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

[User]
Convert the following TOML to JSON:
contract_id = "CTR-896633"
effective_date = "2026-01-03"
term_months = 21
value = 926875
status = "pending"
[[parties]]
name = "Smith-Cross"
role = "party_a"

[[parties]]
name = "Carrillo and Sons"
role = "party_b"

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

Output:
{
  "contract_id": "CTR-896633",
  "parties": [
    {
      "name": "Smith-Cross",
      "role": "party_a"
    },
    {
      "name": "Carrillo and Sons",
      "role": "party_b"
    }
  ],
  "effective_date": "2026-01-03",
  "term_months": 21,
  "value": 926875,
  "status": "pending"
}


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

[User] Generate customer review data in XML format.

[Assistant]
Approach:
1. Task: Create customer review 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"?>
<customer_review>
<review_id>REV-4787173</review_id>
<product_id>PROD-746934</product_id>
<user_id>a1638e54-91af-4e5f-be10-465327f3fbf6</user_id>
<rating>4</rating>
<title>Rock company surface either million.</title>
<content>Suddenly plant stay thank project hand me. Commercial his road carry training trip.</content>
<date>2026-01-02</date>
<verified_purchase>True</verified_purchase>
<helpful_votes>3</helpful_votes>
</customer_review>


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

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

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

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


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

[User]
Convert the following YAML to XML:
contract_id: CTR-544771
parties:
- name: Prince-Finley
  role: party_a
- name: Stone LLC
  role: party_b
effective_date: '2026-01-02'
term_months: 52
value: 394049
status: active

[Assistant]
Approach:
1. Task: Convert contract 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"?>
<contract>
<contract_id>CTR-544771</contract_id>
<parties>
<name>Prince-Finley</name>
<role>party_a</role>
</parties>
<parties>
<name>Stone LLC</name>
<role>party_b</role>
</parties>
<effective_date>2026-01-02</effective_date>
<term_months>52</term_months>
<value>394049</value>
<status>active</status>
</contract>


[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-7317178
headline: Sharable 5thgeneration framework
author: Judy Garner
published: '2026-01-07T07:35:28.380949'
section: Politics
content: 'Cover whole myself late last month authority. Make away choose difficult.

  Shoulder so support like let increase improve movie. Gun career hair necessary improve
  operation detail.'
tags:
- cover
- people
- available
- above
- service
views: 84087
shares: 2480


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

[User] Create a JSON representation of customer review.

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

Output:
{
  "date": "2026-01-05",
  "title": "Teach why painting per short.",
  "rating": 4
}


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

[User] Create a YAML representation of research paper.

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

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


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Assimilated neutral archive API</title>
<version>1.0.0</version>
</info>
<paths>
</sea>
<get>
<summary>Team happen challenge address expert manage beyond</summary>
<parameters>
<name>param0</name>
<in>query</in>
<type>string</type>
</parameters>
<parameters>
<name>param1</name>
<in>query</in>
<type>string</type>
</parameters>
<parameters>
<name>param2</name>
<in>query</in>
<type>string</type>
</parameters>
<responses>
<200>
<description>Success</description>
</200>
<400>
<description>Bad Request</description>
</400>
</responses>
</get>
<//sea>
</paths>
</api_specification>

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

Output:
{
  "openapi": "3.0.0",
  "info": {
    "title": "Assimilated neutral archive API",
    "version": "1.0.0"
  },
  "paths": {
    "/sea": {
      "get": {
        "summary": "Team happen challenge address expert manage beyond",
        "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] Produce a CSV document for a api specification.

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

Output:
abstract,authors,citations,funding_source,info_title,info_version,keywords,openapi,paper_id,paths_/million_get_parameters,paths_/million_get_responses_200_description,paths_/million_get_responses_400_description,paths_/million_get_summary,publication_doi,publication_venue,publication_year,title
,,,,Grass-roots 6thgeneration ability API,1.0.0,,3.0.0,,"[{""name"": ""param0"", ""in"": ""query"", ""type"": ""string""}]",Success,Bad Request,About little above investment already magazine.,,,,
Do remember detail attention take probably. Professional than building sign. Seat activity yard way.,"[{""name"": ""William Summers"", ""affiliation"": ""Morrison Ltd"", ""email"": ""ewilkins@example.org""}, {""name",163,Harvey Ltd,,,"[""state"", ""action"", ""memory""]",,arXiv:2024.14640,,,,,10.6708/cIjJ,Science,2020,Streamlined radical solution
People job also take its read. Budget already network white thank include mission.,"[{""name"": ""Richard Owens"", ""affiliation"": ""Mcmahon, Moran and Hale"", ""email"": ""crosskatie@example.ne",223,None,,,"[""later"", ""material"", ""apply"", ""employee"", ""success""]",,arXiv:2022.29242,,,,,10.7298/MzJv,Science,2023,Extended client-driven core


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

[User] Output api specification as CSV.

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

Output:
abstract,authors,citations,funding_source,info_title,info_version,keywords,openapi,paper_id,paths_/pass_get_parameters,paths_/pass_get_responses_200_description,paths_/pass_get_responses_400_description,paths_/pass_get_summary,publication_doi,publication_venue,publication_year,title
,,,,Upgradable 4thgeneration middleware API,1.0.0,,3.0.0,,"[{""name"": ""param0"", ""in"": ""query"", ""type"": ""string""}]",Success,Bad Request,Story amount nor bed night get message.,,,,
Admit me citizen this like skin. Word Democrat always drive year. She possible mean to open body fin,"[{""name"": ""Shannon Miranda"", ""affiliation"": ""Nelson Inc"", ""email"": ""rguerra@example.org""}, {""name"": ",498,None,,,"[""pass"", ""especially"", ""west""]",,arXiv:2024.49317,,,,,10.3884/ZfIw,Science,2022,Focused solution-oriented application
Type this young reality benefit own. Point former sure push interesting ask. Minute home still anyon,"[{""name"": ""David Edwards"", ""affiliation"": ""Gonzalez, Cooley and Kelley"", ""email"": ""raymond62@example",81,"Howell, Edwards and Curry",,,"[""whole"", ""water"", ""truth""]",,arXiv:2020.39392,,,,,10.9606/CPxC,Science,2023,Compatible 24/7 adapter


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

[User]
Transform this YAML data into JSON format:
review_id: REV-8075236
product_id: PROD-326180
user_id: e70c9373-b1ad-41a5-8939-e3c28041d8f5
rating: 4
title: Most teacher Mrs system watch.
content: 'Address music major. Magazine three about. Security ready result improve.

  Hand other collection name wife remain. Speech perhaps newspaper. Talk place third
  about writer billion physical.'
date: '2026-01-03'
verified_purchase: false
helpful_votes: 50

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

Output:
{
  "review_id": "REV-8075236",
  "product_id": "PROD-326180",
  "user_id": "e70c9373-b1ad-41a5-8939-e3c28041d8f5",
  "rating": 4,
  "title": "Most teacher Mrs system watch.",
  "content": "Address music major. Magazine three about. Security ready result improve.\nHand other collection name wife remain. Speech perhaps newspaper. Talk place third about writer billion physical.",
  "date": "2026-01-03",
  "verified_purchase": false,
  "helpful_votes": 50
}


[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:
{
  "company": "Rodriguez, Sanchez and French",
  "ticker": "TOPI",
  "quarter": "Q3 2022",
  "revenue": 30596216,
  "expenses": 79425858,
  "net_income": 10739155,
  "eps": 9.27,
  "metrics": {
    "profit_margin": 21.79,
    "roe": 22.32
  }
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<financial_report>
<company>Rodriguez, Sanchez and French</company>
<ticker>TOPI</ticker>
<quarter>Q3 2022</quarter>
<revenue>30596216</revenue>
<expenses>79425858</expenses>
<net_income>10739155</net_income>
<eps>9.27</eps>
<metrics>
<profit_margin>21.79</profit_margin>
<roe>22.32</roe>
</metrics>
</financial_report>


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

[User] Generate clinical note data in CSV format.

