", ""frequency"": ""BID"", ""quantity"": 60}, {""name"": ""Metformin"", ",MRN-423030,Zachary Wood,RX-5991956
2026-01-05,"[{""name"": ""Metformin"", ""dosage"": ""10mg"", ""frequency"": ""TID"", ""quantity"": 60}]",MRN-317647,Michael Shah,RX-7154510
2026-01-04,"[{""name"": ""Metformin"", ""dosage"": ""5mg"", ""frequency"": ""daily"", ""quantity"": 90}, {""name"": ""Atorvastati",MRN-699913,Samuel White,RX-6217194


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

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

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

Output:
{
  "net_income": 4233102,
  "metrics": {
    "profit_margin": 14.29,
    "roe": 18.28
  },
  "company": "Blackwell, Simpson and Pace",
  "eps": 0.79,
  "expenses": 41343491
}


[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-3366717
headline: Integrated bi-directional complexity
author: Linda Clark
published: '2026-01-07T13:19:20.433040'
section: Tech
content: 'Anything music blood how public to. Even student idea piece if. Whom phone
  rich long.

  Look memory help find reduce. Structure most tough realize ground.

  Around fear reduce ago. Thus moment letter evening stuff three.

  Her themselves campaign cup four catch as. Part turn leg.'
tags:
- necessary
- listen
- employee
- here
views: 75939
shares: 1143


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

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

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

Output:
{
  "result_id": "LAB-8093004",
  "patient_mrn": "MRN-777027",
  "order_date": "2026-01-05",
  "panel": "CMP",
  "results": [
    {
      "test": "Glucose",
      "value": 140.2,
      "unit": "mg/dL",
      "flag": "low"
    },
    {
      "test": "Hemoglobin",
      "value": 96.3,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "Glucose",
      "value": 185.0,
      "unit": "g/dL",
      "flag": "high"
    },
    {
      "test": "Glucose",
      "value": 139.7,
      "unit": "g/dL",
      "flag": "low"
    }
  ]
}


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

[User] Output student assessment as YAML.

[Assistant]
Approach:
1. Task: Create student assessment 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:
total_score: 96
percentage: 61.11
student_id: STU-785727


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

[User]
Reformat the data below from YAML to XML:
period: May 2020
total_revenue: 9864225
units_sold: 74086
channels:
- name: online
  revenue: 906832
  growth: -8.93
- name: wholesale
  revenue: 2437365
  growth: 2.73
top_products:
- sku: SKU-7032
  sales: 420063
- sku: SKU-9360
  sales: 149398
- sku: SKU-9440
  sales: 105905

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<sales_analytics>
<period>May 2020</period>
<total_revenue>9864225</total_revenue>
<units_sold>74086</units_sold>
<channels>
<name>online</name>
<revenue>906832</revenue>
<growth>-8.93</growth>
</channels>
<channels>
<name>wholesale</name>
<revenue>2437365</revenue>
<growth>2.73</growth>
</channels>
<top_products>
<sku>SKU-7032</sku>
<sales>420063</sales>
</top_products>
<top_products>
<sku>SKU-9360</sku>
<sales>149398</sales>
</top_products>
<top_products>
<sku>SKU-9440</sku>
<sales>105905</sales>
</top_products>
</sales_analytics>


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<contract>
<contract_id>CTR-123472</contract_id>
<parties>
<name>Palmer-White</name>
<role>party_a</role>
</parties>
<parties>
<name>Rodriguez-Moore</name>
<role>party_b</role>
</parties>
<effective_date>2026-01-06</effective_date>
<term_months>59</term_months>
<value>388976</value>
<status>pending</status>
</contract>

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


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

[User] Output news article as YAML.

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

Output:
content: 'Range condition class leader wrong subject wait. Stop we prevent particular
  front method. Force item executive employee green large house nation. General doctor
  material rule head event.

  One will dog chance. Order away music seem director put upon. Find boy again direction
  four.'
article_id: ART-9628131
headline: Re-contextualized logistical paradigm


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

[User] Create a YAML representation of error log.

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

Output:
error_id: 21bf982e-3e24-486f-a8ed-fe9e0227df3b
timestamp: '2026-01-07T13:51:27.797574'
level: CRITICAL
service: letService
message: Story quite another important.
stack_trace:
- at decision.py:100
- at sing.py:289
- at long.py:325
- at special.py:174
context:
  user_id: 8c36ba55-183c-4481-9cd9-dc049447888c
  request_id: 089e0eaa-71d8-4f30-a2f1-bac42a6b74a3


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

[User] Generate transaction record data in TOML format.

[Assistant]
Approach:
1. Task: Create transaction record 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:
payment_method = "paypal"
customer_id = "fe237049-a4a1-4a5c-af14-940bbb31d0e7"
total = 1227.54


[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"?>
<sales_analytics>
<period>February 2024</period>
<total_revenue>3108970</total_revenue>
<units_sold>70292</units_sold>
<channels>
<name>online</name>
<revenue>1867975</revenue>
<growth>-2.95</growth>
</channels>
<channels>
<name>retail</name>
<revenue>1947932</revenue>
<growth>22.54</growth>
</channels>
<top_products>
<sku>SKU-5409</sku>
<sales>492017</sales>
</top_products>
<top_products>
<sku>SKU-4816</sku>
<sales>486050</sales>
</top_products>
<top_products>
<sku>SKU-9957</sku>
<sales>44038</sales>
</top_products>
</sales_analytics>

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

Output:
{
  "period": "February 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 YAML format. Think step-by-step, then generate syntactically perfect YAML.

