lore-extraction — civilization lore-extraction, loreSystem, community, civilization, ide skills, creation, creative, fiction, storytelling, toolkit

v1.0.0

Об этом навыке

Идеально для агентов Worldbuilding, которым необходимы продвинутые возможности анализа повествовательного текста и извлечения сущностей. Base extraction rules for all lore subagents. Governs entity identification, contextual analysis, relationship mapping, and JSON output formatting.

# Core Topics

bivex bivex
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Updated: 3/21/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reference-Only Page Review Score: 7/11

This page remains useful for operators, but Killer-Skills treats it as reference material instead of a primary organic landing page.

Original recommendation layer Concrete use-case guidance Explicit limitations and caution
Review Score
7/11
Quality Score
29
Canonical Locale
en
Detected Body Locale
en

Идеально для агентов Worldbuilding, которым необходимы продвинутые возможности анализа повествовательного текста и извлечения сущностей. Base extraction rules for all lore subagents. Governs entity identification, contextual analysis, relationship mapping, and JSON output formatting.

Зачем использовать этот навык

Наделяет агентов возможностью извлекать сущности из повествовательного текста, классифицировать их в соответствии с картой собственности сущностей и форматировать их как JSON, совместимый с LoreData.to_dict, используя стандартизированный pipeline извлечения и поддерживая протоколы, такие как JSON.

Подходит лучше всего

Идеально для агентов Worldbuilding, которым необходимы продвинутые возможности анализа повествовательного текста и извлечения сущностей.

Реализуемые кейсы использования for lore-extraction

Извлечение сущностей из повествовательных текстов для создания иммерсивных вселенных
Проектирование цивилизаций путем выявления и классификации отношений между сущностями
Автоматизация процесса построения карт собственности сущностей для проектов worldbuilding

! Безопасность и ограничения

  • Требует, чтобы весь исходный текст был прочитан перед извлечением
  • Ограничен анализом повествовательного текста
  • Требует предварительно определенной карты собственности сущностей для классификации

Why this page is reference-only

  • - Current locale does not satisfy the locale-governance contract.
  • - The underlying skill quality score is below the review floor.

Source Boundary

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

After The Review

Decide The Next Action Before You Keep Reading Repository Material

Killer-Skills should not stop at opening repository instructions. It should help you decide whether to install this skill, when to cross-check against trusted collections, and when to move into workflow rollout.

Labs Demo

Browser Sandbox Environment

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Boot Container Sandbox

FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is lore-extraction?

Идеально для агентов Worldbuilding, которым необходимы продвинутые возможности анализа повествовательного текста и извлечения сущностей. Base extraction rules for all lore subagents. Governs entity identification, contextual analysis, relationship mapping, and JSON output formatting.

How do I install lore-extraction?

Run the command: npx killer-skills add bivex/loreSystem/lore-extraction. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for lore-extraction?

Key use cases include: Извлечение сущностей из повествовательных текстов для создания иммерсивных вселенных, Проектирование цивилизаций путем выявления и классификации отношений между сущностями, Автоматизация процесса построения карт собственности сущностей для проектов worldbuilding.

Which IDEs are compatible with lore-extraction?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for lore-extraction?

Требует, чтобы весь исходный текст был прочитан перед извлечением. Ограничен анализом повествовательного текста. Требует предварительно определенной карты собственности сущностей для классификации.

How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add bivex/loreSystem/lore-extraction. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use lore-extraction immediately in the current project.

! Reference-Only Mode

This page remains useful for installation and reference, but Killer-Skills no longer treats it as a primary indexable landing page. Read the review above before relying on the upstream repository instructions.

Upstream Repository Material

The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.

Upstream Source

lore-extraction

Install lore-extraction, an AI agent skill for AI agent workflows and automation. Review the use cases, limitations, and setup path before rollout.

SKILL.md
Readonly
Upstream Repository Material
The section below is imported from the upstream repository and should be treated as secondary evidence. Use the Killer-Skills review above as the primary layer for fit, risk, and installation decisions.
Supporting Evidence

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

Связанные навыки

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