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

Output:
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"": ""diabetes"", ""icd10"": ""I70""}, {""problem"": ""diabetes"", ""icd10"": ""J87""}]",headache,2026-01-01,CN-9947361,30,M,MRN-432243,118/82,91,101.5
"[{""problem"": ""diabetes"", ""icd10"": ""K27""}, {""problem"": ""hypertension"", ""icd10"": ""K78""}, {""problem"": """,headache,2026-01-02,CN-6438068,31,F,MRN-257133,133/70,68,97.3
"[{""problem"": ""diabetes"", ""icd10"": ""J54""}]",fever,2026-01-04,CN-6728848,65,F,MRN-312542,152/101,70,102.3


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

[User] Output course syllabus as TOML.

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

Output:
instructor = "Ryan Griffin"
course_id = "CRS-4864"
code = "NLW161"


[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
,Hear media safe I visit language. Difference part thousand. Society inside describe decision.,,2026-01-06,16,,,,PROD-143836,2,REV-3982215,,,,,Fight and building toward office.,0dd51960-e54b-4127-90d4-b32b17839969,True
books,,USD,,,True,Managed global process improvement,126.18,PROD-869242,3.63,,405,20x85x87cm,42.27,291,,,
electronics,,USD,,,True,Decentralized didactic architecture,766.66,PROD-544058,3.92,,385,45x35x83cm,25.31,686,,,


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

[User] Create a JSON representation of student assessment.

[Assistant]
Approach:
1. Task: Create student assessment in JSON
2. Complexity: 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:
{
  "total_score": 96,
  "percentage": 61.11,
  "student_id": "STU-785727"
}


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

[User] Produce a CSV document for a prescription.

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

Output:
date,medications,patient_mrn,prescriber,rx_id
2026-01-01,"[{""name"": ""Atorvastatin"", ""dosage"": ""10mg"", ""frequency"": ""BID"", ""quantity"": 60}]",,,RX-5523111
2026-01-06,"[{""name"": ""Metformin"", ""dosage"": ""20mg"", ""frequency"": ""BID"", ""quantity"": 30}]",MRN-744561,William Vargas,RX-4860429
2026-01-01,"[{""name"": ""Atorvastatin"", ""dosage"": ""10mg"", ""frequency"": ""TID"", ""quantity"": 60}]",MRN-706968,Adam Harvey,RX-5550531
2026-01-05,"[{""name"": ""Lisinopril"", ""dosage"": ""20mg"", ""frequency"": ""BID"", ""quantity"": 30}]",MRN-553489,Timothy Bean,RX-1383524


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

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


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<student_assessment>
<assessment_id>ASMT-613322</assessment_id>
<student_id>STU-814570</student_id>
<course_id>CRS-3548</course_id>
<type>assignment</type>
<date>2026-01-01</date>
<scores>
<question>1</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>10</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>6</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>7</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>7</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>64</total_score>
<percentage>69.35</percentage>
<grade>C</grade>
</student_assessment>


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

[User] Generate customer review data in JSON format.

[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-5832770",
  "product_id": "PROD-688379",
  "user_id": "d5e035fb-55b8-4fae-85aa-504fb2b837bd",
  "rating": 3,
  "title": "Investment great beat fear step Democrat treat.",
  "content": "Near season take foot decade hold some meet.\nPretty season exist old turn consumer particularly star. Step receive unit different.",
  "date": "2026-01-02",
  "verified_purchase": false,
  "helpful_votes": 62
}


[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"?>
<prescription>
<rx_id>RX-8706225</rx_id>
<patient_mrn>MRN-970748</patient_mrn>
<prescriber>Brady Keller</prescriber>
<date>2026-01-01</date>
<medications>
<name>Lisinopril</name>
<dosage>5mg</dosage>
<frequency>TID</frequency>
<quantity>30</quantity>
</medications>
</prescription>

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

Output:
{
  "rx_id": "RX-8706225",
  "patient_mrn": "MRN-970748",
  "prescriber": "Brady Keller",
  "date": "2026-01-01",
  "medications": [
    {
      "name": "Lisinopril",
      "dosage": "5mg",
      "frequency": "TID",
      "quantity": 30
    }
  ]
}


[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"?>
<transaction_record>
<subtotal>205.31</subtotal>
<payment_method>apple_pay</payment_method>
<total>1732.06</total>
</transaction_record>

[Assistant]
Approach:
1. Task: Convert transaction record 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:
{
  "subtotal": 205.31,
  "payment_method": "apple_pay",
  "total": 1732.06
}


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<transaction_record>
<subtotal>1655.93</subtotal>
<items>
<sku>SKU-62708</sku>
<qty>3</qty>
<price>121.39</price>
</items>
<tax>19.12</tax>
<total>1424.63</total>
</transaction_record>


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

[User]
Reformat the data below from TOML to YAML:
contract_id = "CTR-324198"
effective_date = "2026-01-06"
term_months = 34
value = 725205
status = "pending"
[[parties]]
name = "Alvarado-Barnes"
role = "party_a"

[[parties]]
name = "Lopez, Price and Melendez"
role = "party_b"

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

Output:
contract_id: CTR-324198
parties:
- name: Alvarado-Barnes
  role: party_a
- name: Lopez, Price and Melendez
  role: party_b
effective_date: '2026-01-06'
term_months: 34
value: 725205
status: pending


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

[User]
Convert the following JSON to XML:
{
  "course_id": "CRS-4164",
  "code": "RVR286",
  "title": "Team-oriented incremental info-mediaries 101",
  "instructor": "Shannon Miller",
  "credits": 3,
  "term": "Fall 2023",
  "schedule": [
    {
      "week": 1,
      "topic": "stuff"
    },
    {
      "week": 2,
      "topic": "professional"
    },
    {
      "week": 3,
      "topic": "hard"
    },
    {
      "week": 4,
      "topic": "rather"
    },
    {
      "week": 5,
      "topic": "lawyer"
    },
    {
      "week": 6,
      "topic": "camera"
    },
    {
      "week": 7,
      "topic": "focus"
    },
    {
      "week": 8,
      "topic": "spend"
    },
    {
      "week": 9,
      "topic": "couple"
    },
    {
      "week": 10,
      "topic": "quickly"
    }
  ],
  "grading": {
    "homework": 30,
    "midterm": 30,
    "final": 40
  }
}

[Assistant]
Approach:
1. Task: Convert course syllabus 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"?>
<course_syllabus>
<course_id>CRS-4164</course_id>
RVR286
<title>Team-oriented incremental info-mediaries 101</title>
<instructor>Shannon Miller</instructor>
<credits>3</credits>
<term>Fall 2023</term>
<schedule>
<week>1</week>
<topic>stuff</topic>
</schedule>
<schedule>
<week>2</week>
<topic>professional</topic>
</schedule>
<schedule>
<week>3</week>
<topic>hard</topic>
</schedule>
<schedule>
<week>4</week>
<topic>rather</topic>
</schedule>
<schedule>
<week>5</week>
<topic>lawyer</topic>
</schedule>
<schedule>
<week>6</week>
<topic>camera</topic>
</schedule>
<schedule>
<week>7</week>
<topic>focus</topic>
</schedule>
<schedule>
<week>8</week>
<topic>spend</topic>
</schedule>
<schedule>
<week>9</week>
<topic>couple</topic>
</schedule>
<schedule>
<week>10</week>
<topic>quickly</topic>
</schedule>
<grading>
<homework>30</homework>
<midterm>30</midterm>
<final>40</final>
</grading>
</course_syllabus>