[User]
Convert the following TOML to YAML:
prescriber = "Melinda Black"
date = "2026-01-04"
rx_id = "RX-8618237"

[Assistant]
Approach:
1. Task: Convert prescription from TOML 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:
prescriber: Melinda Black
date: '2026-01-04'
rx_id: RX-8618237


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<social_media_post>
<post_id>POST-69367106</post_id>
<platform>twitter</platform>
<user_id>7643b70d-1c60-436f-974e-7bc6cee5e032</user_id>
<username>gordonalexander</username>
<content>See personal couple road president most next. Laugh teach lawyer character work present.
Page give education middle. Couple save view media instead police guy. Enough test notice capital size.</content>
<timestamp>2026-01-07T13:51:25.991400</timestamp>
<hashtags>#PM</hashtags>
<hashtags>#stage</hashtags>
<hashtags>#government</hashtags>
<engagement>
<likes>1911</likes>
<shares>761</shares>
<comments>62</comments>
</engagement>
</social_media_post>


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

[User] Create a XML representation of error log.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<error_log>
<error_id>0ea30289-ce13-425f-910d-da970e03d0fa</error_id>
<timestamp>2026-01-07T13:51:25.772316</timestamp>
<level>WARNING</level>
<service>theService</service>
<message>Country specific information follow daughter dark.</message>
<stack_trace>at enjoy.py:340</stack_trace>
<stack_trace>at current.py:45</stack_trace>
<stack_trace>at hand.py:478</stack_trace>
<context>
<user_id>91a6b883-2593-4790-8a1e-5acd27aad31b</user_id>
<request_id>1b22b6e6-0879-45de-9655-0fac03142f9b</request_id>
</context>
</error_log>


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

[User]
Transform this CSV data into TOML format:
assessment_id,code,course_id,credits,date,grade,grading_final,grading_homework,grading_midterm,instructor,percentage,schedule,scores,student_id,term,title,total_score,type
ASMT-475777,,CRS-2241,,2026-01-06,B,,,,,81.54,,"[{""question"": 1, ""points_earned"": 8, ""points_possible"": 10}, {""question"": 2, ""points_earned"": 6, ""po",STU-613124,,,75,assignment
,XQE465,CRS-2146,3,,,40,30,30,Jasmin Reyes,,"[{""week"": 1, ""topic"": ""network""}, {""week"": 2, ""topic"": ""hit""}, {""week"": 3, ""topic"": ""site""}, {""week""",,,Fall 2020,Organized reciprocal middleware 101,,
,FAD215,CRS-7496,4,,,40,30,30,Jessica Davenport MD,,"[{""week"": 1, ""topic"": ""watch""}, {""week"": 2, ""topic"": ""recently""}, {""week"": 3, ""topic"": ""family""}, {""",,,Fall 2020,Open-source zero tolerance software 101,,

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

Output:
assessment_id = "ASMT-475777"
student_id = "STU-613124"
course_id = "CRS-2241"
type = "assignment"
date = "2026-01-06"
total_score = 75
percentage = 81.54
grade = "B"
[[scores]]
question = 1
points_earned = 8
points_possible = 10

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

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

[[scores]]
question = 4
points_earned = 1
points_possible = 10

[[scores]]
question = 5
points_earned = 9
points_possible = 10

[[scores]]
question = 6
points_earned = 7
points_possible = 10

[[scores]]
question = 7
points_earned = 0
points_possible = 10

[[scores]]
question = 8
points_earned = 9
points_possible = 10

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


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

[User] Output financial report as TOML.

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

Output:
company = "Nichols, Ferguson and Butler"
ticker = "NDVN"
quarter = "Q1 2022"
revenue = 39470251
expenses = 26562838
net_income = 16784469
eps = 3.2

[metrics]
profit_margin = 27.93
roe = 5.96


[System] You are an expert in 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-370819"
effective_date = "2026-01-01"
term_months = 13
value = 109351
status = "active"
[[parties]]
name = "Stewart, Thompson and Rogers"
role = "party_a"

[[parties]]
name = "Jackson, Griffin and Flowers"
role = "party_b"


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

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

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

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


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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<api_specification>
<openapi>3.0.0</openapi>
<paths>
</sense>
<get>
<summary>Pay yes agree executive year ahead program.</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>
<//sense>
</paths>
<info>
<title>Customer-focused zero-defect array API</title>
<version>1.0.0</version>
</info>
</api_specification>


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

[User] Produce a JSON document for a prescription.

[Assistant]
Approach:
1. Task: Create prescription in JSON
2. Complexity: 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-7309915",
  "patient_mrn": "MRN-389849",
  "prescriber": "Briana Dickerson",
  "date": "2026-01-03",
  "medications": [
    {
      "name": "Metformin",
      "dosage": "20mg",
      "frequency": "daily",
      "quantity": 30
    }
  ]
}


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

[User] Generate lab result data in XML format.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<lab_result>
<result_id>LAB-4504067</result_id>
<patient_mrn>MRN-266543</patient_mrn>
<order_date>2026-01-05</order_date>
<panel>Lipid</panel>
<results>
<test>Glucose</test>
<value>181.1</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>164.3</value>
<unit>mg/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Glucose</test>
<value>140.0</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>113.0</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
</lab_result>


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

[User] Generate prescription data in YAML format.

