Standardized logic for sub-agents to identify and extract narrative entities into structured JSON data.
Install
mkdir -p .claude/skills/lore-extraction && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/17409" && unzip -o skill.zip -d .claude/skills/lore-extraction && rm skill.zipInstalls to .claude/skills/lore-extraction
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Base extraction rules for all lore subagents. Governs entity identification, contextual analysis, relationship mapping, and JSON output formatting.Key capabilities
- →Read source text completely before extraction
- →Identify named, described, or implied entities
- →Classify each entity to its correct type
- →Format extracted data as JSON compatible with LoreData.to_dict
- →Validate output against domain model constraints
- →Review for completeness and accuracy
How it works
The skill processes narrative text by identifying and classifying entities, then formats the extracted data into JSON. It validates the output against domain models and reviews for accuracy.
Inputs & outputs
When to use lore-extraction
- →Extract character data from story text
- →Map relationships between magical systems
- →Format lore content for GUI integration
About this skill
lore-extraction
Base skill for all loreSystem extraction subagents. Common rules for extracting entities from narrative text.
Extraction Pipeline
- Read the source text completely before extracting
- Identify entities — look for named things, described systems, relationships
- Classify each entity to its correct type from the entity ownership map
- Format according to the export schema
- Output as JSON compatible with
LoreData.to_dict(seesrc/presentation/gui/lore_data.py) - Validate against domain model constraints
- 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
When not to use it
- →Creating entities owned by another skill
- →Inventing details not supported by the text
Limitations
- →Does not create entities owned by other skills
- →Does not invent details not supported by the text
- →Requires validation against domain model constraints
How it compares
This skill provides a structured pipeline for extracting and formatting lore data from text into a specific JSON schema, ensuring consistency and validation, unlike manual data entry.
Compared to similar skills
lore-extraction side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| lore-extraction (this skill) | 0 | 5mo | No flags | Intermediate |
| literature-review | 559 | 1mo | Review | Advanced |
| openalex-database | 48 | 7mo | Review | Intermediate |
| scientific-critical-thinking | 18 | 7mo | Review | Advanced |
Try saying
Example prompts that trigger this skill in your AI assistant.
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