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

[User]
Convert the following CSV to TOML:
assessment,chief_complaint,encounter_date,note_id,patient_age,patient_gender,patient_mrn,vitals_bp,vitals_hr,vitals_temp_f
"[{""problem"": ""diabetes"", ""icd10"": ""K80""}]",fever,2026-01-05,CN-5754690,32,M,MRN-521303,101/104,85,99.3
"[{""problem"": ""diabetes"", ""icd10"": ""K81""}, {""problem"": ""diabetes"", ""icd10"": ""J79""}]",headache,2026-01-03,CN-5422353,41,F,MRN-292601,161/78,63,102.7
"[{""problem"": ""diabetes"", ""icd10"": ""I51""}]",chest pain,2026-01-01,CN-5001095,40,M,MRN-496916,127/60,83,97.8
"[{""problem"": ""hypertension"", ""icd10"": ""J35""}, {""problem"": ""diabetes"", ""icd10"": ""K87""}, {""problem"": """,chest pain,2026-01-01,CN-8606609,35,M,MRN-952093,96/99,65,100.2
"[{""problem"": ""hypertension"", ""icd10"": ""K96""}]",chest pain,2026-01-01,CN-5063066,81,F,MRN-389839,164/90,94,98.0

[Assistant]
Approach:
1. Task: Convert clinical note 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:
note_id = "CN-5754690"
encounter_date = "2026-01-05"
chief_complaint = "fever"
[[assessment]]
problem = "diabetes"
icd10 = "K80"

[patient]
mrn = "MRN-521303"
age = 32
gender = "M"

[vitals]
bp = "101/104"
hr = 85
temp_f = 99.3


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

[User] Output contract as YAML.

[Assistant]
Approach:
1. Task: Create contract 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:
contract_id: CTR-640570
parties:
- name: Mitchell-Clark
  role: party_a
- name: Simmons-Marquez
  role: party_b
effective_date: '2026-01-06'
term_months: 52
value: 450714
status: pending


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

[Assistant]
Approach:
1. Task: Convert prescription 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"?>
<prescription>
<medications>
<name>Atorvastatin</name>
<dosage>10mg</dosage>
<frequency>BID</frequency>
<quantity>60</quantity>
</medications>
<rx_id>RX-5523111</rx_id>
<date>2026-01-01</date>
</prescription>


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

[User] Output sales analytics as CSV.

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

Output:
abstract,authors,channels,citations,funding_source,keywords,paper_id,period,publication_doi,publication_venue,publication_year,title,top_products,total_revenue,units_sold
,,"[{""name"": ""online"", ""revenue"": 906832, ""growth"": -8.93}, {""name"": ""wholesale"", ""revenue"": 2437365, """,,,,,May 2020,,,,,"[{""sku"": ""SKU-7032"", ""sales"": 420063}, {""sku"": ""SKU-9360"", ""sales"": 149398}, {""sku"": ""SKU-9440"", ""sa",9864225,74086
Food true outside draw. Relationship these by shake watch man. Ground recognize some which hot proba,"[{""name"": ""Andrew Smith"", ""affiliation"": ""Knapp PLC"", ""email"": ""henrymike@example.com""}, {""name"": ""J",,370,None,"[""fill"", ""five"", ""better""]",arXiv:2023.17745,,10.4215/DDGD,Cell,2021,Upgradable well-modulated leverage,,,
Claim garden recognize mind occur management prove area. Whose how letter give. Include nature budge,"[{""name"": ""Michael House"", ""affiliation"": ""Hancock, Clark and Franklin"", ""email"": ""makaylasmith@exam",,3,None,"[""third"", ""market"", ""action"", ""I"", ""natural""]",arXiv:2024.21255,,10.3222/fqKt,Cell,2021,Distributed leadingedge complexity,,,
"Hospital you leave lawyer open affect. Hour such human open list grow.
On short off month political ","[{""name"": ""Laurie Flynn"", ""affiliation"": ""Lyons PLC"", ""email"": ""wattspaige@example.net""}, {""name"": """,,487,"Mclaughlin, Higgins and Fox","[""feeling"", ""author"", ""me"", ""then"", ""physical""]",arXiv:2021.29106,,10.9021/fLSB,Nature,2022,Realigned attitude-oriented workforce,,,


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

[User] Generate product listing data in CSV format.

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

Output:
abstract,authors,category,citations,funding_source,keywords,paper_id,price,publication_doi,publication_venue,publication_year,specs_dimensions,specs_weight_kg,stock,title
,,electronics,,,,,218.58,,,,23x92x45cm,38.59,596,
"Fact address game. Site before learn food send because. Measure price whom skin.
Financial house ter","[{""name"": ""Charles Rice"", ""affiliation"": ""Page LLC"", ""email"": ""larrygalvan@example.com""}, {""name"": """,,266,Martin Ltd,"[""vote"", ""letter"", ""environment""]",arXiv:2022.93168,,10.6218/MBxQ,Nature,2022,,,,Adaptive mission-critical protocol
During artist suffer wait simple he indicate organization. Two person today kitchen.,"[{""name"": ""Kristina Austin"", ""affiliation"": ""Beck-Obrien"", ""email"": ""marco09@example.com""}, {""name"":",,284,Blackwell and Sons,"[""drive"", ""morning"", ""drug""]",arXiv:2021.23576,,10.4880/qHey,Science,2021,,,,Cross-platform real-time hub
Build six remember current. Task per nice fact attention result speak push. Apply local pressure pro,"[{""name"": ""Scott Castro MD"", ""affiliation"": ""Williams Group"", ""email"": ""chavezadam@example.org""}, {""",,233,Reyes-Greene,"[""north"", ""exist"", ""market"", ""cause""]",arXiv:2023.18133,,10.7605/Qgmh,Nature,2023,,,,Cross-platform multi-tasking strategy
Language space agent somebody summer.,"[{""name"": ""Zachary Murphy"", ""affiliation"": ""Young-Simmons"", ""email"": ""john71@example.net""}, {""name"":",,469,None,"[""eat"", ""style"", ""option""]",arXiv:2024.63810,,10.7603/kKkD,Nature,2021,,,,Vision-oriented human-resource model


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

[User] Create a XML representation of prescription.

[Assistant]
Approach:
1. Task: Create prescription in XML
2. Complexity: 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-5855932</rx_id>
<patient_mrn>MRN-921122</patient_mrn>
<prescriber>Spencer Smith</prescriber>
<date>2026-01-05</date>
<medications>
<name>Metformin</name>
<dosage>20mg</dosage>
<frequency>daily</frequency>
<quantity>30</quantity>
</medications>
</prescription>


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

[User] Output transaction record as YAML.

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

Output:
txn_id: TXN-30876983
customer_id: b5aca191-66fe-49e0-85ce-2d363d5ef454
timestamp: '2026-01-07T13:51:26.163076'
items:
- sku: SKU-56664
  qty: 2
  price: 285.83
- sku: SKU-25305
  qty: 1
  price: 45.15
- sku: SKU-78820
  qty: 4
  price: 47.49
subtotal: 199.93
tax: 118.13
total: 913.78
payment_method: apple_pay


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

[User] Create a YAML representation of student assessment.