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

Output:
rx_id: RX-6036951
patient_mrn: MRN-440463
prescriber: Lisa Mathews
date: '2026-01-05'
medications:
- name: Metformin
  dosage: 20mg
  frequency: TID
  quantity: 90


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

[User]
Convert the following JSON to XML:
{
  "review_id": "REV-9529513",
  "product_id": "PROD-542599",
  "user_id": "67bb80c4-7c72-4c1b-886f-8186f18f45e3",
  "rating": 3,
  "title": "Money face statement talk day.",
  "content": "Candidate stuff mission end nature hundred. Recently game stage agreement. Seem central blood add environment several.\nSet less job reveal protect. Similar second staff owner international major.",
  "date": "2026-01-01",
  "verified_purchase": true,
  "helpful_votes": 8
}

[Assistant]
Approach:
1. Task: Convert customer review 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"?>
<customer_review>
<review_id>REV-9529513</review_id>
<product_id>PROD-542599</product_id>
<user_id>67bb80c4-7c72-4c1b-886f-8186f18f45e3</user_id>
<rating>3</rating>
<title>Money face statement talk day.</title>
<content>Candidate stuff mission end nature hundred. Recently game stage agreement. Seem central blood add environment several.
Set less job reveal protect. Similar second staff owner international major.</content>
<date>2026-01-01</date>
<verified_purchase>True</verified_purchase>
<helpful_votes>8</helpful_votes>
</customer_review>


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<financial_report>
<company>Ortega-Owens</company>
<ticker>YLLB</ticker>
<quarter>Q3 2022</quarter>
<revenue>37598920</revenue>
<expenses>44591506</expenses>
<net_income>3197580</net_income>
<eps>1.51</eps>
<metrics>
<profit_margin>5.54</profit_margin>
<roe>6.32</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": "Ortega-Owens",
  "ticker": "YLLB",
  "quarter": "Q3 2022",
  "revenue": 37598920,
  "expenses": 44591506,
  "net_income": 3197580,
  "eps": 1.51,
  "metrics": {
    "profit_margin": 5.54,
    "roe": 6.32
  }
}


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

[User] Create a XML representation of research paper.

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

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


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

[User] Generate prescription data in XML format.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<prescription>
<rx_id>RX-5160762</rx_id>
<patient_mrn>MRN-568012</patient_mrn>
<prescriber>Linda Gonzalez</prescriber>
<date>2026-01-06</date>
<medications>
<name>Lisinopril</name>
<dosage>20mg</dosage>
<frequency>TID</frequency>
<quantity>30</quantity>
</medications>
<medications>
<name>Atorvastatin</name>
<dosage>5mg</dosage>
<frequency>daily</frequency>
<quantity>60</quantity>
</medications>
</prescription>


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

[User] Create a TOML representation of lab result.

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

Output:
result_id = "LAB-2441646"
patient_mrn = "MRN-228148"
order_date = "2026-01-01"
panel = "Lipid"
[[results]]
test = "Glucose"
value = 81.9
unit = "g/dL"
flag = "high"

[[results]]
test = "WBC"
value = 107.7
unit = "mg/dL"
flag = "high"

[[results]]
test = "Hemoglobin"
value = 101.6
unit = "mg/dL"
flag = "normal"

[[results]]
test = "Hemoglobin"
value = 197.9
unit = "g/dL"
flag = "low"


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

[User] Create a CSV representation of student assessment.

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

Output:
assessment_id,code,course_id,credits,date,grade,grading_final,grading_homework,grading_midterm,instructor,percentage,schedule,scores,student_id,term,title,total_score,type
ASMT-672485,,CRS-8704,,2026-01-01,A,,,,,72.48,,"[{""question"": 1, ""points_earned"": 0, ""points_possible"": 10}, {""question"": 2, ""points_earned"": 9, ""po",STU-183204,,,82,quiz
,PZB112,CRS-5564,3,,,40,30,30,Christine Henderson,,"[{""week"": 1, ""topic"": ""work""}, {""week"": 2, ""topic"": ""Congress""}, {""week"": 3, ""topic"": ""two""}, {""week",,,Fall 2023,Devolved object-oriented success 101,,
,BEQ149,CRS-4438,4,,,40,30,30,Tara Boone,,"[{""week"": 1, ""topic"": ""buy""}, {""week"": 2, ""topic"": ""keep""}, {""week"": 3, ""topic"": ""wear""}, {""week"": 4",,,Spring 2020,Re-engineered intangible orchestration 101,,
,JHT352,CRS-3207,4,,,40,30,30,Charlene Velez,,"[{""week"": 1, ""topic"": ""at""}, {""week"": 2, ""topic"": ""role""}, {""week"": 3, ""topic"": ""better""}, {""week"": ",,,Spring 2023,Fully-configurable composite product 101,,


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

[User] Generate contract data in CSV format.

[Assistant]
Approach:
1. Task: Create contract 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:
contract_id,effective_date,parties,status,term_months,value
CTR-449984,2026-01-04,"[{""name"": ""Garcia-Henson"", ""role"": ""party_a""}, {""name"": ""Moore LLC"", ""role"": ""party_b""}]",pending,49,694475
CTR-397079,2026-01-06,"[{""name"": ""Johnson LLC"", ""role"": ""party_a""}, {""name"": ""Powers Inc"", ""role"": ""party_b""}]",pending,46,361849
CTR-657773,2026-01-02,"[{""name"": ""Taylor, Harrison and Smith"", ""role"": ""party_a""}, {""name"": ""Saunders-Hayes"", ""role"": ""part",pending,30,143616
CTR-615113,2026-01-01,"[{""name"": ""Brown, Walker and Walker"", ""role"": ""party_a""}, {""name"": ""Doyle, Padilla and Collins"", ""ro",executed,22,439851


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

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

[Assistant]
Approach:
1. Task: Create student assessment 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:
{
  "assessment_id": "ASMT-422317",
  "student_id": "STU-280699",
  "course_id": "CRS-7308",
  "type": "exam",
  "date": "2026-01-01",
  "scores": [
    {
      "question": 1,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 3,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 10,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 10,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 3,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 7,
      "points_possible": 10
    }
  ],
  "total_score": 75,
  "percentage": 83.59,
  "grade": "B"
}


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

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

[Assistant]
Approach:
1. Task: Create error log 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:
{
  "error_id": "8ef553f5-74fa-47eb-bfcb-571b6fa73c35",
  "timestamp": "2026-01-07T13:51:27.105544",
  "level": "WARNING",
  "service": "radioService",
  "message": "Professional pull soon.",
  "stack_trace": [
    "at eye.py:220",
    "at short.py:148",
    "at the.py:448"
  ],
  "context": {
    "user_id": "162209b9-e3ae-4c7a-af39-f96af44cdcaa",
    "request_id": "a05e806a-f592-4611-8d80-dbe2773bec40"
  }
}


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

[User] Output customer review as YAML.

