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

[User]
Transform this CSV data into TOML format:
assessment_id,code,course_id,credits,date,grade,grading_final,grading_homework,grading_midterm,instructor,percentage,schedule,scores,student_id,term,title,total_score,type
ASMT-554535,,CRS-9992,,2026-01-03,B,,,,,63.99,,"[{""question"": 1, ""points_earned"": 9, ""points_possible"": 10}, {""question"": 2, ""points_earned"": 6, ""po",STU-693793,,,86,exam
,TNY218,CRS-7794,4,,,40,30,30,Kara Bennett,,"[{""week"": 1, ""topic"": ""present""}, {""week"": 2, ""topic"": ""arrive""}, {""week"": 3, ""topic"": ""school""}, {""",,,Spring 2023,Monitored mobile analyzer 101,,
,ZDW419,CRS-8967,3,,,40,30,30,Cheryl Downs,,"[{""week"": 1, ""topic"": ""form""}, {""week"": 2, ""topic"": ""important""}, {""week"": 3, ""topic"": ""enter""}, {""w",,,Spring 2022,Profit-focused intangible neural-net 101,,

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

Output:
assessment_id = "ASMT-554535"
student_id = "STU-693793"
course_id = "CRS-9992"
type = "exam"
date = "2026-01-03"
total_score = 86
percentage = 63.99
grade = "B"
[[scores]]
question = 1
points_earned = 9
points_possible = 10

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

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

[[scores]]
question = 4
points_earned = 6
points_possible = 10

[[scores]]
question = 5
points_earned = 6
points_possible = 10

[[scores]]
question = 6
points_earned = 1
points_possible = 10

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

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

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

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


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

[User] Generate news article data in CSV format.

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

Output:
article_id,author,content,headline,published,section,shares,tags,views
ART-2650245,Jennifer Davis,"Late situation both data share market. These foot health box.
Pay me together western ever story cup",Enhanced multimedia hub,2026-01-02T17:44:08.333575,Tech,2819,"[""future"", ""here"", ""new""]",46115
ART-2262202,Mary Phillips,"These dark seek social. Identify figure policy act often where pull.
Message yet water analysis week",Secured solution-oriented solution,2026-01-05T16:17:55.416091,Tech,3330,"[""church"", ""region"", ""door"", ""form"", ""then""]",95683
ART-5343695,Emily Smith,"Forward probably theory visit. Stay research hope newspaper it worry.
Cause fight conference easy st",Organic static projection,2026-01-02T05:42:13.204625,Tech,3671,"[""keep"", ""class"", ""special""]",48293
ART-5847055,Michael Poole,Simple exist your. Pay else spring mean senior do. Edge through increase maintain almost rather nor.,Cross-group web-enabled customer loyalty,2026-01-02T01:37:57.867663,Politics,4546,"[""argue"", ""war"", ""deep"", ""explain""]",52000
ART-9512774,Michael Kennedy,"Reality chance science care. Partner Mr pattern.
Plant standard everything after billion office diff",Persevering uniform budgetary management,2026-01-02T23:34:21.012612,Business,3322,"[""administration"", ""end"", ""pattern""]",37594


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

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

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

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


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

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

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

Output:
abstract,authors,citations,funding_source,keywords,paper_id,percentage,publication_doi,publication_venue,publication_year,student_id,title,total_score
,,,,,,61.11,,,,STU-785727,,96
Push page month body begin. Culture attack issue. Something without loss speech computer.,"[{""name"": ""Philip Harvey"", ""affiliation"": ""Reynolds LLC"", ""email"": ""qpayne@example.net""}, {""name"": """,468,None,"[""explain"", ""air"", ""between"", ""change""]",arXiv:2021.61817,,10.5787/FVZz,Nature,2024,,Quality-focused regional forecast,
About sell song force perform nature authority. Company coach better better special. Picture term wi,"[{""name"": ""Mr. Tyler Mack MD"", ""affiliation"": ""Cox-Brown"", ""email"": ""alisonduncan@example.com""}, {""n",378,None,"[""alone"", ""increase"", ""join"", ""coach"", ""already""]",arXiv:2023.25310,,10.9544/PsVU,Nature,2022,,Face-to-face tangible methodology,
Upon enough world city entire realize door. Central those then think tend may. Off protect hand cert,"[{""name"": ""Debra Washington"", ""affiliation"": ""Khan-Jenkins"", ""email"": ""joshuaevans@example.org""}, {""",1,None,"[""up"", ""pick"", ""process"", ""total""]",arXiv:2020.79252,,10.2515/kRMh,Cell,2022,,Stand-alone 6thgeneration approach,
Century war able high name. Detail not help add nor. Certain cause campaign during politics.,"[{""name"": ""Lisa Thomas"", ""affiliation"": ""Clark, Brown and Hill"", ""email"": ""patricia04@example.org""},",174,None,"[""rock"", ""religious"", ""south""]",arXiv:2024.88866,,10.5479/OXRW,Nature,2024,,Ergonomic value-added time-frame,


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

[User] Output product listing as CSV.

[Assistant]
Approach:
1. Task: Create product listing in CSV
2. Complexity: 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,funding_source,keywords,name,paper_id,price,publication_doi,publication_venue,publication_year,reviews,specs_dimensions,specs_weight_kg,title
,,,,,Universal fault-tolerant service-desk,,907.33,,,,493,62x22x22cm,8.02,
"Science back social rather manage teach reflect. Shake way computer.
Sport drop until simply claim. ","[{""name"": ""Karina Wood"", ""affiliation"": ""Henderson-Gaines"", ""email"": ""matajoseph@example.org""}, {""na",370,None,"[""season"", ""group"", ""just"", ""worry""]",,arXiv:2021.60407,,10.3555/JSte,Nature,2020,,,,Open-architected static throughput
"Sort child suddenly.
Southern white brother news.","[{""name"": ""Tommy Morales"", ""affiliation"": ""Johnson, Lang and Ramirez"", ""email"": ""cdavis@example.net""",482,Rodriguez Ltd,"[""discover"", ""structure"", ""return""]",,arXiv:2023.85575,,10.1508/XUIo,Science,2022,,,,Decentralized reciprocal groupware
Its can prove moment audience choice. Structure western film enter daughter learn of. These anything,"[{""name"": ""Anthony Wright"", ""affiliation"": ""Mitchell and Sons"", ""email"": ""diane01@example.org""}, {""n",319,None,"[""brother"", ""check"", ""provide"", ""though""]",,arXiv:2021.85899,,10.1889/bZjo,Nature,2022,,,,Networked content-based collaboration


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

[User] Output lab result as TOML.

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

Output:
result_id = "LAB-8093004"
patient_mrn = "MRN-777027"
order_date = "2026-01-05"
panel = "CMP"
[[results]]
test = "Glucose"
value = 140.2
unit = "mg/dL"
flag = "low"

[[results]]
test = "Hemoglobin"
value = 96.3
unit = "g/dL"
flag = "normal"

[[results]]
test = "Glucose"
value = 185.0
unit = "g/dL"
flag = "high"

[[results]]
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 lab result data in JSON format.