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

Output:
assessment_id: ASMT-871992
student_id: STU-916232
course_id: CRS-5865
type: quiz
date: '2026-01-05'
scores:
- question: 1
  points_earned: 1
  points_possible: 10
- question: 2
  points_earned: 6
  points_possible: 10
- question: 3
  points_earned: 10
  points_possible: 10
- question: 4
  points_earned: 2
  points_possible: 10
- question: 5
  points_earned: 5
  points_possible: 10
- question: 6
  points_earned: 5
  points_possible: 10
- question: 7
  points_earned: 0
  points_possible: 10
- question: 8
  points_earned: 7
  points_possible: 10
- question: 9
  points_earned: 2
  points_possible: 10
- question: 10
  points_earned: 4
  points_possible: 10
- question: 11
  points_earned: 5
  points_possible: 10
total_score: 83
percentage: 70.57
grade: B


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<news_article>
<views>92789</views>
<content>Couple and teacher radio compare consumer. Pass thing much rather light.
Foot four country subject first interview. Defense TV artist to of. Fund miss window scene.
Wish successful movement city door politics measure. Police media TV out word remain as. Report option appear station example role.</content>
<shares>213</shares>
<headline>Re-engineered composite Local Area Network</headline>
<tags>couple</tags>
<tags>this</tags>
<tags>themselves</tags>
<tags>whom</tags>
</news_article>

[Assistant]
Approach:
1. Task: Convert news article 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:
{
  "views": 92789,
  "content": "Couple and teacher radio compare consumer. Pass thing much rather light.\nFoot four country subject first interview. Defense TV artist to of. Fund miss window scene.\nWish successful movement city door politics measure. Police media TV out word remain as. Report option appear station example role.",
  "shares": 213,
  "headline": "Re-engineered composite Local Area Network",
  "tags": [
    "couple",
    "this",
    "themselves",
    "whom"
  ]
}


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

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

[Assistant]
Approach:
1. Task: Create student assessment in TOML
2. Complexity: 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:
total_score = 65
percentage = 51.02
assessment_id = "ASMT-810488"


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

[User]
Reformat the data below from XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<sales_analytics>
<period>June 2021</period>
<total_revenue>1467254</total_revenue>
<units_sold>63744</units_sold>
<channels>
<name>wholesale</name>
<revenue>2975287</revenue>
<growth>-1.88</growth>
</channels>
<channels>
<name>online</name>
<revenue>2665464</revenue>
<growth>14.77</growth>
</channels>
<top_products>
<sku>SKU-1172</sku>
<sales>348860</sales>
</top_products>
<top_products>
<sku>SKU-4431</sku>
<sales>479568</sales>
</top_products>
<top_products>
<sku>SKU-6244</sku>
<sales>245719</sales>
</top_products>
</sales_analytics>

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

Output:
{
  "period": "June 2021",
  "total_revenue": 1467254,
  "units_sold": 63744,
  "channels": [
    {
      "name": "wholesale",
      "revenue": 2975287,
      "growth": -1.88
    },
    {
      "name": "online",
      "revenue": 2665464,
      "growth": 14.77
    }
  ],
  "top_products": [
    {
      "sku": "SKU-1172",
      "sales": 348860
    },
    {
      "sku": "SKU-4431",
      "sales": 479568
    },
    {
      "sku": "SKU-6244",
      "sales": 245719
    }
  ]
}


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

[User]
Convert the following CSV to TOML:
customer_id,items,payment_method,subtotal,tax,timestamp,total,txn_id
681a59bc-1151-4d49-8e75-1af0878315cb,"[{""sku"": ""SKU-50616"", ""qty"": 3, ""price"": 180.94}, {""sku"": ""SKU-82812"", ""qty"": 5, ""price"": 490.31}]",credit_card,948.16,93.65,2026-01-07T13:51:26.087659,1389.7,TXN-98000345
922f5254-ad59-4f90-9740-bf684634228a,"[{""sku"": ""SKU-70076"", ""qty"": 5, ""price"": 386.96}, {""sku"": ""SKU-80036"", ""qty"": 5, ""price"": 147.45}, {",apple_pay,777.16,74.29,2026-01-07T13:51:26.089112,790.22,TXN-90251692
1f5c625d-d023-43eb-b0b2-50b07f77babc,"[{""sku"": ""SKU-98932"", ""qty"": 5, ""price"": 478.63}, {""sku"": ""SKU-88322"", ""qty"": 2, ""price"": 65.75}, {""",paypal,447.17,89.13,2026-01-07T13:51:26.089166,617.67,TXN-28934087
a032b831-c97a-46b1-ada1-cd8ecce91588,"[{""sku"": ""SKU-84448"", ""qty"": 2, ""price"": 482.26}]",paypal,462.51,149.82,2026-01-07T13:51:26.089207,1349.47,TXN-18349812
0a381195-52e2-43bb-a027-9135179b0bc7,"[{""sku"": ""SKU-96887"", ""qty"": 3, ""price"": 65.06}, {""sku"": ""SKU-57777"", ""qty"": 5, ""price"": 45.11}, {""s",paypal,532.84,55.09,2026-01-07T13:51:26.089237,877.51,TXN-83459278

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

[[items]]
sku = "SKU-82812"
qty = 5
price = 490.31


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

[User] Create a XML representation of product listing.

[Assistant]
Approach:
1. Task: Create product listing 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"?>
<product_listing>
<product_id>PROD-239354</product_id>
<name>User-centric tertiary contingency</name>
<category>electronics</category>
<price>998.51</price>
<currency>USD</currency>
<stock>842</stock>
<is_available>True</is_available>
<rating>2.36</rating>
<reviews>630</reviews>
<specs>
<weight_kg>0.61</weight_kg>
<dimensions>88x23x10cm</dimensions>
</specs>
</product_listing>


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

[User] Output transaction record as XML.

[Assistant]
Approach:
1. Task: Create transaction record 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"?>
<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>


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

[User] Create a JSON representation of error log.

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

Output:
{
  "error_id": "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] Create a TOML representation of customer review.

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

Output:
title = "Exactly almost full new record save."
date = "2026-01-02"
product_id = "PROD-922306"
content = "Arrive much low will teach. By possible nature learn could. Act hot whole guy experience.\nIdentify world fight stock. Force fear soon. Author night think."


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

[User] Generate news article data in YAML format.

[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:
section: Politics
tags:
- machine
- fund
- station
- our
published: '2026-01-05T17:58:55.100855'
views: 86295


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

[User] Output prescription as TOML.

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

Output:
prescriber = "Melinda Black"
date = "2026-01-04"
rx_id = "RX-8618237"


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<transaction_record>
<txn_id>TXN-95106885</txn_id>
<customer_id>9090a0a6-3421-4a93-9d6e-78b6a1f8fed7</customer_id>
<timestamp>2026-01-07T13:51:27.692524</timestamp>
<items>
<sku>SKU-33525</sku>
<qty>3</qty>
<price>130.6</price>
</items>
<subtotal>793.41</subtotal>
<tax>85.16</tax>
<total>1645.24</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-95106885",
  "customer_id": "9090a0a6-3421-4a93-9d6e-78b6a1f8fed7",
  "timestamp": "2026-01-07T13:51:27.692524",
  "items": [
    {
      "sku": "SKU-33525",
      "qty": 3,
      "price": 130.6
    }
  ],
  "subtotal": 793.41,
  "tax": 85.16,
  "total": 1645.24,
  "payment_method": "apple_pay"
}


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

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

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

Output:
post_id: POST-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 TOML format. Think step-by-step, then generate syntactically perfect TOML.

[User] Create a TOML representation of course syllabus.

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

Output:
course_id = "CRS-8328"
code = "QKE428"
title = "Decentralized content-based leverage 101"
instructor = "Sarah Simon"
credits = 3
term = "Fall 2022"
[[schedule]]
week = 1
topic = "whole"

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

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

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

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

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

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

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

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


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

[User] Create a CSV representation of course syllabus.

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

Output:
abstract,authors,citations,code,credits,funding_source,grading_final,grading_homework,grading_midterm,keywords,paper_id,publication_doi,publication_venue,publication_year,schedule,term,title
,,,GHC481,4,,40,30,30,,,,,,"[{""week"": 1, ""topic"": ""table""}, {""week"": 2, ""topic"": ""team""}, {""week"": 3, ""topic"": ""miss""}, {""week"":",Spring 2020,
Red think source science employee political. Laugh hotel section pull reach final explain. Mission t,"[{""name"": ""Hayley Phillips"", ""affiliation"": ""Carroll, Harris and Hughes"", ""email"": ""sanchezkimberly@",7,,,None,,,,"[""value"", ""shoulder"", ""less""]",arXiv:2024.29302,10.2943/KGtM,Science,2024,,,Multi-channeled empowering data-warehouse
Condition blue enter computer economy cultural might. Hear government around kid anything meet cost.,"[{""name"": ""Sarah Harris"", ""affiliation"": ""Ortiz-Campbell"", ""email"": ""chad23@example.com""}, {""name"": ",8,,,None,,,,"[""learn"", ""expect"", ""trial""]",arXiv:2022.36659,10.9474/ZEqK,Nature,2020,,,Configurable optimizing functionalities


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

[User] Generate financial report data in JSON format.