[Assistant]
Approach:
1. Task: Create customer review 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:
verified_purchase: true
title: Country especially hand.
review_id: REV-4835597
product_id: PROD-713270


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

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

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

Output:
experiment_id = "EXP-500587"
title = "Effect of seem on put"
conclusion = "significant"
[[results]]
metric = "safety"
baseline = 59.15
endpoint = 80.7
p_value = 0.0751

[[results]]
metric = "efficacy"
baseline = 25.67
endpoint = 99.48
p_value = 0.1142

[[results]]
metric = "safety"
baseline = 72.29
endpoint = 18.69
p_value = 0.2768

[[results]]
metric = "safety"
baseline = 16.24
endpoint = 94.98
p_value = 0.315

[methodology]
design = "cohort"
sample_size = 806
duration_days = 332


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

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

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


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

[User]
Convert the following JSON to XML:
{
  "result_id": "LAB-3990665",
  "patient_mrn": "MRN-508219",
  "order_date": "2026-01-04",
  "panel": "Lipid",
  "results": [
    {
      "test": "Hemoglobin",
      "value": 80.7,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "Glucose",
      "value": 90.9,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "Hemoglobin",
      "value": 138.0,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "WBC",
      "value": 131.3,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "Glucose",
      "value": 172.4,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "WBC",
      "value": 151.6,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "Hemoglobin",
      "value": 188.6,
      "unit": "g/dL",
      "flag": "high"
    }
  ]
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<lab_result>
<result_id>LAB-3990665</result_id>
<patient_mrn>MRN-508219</patient_mrn>
<order_date>2026-01-04</order_date>
<panel>Lipid</panel>
<results>
<test>Hemoglobin</test>
<value>80.7</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Glucose</test>
<value>90.9</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>138.0</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>WBC</test>
<value>131.3</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Glucose</test>
<value>172.4</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>WBC</test>
<value>151.6</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>188.6</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
</lab_result>


[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: 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"?>
<contract>
<contract_id>CTR-313579</contract_id>
<parties>
<name>Roberts, Newton and Ortiz</name>
<role>party_a</role>
</parties>
<parties>
<name>Garcia PLC</name>
<role>party_b</role>
</parties>
<effective_date>2026-01-01</effective_date>
<term_months>55</term_months>
<value>108642</value>
<status>active</status>
</contract>


[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-6709459"
encounter_date = "2026-01-03"
chief_complaint = "fever"
[[assessment]]
problem = "diabetes"
icd10 = "J90"

[[assessment]]
problem = "hypertension"
icd10 = "I22"

[[assessment]]
problem = "hypertension"
icd10 = "K97"

[patient]
mrn = "MRN-104418"
age = 50
gender = "M"

[vitals]
bp = "143/96"
hr = 69
temp_f = 101.3


[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"?>
<course_syllabus>
<course_id>CRS-8422</course_id>
OMY437
<title>Optimized upward-trending conglomeration 101</title>
<instructor>Rodney Anderson</instructor>
<credits>3</credits>
<term>Spring 2023</term>
<schedule>
<week>1</week>
<topic>answer</topic>
</schedule>
<schedule>
<week>2</week>
<topic>best</topic>
</schedule>
<schedule>
<week>3</week>
<topic>meet</topic>
</schedule>
<schedule>
<week>4</week>
<topic>simple</topic>
</schedule>
<schedule>
<week>5</week>
<topic>peace</topic>
</schedule>
<schedule>
<week>6</week>
<topic>upon</topic>
</schedule>
<schedule>
<week>7</week>
<topic>power</topic>
</schedule>
<grading>
<homework>30</homework>
<midterm>30</midterm>
<final>40</final>
</grading>
</course_syllabus>

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

Output:
{
  "course_id": "CRS-8422",
  "code": "OMY437",
  "title": "Optimized upward-trending conglomeration 101",
  "instructor": "Rodney Anderson",
  "credits": 3,
  "term": "Spring 2023",
  "schedule": [
    {
      "week": 1,
      "topic": "answer"
    },
    {
      "week": 2,
      "topic": "best"
    },
    {
      "week": 3,
      "topic": "meet"
    },
    {
      "week": 4,
      "topic": "simple"
    },
    {
      "week": 5,
      "topic": "peace"
    },
    {
      "week": 6,
      "topic": "upon"
    },
    {
      "week": 7,
      "topic": "power"
    }
  ],
  "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] Generate error log data in XML format.

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

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


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

[User] Generate lab result data in YAML format.

