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

v1.0.0

关于此技能

非常适合需要高级叙事文本分析和实体提取能力的世界构建代理 Base extraction rules for all lore subagents. Governs entity identification, contextual analysis, relationship mapping, and JSON output formatting.

# 核心主题

bivex bivex
[0]
[0]
更新于: 3/21/2026

Killer-Skills Review

Decision support comes first. Repository text comes second.

Reference-Only Page Review Score: 6/11

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
6/11
Quality Score
29
Canonical Locale
en
Detected Body Locale
en

非常适合需要高级叙事文本分析和实体提取能力的世界构建代理 Base extraction rules for all lore subagents. Governs entity identification, contextual analysis, relationship mapping, and JSON output formatting.

核心价值

赋予代理从叙事文本中提取实体、根据实体所有权映射对其进行分类,并以LoreData.to_dict兼容的JSON格式输出,利用标准化的提取管道并支持JSON等协议

适用 Agent 类型

非常适合需要高级叙事文本分析和实体提取能力的世界构建代理

赋予的主要能力 · lore-extraction

从叙事文本中提取实体以创建沉浸式宇宙
通过识别和分类实体之间的关系来设计文明
自动构建世界构建项目的实体所有权映射

! 使用限制与门槛

  • 需要完整的源文本被读取后才能进行提取
  • 仅限于叙事文本分析
  • 需要预定义的实体所有权映射来进行分类

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 supporting source material from the upstream repository. Use the Killer-Skills review above as the primary decision layer.

实验室 Demo

Browser Sandbox Environment

⚡️ Ready to unleash?

Experience this Agent in a zero-setup browser environment powered by WebContainers. No installation required.

Boot Container Sandbox

常见问题与安装步骤

以下问题与步骤与页面结构化数据保持一致,便于搜索引擎理解页面内容。

? FAQ

lore-extraction 是什么?

非常适合需要高级叙事文本分析和实体提取能力的世界构建代理 Base extraction rules for all lore subagents. Governs entity identification, contextual analysis, relationship mapping, and JSON output formatting.

如何安装 lore-extraction?

运行命令:npx killer-skills add bivex/loreSystem/lore-extraction。支持 Cursor、Windsurf、VS Code、Claude Code 等 19+ IDE/Agent。

lore-extraction 适用于哪些场景?

典型场景包括:从叙事文本中提取实体以创建沉浸式宇宙、通过识别和分类实体之间的关系来设计文明、自动构建世界构建项目的实体所有权映射。

lore-extraction 支持哪些 IDE 或 Agent?

该技能兼容 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。可使用 Killer-Skills CLI 一条命令通用安装。

lore-extraction 有哪些限制?

需要完整的源文本被读取后才能进行提取;仅限于叙事文本分析;需要预定义的实体所有权映射来进行分类。

安装步骤

  1. 1. 打开终端

    在你的项目目录中打开终端或命令行。

  2. 2. 执行安装命令

    运行:npx killer-skills add bivex/loreSystem/lore-extraction。CLI 会自动识别 IDE 或 AI Agent 并完成配置。

  3. 3. 开始使用技能

    lore-extraction 已启用,可立即在当前项目中调用。

! 参考页模式

此页面仍可作为安装与查阅参考,但 Killer-Skills 不再把它视为主要可索引落地页。请优先阅读上方评审结论,再决定是否继续查看上游仓库说明。

Imported Repository Instructions

The section below is supporting source material from the upstream repository. Use the Killer-Skills review above as the primary decision layer.

Supporting Evidence

lore-extraction

安装 lore-extraction,这是一款面向AI agent workflows and automation的 AI Agent Skill。支持 Claude Code、Cursor、Windsurf,一键安装。

SKILL.md
Readonly
Imported Repository Instructions
The section below is supporting source material from the upstream repository. Use the Killer-Skills review above as the primary decision layer.
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

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