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

Output:
{
  "company": "Williams Ltd",
  "ticker": "IHFM",
  "quarter": "Q3 2022",
  "revenue": 93368790,
  "expenses": 48847964,
  "net_income": 12028281,
  "eps": 9.18,
  "metrics": {
    "profit_margin": 7.56,
    "roe": 13.89
  }
}


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<social_media_post>
<post_id>POST-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>

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

Output:
{
  "post_id": "POST-69367106",
  "platform": "twitter",
  "user_id": "7643b70d-1c60-436f-974e-7bc6cee5e032",
  "username": "gordonalexander",
  "content": "See personal couple road president most next. Laugh teach lawyer character work present.\nPage give education middle. Couple save view media instead police guy. Enough test notice capital size.",
  "timestamp": "2026-01-07T13:51:25.991400",
  "hashtags": [
    "#PM",
    "#stage",
    "#government"
  ],
  "engagement": {
    "likes": 1911,
    "shares": 761,
    "comments": 62
  }
}


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

[User] Output lab result as CSV.

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

Output:
order_date,panel,patient_mrn,result_id,results
2026-01-02,CMP,MRN-380513,LAB-2309770,"[{""test"": ""Glucose"", ""value"": 62.8, ""unit"": ""mg/dL"", ""flag"": ""normal""}, {""test"": ""Hemoglobin"", ""valu"
2026-01-02,CMP,MRN-959340,LAB-9370343,"[{""test"": ""WBC"", ""value"": 155.4, ""unit"": ""mg/dL"", ""flag"": ""normal""}, {""test"": ""Hemoglobin"", ""value"":"
2026-01-02,Lipid,MRN-315430,LAB-2628607,"[{""test"": ""Glucose"", ""value"": 101.5, ""unit"": ""g/dL"", ""flag"": ""normal""}, {""test"": ""Glucose"", ""value"":"
2026-01-04,Lipid,MRN-240303,LAB-7885452,"[{""test"": ""Glucose"", ""value"": 94.3, ""unit"": ""mg/dL"", ""flag"": ""normal""}, {""test"": ""Glucose"", ""value"":"


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

[User]
Transform this TOML data into JSON format:
period = "June 2021"
total_revenue = 1467254
units_sold = 63744
[[channels]]
name = "wholesale"
revenue = 2975287
growth = -1.88

[[channels]]
name = "online"
revenue = 2665464
growth = 14.77

[[top_products]]
sku = "SKU-1172"
sales = 348860

[[top_products]]
sku = "SKU-4431"
sales = 479568

[[top_products]]
sku = "SKU-6244"
sales = 245719

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

Output:
{
  "period": "June 2021",
  "total_revenue": 1467254,
  "units_sold": 63744,
  "channels": [
    {
      "name": "wholesale",
      "revenue": 2975287,
      "growth": -1.88
    },
    {
      "name": "online",
      "revenue": 2665464,
      "growth": 14.77
    }
  ],
  "top_products": [
    {
      "sku": "SKU-1172",
      "sales": 348860
    },
    {
      "sku": "SKU-4431",
      "sales": 479568
    },
    {
      "sku": "SKU-6244",
      "sales": 245719
    }
  ]
}


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

[User] Create a CSV representation of financial report.

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

Output:
company,eps,expenses,metrics_profit_margin,metrics_roe,net_income,quarter,revenue,ticker
Hardy-Nguyen,3.22,30350118,18.82,21.21,14673850,Q3 2024,23201336,ZAMS
Vincent PLC,6.65,13605841,19.41,22.33,19701370,Q1 2021,36113078,MBYQ
Walker-Zhang,6.58,16600202,15.22,15.35,19679689,Q2 2024,76575005,OLSH
"Smith, Dixon and Kirby",3.95,18617743,20.79,16.39,7577797,Q1 2021,10615274,TKLC


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

[User] Generate student assessment data in JSON format.

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

Output:
{
  "total_score": 97,
  "scores": [
    {
      "question": 1,
      "points_earned": 0,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 10,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 5,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 5,
      "points_possible": 10
    },
    {
      "question": 9,
      "points_earned": 3,
      "points_possible": 10
    },
    {
      "question": 10,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 11,
      "points_earned": 5,
      "points_possible": 10
    }
  ],
  "percentage": 78.32,
  "course_id": "CRS-4089"
}


[System] You are an expert in 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>Moore-Thompson</company>
<ticker>XFVE</ticker>
<quarter>Q2 2022</quarter>
<revenue>73324772</revenue>
<expenses>43130054</expenses>
<net_income>18329728</net_income>
<eps>9.88</eps>
<metrics>
<profit_margin>22.03</profit_margin>
<roe>10.54</roe>
</metrics>
</financial_report>

[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": "Moore-Thompson",
  "ticker": "XFVE",
  "quarter": "Q2 2022",
  "revenue": 73324772,
  "expenses": 43130054,
  "net_income": 18329728,
  "eps": 9.88,
  "metrics": {
    "profit_margin": 22.03,
    "roe": 10.54
  }
}


[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-544771</contract_id>
<parties>
<name>Prince-Finley</name>
<role>party_a</role>
</parties>
<parties>
<name>Stone LLC</name>
<role>party_b</role>
</parties>
<effective_date>2026-01-02</effective_date>
<term_months>52</term_months>
<value>394049</value>
<status>active</status>
</contract>

[Assistant]
Approach:
1. Task: Convert contract 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:
{
  "contract_id": "CTR-544771",
  "parties": [
    {
      "name": "Prince-Finley",
      "role": "party_a"
    },
    {
      "name": "Stone LLC",
      "role": "party_b"
    }
  ],
  "effective_date": "2026-01-02",
  "term_months": 52,
  "value": 394049,
  "status": "active"
}


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

[User] Produce a CSV document for a prescription.

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

Output:
date,medications,patient_mrn,prescriber,rx_id
2026-01-03,"[{""name"": ""Atorvastatin"", ""dosage"": ""20mg"", ""frequency"": ""daily"", ""quantity"": 90}]",MRN-551064,Eric Jackson,RX-3305496
2026-01-03,"[{""name"": ""Atorvastatin"", ""dosage"": ""20mg"", ""frequency"": ""BID"", ""quantity"": 60}, {""name"": ""Atorvasta",MRN-979601,Benjamin Lee,RX-2433711
2026-01-02,"[{""name"": ""Metformin"", ""dosage"": ""5mg"", ""frequency"": ""daily"", ""quantity"": 60}, {""name"": ""Lisinopril""",MRN-209290,Jesus Johnson,RX-5553915
2026-01-04,"[{""name"": ""Metformin"", ""dosage"": ""5mg"", ""frequency"": ""BID"", ""quantity"": 60}, {""name"": ""Metformin"", """,MRN-161008,David Benson,RX-5302143
2026-01-06,"[{""name"": ""Lisinopril"", ""dosage"": ""10mg"", ""frequency"": ""TID"", ""quantity"": 60}, {""name"": ""Lisinopril""",MRN-658873,Claudia Williams,RX-4368294


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

[User]
Reformat the data below from CSV to JSON:
assessment,chief_complaint,encounter_date,note_id,patient_age,patient_gender,patient_mrn,vitals_bp,vitals_hr,vitals_temp_f
"[{""problem"": ""hypertension"", ""icd10"": ""I84""}, {""problem"": ""hypertension"", ""icd10"": ""J93""}]",fever,2026-01-04,CN-3041313,45,F,MRN-164256,153/76,98,102.6
"[{""problem"": ""hypertension"", ""icd10"": ""I98""}, {""problem"": ""diabetes"", ""icd10"": ""I94""}, {""problem"": """,fever,2026-01-01,CN-5909970,26,F,MRN-895723,124/83,110,98.4
"[{""problem"": ""hypertension"", ""icd10"": ""K67""}]",fever,2026-01-06,CN-7456761,64,F,MRN-427862,167/70,94,100.4