[Assistant]
Approach:
1. Task: Create lab result in YAML
2. Complexity: 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:
patient_mrn: MRN-135092
order_date: '2026-01-02'
panel: CBC
results:
- test: Hemoglobin
  value: 129.6
  unit: g/dL
  flag: low
- test: Hemoglobin
  value: 120.7
  unit: mg/dL
  flag: low
- test: Hemoglobin
  value: 141.8
  unit: g/dL
  flag: low
- test: Hemoglobin
  value: 131.3
  unit: g/dL
  flag: low
- test: Glucose
  value: 147.1
  unit: mg/dL
  flag: high
result_id: LAB-9224780


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<transaction_record>
<txn_id>TXN-85338602</txn_id>
<customer_id>ea7970e3-49c7-4d3a-bbe0-6c539dc6c3d3</customer_id>
<timestamp>2026-01-07T13:51:25.620781</timestamp>
<items>
<sku>SKU-22630</sku>
<qty>3</qty>
<price>89.97</price>
</items>
<subtotal>468.67</subtotal>
<tax>148.91</tax>
<total>792.01</total>
<payment_method>apple_pay</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-85338602",
  "customer_id": "ea7970e3-49c7-4d3a-bbe0-6c539dc6c3d3",
  "timestamp": "2026-01-07T13:51:25.620781",
  "items": [
    {
      "sku": "SKU-22630",
      "qty": 3,
      "price": 89.97
    }
  ],
  "subtotal": 468.67,
  "tax": 148.91,
  "total": 792.01,
  "payment_method": "apple_pay"
}


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

[User] Produce a XML document for a contract.

[Assistant]
Approach:
1. Task: Create contract 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"?>
<contract>
<contract_id>CTR-324198</contract_id>
<parties>
<name>Alvarado-Barnes</name>
<role>party_a</role>
</parties>
<parties>
<name>Lopez, Price and Melendez</name>
<role>party_b</role>
</parties>
<effective_date>2026-01-06</effective_date>
<term_months>34</term_months>
<value>725205</value>
<status>pending</status>
</contract>


[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-308726",
  "name": "Cross-platform client-server attitude",
  "category": "electronics",
  "price": 875.12,
  "currency": "USD",
  "stock": 161,
  "is_available": true,
  "rating": 1.18,
  "reviews": 705,
  "specs": {
    "weight_kg": 37.34,
    "dimensions": "78x81x41cm"
  }
}

[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-308726</product_id>
<name>Cross-platform client-server attitude</name>
<category>electronics</category>
<price>875.12</price>
<currency>USD</currency>
<stock>161</stock>
<is_available>True</is_available>
<rating>1.18</rating>
<reviews>705</reviews>
<specs>
<weight_kg>37.34</weight_kg>
<dimensions>78x81x41cm</dimensions>
</specs>
</product_listing>


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

[User] Produce a JSON document for a contract.

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

Output:
{
  "contract_id": "CTR-313579",
  "parties": [
    {
      "name": "Roberts, Newton and Ortiz",
      "role": "party_a"
    },
    {
      "name": "Garcia PLC",
      "role": "party_b"
    }
  ],
  "effective_date": "2026-01-01",
  "term_months": 55,
  "value": 108642,
  "status": "active"
}


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

[User]
Transform this CSV data into TOML format:
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
,"Guy generation provide economy test bit. Page cost and.
Arm test ok green. Likely card reality schoo",,2026-01-06,22,,,,PROD-108019,4,REV-8549692,,,,,Development know write believe teacher ability.,a4c4fbe3-7a0e-49f5-b14b-2ab1ca2d6ed5,True
books,,USD,,,True,Persistent explicit complexity,258.43,PROD-964415,4.63,,413,79x78x48cm,36.71,140,,,
clothing,,USD,,,True,Customer-focused systemic time-frame,716.71,PROD-482790,1.49,,101,71x89x36cm,40.1,373,,,
clothing,,USD,,,True,Monitored tertiary groupware,15.29,PROD-105916,4.82,,899,37x45x98cm,3.3,949,,,
books,,USD,,,True,Integrated homogeneous customer loyalty,978.79,PROD-319686,1.85,,914,54x20x47cm,45.96,520,,,

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

Output:
review_id = "REV-8549692"
product_id = "PROD-108019"
user_id = "a4c4fbe3-7a0e-49f5-b14b-2ab1ca2d6ed5"
rating = 4
title = "Development know write believe teacher ability."
content = "Guy generation provide economy test bit. Page cost and.\nArm test ok green. Likely card reality school stop something those.\nYour spend discuss yeah hear. Same language box us magazine simple."
date = "2026-01-06"
verified_purchase = true
helpful_votes = 22


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<sales_analytics>
<period>November 2022</period>
<total_revenue>9138741</total_revenue>
<units_sold>89798</units_sold>
<channels>
<name>wholesale</name>
<revenue>1234153</revenue>
<growth>40.64</growth>
</channels>
<channels>
<name>online</name>
<revenue>991509</revenue>
<growth>-4.15</growth>
</channels>
<top_products>
<sku>SKU-9585</sku>
<sales>30234</sales>
</top_products>
<top_products>
<sku>SKU-8072</sku>
<sales>57362</sales>
</top_products>
<top_products>
<sku>SKU-4011</sku>
<sales>249730</sales>
</top_products>
</sales_analytics>

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

Output:
{
  "period": "November 2022",
  "total_revenue": 9138741,
  "units_sold": 89798,
  "channels": [
    {
      "name": "wholesale",
      "revenue": 1234153,
      "growth": 40.64
    },
    {
      "name": "online",
      "revenue": 991509,
      "growth": -4.15
    }
  ],
  "top_products": [
    {
      "sku": "SKU-9585",
      "sales": 30234
    },
    {
      "sku": "SKU-8072",
      "sales": 57362
    },
    {
      "sku": "SKU-4011",
      "sales": 249730
    }
  ]
}


[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"?>
<student_assessment>
<scores>
<question>1</question>
<points_earned>8</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>4</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>3</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>4</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>8</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>10</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>4</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>0</points_earned>
<points_possible>10</points_possible>
</scores>
<grade>C</grade>
<date>2026-01-01</date>
</student_assessment>

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

Output:
{
  "scores": [
    {
      "question": 1,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 8,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 10,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 0,
      "points_possible": 10
    }
  ],
  "grade": "C",
  "date": "2026-01-01"
}


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

[User] Output product listing as JSON.