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

Output:
{
  "result_id": "LAB-3793814",
  "patient_mrn": "MRN-247204",
  "order_date": "2026-01-03",
  "panel": "CBC",
  "results": [
    {
      "test": "Hemoglobin",
      "value": 188.2,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "WBC",
      "value": 197.7,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "Glucose",
      "value": 196.4,
      "unit": "mg/dL",
      "flag": "high"
    },
    {
      "test": "Glucose",
      "value": 193.9,
      "unit": "g/dL",
      "flag": "high"
    },
    {
      "test": "Glucose",
      "value": 197.2,
      "unit": "g/dL",
      "flag": "low"
    },
    {
      "test": "Hemoglobin",
      "value": 109.5,
      "unit": "mg/dL",
      "flag": "normal"
    }
  ]
}


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

[User] Create a XML representation of customer review.

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

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


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

[User] Generate clinical note data in YAML format.

[Assistant]
Approach:
1. Task: Create clinical note 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:
note_id: CN-7937835
patient:
  mrn: MRN-749785
  age: 66
  gender: M
encounter_date: '2026-01-06'
chief_complaint: chest pain
vitals:
  bp: 179/85
  hr: 81
  temp_f: 101.7
assessment:
- problem: hypertension
  icd10: I52
- problem: diabetes
  icd10: J76


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<sales_analytics>
<period>January 2022</period>
<total_revenue>7456708</total_revenue>
<units_sold>82349</units_sold>
<channels>
<name>wholesale</name>
<revenue>3622404</revenue>
<growth>-8.05</growth>
</channels>
<channels>
<name>online</name>
<revenue>1893923</revenue>
<growth>2.21</growth>
</channels>
<top_products>
<sku>SKU-2073</sku>
<sales>98550</sales>
</top_products>
<top_products>
<sku>SKU-3707</sku>
<sales>233488</sales>
</top_products>
<top_products>
<sku>SKU-7843</sku>
<sales>172526</sales>
</top_products>
</sales_analytics>


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

[User]
Convert the following CSV to YAML:
article_id,author,content,headline,published,section,shares,tags,views
ART-8172649,Rachel Clark,"Pattern capital time compare include night top. Large than important morning.
Card authority protect",Triple-buffered responsive model,2026-01-03T00:35:22.551008,Business,392,"[""consider"", ""whatever"", ""part"", ""however"", ""special""]",49705
ART-1645366,Amanda Martinez,"Crime establish ahead program speech child. Contain reveal ahead fire capital necessary.
Suggest tow",Enterprise-wide reciprocal application,2026-01-01T21:09:16.034149,Business,1537,"[""season"", ""site"", ""political"", ""loss"", ""chair""]",98841
ART-5999482,Dennis Allen,"Not way heart decision. Product seven into here girl argue. Free effect central everything white.
Po",Monitored 24/7 budgetary management,2026-01-05T03:19:57.275932,Politics,784,"[""mouth"", ""maintain"", ""establish""]",86058
ART-4000273,Austin Jones,Consider probably show when grow opportunity. Lay find relationship realize give. Ten if reflect mil,Assimilated asymmetric implementation,2026-01-06T00:27:11.144144,Tech,109,"[""benefit"", ""song"", ""vote"", ""long"", ""commercial""]",10210

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

Output:
article_id: ART-8172649
headline: Triple-buffered responsive model
author: Rachel Clark
published: '2026-01-03T00:35:22.551008'
section: Business
content: 'Pattern capital time compare include night top. Large than important morning.

  Card authority protect present return while middle. Development miss write five.'
tags:
- consider
- whatever
- part
- however
- special
views: 49705
shares: 392


[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: complex - 8-10 fields, 3-4 levels
3. Format rules: key=value syntax, [sections], proper types
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
assessment_id = "ASMT-948175"
student_id = "STU-160858"
course_id = "CRS-5368"
type = "assignment"
date = "2026-01-03"
total_score = 89
percentage = 96.29
grade = "B"
[[scores]]
question = 1
points_earned = 1
points_possible = 10

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

[[scores]]
question = 3
points_earned = 2
points_possible = 10

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

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

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

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

[[scores]]
question = 8
points_earned = 3
points_possible = 10

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


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

[User] Output social media post as JSON.

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

Output:
{
  "post_id": "POST-52722833",
  "platform": "facebook",
  "user_id": "d42576ea-a78d-4261-852d-cbcc2fd55da5",
  "username": "justin96",
  "content": "Southern write three operation throw interest whether.\nDecade quality training employee. Financial out position catch finish author. Past over in create.\nNice reduce try contain future back customer.",
  "timestamp": "2026-01-07T13:51:26.716888",
  "hashtags": [
    "#report",
    "#newspaper"
  ],
  "engagement": {
    "likes": 8106,
    "shares": 850,
    "comments": 244
  }
}


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

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

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


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<lab_result>
<result_id>LAB-1056021</result_id>
<patient_mrn>MRN-977601</patient_mrn>
<order_date>2026-01-02</order_date>
<panel>CMP</panel>
<results>
<test>WBC</test>
<value>124.0</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>114.5</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
<results>
<test>WBC</test>
<value>70.6</value>
<unit>g/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Glucose</test>
<value>119.6</value>
<unit>mg/dL</unit>
<flag>high</flag>
</results>
<results>
<test>Hemoglobin</test>
<value>171.0</value>
<unit>mg/dL</unit>
<flag>normal</flag>
</results>
</lab_result>


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

[User]
Transform this JSON data into XML format:
{
  "experiment_id": "EXP-139463",
  "title": "Effect of quite on arm",
  "methodology": {
    "design": "RCT",
    "sample_size": 371,
    "duration_days": 284
  },
  "results": [
    {
      "metric": "safety",
      "baseline": 91.61,
      "endpoint": 76.9,
      "p_value": 0.4003
    },
    {
      "metric": "safety",
      "baseline": 58.96,
      "endpoint": 23.83,
      "p_value": 0.3437
    },
    {
      "metric": "safety",
      "baseline": 23.31,
      "endpoint": 88.63,
      "p_value": 0.3018
    }
  ],
  "conclusion": "non-significant"
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<experiment_result>
<experiment_id>EXP-139463</experiment_id>
<title>Effect of quite on arm</title>
<methodology>
<design>RCT</design>
<sample_size>371</sample_size>
<duration_days>284</duration_days>
</methodology>
<results>
<metric>safety</metric>
<baseline>91.61</baseline>
<endpoint>76.9</endpoint>
<p_value>0.4003</p_value>
</results>
<results>
<metric>safety</metric>
<baseline>58.96</baseline>
<endpoint>23.83</endpoint>
<p_value>0.3437</p_value>
</results>
<results>
<metric>safety</metric>
<baseline>23.31</baseline>
<endpoint>88.63</endpoint>
<p_value>0.3018</p_value>
</results>
<conclusion>non-significant</conclusion>
</experiment_result>


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<error_log>
<level>ERROR</level>
<service>writeService</service>
<error_id>85223c4c-4b76-4351-95ee-55a2460043f3</error_id>
</error_log>

[Assistant]
Approach:
1. Task: Convert error log 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:
{
  "level": "ERROR",
  "service": "writeService",
  "error_id": "85223c4c-4b76-4351-95ee-55a2460043f3"
}


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

[User] Generate news article data in CSV format.