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

Output:
{
  "note_id": "CN-3041313",
  "patient": {
    "mrn": "MRN-164256",
    "age": 45,
    "gender": "F"
  },
  "encounter_date": "2026-01-04",
  "chief_complaint": "fever",
  "vitals": {
    "bp": "153/76",
    "hr": 98,
    "temp_f": 102.6
  },
  "assessment": [
    {
      "problem": "hypertension",
      "icd10": "I84"
    },
    {
      "problem": "hypertension",
      "icd10": "J93"
    }
  ]
}


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

[User]
Reformat the data below from YAML to CSV:
review_id: REV-4787173
product_id: PROD-746934
user_id: a1638e54-91af-4e5f-be10-465327f3fbf6
rating: 4
title: Rock company surface either million.
content: Suddenly plant stay thank project hand me. Commercial his road carry training
  trip.
date: '2026-01-02'
verified_purchase: true
helpful_votes: 3

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

Output:
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
,Suddenly plant stay thank project hand me. Commercial his road carry training trip.,,2026-01-02,3,,,,PROD-746934,4,REV-4787173,,,,,Rock company surface either million.,a1638e54-91af-4e5f-be10-465327f3fbf6,True
electronics,,USD,,,True,Reverse-engineered heuristic Graphic Interface,402.12,PROD-773869,1.81,,452,55x82x22cm,47.84,119,,,
books,,USD,,,True,Pre-emptive context-sensitive capability,996.67,PROD-767618,4.94,,641,31x72x14cm,49.43,912,,,


[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:
{
  "article_id": "ART-9178511",
  "headline": "Fully-configurable secondary access",
  "author": "Gabrielle Daugherty",
  "published": "2026-01-05T07:34:40.744934",
  "section": "Tech",
  "content": "Lawyer might home mouth end so science. Hope attention strong public teach person beautiful though. Really decision land evening year.\nJust role ground discover. Five stand writer floor.",
  "tags": [
    "maybe",
    "glass",
    "election",
    "moment"
  ],
  "views": 24250,
  "shares": 778
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<news_article>
<article_id>ART-9178511</article_id>
<headline>Fully-configurable secondary access</headline>
<author>Gabrielle Daugherty</author>
<published>2026-01-05T07:34:40.744934</published>

Tech

<content>Lawyer might home mouth end so science. Hope attention strong public teach person beautiful though. Really decision land evening year.
Just role ground discover. Five stand writer floor.</content>
<tags>maybe</tags>
<tags>glass</tags>
<tags>election</tags>
<tags>moment</tags>
<views>24250</views>
<shares>778</shares>
</news_article>


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

[User] Generate error log data in TOML format.

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

Output:
error_id = "d03afc03-94bd-4dbb-bf49-9cda441c119b"
timestamp = "2026-01-07T13:51:25.952127"
level = "CRITICAL"
service = "fromService"
message = "Add perform politics some card score brother."
stack_trace = [ "at send.py:152", "at young.py:309",]

[context]
user_id = "2b3e5573-7b69-4807-a899-cbaa4adadf38"
request_id = "beac9c14-4ae5-407d-9aae-d7a56f6790f6"


[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"?>
<course_syllabus>
<course_id>CRS-4513</course_id>
NEE477
<title>Exclusive bottom-line artificial intelligence 101</title>
<instructor>Jaime Roman</instructor>
<credits>3</credits>
<term>Spring 2022</term>
<schedule>
<week>1</week>
<topic>marriage</topic>
</schedule>
<schedule>
<week>2</week>
<topic>wonder</topic>
</schedule>
<schedule>
<week>3</week>
<topic>system</topic>
</schedule>
<schedule>
<week>4</week>
<topic>order</topic>
</schedule>
<schedule>
<week>5</week>
<topic>very</topic>
</schedule>
<schedule>
<week>6</week>
<topic>laugh</topic>
</schedule>
<schedule>
<week>7</week>
<topic>practice</topic>
</schedule>
<schedule>
<week>8</week>
<topic>sister</topic>
</schedule>
<schedule>
<week>9</week>
<topic>join</topic>
</schedule>
<schedule>
<week>10</week>
<topic>expect</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: medium - 5-8 fields, 2-3 levels
3. Format rules: proper braces/brackets, quoted keys, correct value types
4. Structure: Organize data logically with appropriate nesting
5. Transform values to match the target format specifications.

Output:
{
  "course_id": "CRS-4513",
  "code": "NEE477",
  "title": "Exclusive bottom-line artificial intelligence 101",
  "instructor": "Jaime Roman",
  "credits": 3,
  "term": "Spring 2022",
  "schedule": [
    {
      "week": 1,
      "topic": "marriage"
    },
    {
      "week": 2,
      "topic": "wonder"
    },
    {
      "week": 3,
      "topic": "system"
    },
    {
      "week": 4,
      "topic": "order"
    },
    {
      "week": 5,
      "topic": "very"
    },
    {
      "week": 6,
      "topic": "laugh"
    },
    {
      "week": 7,
      "topic": "practice"
    },
    {
      "week": 8,
      "topic": "sister"
    },
    {
      "week": 9,
      "topic": "join"
    },
    {
      "week": 10,
      "topic": "expect"
    }
  ],
  "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 customer review data in XML format.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<verified_purchase>False</verified_purchase>
<rating>2</rating>
<date>2026-01-02</date>
<user_id>ccea0611-b57c-4ee0-9ab6-48c5cb4c2b4c</user_id>
<title>Nature prepare style hit cell feeling start societ</title>
</customer_review>


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

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

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

Output:
assessment_id: ASMT-946690
student_id: STU-268675
course_id: CRS-1216
type: assignment
date: '2026-01-01'
scores:
- question: 1
  points_earned: 10
  points_possible: 10
- question: 2
  points_earned: 1
  points_possible: 10
- question: 3
  points_earned: 2
  points_possible: 10
- question: 4
  points_earned: 8
  points_possible: 10
- question: 5
  points_earned: 2
  points_possible: 10
- question: 6
  points_earned: 5
  points_possible: 10
- question: 7
  points_earned: 8
  points_possible: 10
- question: 8
  points_earned: 5
  points_possible: 10
- question: 9
  points_earned: 0
  points_possible: 10
- question: 10
  points_earned: 4
  points_possible: 10
- question: 11
  points_earned: 2
  points_possible: 10
- question: 12
  points_earned: 2
  points_possible: 10
total_score: 81
percentage: 50.49
grade: B


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

[User] Output news article as TOML.

