Your task is to generate unique, realistic, and demographically heterogeneous human profiles that fully match the provided input filters. These profiles simulate diverse human lives across different countries and contexts. Use your knowledge of the specified country’s population, economy, social structure, and culture to ensure realism. Profiles must be plausible, internally consistent, and contextually grounded — not artificial or pattern-based.

<input> {{inputFields}} </input> Generation Principles 1. Strict Filter Compliance (Mandatory) Every generated profile must strictly follow the input filters: Gender Age range Country Number of profiles (exactly {{amount}}) Any specified education level, family situation, or other attributes Instructions or requests in the other field Filters are non-negotiable. If the filter says “PhD only,” every profile must reflect that. If fields are set to “All,” variety is encouraged. 2. Dynamic Cultural Localization Use the country field to ground each profile in local reality. Reflect: Culturally plausible names, family roles, and lifestyles Local education systems and credential formats Income levels and economic patterns relevant to that region Professions typical for that country and geography (urban/rural) Social and demographic norms (e.g. living arrangements, work patterns) Avoid generic or Westernized profiles. Make each one feel like it belongs where it's located. 3. Interpret the other Field as a Narrative Guide The other field contains free-text instructions. These may ask for: Personality traits or story types (e.g., “Include idealists or activists”) Social characteristics (e.g., “Include LGBTQ+ or neurodivergent people”) Life experiences (e.g., “Include people who failed school and recovered”) These inputs are not filters but creative cues. Include such characters where possible and reflect them subtly and realistically in some profiles. 4. Diversity Without Artificial Balance When filters allow flexibility, simulate natural demographic variation: Education levels Income brackets Family types Living environments (urban, suburban, rural) Professions across blue collar, white collar, care, STEM, manual, gig work, etc. Avoid repeated combinations like: “Bachelor’s + $50k–70k + single + urban + white-collar job”. Diversity should reflect how life unfolds, not how spreadsheets balance. 5. Real-World Messiness and Life Variation Some profiles should reflect: People in unstable or transitional life stages (e.g., retraining, career shift, student-parent) Migrants, expats, or marginalized groups Underemployed or overqualified individuals Economic hardship or social complexity Non-traditional or culturally variable family structures Non-linear career or education paths Let each profile represent a believable person — not an optimized datapoint. 6. Internal and External Edge Case Awareness Internal consistency: Education, job, income, family status, and geography must align logically Avoid improbable timelines (e.g., 20-year-old executives unless justified in other) If an edge case appears (e.g., highly educated person in low-income job), provide contextual plausibility (e.g., migrant status, career shift) External realism: Match country-specific job markets, family norms, naming conventions, and cost-of-living Do not apply one country's social structure or economics to another’s context Edge cases must still fit within local cultural expectations Format your output as a pure JSON array of profile objects Here's an example of the expected structure: <output> [ { "ID": "001", "Urban/Rural": "Urban", "gender": "Female", "education": "Bachelor's degree", "income": "$50,000 - $75,000", "profession": "Software Developer", "family": "Married, 1 child", "age": 32, "country": "United States" }, { "ID": "002", "Urban/Rural": "Rural", "gender": "Male", "education": "High school diploma", "income": "$30,000 - $45,000", "profession": "Construction Worker", "family": "Single", "age": 28, "country": "United States" } ] </ouput> After generating the profiles, enclose your final output within <output> tags only — without any markdown, backticks, or language indicators. Remember to maintain diversity, reflect regional trends, and ensure all profiles are realistic and coherent.