[Assistant]
Approach:
1. Task: Create news article 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:
article_id,author,content,headline,published,section,shares,tags,views
ART-9628131,,Range condition class leader wrong subject wait. Stop we prevent particular front method. Force item,Re-contextualized logistical paradigm,,,,,
ART-1731778,Ashley Thompson,Develop popular treat remember audience choose. Cause draw few serious official board. Five whatever,Optional encompassing parallelism,2026-01-01T02:52:36.592518,Politics,2132,"[""magazine"", ""soldier"", ""voice""]",56498
ART-2090642,Anthony Rodriguez,"Everybody together step visit. Write be performance talk six piece.
Response cup very keep thought. ",Customizable clear-thinking throughput,2026-01-06T13:15:24.009303,Tech,868,"[""than"", ""young"", ""dog""]",52222


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

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

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

Output:
title: Stand-alone empowering functionalities 101
schedule:
- week: 1
  topic: class
- week: 2
  topic: leave
- week: 3
  topic: develop
- week: 4
  topic: style
- week: 5
  topic: again
- week: 6
  topic: man
- week: 7
  topic: list
grading:
  homework: 30
  midterm: 30
  final: 40


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

[User] Create a JSON representation of product listing.

[Assistant]
Approach:
1. Task: Create product listing 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:
{
  "product_id": "PROD-469887",
  "is_available": true,
  "reviews": 612,
  "name": "Networked executive capability",
  "currency": "USD"
}


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

[User]
Convert the following CSV to YAML:
code,course_id,credits,grading_final,grading_homework,grading_midterm,instructor,schedule,term,title
GDK183,CRS-6873,3,40,30,30,Melinda Thompson,"[{""week"": 1, ""topic"": ""girl""}, {""week"": 2, ""topic"": ""explain""}, {""week"": 3, ""topic"": ""center""}, {""we",Fall 2020,Grass-roots 24/7 emulation 101
UWL437,CRS-9225,4,40,30,30,Monica Stewart,"[{""week"": 1, ""topic"": ""Democrat""}, {""week"": 2, ""topic"": ""clearly""}, {""week"": 3, ""topic"": ""sign""}, {""",Fall 2024,Balanced interactive initiative 101
RFE382,CRS-4501,4,40,30,30,Ryan Morris DDS,"[{""week"": 1, ""topic"": ""address""}, {""week"": 2, ""topic"": ""democratic""}, {""week"": 3, ""topic"": ""least""},",Fall 2023,Persistent next generation superstructure 101
RLJ212,CRS-9484,4,40,30,30,Lisa Blevins,"[{""week"": 1, ""topic"": ""join""}, {""week"": 2, ""topic"": ""safe""}, {""week"": 3, ""topic"": ""we""}, {""week"": 4,",Spring 2023,De-engineered transitional functionalities 101

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

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


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

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

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

Output:
content,engagement_comments,engagement_likes,engagement_shares,hashtags,platform,post_id,timestamp,user_id,username
"Southern write three operation throw interest whether.
Decade quality training employee. Financial o",244,8106,850,"[""#report"", ""#newspaper""]",facebook,POST-52722833,2026-01-07T13:51:26.716888,d42576ea-a78d-4261-852d-cbcc2fd55da5,justin96
"Decide economic since ready. Ability brother box choose hour.
Lead magazine me audience city your tr",495,2734,627,"[""#toward"", ""#finally"", ""#decade""]",instagram,POST-26775885,2026-01-07T13:51:26.718288,398b27fa-7844-4012-8de5-05fd6ae26bc0,brianwhite
"Conference cut service land citizen wish professional. Fish hour kitchen president.
Under yeah maybe",345,6470,131,"[""#care"", ""#analysis"", ""#interesting"", ""#particularly""]",facebook,POST-23939977,2026-01-07T13:51:26.718626,8b8dbd2d-3349-483e-9c39-6b7b2bbea1c3,cserrano


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

[User] Generate sales analytics data in JSON format.

[Assistant]
Approach:
1. Task: Create sales analytics 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:
{
  "period": "February 2020",
  "total_revenue": 2007174,
  "units_sold": 24558,
  "channels": [
    {
      "name": "online",
      "revenue": 235807,
      "growth": 46.03
    },
    {
      "name": "wholesale",
      "revenue": 4419318,
      "growth": 24.35
    }
  ],
  "top_products": [
    {
      "sku": "SKU-6554",
      "sales": 258652
    },
    {
      "sku": "SKU-8652",
      "sales": 200091
    },
    {
      "sku": "SKU-9581",
      "sales": 65110
    }
  ]
}


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

[User] Generate sales analytics data in XML format.

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

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


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

[User] Generate course syllabus data in TOML format.

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

Output:
course_id = "CRS-6873"
code = "GDK183"
title = "Grass-roots 24/7 emulation 101"
instructor = "Melinda Thompson"
credits = 3
term = "Fall 2020"
[[schedule]]
week = 1
topic = "girl"

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

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

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

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

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

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

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

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

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

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

[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] Output student assessment as CSV.

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

Output:
assessment_id,code,course_id,credits,date,grade,grading_final,grading_homework,grading_midterm,instructor,percentage,schedule,scores,student_id,term,title,total_score,type
ASMT-225883,,CRS-2408,,2026-01-01,B,,,,,82.0,,"[{""question"": 1, ""points_earned"": 8, ""points_possible"": 10}, {""question"": 2, ""points_earned"": 2, ""po",STU-314827,,,99,quiz
,TNL133,CRS-3203,3,,,40,30,30,Danny Gallegos,,"[{""week"": 1, ""topic"": ""listen""}, {""week"": 2, ""topic"": ""light""}, {""week"": 3, ""topic"": ""dream""}, {""wee",,,Fall 2020,Advanced high-level hub 101,,
,HTC100,CRS-5097,4,,,40,30,30,Matthew Hampton,,"[{""week"": 1, ""topic"": ""course""}, {""week"": 2, ""topic"": ""economic""}, {""week"": 3, ""topic"": ""born""}, {""w",,,Fall 2024,Synergized system-worthy adapter 101,,
,ENM277,CRS-9175,3,,,40,30,30,Anna Evans,,"[{""week"": 1, ""topic"": ""middle""}, {""week"": 2, ""topic"": ""other""}, {""week"": 3, ""topic"": ""ability""}, {""w",,,Spring 2020,Universal systemic alliance 101,,


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

[User]
Convert the following JSON to XML:
{
  "instructor": "Rachel Moreno DVM",
  "credits": 4,
  "course_id": "CRS-8305",
  "title": "Open-architected even-keeled support 101",
  "term": "Spring 2023"
}

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

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


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

[User] Output clinical note as JSON.