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

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


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

Output:
contract_id,effective_date,parties,status,term_months,value
CTR-619223,2026-01-03,"[{""name"": ""Mcdaniel LLC"", ""role"": ""party_a""}, {""name"": ""Hunt-Bowman"", ""role"": ""party_b""}]",pending,21,87478
CTR-950216,2026-01-05,"[{""name"": ""Espinoza PLC"", ""role"": ""party_a""}, {""name"": ""Moreno, Bean and Simpson"", ""role"": ""party_b""",active,55,613104
CTR-287645,2026-01-06,"[{""name"": ""Phillips and Sons"", ""role"": ""party_a""}, {""name"": ""Shah LLC"", ""role"": ""party_b""}]",active,22,684985
CTR-495460,2026-01-05,"[{""name"": ""Stone, Ashley and Gomez"", ""role"": ""party_a""}, {""name"": ""Torres LLC"", ""role"": ""party_b""}]",active,33,184441


[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"?>
<course_syllabus>
<grading>
<homework>30</homework>
<midterm>30</midterm>
<final>40</final>
</grading>
<credits>4</credits>
<course_id>CRS-7759</course_id>
<schedule>
<week>1</week>
<topic>meet</topic>
</schedule>
<schedule>
<week>2</week>
<topic>around</topic>
</schedule>
<schedule>
<week>3</week>
<topic>college</topic>
</schedule>
<schedule>
<week>4</week>
<topic>fly</topic>
</schedule>
<schedule>
<week>5</week>
<topic>summer</topic>
</schedule>
<schedule>
<week>6</week>
<topic>painting</topic>
</schedule>
<schedule>
<week>7</week>
<topic>size</topic>
</schedule>
<schedule>
<week>8</week>
<topic>off</topic>
</schedule>
<schedule>
<week>9</week>
<topic>point</topic>
</schedule>
<schedule>
<week>10</week>
<topic>light</topic>
</schedule>
<schedule>
<week>11</week>
<topic>nothing</topic>
</schedule>
<instructor>Matthew Johnson</instructor>
</course_syllabus>

[Assistant]
Approach:
1. Task: Convert course syllabus 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:
{
  "grading": {
    "homework": 30,
    "midterm": 30,
    "final": 40
  },
  "credits": 4,
  "course_id": "CRS-7759",
  "schedule": [
    {
      "week": 1,
      "topic": "meet"
    },
    {
      "week": 2,
      "topic": "around"
    },
    {
      "week": 3,
      "topic": "college"
    },
    {
      "week": 4,
      "topic": "fly"
    },
    {
      "week": 5,
      "topic": "summer"
    },
    {
      "week": 6,
      "topic": "painting"
    },
    {
      "week": 7,
      "topic": "size"
    },
    {
      "week": 8,
      "topic": "off"
    },
    {
      "week": 9,
      "topic": "point"
    },
    {
      "week": 10,
      "topic": "light"
    },
    {
      "week": 11,
      "topic": "nothing"
    }
  ],
  "instructor": "Matthew Johnson"
}


[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"?>
<student_assessment>
<grade>A</grade>
<course_id>CRS-4519</course_id>
<total_score>75</total_score>
</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:
{
  "grade": "A",
  "course_id": "CRS-4519",
  "total_score": 75
}


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

[User] Output api specification as JSON.

[Assistant]
Approach:
1. Task: Create api specification in JSON
2. Complexity: 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:
{
  "info": {
    "title": "Object-based multimedia secured line API",
    "version": "1.0.0"
  },
  "openapi": "3.0.0",
  "paths": {
    "/party": {
      "get": {
        "summary": "Discussion partner stay wear again.",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          },
          {
            "name": "param1",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  }
}


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

[User] Create a XML representation of contract.

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<contract>
<contract_id>CTR-544771</contract_id>
<parties>
<name>Prince-Finley</name>
<role>party_a</role>
</parties>
<parties>
<name>Stone LLC</name>
<role>party_b</role>
</parties>
<effective_date>2026-01-02</effective_date>
<term_months>52</term_months>
<value>394049</value>
<status>active</status>
</contract>


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

[User] Generate course syllabus data in JSON format.

[Assistant]
Approach:
1. Task: Create course syllabus 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:
{
  "course_id": "CRS-3440",
  "code": "KLD251",
  "title": "Reverse-engineered foreground infrastructure 101",
  "instructor": "Courtney Escobar",
  "credits": 4,
  "term": "Spring 2022",
  "schedule": [
    {
      "week": 1,
      "topic": "despite"
    },
    {
      "week": 2,
      "topic": "choose"
    },
    {
      "week": 3,
      "topic": "action"
    },
    {
      "week": 4,
      "topic": "couple"
    },
    {
      "week": 5,
      "topic": "big"
    },
    {
      "week": 6,
      "topic": "trade"
    },
    {
      "week": 7,
      "topic": "measure"
    },
    {
      "week": 8,
      "topic": "music"
    }
  ],
  "grading": {
    "homework": 30,
    "midterm": 30,
    "final": 40
  }
}


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

[User]
Reformat the data below from JSON to XML:
{
  "date": "2026-01-05",
  "title": "Teach why painting per short.",
  "rating": 4
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<date>2026-01-05</date>
<title>Teach why painting per short.</title>
<rating>4</rating>
</customer_review>


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

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

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

Output:
code,course_id,credits,grading_final,grading_homework,grading_midterm,instructor,schedule,term,title
BXM405,CRS-5704,3,40,30,30,Emily Bryan,"[{""week"": 1, ""topic"": ""southern""}, {""week"": 2, ""topic"": ""raise""}, {""week"": 3, ""topic"": ""across""}, {""",Spring 2021,Profit-focused responsive throughput 101
ORB453,CRS-1733,4,40,30,30,Joel Martin,"[{""week"": 1, ""topic"": ""free""}, {""week"": 2, ""topic"": ""star""}, {""week"": 3, ""topic"": ""rate""}, {""week"": ",Fall 2023,Programmable non-volatile productivity 101
HWN197,CRS-8444,4,40,30,30,Sara Hill,"[{""week"": 1, ""topic"": ""light""}, {""week"": 2, ""topic"": ""court""}, {""week"": 3, ""topic"": ""machine""}, {""we",Spring 2021,Reactive object-oriented array 101
UDW352,CRS-5746,3,40,30,30,Krystal Sutton,"[{""week"": 1, ""topic"": ""drop""}, {""week"": 2, ""topic"": ""surface""}, {""week"": 3, ""topic"": ""dark""}, {""week",Fall 2022,User-friendly interactive hardware 101


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


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

[User] Create a YAML representation of student assessment.

[Assistant]
Approach:
1. Task: Create student assessment in YAML
2. Complexity: 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:
assessment_id: ASMT-503362
student_id: STU-235214
course_id: CRS-9952
type: assignment
date: '2026-01-01'
scores:
- question: 1
  points_earned: 1
  points_possible: 10
- question: 2
  points_earned: 0
  points_possible: 10
- question: 3
  points_earned: 0
  points_possible: 10
- question: 4
  points_earned: 4
  points_possible: 10
- question: 5
  points_earned: 1
  points_possible: 10
- question: 6
  points_earned: 6
  points_possible: 10
- question: 7
  points_earned: 8
  points_possible: 10
- question: 8
  points_earned: 5
  points_possible: 10
- question: 9
  points_earned: 4
  points_possible: 10
- question: 10
  points_earned: 0
  points_possible: 10
- question: 11
  points_earned: 1
  points_possible: 10
- question: 12
  points_earned: 8
  points_possible: 10
total_score: 52
percentage: 94.35
grade: C


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

[User]
Reformat the data below from JSON to TOML:
{
  "company": "Martinez, Patterson and Hunter",
  "ticker": "PPOB",
  "quarter": "Q1 2023",
  "revenue": 66694743,
  "expenses": 21448775,
  "net_income": 421192,
  "eps": 2.32,
  "metrics": {
    "profit_margin": 7.89,
    "roe": 9.32
  }
}

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

Output:
company = "Martinez, Patterson and Hunter"
ticker = "PPOB"
quarter = "Q1 2023"
revenue = 66694743
expenses = 21448775
net_income = 421192
eps = 2.32

[metrics]
profit_margin = 7.89
roe = 9.32


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

[User]
Reformat the data below from JSON to CSV:
{
  "subtotal": 205.31,
  "payment_method": "apple_pay",
  "total": 1732.06
}

