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lore-extraction

Base extraction rules for all lore subagents. Governs entity identification, contextual analysis, relationship mapping, and JSON output formatting.

Datos de origen

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bivex/loreSystem
Última actividad en el origen
21 de marzo de 2026 a las 15:19
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SKILL.md
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name
lore-extraction
description
Base extraction rules for all lore subagents. Governs entity identification, contextual analysis, relationship mapping, and JSON output formatting.
user-invocable
false
# lore-extraction Base skill for all loreSystem extraction subagents. Common rules for extracting entities from narrative text. ## Extraction Pipeline 1. **Read** the source text completely before extracting 2. **Identify** entities — look for named things, described systems, relationships 3. **Classify** each entity to its correct type from the entity ownership map 4. **Format** according to the export schema 5. **Output** as JSON compatible with `LoreData.to_dict` (see `src/presentation/gui/lore_data.py`) 6. **Validate** against domain model constraints 7. **Review** for completeness and accuracy ## Entity Identification Rules - Named entities (proper nouns, titles) → extract with exact name - Described systems (magic system, economy) → extract with descriptive name - Implied entities (unnamed but significant) → extract with contextual name - Groups/collections → extract as single entity with members in description ## Cross-Domain References When text mentions an entity owned by another skill: - Do NOT create the entity — it belongs to the other skill - Record the reference in a separate draft note for the lead to merge - Include enough context (name, location, relation) for reconciliation ## Quality Rules - Extract only what the text explicitly states or strongly implies - Do not invent details not supported by the text - If unsure, add a short comment in your draft note (not in the JSON export) - Prefer fewer high-quality entities over many low-quality ones
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