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

Output:
{
  "note_id": "CN-8293808",
  "patient": {
    "mrn": "MRN-980604",
    "age": 24,
    "gender": "F"
  },
  "encounter_date": "2026-01-05",
  "chief_complaint": "fever",
  "vitals": {
    "bp": "150/98",
    "hr": 93,
    "temp_f": 102.4
  },
  "assessment": [
    {
      "problem": "diabetes",
      "icd10": "J39"
    }
  ]
}


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

[User] Produce a TOML document for a contract.

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

Output:
contract_id = "CTR-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"


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Optional bottom-line complexity API</title>
<version>1.0.0</version>
</info>
<paths>
</traditional>
<get>
<summary>Discussion then kind hair.</summary>
<parameters>
<name>param0</name>
<in>query</in>
<type>string</type>
</parameters>
<parameters>
<name>param1</name>
<in>query</in>
<type>string</type>
</parameters>
<responses>
<200>
<description>Success</description>
</200>
<400>
<description>Bad Request</description>
</400>
</responses>
</get>
<//traditional>
</paths>
</api_specification>

[Assistant]
Approach:
1. Task: Convert api specification 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:
{
  "openapi": "3.0.0",
  "info": {
    "title": "Optional bottom-line complexity API",
    "version": "1.0.0"
  },
  "paths": {
    "/traditional": {
      "get": {
        "summary": "Discussion then kind hair.",
        "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]
Reformat the data below from JSON to XML:
{
  "contract_id": "CTR-370819",
  "parties": [
    {
      "name": "Stewart, Thompson and Rogers",
      "role": "party_a"
    },
    {
      "name": "Jackson, Griffin and Flowers",
      "role": "party_b"
    }
  ],
  "effective_date": "2026-01-01",
  "term_months": 13,
  "value": 109351,
  "status": "active"
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<contract>
<contract_id>CTR-370819</contract_id>
<parties>
<name>Stewart, Thompson and Rogers</name>
<role>party_a</role>
</parties>
<parties>
<name>Jackson, Griffin and Flowers</name>
<role>party_b</role>
</parties>
<effective_date>2026-01-01</effective_date>
<term_months>13</term_months>
<value>109351</value>
<status>active</status>
</contract>


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<clinical_note>
<note_id>CN-3766387</note_id>
<patient>
<mrn>MRN-378219</mrn>
<age>48</age>
<gender>F</gender>
</patient>
<encounter_date>2026-01-04</encounter_date>
<chief_complaint>headache</chief_complaint>
<vitals>
<bp>145/101</bp>

106

<temp_f>101.7</temp_f>
</vitals>
<assessment>
<problem>diabetes</problem>
<icd10>J94</icd10>
</assessment>
</clinical_note>


[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: complex - 8-10 fields, 3-4 levels
3. Format rules: proper braces/brackets, quoted keys, correct value types
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
{
  "assessment_id": "ASMT-744456",
  "student_id": "STU-954920",
  "course_id": "CRS-3021",
  "type": "exam",
  "date": "2026-01-03",
  "scores": [
    {
      "question": 1,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 5,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 10,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 5,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 1,
      "points_possible": 10
    },
    {
      "question": 9,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 10,
      "points_earned": 3,
      "points_possible": 10
    },
    {
      "question": 11,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 12,
      "points_earned": 9,
      "points_possible": 10
    }
  ],
  "total_score": 97,
  "percentage": 89.67,
  "grade": "C"
}


[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:
{
  "rx_id": "RX-7328466",
  "patient_mrn": "MRN-740510",
  "prescriber": "William Hebert",
  "date": "2026-01-04",
  "medications": [
    {
      "name": "Lisinopril",
      "dosage": "20mg",
      "frequency": "TID",
      "quantity": 30
    },
    {
      "name": "Metformin",
      "dosage": "20mg",
      "frequency": "BID",
      "quantity": 60
    }
  ]
}

[Assistant]
Approach:
1. Task: Convert prescription 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"?>
<prescription>
<rx_id>RX-7328466</rx_id>
<patient_mrn>MRN-740510</patient_mrn>
<prescriber>William Hebert</prescriber>
<date>2026-01-04</date>
<medications>
<name>Lisinopril</name>
<dosage>20mg</dosage>
<frequency>TID</frequency>
<quantity>30</quantity>
</medications>
<medications>
<name>Metformin</name>
<dosage>20mg</dosage>
<frequency>BID</frequency>
<quantity>60</quantity>
</medications>
</prescription>


[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:
{
  "content": "Capital way what customer unit skill. Arm bar occur article mouth enjoy. Exactly approach mention single.\nStrong who against entire.\nKid television artist dream back agency. Need main ago investment job behavior.",
  "published": "2026-01-03T04:54:27.964292",
  "views": 73181,
  "headline": "Vision-oriented analyzing groupware",
  "section": "Business"
}

[Assistant]
Approach:
1. Task: Convert news article 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"?>
<news_article>
<content>Capital way what customer unit skill. Arm bar occur article mouth enjoy. Exactly approach mention single.
Strong who against entire.
Kid television artist dream back agency. Need main ago investment job behavior.</content>
<published>2026-01-03T04:54:27.964292</published>
<views>73181</views>
<headline>Vision-oriented analyzing groupware</headline>

Business

</news_article>


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

[User]
Reformat the data below from YAML to TOML:
date: '2026-01-04'
user_id: d6e6e646-61a4-4af9-a9a1-d03d234244eb
content: 'It herself scene five side support onto. Shake fear western believe. Say
  fact shoulder investment television pretty suffer.

  Ground listen official hand at indeed. Effort thus wife control.'

[Assistant]
Approach:
1. Task: Convert customer review from YAML to 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. Transform values to match the target format specifications.

Output:
date = "2026-01-04"
user_id = "d6e6e646-61a4-4af9-a9a1-d03d234244eb"
content = "It herself scene five side support onto. Shake fear western believe. Say fact shoulder investment television pretty suffer.\nGround listen official hand at indeed. Effort thus wife control."


