| {"id": "cbdcec2fecf9", "prompt": "Generate a JSON document representing a CI/CD pipeline run. Include: run_id, repository, branch, commit_sha (short), triggered_by, status, started_at, duration_seconds, and stages (array with name, status, duration_seconds for at least 4 stages).", "format": "json", "schema_description": "CI/CD pipeline run with stages array", "completion": "{\n \"run_id\": \"run-14892\",\n \"repository\": \"acme-corp/checkout-service\",\n \"branch\": \"main\",\n \"commit_sha\": \"a3f9c12\",\n \"triggered_by\": \"push\",\n \"status\": \"passed\",\n \"started_at\": \"2024-11-01T11:00:00Z\",\n \"duration_seconds\": 183,\n \"stages\": [\n {\"name\": \"lint\", \"status\": \"passed\", \"duration_seconds\": 14},\n {\"name\": \"test\", \"status\": \"passed\", \"duration_seconds\": 62},\n {\"name\": \"build\", \"status\": \"passed\", \"duration_seconds\": 88},\n {\"name\": \"deploy\", \"status\": \"passed\", \"duration_seconds\": 19}\n ]\n}", "domain": "software", "difficulty": "hard", "num_fields": 9} |
| {"id": "c90a65dd4836", "prompt": "Produce a YAML configuration for a feature flag system. Define three flags: dark_mode (enabled for 100% of users), new_checkout_flow (enabled for 10% of users via percentage rollout), and beta_dashboard (enabled only for users with role 'beta_tester').", "format": "yaml", "schema_description": "Feature flag configuration with rollout rules", "completion": "feature_flags:\n dark_mode:\n enabled: true\n rollout:\n type: all_users\n percentage: 100\n\n new_checkout_flow:\n enabled: true\n rollout:\n type: percentage\n percentage: 10\n\n beta_dashboard:\n enabled: true\n rollout:\n type: attribute_match\n attribute: role\n values:\n - beta_tester", "domain": "software", "difficulty": "medium", "num_fields": 5} |
| {"id": "4801e401b93f", "prompt": "Generate a YAML file for a patient medication schedule. Include: patient_id, patient_name, medications as a list (each with drug_name, dose_mg, frequency, route, start_date, end_date, and notes).", "format": "yaml", "schema_description": "Patient medication schedule", "completion": "patient_id: PAT-88210\npatient_name: \"Carmen Rodríguez\"\nmedications:\n - drug_name: Amoxicillin\n dose_mg: 500\n frequency: \"every 8 hours\"\n route: oral\n start_date: 2024-10-28\n end_date: 2024-11-07\n notes: \"Take with food\"\n - drug_name: Ibuprofen\n dose_mg: 400\n frequency: \"every 6 hours as needed\"\n route: oral\n start_date: 2024-10-28\n end_date: 2024-11-03\n notes: \"Do not exceed 1600mg per day\"", "domain": "healthcare", "difficulty": "medium", "num_fields": 7} |
| {"id": "010b344e1b8b", "prompt": "Create a Markdown table listing key vitamins. Columns: Vitamin, Type (fat-soluble/water-soluble), Primary Function, Deficiency Disease, Major Food Sources.", "format": "markdown_table", "schema_description": "Vitamin reference table, 8 vitamins", "completion": "| Vitamin | Type | Primary Function | Deficiency Disease | Major Food Sources |\n|---|---|---|---|---|\n| A (Retinol) | Fat-soluble | Vision, immune function, skin | Night blindness | Liver, carrots, sweet potato |\n| B1 (Thiamine) | Water-soluble | Carbohydrate metabolism, nerve function | Beriberi | Whole grains, legumes, pork |\n| B12 (Cobalamin) | Water-soluble | DNA synthesis, nerve myelin | Pernicious anaemia | Meat, dairy, eggs |\n| C (Ascorbic acid) | Water-soluble | Collagen synthesis, antioxidant | Scurvy | Citrus fruit, bell peppers, broccoli |\n| D (Calciferol) | Fat-soluble | Calcium absorption, bone health | Rickets / osteomalacia | Sunlight, oily fish, fortified milk |\n| E (Tocopherol) | Fat-soluble | Antioxidant, cell membrane protection | Rare — peripheral neuropathy | Nuts, seeds, vegetable oils |\n| K (Phylloquinone) | Fat-soluble | Blood clotting, bone mineralisation | Haemorrhage | Leafy greens, fermented foods |\n| B9 (Folate) | Water-soluble | DNA synthesis, red blood cell production | Neural tube defects, anaemia | Legumes, leafy greens, fortified grain |", "domain": "healthcare", "difficulty": "medium", "num_fields": 5} |
