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urban-design

Extract urban planning entities from narrative text. Use when analyzing city districts, wards, quarters, plazas, markets, slums, noble districts, and port areas.

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Dépôt
bivex/loreSystem
Dernière activité de la source
21 mars 2026 à 15:19
Langue détectée de SKILL.md
anglais
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0
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SKILL.md
Instructions source · Aperçu en lecture seule
name
urban-design
description
Extract urban planning entities from narrative text. Use when analyzing city districts, wards, quarters, plazas, markets, slums, noble districts, and port areas.
# urban-design Domain skill for urban planning and city structure extraction. ## Entity Types | Type | Description | |------|-------------| | `district` | Named city district or neighborhood | | `ward` | Administrative ward or section | | `quarter` | City quarter (e.g., merchant quarter) | | `plaza` | Public plaza or gathering space | | `market_square` | Market area or trade hub | | `slums` | Impoverished area | | `noble_district` | Wealthy or aristocratic area | | `port_district` | Waterfront or harbor area | ## Extraction Rules 1. **Named districts**: Extract with exact name and characteristics 2. **Social geography**: Map wealth distribution across the city 3. **Infrastructure**: Roads, walls, gates, utilities mentioned 4. **Activity zones**: Commercial, residential, religious, industrial areas 5. **Historical layers**: Old vs new city sections ## Output Format Write to `entities/world.json` (world-team file): ```json { "districts": [ { "id": "4dbf72a5-1a2b-4b3c-9d4e-5f6a7b8c9d0e", "tenant_id": "t-1", "name": "Merchant Quarter", "city_id": "l-1", "district_type": "commercial", "population": 12000, "safety_level": 0.6, "prosperity_level": 0.8, "is_active": true, "created_at": "2026-02-14T10:00:00+00:00", "updated_at": "2026-02-14T10:00:00+00:00" } ], "slums": [ { "id": "c2d8b8a1-9e7b-4c6d-8a1b-2c3d4e5f6a7b", "tenant_id": "t-1", "name": "The Warrens", "city_id": "l-1", "district_type": "slums", "population": 25000, "safety_level": 0.2, "prosperity_level": 0.1, "is_active": true, "created_at": "2026-02-14T10:00:00+00:00", "updated_at": "2026-02-14T10:00:00+00:00" } ] } ``` ## Key Considerations - **Social inequality**: Slums vs noble districts show wealth gap - **Mixed use**: Many areas are residential + commercial - **Historical layers**: Cities have old and new sections - **Cross-references**: If needed, track relationships separately in drafts, but final JSON must match `LoreData.from_dict`.
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