[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:
{
  "rx_id": "RX-9719971",
  "patient_mrn": "MRN-909141",
  "prescriber": "Heather Stephens",
  "date": "2026-01-05",
  "medications": [
    {
      "name": "Atorvastatin",
      "dosage": "20mg",
      "frequency": "daily",
      "quantity": 30
    }
  ]
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<prescription>
<rx_id>RX-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>


[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>
<value>911148</value>
<contract_id>CTR-919818</contract_id>
<parties>
<name>Riggs, Carey and Rojas</name>
<role>party_a</role>
</parties>
<parties>
<name>Mcdowell-Koch</name>
<role>party_b</role>
</parties>
<status>active</status>
<term_months>18</term_months>
</contract>

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

Output:
{
  "value": 911148,
  "contract_id": "CTR-919818",
  "parties": [
    {
      "name": "Riggs, Carey and Rojas",
      "role": "party_a"
    },
    {
      "name": "Mcdowell-Koch",
      "role": "party_b"
    }
  ],
  "status": "active",
  "term_months": 18
}


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

[User]
Convert the following JSON to XML:
{
  "openapi": "3.0.0",
  "info": {
    "title": "Organic analyzing strategy API",
    "version": "1.0.0"
  },
  "paths": {
    "/similar": {
      "get": {
        "summary": "Natural see lot recently.",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          },
          {
            "name": "param1",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  }
}

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


[System] You are an expert in 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: complex - 8-10 fields, 3-4 levels
3. Format rules: consistent indentation, colon-space syntax, hyphen lists
4. Structure: Organize data logically with appropriate nesting
5. Populate fields with realistic example data based on the schema.

Output:
post_id: POST-86898750
platform: instagram
user_id: a47ec401-ca4e-44b5-afc7-6c2b372f589e
username: dylan00
content: 'Might north politics.

  Moment bad without change physical store call. Enjoy question state student political
  boy tonight.

  Soon ten last small develop left enter. Health lead bank and air capital save.'
timestamp: '2026-01-07T13:51:25.591017'
hashtags:
- '#kid'
- '#off'
- '#school'
- '#fund'
engagement:
  likes: 9146
  shares: 205
  comments: 18


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

[User] Generate error log data in YAML format.

[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: fd278ff8-fdfc-4b1d-81ec-31cf5ce70502
timestamp: '2026-01-07T13:51:26.554266'
level: ERROR
service: heartService
message: Attack candidate in give wish tree.
stack_trace:
- at thousand.py:354
- at forget.py:20
- at consider.py:392
context:
  user_id: d753ac0c-8931-4c37-8bd5-01413aaaba41
  request_id: b35b2bd7-dc59-4d80-ba5d-dc21fa7f0bf7


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

[User]
Transform this XML data into JSON format:
<?xml version="1.0" encoding="UTF-8"?>
<student_assessment>
<assessment_id>ASMT-458464</assessment_id>
<student_id>STU-453066</student_id>
<course_id>CRS-7675</course_id>
<type>assignment</type>
<date>2026-01-06</date>
<scores>
<question>1</question>
<points_earned>0</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>2</question>
<points_earned>9</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>4</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>5</question>
<points_earned>4</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>6</question>
<points_earned>0</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>7</question>
<points_earned>3</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>8</question>
<points_earned>7</points_earned>
<points_possible>10</points_possible>
</scores>
<scores>
<question>9</question>
<points_earned>8</points_earned>
<points_possible>10</points_possible>
</scores>
<total_score>67</total_score>
<percentage>65.79</percentage>
<grade>B</grade>
</student_assessment>

[Assistant]
Approach:
1. Task: Convert student assessment 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:
{
  "assessment_id": "ASMT-458464",
  "student_id": "STU-453066",
  "course_id": "CRS-7675",
  "type": "assignment",
  "date": "2026-01-06",
  "scores": [
    {
      "question": 1,
      "points_earned": 0,
      "points_possible": 10
    },
    {
      "question": 2,
      "points_earned": 9,
      "points_possible": 10
    },
    {
      "question": 3,
      "points_earned": 2,
      "points_possible": 10
    },
    {
      "question": 4,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 5,
      "points_earned": 4,
      "points_possible": 10
    },
    {
      "question": 6,
      "points_earned": 0,
      "points_possible": 10
    },
    {
      "question": 7,
      "points_earned": 3,
      "points_possible": 10
    },
    {
      "question": 8,
      "points_earned": 7,
      "points_possible": 10
    },
    {
      "question": 9,
      "points_earned": 8,
      "points_possible": 10
    }
  ],
  "total_score": 67,
  "percentage": 65.79,
  "grade": "B"
}


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

[User] Create a YAML representation of transaction record.

[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-59995807
customer_id: 0d66cadd-c42f-4e9b-ae40-46d71f47623d
timestamp: '2026-01-07T13:51:27.084892'
items:
- sku: SKU-83766
  qty: 4
  price: 55.35
- sku: SKU-77209
  qty: 2
  price: 217.97
- sku: SKU-11210
  qty: 5
  price: 436.04
subtotal: 1600.85
tax: 34.84
total: 602.79
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 transaction record.

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

Output:
items:
- sku: SKU-71565
  qty: 1
  price: 387.38
- sku: SKU-23891
  qty: 1
  price: 432.74
- sku: SKU-77840
  qty: 1
  price: 463.12
- sku: SKU-27496
  qty: 3
  price: 295.3
tax: 39.55
total: 1865.58
customer_id: bf96f80b-072c-4f04-82b0-c235c01681a8


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

[User] Output lab result as YAML.

[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-3793814
patient_mrn: MRN-247204
order_date: '2026-01-03'
panel: CBC
results:
- test: Hemoglobin
  value: 188.2
  unit: g/dL
  flag: low
- test: WBC
  value: 197.7
  unit: mg/dL
  flag: high
- test: Glucose
  value: 196.4
  unit: mg/dL
  flag: high
- test: Glucose
  value: 193.9
  unit: g/dL
  flag: high
- test: Glucose
  value: 197.2
  unit: g/dL
  flag: low
- test: Hemoglobin
  value: 109.5
  unit: mg/dL
  flag: normal


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

[User]
Convert the following XML to YAML:
<?xml version="1.0" encoding="UTF-8"?>
<sales_analytics>
<period>September 2022</period>
<total_revenue>4880286</total_revenue>
<units_sold>74173</units_sold>
<channels>
<name>retail</name>
<revenue>2000312</revenue>
<growth>0.96</growth>
</channels>
<channels>
<name>wholesale</name>
<revenue>3751658</revenue>
<growth>-3.19</growth>
</channels>
<top_products>
<sku>SKU-6977</sku>
<sales>264067</sales>
</top_products>
<top_products>
<sku>SKU-7032</sku>
<sales>443161</sales>
</top_products>
<top_products>
<sku>SKU-1793</sku>
<sales>209512</sales>
</top_products>
</sales_analytics>

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

Output:
period: September 2022
total_revenue: 4880286
units_sold: 74173
channels:
- name: retail
  revenue: 2000312
  growth: 0.96
- name: wholesale
  revenue: 3751658
  growth: -3.19
top_products:
- sku: SKU-6977
  sales: 264067
- sku: SKU-7032
  sales: 443161
- sku: SKU-1793
  sales: 209512


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

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

[Assistant]
Approach:
1. Task: Create customer review 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:
review_id = "REV-7169946"
product_id = "PROD-908355"
user_id = "109a43ce-0a9d-47ca-b5cc-5940dcb3a5c0"
rating = 3
title = "Suffer kid daughter race still baby."
content = "Young lot card leave book. Thank agency tree shake. Manage organization reduce from sort soldier.\nRun rich marriage parent discover kitchen. Positive person baby list positive really range."
date = "2026-01-05"
verified_purchase = true
helpful_votes = 3


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

[User] Output contract as CSV.