[Assistant]
Approach:
1. Task: Create product listing 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:
{
  "product_id": "PROD-685161",
  "name": "Balanced demand-driven capacity",
  "category": "clothing",
  "price": 554.83,
  "currency": "USD",
  "stock": 872,
  "is_available": true,
  "rating": 3.32,
  "reviews": 212,
  "specs": {
    "weight_kg": 39.83,
    "dimensions": "86x88x63cm"
  }
}


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

[User] Create a JSON representation of clinical note.

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

Output:
{
  "encounter_date": "2026-01-03",
  "note_id": "CN-2646438",
  "patient": {
    "mrn": "MRN-771263",
    "age": 41,
    "gender": "M"
  }
}


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

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

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

Output:
post_id: POST-29576154
platform: instagram
user_id: b3774d2a-dced-4164-bd7b-7d043d7ec920
username: boydkaren
content: Responsibility this statement area thing imagine free. Under quickly treatment
  ever end social military. Majority before treatment decide.
timestamp: '2026-01-07T13:51:27.160344'
hashtags:
- '#involve'
- '#fact'
- '#rest'
engagement:
  likes: 923
  shares: 56
  comments: 396


[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: 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:
period = "May 2020"
total_revenue = 534039
units_sold = 34851
[[channels]]
name = "retail"
revenue = 707158
growth = 43.16

[[channels]]
name = "wholesale"
revenue = 2548868
growth = 26.24

[[top_products]]
sku = "SKU-6020"
sales = 18280

[[top_products]]
sku = "SKU-3349"
sales = 458703

[[top_products]]
sku = "SKU-8781"
sales = 265385


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

[User] Produce a CSV document for a 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
,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
books,,USD,,,True,Re-contextualized executive implementation,266.1,PROD-482189,1.07,,21,24x60x94cm,41.45,868,,,
clothing,,USD,,,True,Proactive full-range framework,80.19,PROD-142533,3.04,,543,22x50x27cm,27.75,190,,,
electronics,,USD,,,True,Progressive disintermediate pricing structure,582.78,PROD-819363,2.25,,593,86x67x66cm,2.76,328,,,


[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-842353",
  "name": "Synergistic bottom-line conglomeration",
  "category": "books",
  "price": 609.49,
  "currency": "USD",
  "stock": 399,
  "is_available": true,
  "rating": 1.05,
  "reviews": 570,
  "specs": {
    "weight_kg": 25.04,
    "dimensions": "30x19x82cm"
  }
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<product_listing>
<product_id>PROD-842353</product_id>
<name>Synergistic bottom-line conglomeration</name>
<category>books</category>
<price>609.49</price>
<currency>USD</currency>
<stock>399</stock>
<is_available>True</is_available>
<rating>1.05</rating>
<reviews>570</reviews>
<specs>
<weight_kg>25.04</weight_kg>
<dimensions>30x19x82cm</dimensions>
</specs>
</product_listing>


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

[User]
Transform this JSON data into XML format:
{
  "period": "June 2021",
  "total_revenue": 4317671,
  "units_sold": 11582,
  "channels": [
    {
      "name": "wholesale",
      "revenue": 2780960,
      "growth": 22.76
    },
    {
      "name": "retail",
      "revenue": 4140341,
      "growth": -9.84
    }
  ],
  "top_products": [
    {
      "sku": "SKU-8636",
      "sales": 261407
    },
    {
      "sku": "SKU-9950",
      "sales": 107242
    },
    {
      "sku": "SKU-8311",
      "sales": 494004
    }
  ]
}

[Assistant]
Approach:
1. Task: Convert sales analytics 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"?>
<sales_analytics>
<period>June 2021</period>
<total_revenue>4317671</total_revenue>
<units_sold>11582</units_sold>
<channels>
<name>wholesale</name>
<revenue>2780960</revenue>
<growth>22.76</growth>
</channels>
<channels>
<name>retail</name>
<revenue>4140341</revenue>
<growth>-9.84</growth>
</channels>
<top_products>
<sku>SKU-8636</sku>
<sales>261407</sales>
</top_products>
<top_products>
<sku>SKU-9950</sku>
<sales>107242</sales>
</top_products>
<top_products>
<sku>SKU-8311</sku>
<sales>494004</sales>
</top_products>
</sales_analytics>


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

[User] Generate news article data in JSON format.

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

Output:
{
  "article_id": "ART-8136358",
  "headline": "Realigned multimedia paradigm",
  "author": "Brian White",
  "published": "2026-01-02T14:21:25.908532",
  "section": "Sports",
  "content": "Give model worry sense. Including reflect teacher near image.\nCulture kitchen run first would. Agency media particularly past office every.\nBag water address admit. Skin tend Mr significant dark pretty. Painting water campaign.",
  "tags": [
    "involve",
    "service",
    "along",
    "stand"
  ],
  "views": 7987,
  "shares": 4175
}


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

[User]
Convert the following JSON to XML:
{
  "product_id": "PROD-210763",
  "name": "Team-oriented grid-enabled support",
  "category": "clothing",
  "price": 360.14,
  "currency": "USD",
  "stock": 657,
  "is_available": true,
  "rating": 3.34,
  "reviews": 923,
  "specs": {
    "weight_kg": 14.15,
    "dimensions": "28x80x26cm"
  }
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<product_listing>
<product_id>PROD-210763</product_id>
<name>Team-oriented grid-enabled support</name>
<category>clothing</category>
<price>360.14</price>
<currency>USD</currency>
<stock>657</stock>
<is_available>True</is_available>
<rating>3.34</rating>
<reviews>923</reviews>
<specs>
<weight_kg>14.15</weight_kg>
<dimensions>28x80x26cm</dimensions>
</specs>
</product_listing>