[Assistant]
Approach:
1. Task: Convert transaction record from JSON 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:
abstract,authors,citations,funding_source,keywords,paper_id,payment_method,publication_doi,publication_venue,publication_year,subtotal,title,total
,,,,,,apple_pay,,,,205.31,,1732.06
Figure situation each watch conference. Cause plant ball notice begin set arrive. Blue station reaso,"[{""name"": ""Jason Carrillo"", ""affiliation"": ""Maynard, Howell and Hayes"", ""email"": ""kevin65@example.ne",479,None,"[""threat"", ""you"", ""true"", ""human"", ""air""]",arXiv:2021.87833,,10.8398/PLnl,Cell,2022,,Pre-emptive homogeneous strategy,
"Game floor want sign. Well our exactly health.
With his strategy add positive fish protect place.","[{""name"": ""William Cox"", ""affiliation"": ""Simpson, Vaughn and Bridges"", ""email"": ""briansanders@exampl",487,Jacobson-Jackson,"[""put"", ""education"", ""author"", ""direction""]",arXiv:2024.73009,,10.8216/Kwti,Cell,2023,,Cross-group real-time methodology,
Professional clearly foot. Half them protect message situation young place. Seem Democrat over hit p,"[{""name"": ""Brenda Hayes"", ""affiliation"": ""Fleming, Evans and Jones"", ""email"": ""phillipsgarrett@examp",363,None,"[""interesting"", ""rise"", ""smile"", ""course"", ""building""]",arXiv:2024.27362,,10.4582/fBmR,Science,2023,,Multi-layered disintermediate focus group,
Card break real sometimes recent. Product attention act movie director. Mention traditional scene wo,"[{""name"": ""Jonathan Lee"", ""affiliation"": ""Harper-Hodge"", ""email"": ""ybrooks@example.org""}, {""name"": """,227,None,"[""something"", ""wish"", ""stuff"", ""ground"", ""peace""]",arXiv:2022.70155,,10.7574/DCWf,Science,2023,,Seamless motivating access,


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

[User] Create a YAML representation of lab result.

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

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

[User] Generate contract data in JSON format.

[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-324198",
  "parties": [
    {
      "name": "Alvarado-Barnes",
      "role": "party_a"
    },
    {
      "name": "Lopez, Price and Melendez",
      "role": "party_b"
    }
  ],
  "effective_date": "2026-01-06",
  "term_months": 34,
  "value": 725205,
  "status": "pending"
}


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<student_assessment>
<assessment_id>ASMT-946690</assessment_id>
<student_id>STU-268675</student_id>
<course_id>CRS-1216</course_id>
<type>assignment</type>
<date>2026-01-01</date>
<scores>
<question>1</question>
<points_earned>10</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>1</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>3</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>4</question>
<points_earned>8</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>5</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>8</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>5</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>9</question>
<points_earned>0</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>10</question>
<points_earned>4</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>11</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>12</question>
<points_earned>2</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>81</total_score>
<percentage>50.49</percentage>
<grade>B</grade>
</student_assessment>


[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:
{
  "date": "2026-01-01",
  "total_score": 85,
  "student_id": "STU-920172"
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<student_assessment>
<date>2026-01-01</date>
<total_score>85</total_score>
<student_id>STU-920172</student_id>
</student_assessment>


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

[User] Output error log as YAML.

[Assistant]
Approach:
1. Task: Create error log 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:
message: Computer so cold feeling huge reason reach.
error_id: ddf52566-8f32-4c90-8477-d7f45504f7db
stack_trace:
- at their.py:436
- at activity.py:81
- at test.py:46
timestamp: '2026-01-07T13:51:26.578554'
context:
  user_id: 97fc14e5-867d-4c23-9d2e-00b538b50acf
  request_id: ab94fb1e-d258-4626-9686-12f860249c41


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

[User] Output customer review as JSON.

[Assistant]
Approach:
1. Task: Create customer review 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:
{
  "review_id": "REV-5650887",
  "product_id": "PROD-601157",
  "user_id": "ac7725ae-2567-44d1-8d40-a64432b9801b",
  "rating": 3,
  "title": "Personal order single check off but my.",
  "content": "Key Mrs say because walk old certainly. Product figure event choice.\nSkill cut plan per side same. Between common join partner kid enter page discover.",
  "date": "2026-01-06",
  "verified_purchase": true,
  "helpful_votes": 66
}


[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"?>
<prescription>
<rx_id>RX-9719971</rx_id>
<patient_mrn>MRN-909141</patient_mrn>
<prescriber>Heather Stephens</prescriber>
<date>2026-01-05</date>
<medications>
<name>Atorvastatin</name>
<dosage>20mg</dosage>
<frequency>daily</frequency>
<quantity>30</quantity>
</medications>
</prescription>

[Assistant]
Approach:
1. Task: Convert prescription 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:
date,medications,patient_mrn,prescriber,rx_id
2026-01-05,"[{""name"": ""Atorvastatin"", ""dosage"": ""20mg"", ""frequency"": ""daily"", ""quantity"": 30}]",MRN-909141,Heather Stephens,RX-9719971
2026-01-03,"[{""name"": ""Atorvastatin"", ""dosage"": ""20mg"", ""frequency"": ""daily"", ""quantity"": 30}]",MRN-991543,Dawn Lewis,RX-5537863
2026-01-02,"[{""name"": ""Metformin"", ""dosage"": ""20mg"", ""frequency"": ""TID"", ""quantity"": 90}]",MRN-999851,Elizabeth Mcknight,RX-1269800
2026-01-06,"[{""name"": ""Atorvastatin"", ""dosage"": ""20mg"", ""frequency"": ""BID"", ""quantity"": 60}]",MRN-883667,Allison Hudson,RX-5588769
2026-01-06,"[{""name"": ""Metformin"", ""dosage"": ""5mg"", ""frequency"": ""BID"", ""quantity"": 90}, {""name"": ""Atorvastatin""",MRN-945206,Timothy Norris,RX-8162626


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

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

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

Output:
company,eps,expenses,metrics_profit_margin,metrics_roe,net_income,quarter,revenue,ticker
"Thompson, Yang and Roberts",8.84,36274579,17.46,22.69,7802792,Q1 2022,59725729,ATOM
"Clark, Henderson and Poole",9.39,43144274,24.73,14.98,14788227,Q2 2020,29102144,WNQB
Webb-Williams,8.69,15095366,17.64,22.79,19611879,Q1 2022,14474734,KJEE


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

[User] Produce a YAML document for a prescription.

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

Output:
rx_id: RX-7665793
patient_mrn: MRN-934255
prescriber: Danielle Brown
date: '2026-01-06'
medications:
- name: Atorvastatin
  dosage: 20mg
  frequency: daily
  quantity: 90
- name: Atorvastatin
  dosage: 5mg
  frequency: BID
  quantity: 90
- name: Metformin
  dosage: 5mg
  frequency: BID
  quantity: 60


[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"?>
<research_paper>
<paper_id>arXiv:2020.59386</paper_id>
<title>Self-enabling demand-driven application</title>
<authors>
<name>Keith Wilcox</name>
<affiliation>Ruiz-Torres</affiliation>
<email>martinstephanie@example.org</email>
</authors>
<authors>
<name>Jennifer Mccoy</name>
<affiliation>Thompson-Marshall</affiliation>
<email>brianvelasquez@example.org</email>
</authors>
<abstract>Before today call network oil future. Admit itself catch song various rest. Personal worry quality director.</abstract>
<keywords>song</keywords>
<keywords>TV</keywords>
<keywords>southern</keywords>
<publication>
<venue>Nature</venue>
<year>2020</year>
<doi>10.1369/MikD</doi>
</publication>
<citations>274</citations>
<funding_source />
</research_paper>

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

Output:
{
  "paper_id": "arXiv:2020.59386",
  "title": "Self-enabling demand-driven application",
  "authors": [
    {
      "name": "Keith Wilcox",
      "affiliation": "Ruiz-Torres",
      "email": "martinstephanie@example.org"
    },
    {
      "name": "Jennifer Mccoy",
      "affiliation": "Thompson-Marshall",
      "email": "brianvelasquez@example.org"
    }
  ],
  "abstract": "Before today call network oil future. Admit itself catch song various rest. Personal worry quality director.",
  "keywords": [
    "song",
    "TV",
    "southern"
  ],
  "publication": {
    "venue": "Nature",
    "year": 2020,
    "doi": "10.1369/MikD"
  },
  "citations": 274,
  "funding_source": null
}