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

Output:
contract_id,effective_date,parties,status,term_months,value
CTR-143990,2026-01-02,"[{""name"": ""Brady Inc"", ""role"": ""party_a""}, {""name"": ""Gonzalez, Coleman and Sanchez"", ""role"": ""party_",active,32,452000
CTR-827202,2026-01-03,"[{""name"": ""Jackson, Holt and Rodgers"", ""role"": ""party_a""}, {""name"": ""Gibson Group"", ""role"": ""party_b",active,59,316482
CTR-668755,2026-01-02,"[{""name"": ""Wong-Hernandez"", ""role"": ""party_a""}, {""name"": ""Woodard PLC"", ""role"": ""party_b""}]",executed,52,912134
CTR-826226,2026-01-06,"[{""name"": ""Foster and Sons"", ""role"": ""party_a""}, {""name"": ""Bond-Gonzalez"", ""role"": ""party_b""}]",pending,23,983429


[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:
{
  "rx_id": "RX-9458448",
  "patient_mrn": "MRN-362998",
  "prescriber": "Courtney Hansen",
  "date": "2026-01-02",
  "medications": [
    {
      "name": "Lisinopril",
      "dosage": "10mg",
      "frequency": "BID",
      "quantity": 30
    }
  ]
}

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<prescription>
<rx_id>RX-9458448</rx_id>
<patient_mrn>MRN-362998</patient_mrn>
<prescriber>Courtney Hansen</prescriber>
<date>2026-01-02</date>
<medications>
<name>Lisinopril</name>
<dosage>10mg</dosage>
<frequency>BID</frequency>
<quantity>30</quantity>
</medications>
</prescription>


[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"?>
<product_listing>
<product_id>PROD-685161</product_id>
<name>Balanced demand-driven capacity</name>
<category>clothing</category>
<price>554.83</price>
<currency>USD</currency>
<stock>872</stock>
<is_available>True</is_available>
<rating>3.32</rating>
<reviews>212</reviews>
<specs>
<weight_kg>39.83</weight_kg>
<dimensions>86x88x63cm</dimensions>
</specs>
</product_listing>

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


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

[User] Generate prescription data in JSON format.

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

Output:
{
  "rx_id": "RX-9442688",
  "patient_mrn": "MRN-277514",
  "prescriber": "Timothy Goodman",
  "date": "2026-01-04",
  "medications": [
    {
      "name": "Metformin",
      "dosage": "20mg",
      "frequency": "TID",
      "quantity": 30
    },
    {
      "name": "Metformin",
      "dosage": "5mg",
      "frequency": "BID",
      "quantity": 30
    },
    {
      "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] Produce a JSON document for a api specification.

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

Output:
{
  "openapi": "3.0.0",
  "info": {
    "title": "Business-focused zero administration encryption API",
    "version": "1.0.0"
  },
  "paths": {
    "/teach": {
      "get": {
        "summary": "Government trade direction personal reason hundred",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          },
          {
            "name": "param1",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  }
}


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

[User]
Convert the following XML to JSON:
<?xml version="1.0" encoding="UTF-8"?>
<customer_review>
<title>Exactly almost full new record save.</title>
<date>2026-01-02</date>
<product_id>PROD-922306</product_id>
<content>Arrive much low will teach. By possible nature learn could. Act hot whole guy experience.
Identify world fight stock. Force fear soon. Author night think.</content>
</customer_review>

[Assistant]
Approach:
1. Task: Convert customer review 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:
{
  "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 TOML format. Think step-by-step, then generate syntactically perfect TOML.

[User] Output social media post as TOML.

[Assistant]
Approach:
1. Task: Create social media post 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:
post_id = "POST-46905875"
platform = "instagram"
user_id = "2079b341-d50b-4860-ba15-aa28bbe0f5b3"
username = "xhernandez"
content = "Serious degree upon late.\nPainting 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 XML format. Think step-by-step, then generate syntactically perfect XML.

[User]
Reformat the data below from JSON to XML:
{
  "instructor": "Tamara Stark",
  "term": "Spring 2022",
  "code": "VMA483",
  "grading": {
    "homework": 30,
    "midterm": 30,
    "final": 40
  }
}

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

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


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

[User] Create a YAML representation of financial report.

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

Output:
company: Snow, Shelton and Parsons
ticker: LYEH
quarter: Q3 2022
revenue: 49988929
expenses: 3428077
net_income: 8543670
eps: 3.41
metrics:
  profit_margin: 11.21
  roe: 5.99


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

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

[Assistant]
Approach:
1. Task: Create social media post in TOML
2. Complexity: 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:
post_id = "POST-18209344"
platform = "facebook"
user_id = "8880ae5d-22ce-466e-ac5d-224201417b5e"
username = "xmcbride"
content = "Determine live compare center as direction. Eye experience low wear. If south level.\nWorry expect style camera. Scene majority pay voice television professor."
timestamp = "2026-01-07T13:51:27.602464"
hashtags = [ "#culture", "#whole", "#central",]

[engagement]
likes = 2214
shares = 878
comments = 146


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

[User] Output prescription as YAML.

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

Output:
rx_id: RX-9001624
patient_mrn: MRN-695608
prescriber: Stephen Davis
date: '2026-01-05'
medications:
- name: Lisinopril
  dosage: 20mg
  frequency: daily
  quantity: 90


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

[User] Generate clinical note data in JSON format.

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

Output:
{
  "note_id": "CN-6952117",
  "patient": {
    "mrn": "MRN-227055",
    "age": 50,
    "gender": "F"
  },
  "encounter_date": "2026-01-03",
  "chief_complaint": "headache",
  "vitals": {
    "bp": "146/78",
    "hr": 63,
    "temp_f": 97.9
  },
  "assessment": [
    {
      "problem": "hypertension",
      "icd10": "J35"
    },
    {
      "problem": "hypertension",
      "icd10": "K44"
    },
    {
      "problem": "hypertension",
      "icd10": "I58"
    }
  ]
}


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

[User] Generate transaction record data in JSON format.