[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"?>
<lab_result>
<result_id>LAB-8093004</result_id>
<patient_mrn>MRN-777027</patient_mrn>
<order_date>2026-01-05</order_date>
<panel>CMP</panel>
<results>
<test>Glucose</test>
<value>140.2</value>
<unit>mg/dL</unit>
<flag>low</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>96.3</value>
<unit>g/dL</unit>
<flag>normal</flag>
</results>
<results>
<test>Glucose</test>
<value>185.0</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Glucose</test>
<value>139.7</value>
<unit>g/dL</unit>
<flag>low</flag>
</results>
</lab_result>

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

Output:
{
  "result_id": "LAB-8093004",
  "patient_mrn": "MRN-777027",
  "order_date": "2026-01-05",
  "panel": "CMP",
  "results": [
    {
      "test": "Glucose",
      "value": 140.2,
      "unit": "mg/dL",
      "flag": "low"
    },
    {
      "test": "Hemoglobin",
      "value": 96.3,
      "unit": "g/dL",
      "flag": "normal"
    },
    {
      "test": "Glucose",
      "value": 185.0,
      "unit": "g/dL",
      "flag": "high"
    },
    {
      "test": "Glucose",
      "value": 139.7,
      "unit": "g/dL",
      "flag": "low"
    }
  ]
}


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

[User] Output experiment result as TOML.

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

Output:
experiment_id = "EXP-330074"
title = "Effect of politics on stop"
conclusion = "non-significant"
[[results]]
metric = "efficacy"
baseline = 34.54
endpoint = 53.32
p_value = 0.0487

[[results]]
metric = "safety"
baseline = 10.4
endpoint = 13.84
p_value = 0.1164

[[results]]
metric = "efficacy"
baseline = 78.27
endpoint = 47.78
p_value = 0.0781

[methodology]
design = "RCT"
sample_size = 328
duration_days = 247


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

[User] Create a CSV representation of sales analytics.

[Assistant]
Approach:
1. Task: Create sales analytics in CSV
2. Complexity: 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"": ""wholesale"", ""revenue"": 3169564, ""growth"": 42.35}, {""name"": ""retail"", ""revenue"": 2683860, ",,,,,November 2021,,,,,"[{""sku"": ""SKU-9614"", ""sales"": 412171}, {""sku"": ""SKU-7573"", ""sales"": 203488}, {""sku"": ""SKU-4372"", ""sa",8992427,30636
Help prove half both. Oil picture society because option window certain. Take goal black water refle,"[{""name"": ""Eric Dawson"", ""affiliation"": ""Shields Group"", ""email"": ""aaron01@example.org""}, {""name"": """,,281,None,"[""industry"", ""itself"", ""statement""]",arXiv:2024.53299,,10.2208/cbrJ,Science,2024,Programmable impactful policy,,,
"Much another view type. Notice before a music trial.
Him health imagine set southern. Available Mrs ","[{""name"": ""Mrs. Melissa Graham"", ""affiliation"": ""Logan, Wheeler and Joyce"", ""email"": ""brownmicheal@e",,238,None,"[""well"", ""my"", ""production"", ""theory""]",arXiv:2024.41729,,10.1142/iUkl,Nature,2023,Sharable full-range utilization,,,


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

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

[Assistant]
Approach:
1. Task: Create sales analytics in XML
2. Complexity: 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"?>
<sales_analytics>
<period>September 2022</period>
<total_revenue>4880286</total_revenue>
<units_sold>74173</units_sold>
<channels>
<name>retail</name>
<revenue>2000312</revenue>
<growth>0.96</growth>
</channels>
<channels>
<name>wholesale</name>
<revenue>3751658</revenue>
<growth>-3.19</growth>
</channels>
<top_products>
<sku>SKU-6977</sku>
<sales>264067</sales>
</top_products>
<top_products>
<sku>SKU-7032</sku>
<sales>443161</sales>
</top_products>
<top_products>
<sku>SKU-1793</sku>
<sales>209512</sales>
</top_products>
</sales_analytics>


[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>
<contract_id>CTR-370819</contract_id>
<parties>
<name>Stewart, Thompson and Rogers</name>
<role>party_a</role>
</parties>
<parties>
<name>Jackson, Griffin and Flowers</name>
<role>party_b</role>
</parties>
<effective_date>2026-01-01</effective_date>
<term_months>13</term_months>
<value>109351</value>
<status>active</status>
</contract>

[Assistant]
Approach:
1. Task: Convert contract 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:
{
  "contract_id": "CTR-370819",
  "parties": [
    {
      "name": "Stewart, Thompson and Rogers",
      "role": "party_a"
    },
    {
      "name": "Jackson, Griffin and Flowers",
      "role": "party_b"
    }
  ],
  "effective_date": "2026-01-01",
  "term_months": 13,
  "value": 109351,
  "status": "active"
}


[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: 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-239354"
name = "User-centric tertiary contingency"
category = "electronics"
price = 998.51
currency = "USD"
stock = 842
is_available = true
rating = 2.36
reviews = 630

[specs]
weight_kg = 0.61
dimensions = "88x23x10cm"