| {"id": "791a21934d0c", "prompt": "Produce a JSON object for a hotel reservation. Include: reservation_id, hotel_name, check_in, check_out, nights, room_type, guests (adults, children), breakfast_included, rate_per_night_usd, total_usd, loyalty_points_earned, and special_requests.", "format": "json", "schema_description": "Hotel reservation record", "completion": "{\n \"reservation_id\": \"HTL-20241115-8821\",\n \"hotel_name\": \"Grand Meridian Tokyo\",\n \"check_in\": \"2024-12-01\",\n \"check_out\": \"2024-12-05\",\n \"nights\": 4,\n \"room_type\": \"Deluxe King\",\n \"guests\": {\n \"adults\": 2,\n \"children\": 0\n },\n \"breakfast_included\": true,\n \"rate_per_night_usd\": 180.00,\n \"total_usd\": 720.00,\n \"loyalty_points_earned\": 720,\n \"special_requests\": \"High floor with city view preferred; late check-out if available.\"\n}", "domain": "logistics", "difficulty": "medium", "num_fields": 11} |
| {"id": "7b2905b4f2cf", "prompt": "Create a Markdown table comparing three cloud providers (AWS, Azure, GCP) on the following dimensions: object storage name, managed Kubernetes name, serverless compute name, and global regions count (approximate).", "format": "markdown_table", "schema_description": "Cloud provider comparison table, 4 attributes × 3 providers", "completion": "| Feature | AWS | Azure | GCP |\n|---|---|---|---|\n| Object Storage | S3 | Blob Storage | Cloud Storage |\n| Managed Kubernetes | EKS | AKS | GKE |\n| Serverless Compute | Lambda | Azure Functions | Cloud Functions |\n| Global Regions (approx.) | 33 | 60+ | 40 |", "domain": "software", "difficulty": "easy", "num_fields": 4} |
| {"id": "2975d9ecf442", "prompt": "Return a CSV of 4 countries' economic indicators for 2023. Columns: country, gdp_usd_trillions, gdp_growth_pct, inflation_pct, unemployment_pct, debt_to_gdp_pct, currency.", "format": "csv", "schema_description": "Economic indicators by country, 4 rows", "completion": "country,gdp_usd_trillions,gdp_growth_pct,inflation_pct,unemployment_pct,debt_to_gdp_pct,currency\nUnited States,27.36,2.5,3.4,3.7,122.3,USD\nGermany,4.46,0.2,5.9,5.5,64.3,EUR\nIndia,3.73,8.2,5.4,7.8,81.9,INR\nBrazil,2.13,2.9,4.6,7.8,88.1,BRL", "domain": "finance", "difficulty": "medium", "num_fields": 7} |
| {"id": "7a2d89c1db3d", "prompt": "Produce a JSON object for a sports match result. Include: match_id, sport, competition, date, venue, home_team (name, score, goals list as strings), away_team (name, score, goals list), status, and attendance.", "format": "json", "schema_description": "Football match result with goal lists", "completion": "{\n \"match_id\": \"MTH-202411-4481\",\n \"sport\": \"football\",\n \"competition\": \"UEFA Champions League, Group Stage\",\n \"date\": \"2024-11-05\",\n \"venue\": \"Allianz Arena, Munich\",\n \"home_team\": {\n \"name\": \"FC Bayern München\",\n \"score\": 3,\n \"goals\": [\"Müller 24'\", \"Kane 58' (pen)\", \"Sané 78'\"]\n },\n \"away_team\": {\n \"name\": \"Manchester City\",\n \"score\": 1,\n \"goals\": [\"Haaland 45+2'\"]\n },\n \"status\": \"full-time\",\n \"attendance\": 75024\n}", "domain": "sports", "difficulty": "medium", "num_fields": 7} |
| {"id": "3fdd2c40c8e0", "prompt": "Create a Markdown table of 5 open-source LLMs with columns: Model, Creator, Parameters, License, Context Window, Best For.", "format": "markdown_table", "schema_description": "Open-source LLM comparison table", "completion": "| Model | Creator | Parameters | License | Context Window | Best For |\n|---|---|---|---|---|---|\n| Llama 3.1 70B | Meta | 70B | Llama 3.1 Community | 128K tokens | General purpose, coding |\n| Mistral 7B | Mistral AI | 7B | Apache 2.0 | 32K tokens | Fast inference, edge |\n| Qwen2.5 72B | Alibaba | 72B | Qwen License | 128K tokens | Multilingual, coding |\n| Gemma 2 27B | Google | 27B | Gemma License | 8K tokens | Research, instruction following |\n| Phi-3.5 Mini | Microsoft | 3.8B | MIT | 128K tokens | On-device, low resource |", "domain": "ai", "difficulty": "medium", "num_fields": 6} |
| {"id": "ede489cc6c42", "prompt": "Return a JSON array of three countries, each with fields: name, iso_code, capital, population_millions, and continent.", "format": "json", "schema_description": "Array of country objects", "completion": "[\n {\n \"name\": \"Germany\",\n \"iso_code\": \"DE\",\n \"capital\": \"Berlin\",\n \"population_millions\": 84.4,\n \"continent\": \"Europe\"\n },\n {\n \"name\": \"Brazil\",\n \"iso_code\": \"BR\",\n \"capital\": \"Brasília\",\n \"population_millions\": 215.3,\n \"continent\": \"South America\"\n },\n {\n \"name\": \"Japan\",\n \"iso_code\": \"JP\",\n \"capital\": \"Tokyo\",\n \"population_millions\": 124.5,\n \"continent\": \"Asia\"\n }\n]", "domain": "geography", "difficulty": "easy", "num_fields": 5} |
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