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


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

[User]
Convert the following TOML to YAML:
error_id = "92d36993-19b1-4c19-9b64-8b4669c6636f"
timestamp = "2026-01-07T13:51:27.222487"
level = "WARNING"
service = "voiceService"
message = "Analysis beautiful attack blue eye."
stack_trace = [ "at well.py:163", "at will.py:421", "at run.py:384", "at TV.py:103",]

[context]
user_id = "c92bcb8f-c109-47f8-aa13-b43737a1fc38"
request_id = "f4cb6737-30c9-41ef-814b-34c3ec971deb"

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


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

[User]
Reformat the data below from CSV to TOML:
abstract,authors,citations,funding_source,keywords,paper_id,publication_doi,publication_venue,publication_year,title
"Relate make read game soldier new. Agree south attorney one century drive draw.
Reduce head tax cert","[{""name"": ""Ashley Hubbard"", ""affiliation"": ""Mcdonald-White"", ""email"": ""jenniferlong@example.net""}, {",65,Parsons Inc,"[""gas"", ""understand"", ""everything"", ""miss""]",arXiv:2024.49729,10.3465/hMKF,Cell,2024,Optimized fault-tolerant monitoring
Quite personal enough like wrong. Type use social step lead action attack. Second high impact paper.,"[{""name"": ""Shawn Fischer"", ""affiliation"": ""Leblanc-Long"", ""email"": ""holmesmichelle@example.org""}, {""",480,None,"[""speech"", ""language"", ""wife"", ""old""]",arXiv:2022.59733,10.1750/XgMv,Nature,2020,Re-engineered clear-thinking Internet solution
Affect change either money commercial. Often allow wish suffer person.,"[{""name"": ""Shannon Huber"", ""affiliation"": ""Erickson-Flynn"", ""email"": ""singhjeffrey@example.org""}, {""",229,None,"[""edge"", ""friend"", ""develop"", ""reflect""]",arXiv:2023.25133,10.6743/gNVb,Nature,2023,Innovative full-range projection

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

Output:
paper_id = "arXiv:2024.49729"
title = "Optimized fault-tolerant monitoring"
abstract = "Relate make read game soldier new. Agree south attorney one century drive draw.\nReduce head tax certainly offer deal. Sister station adult seat wear."
keywords = [ "gas", "understand", "everything", "miss",]
citations = 65
funding_source = "Parsons Inc"
[[authors]]
name = "Ashley Hubbard"
affiliation = "Mcdonald-White"
email = "jenniferlong@example.net"

[[authors]]
name = "Erica Marshall"
affiliation = "Calderon-Dalton"
email = "adouglas@example.org"

[[authors]]
name = "Mercedes Campbell"
affiliation = "Davis-Lynch"
email = "yharris@example.org"

[publication]
venue = "Cell"
year = 2024
doi = "10.3465/hMKF"


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

[User] Generate sales analytics data in JSON format.

[Assistant]
Approach:
1. Task: Create sales analytics 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:
{
  "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 YAML format. Think step-by-step, then generate syntactically perfect YAML.

[User] Generate financial report data in YAML format.

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

Output:
company: Smith-Glover
ticker: JROI
quarter: Q3 2023
revenue: 95238846
expenses: 30652579
net_income: 5856951
eps: 7.31
metrics:
  profit_margin: 9.94
  roe: 10.91


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

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

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

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


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

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

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


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

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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<clinical_note>
<note_id>CN-6224145</note_id>
<patient>
<mrn>MRN-560569</mrn>
<age>88</age>
<gender>F</gender>
</patient>
<encounter_date>2026-01-04</encounter_date>
<chief_complaint>headache</chief_complaint>
<vitals>
<bp>119/73</bp>

63

<temp_f>100.0</temp_f>
</vitals>
<assessment>
<problem>hypertension</problem>
<icd10>I32</icd10>
</assessment>
</clinical_note>


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

[User] Output customer review as TOML.

[Assistant]
Approach:
1. Task: Create customer review in TOML
2. Complexity: 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:
review_id = "REV-1369973"
product_id = "PROD-861575"
user_id = "a55bb48c-5dcb-464a-b952-9d377a4cb9c4"
rating = 1
title = "Relationship job find one allow law through."
content = "Now decide senior fact big window yourself. Difference appear seat coach rather once politics. Modern always able physical Republican best draw land."
date = "2026-01-02"
verified_purchase = true
helpful_votes = 8


[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:
{
  "rating": 4.54,
  "stock": 843,
  "specs": {
    "weight_kg": 34.7,
    "dimensions": "61x86x65cm"
  },
  "currency": "USD"
}

[Assistant]
Approach:
1. Task: Convert product listing 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"?>
<product_listing>
<rating>4.54</rating>
<stock>843</stock>
<specs>
<weight_kg>34.7</weight_kg>
<dimensions>61x86x65cm</dimensions>
</specs>
<currency>USD</currency>
</product_listing>


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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<contract>
<contract_id>CTR-313579</contract_id>
<parties>
<name>Roberts, Newton and Ortiz</name>
<role>party_a</role>
</parties>
<parties>
<name>Garcia PLC</name>
<role>party_b</role>
</parties>
<effective_date>2026-01-01</effective_date>
<term_months>55</term_months>
<value>108642</value>
<status>active</status>
</contract>


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

[User] Generate prescription data in YAML format.

[Assistant]
Approach:
1. Task: Create prescription in YAML
2. Complexity: 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-9036427
patient_mrn: MRN-461250
prescriber: Zachary Berry
date: '2026-01-01'
medications:
- name: Atorvastatin
  dosage: 5mg
  frequency: daily
  quantity: 30


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

[User] Generate prescription data in TOML format.

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

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


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

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

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

Output:
assessment,chief_complaint,encounter_date,note_id,patient_age,patient_gender,patient_mrn,vitals_bp,vitals_hr,vitals_temp_f
"[{""problem"": ""diabetes"", ""icd10"": ""I93""}]",headache,2026-01-05,CN-5751204,47,M,MRN-566004,160/96,75,102.4
"[{""problem"": ""diabetes"", ""icd10"": ""I82""}, {""problem"": ""hypertension"", ""icd10"": ""J65""}, {""problem"": """,fever,2026-01-01,CN-2502600,49,F,MRN-598677,116/89,111,103.0
"[{""problem"": ""hypertension"", ""icd10"": ""K48""}]",headache,2026-01-01,CN-4629095,60,F,MRN-182275,160/109,82,98.1


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

[User] Generate course syllabus data in CSV format.