[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>Mcintyre, French and Sherman</company>
<ticker>GRIC</ticker>
<quarter>Q4 2021</quarter>
<revenue>78125638</revenue>
<expenses>13448897</expenses>
<net_income>14876002</net_income>
<eps>9.04</eps>
<metrics>
<profit_margin>9.81</profit_margin>
<roe>23.34</roe>
</metrics>
</financial_report>

[Assistant]
Approach:
1. Task: Convert financial report 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:
{
  "company": "Mcintyre, French and Sherman",
  "ticker": "GRIC",
  "quarter": "Q4 2021",
  "revenue": 78125638,
  "expenses": 13448897,
  "net_income": 14876002,
  "eps": 9.04,
  "metrics": {
    "profit_margin": 9.81,
    "roe": 23.34
  }
}


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

[User]
Convert the following CSV to YAML:
content,engagement_comments,engagement_likes,engagement_shares,hashtags,platform,post_id,timestamp,user_id,username
"Serious degree upon late.
Painting throughout direction indicate night. Political business voice str",24,6808,9,"[""#easy"", ""#miss""]",instagram,POST-46905875,2026-01-07T13:51:26.735117,2079b341-d50b-4860-ba15-aa28bbe0f5b3,xhernandez
"Office walk worry toward agent base write. Far beautiful significant before.
List agree job respond.",28,607,30,"[""#ago"", ""#start"", ""#head"", ""#can""]",instagram,POST-73045498,2026-01-07T13:51:26.738121,af2af60b-ef5b-4c0b-8fed-9298a42103ab,qking
Require main into which. Have almost energy because usually short. Draw thus attorney physical almos,400,4804,359,"[""#six"", ""#manager"", ""#medical"", ""#travel""]",instagram,POST-61571242,2026-01-07T13:51:26.738474,adf1086f-f423-4a59-af84-529346f3fcbd,daniel04

[Assistant]
Approach:
1. Task: Convert social media post from CSV 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:
post_id: POST-46905875
platform: instagram
user_id: 2079b341-d50b-4860-ba15-aa28bbe0f5b3
username: xhernandez
content: 'Serious degree upon late.

  Painting throughout direction indicate night. Political business voice street child.
  Across between ready. Majority red mission prepare state.'
timestamp: '2026-01-07T13:51:26.735117'
hashtags:
- '#easy'
- '#miss'
engagement:
  likes: 6808
  shares: 9
  comments: 24


[System] You are an expert in 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: Centralized web-enabled hardware API
  version: 1.0.0
paths:
  /improve:
    get:
      summary: Act attention yes herself significant recent.
      parameters:
      - name: param0
        in: query
        type: string
      - name: param1
        in: query
        type: string
      - name: param2
        in: query
        type: string
      responses:
        '200':
          description: Success
        '400':
          description: Bad Request


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

[User] Produce a JSON document for a prescription.

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

Output:
{
  "rx_id": "RX-4278484",
  "patient_mrn": "MRN-990980",
  "prescriber": "Andrew Kelly",
  "date": "2026-01-06",
  "medications": [
    {
      "name": "Metformin",
      "dosage": "10mg",
      "frequency": "BID",
      "quantity": 30
    },
    {
      "name": "Atorvastatin",
      "dosage": "10mg",
      "frequency": "BID",
      "quantity": 90
    }
  ]
}


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

[User] Create a YAML representation of sales analytics.

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

Output:
period: January 2024
total_revenue: 3091656
units_sold: 63856
channels:
- name: wholesale
  revenue: 2739604
  growth: -0.52
- name: online
  revenue: 247982
  growth: 14.46
top_products:
- sku: SKU-7268
  sales: 409348
- sku: SKU-4030
  sales: 70087
- sku: SKU-4380
  sales: 298376


[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-313579"
effective_date = "2026-01-01"
term_months = 55
value = 108642
status = "active"
[[parties]]
name = "Roberts, Newton and Ortiz"
role = "party_a"

[[parties]]
name = "Garcia PLC"
role = "party_b"


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

[User] Create a JSON representation of experiment result.

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

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


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

[User] Generate experiment result data in JSON format.

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

Output:
{
  "experiment_id": "EXP-160417",
  "title": "Effect of agree on both",
  "methodology": {
    "design": "cohort",
    "sample_size": 663,
    "duration_days": 354
  },
  "results": [
    {
      "metric": "safety",
      "baseline": 13.92,
      "endpoint": 49.07,
      "p_value": 0.4102
    },
    {
      "metric": "safety",
      "baseline": 15.99,
      "endpoint": 65.81,
      "p_value": 0.3043
    },
    {
      "metric": "efficacy",
      "baseline": 46.51,
      "endpoint": 82.23,
      "p_value": 0.4775
    }
  ],
  "conclusion": "non-significant"
}


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

[User] Generate financial report data in TOML format.

[Assistant]
Approach:
1. Task: Create financial report in TOML
2. Complexity: 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 = "Leon-Lewis"
ticker = "FGCI"
quarter = "Q4 2022"
revenue = 56885685
expenses = 46362888
net_income = 14538939
eps = 7.9

[metrics]
profit_margin = 25.04
roe = 5.27


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

[User] Generate product listing data in CSV format.

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

Output:
category,currency,is_available,name,price,product_id,rating,reviews,specs_dimensions,specs_weight_kg,stock
books,USD,True,Organic demand-driven installation,698.66,PROD-942707,4.45,103,66x30x83cm,32.63,819
electronics,USD,True,Triple-buffered optimizing middleware,638.56,PROD-568809,4.06,709,41x42x14cm,25.98,815
clothing,USD,True,Expanded next generation frame,775.55,PROD-749642,4.97,651,52x29x67cm,35.66,747
books,USD,True,Public-key high-level encryption,819.66,PROD-561106,2.36,830,17x96x40cm,32.31,642