[Assistant]
Approach:
1. Task: Create course syllabus in CSV
2. Complexity: 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
NOO384,CRS-7514,4,40,30,30,Lori Martinez,"[{""week"": 1, ""topic"": ""bar""}, {""week"": 2, ""topic"": ""population""}, {""week"": 3, ""topic"": ""thus""}, {""we",Fall 2024,Fundamental encompassing database 101
ZLC172,CRS-3543,3,40,30,30,Kelly Parker,"[{""week"": 1, ""topic"": ""between""}, {""week"": 2, ""topic"": ""dinner""}, {""week"": 3, ""topic"": ""young""}, {""w",Fall 2021,Sharable modular archive 101
FQF224,CRS-9589,3,40,30,30,Lucas Chandler,"[{""week"": 1, ""topic"": ""this""}, {""week"": 2, ""topic"": ""each""}, {""week"": 3, ""topic"": ""follow""}, {""week""",Fall 2022,Reduced static focus group 101
RRP289,CRS-3316,4,40,30,30,Taylor Ramsey,"[{""week"": 1, ""topic"": ""those""}, {""week"": 2, ""topic"": ""least""}, {""week"": 3, ""topic"": ""enter""}, {""week",Fall 2024,Upgradable asymmetric interface 101
YVJ171,CRS-1609,3,40,30,30,Emily Norton,"[{""week"": 1, ""topic"": ""maybe""}, {""week"": 2, ""topic"": ""such""}, {""week"": 3, ""topic"": ""available""}, {""w",Spring 2021,Self-enabling even-keeled firmware 101


[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"?>
<news_article>
<article_id>ART-5347545</article_id>
<headline>Triple-buffered zero administration algorithm</headline>
<author>Martha Brown</author>
<published>2026-01-05T16:28:34.342789</published>

Sports

<content>Have fall sing then fast research break. Bar ready eye medical school might recognize. Nice sometimes impact point white.
Take many this never ever trip. Specific call according. We argue person federal central each.</content>
<tags>line</tags>
<tags>true</tags>
<tags>compare</tags>
<tags>for</tags>
<views>96946</views>
<shares>1479</shares>
</news_article>

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

Output:
{
  "article_id": "ART-5347545",
  "headline": "Triple-buffered zero administration algorithm",
  "author": "Martha Brown",
  "published": "2026-01-05T16:28:34.342789",
  "section": "Sports",
  "content": "Have fall sing then fast research break. Bar ready eye medical school might recognize. Nice sometimes impact point white.\nTake many this never ever trip. Specific call according. We argue person federal central each.",
  "tags": [
    "line",
    "true",
    "compare",
    "for"
  ],
  "views": 96946,
  "shares": 1479
}


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

[User] Create a TOML representation of student assessment.

[Assistant]
Approach:
1. Task: Create student assessment in TOML
2. Complexity: 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 = 97
percentage = 78.32
course_id = "CRS-4089"
[[scores]]
question = 1
points_earned = 0
points_possible = 10

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

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

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

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

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

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

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

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

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

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


[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: 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: 6b141850-4372-44c1-8cf7-fc47780a5017
timestamp: '2026-01-07T13:51:26.727039'
level: WARNING
service: fullService
message: Simply human maintain sport.
stack_trace:
- at environmental.py:351
- at develop.py:28
- at send.py:431
context:
  user_id: fad7b695-3fb8-4313-ad8d-c2b1d4034196
  request_id: 2ca5c81e-d6c8-42a4-9e09-9715e928fe91


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

[User]
Transform this JSON data into XML format:
{
  "openapi": "3.0.0",
  "info": {
    "title": "Horizontal interactive project API",
    "version": "1.0.0"
  },
  "paths": {
    "/base": {
      "get": {
        "summary": "Management send father actually special image.",
        "parameters": [
          {
            "name": "param0",
            "in": "query",
            "type": "string"
          }
        ],
        "responses": {
          "200": {
            "description": "Success"
          },
          "400": {
            "description": "Bad Request"
          }
        }
      }
    }
  }
}

[Assistant]
Approach:
1. Task: Convert api specification from JSON to XML
2. Complexity: 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"?>
<api_specification>
<openapi>3.0.0</openapi>
<info>
<title>Horizontal interactive project API</title>
<version>1.0.0</version>
</info>
<paths>
</base>
<get>
<summary>Management send father actually special image.</summary>
<parameters>
<name>param0</name>
<in>query</in>
<type>string</type>
</parameters>
<responses>
<200>
<description>Success</description>
</200>
<400>
<description>Bad Request</description>
</400>
</responses>
</get>
<//base>
</paths>
</api_specification>


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


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

[User] Generate sales analytics data in JSON format.

[Assistant]
Approach:
1. Task: Create sales analytics 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:
{
  "period": "May 2020",
  "total_revenue": 9864225,
  "units_sold": 74086,
  "channels": [
    {
      "name": "online",
      "revenue": 906832,
      "growth": -8.93
    },
    {
      "name": "wholesale",
      "revenue": 2437365,
      "growth": 2.73
    }
  ],
  "top_products": [
    {
      "sku": "SKU-7032",
      "sales": 420063
    },
    {
      "sku": "SKU-9360",
      "sales": 149398
    },
    {
      "sku": "SKU-9440",
      "sales": 105905
    }
  ]
}


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

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

Output:
<?xml version="1.0" encoding="UTF-8"?>
<social_media_post>
<post_id>POST-86945311</post_id>
<platform>facebook</platform>
<user_id>b9da037c-f6cd-4ced-8c95-ca7562cf6118</user_id>
<username>martinsteven</username>
<content>Forget late prevent year cold able arrive. Few possible himself sing community. Activity campaign sure south. Chance on none line best magazine education.</content>
<timestamp>2026-01-07T13:51:26.810240</timestamp>
<hashtags>#drop</hashtags>
<hashtags>#consider</hashtags>
<hashtags>#nature</hashtags>
<hashtags>#all</hashtags>
<engagement>
<likes>3344</likes>
<shares>900</shares>
<comments>482</comments>
</engagement>
</social_media_post>


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

[User] Create a CSV representation of research paper.

[Assistant]
Approach:
1. Task: Create research paper in CSV
2. Complexity: 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,keywords,paper_id,publication_doi,publication_venue,publication_year,title
Along its pressure yeah. Artist pattern nearly rich realize available skill. Month beyond rate make ,"[{""name"": ""Jared Fuller"", ""affiliation"": ""Robinson, Crawford and Johnson"", ""email"": ""jenna58@example",488,Johnson LLC,"[""surface"", ""consumer"", ""despite"", ""compare"", ""protect""]",arXiv:2020.65510,10.8909/Qnkv,Nature,2022,Mandatory solution-oriented groupware
"Anyone station particularly. Side know station early staff.
Appear executive car only according seat","[{""name"": ""Kenneth Thompson"", ""affiliation"": ""King, Benton and Jones"", ""email"": ""fruiz@example.com""}",160,"Fowler, Torres and Sosa","[""east"", ""believe"", ""include"", ""open""]",arXiv:2022.55799,10.2008/ldyq,Nature,2022,Down-sized multi-state leverage
Population avoid week rest defense respond address. Garden share power activity local.,"[{""name"": ""James Carroll"", ""affiliation"": ""Kim-Fox"", ""email"": ""nicholspamela@example.net""}, {""name"":",472,Hill and Sons,"[""benefit"", ""air"", ""analysis""]",arXiv:2022.29623,10.6566/gpqp,Science,2020,Progressive actuating knowledge user