narrative-extractor

Name: narrative-extractor
Availability: InStock
Author: kazumasakawahara

Extract structured narrative data into JSON for Neo4j ingestion.

Updated Feb 21, 2026

Search Tags:#narrative #json #data-extraction #neo4j #structured-data #entity-resolution #care-planning

Ready to run

npx skills add https://github.com/kazumasakawahara/nest-support --skill narrative-extractor

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: narrative-extractor
Source: https://github.com/kazumasakawahara/nest-support/tree/main/claude-skills/narrative-extractor
Command: npx skills add https://github.com/kazumasakawahara/nest-support --skill narrative-extractor

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill converts unstructured caregiver and support narratives into a consistent JSON schema ready for Neo4j ingestion, eliminating manual transcription errors and ensuring safe data capture.

Core Features & Use Cases

Extract structured data from narratives and documents into a JSON schema for Neo4j.
Enforce strict extraction rules to avoid fabricating information, prioritize implicit insights, and normalize dates and entities.
Use cases include converting interview notes, family narratives, and attached reports into connected client records with support of NgActions, care preferences, and logs.

Quick Start

Provide your narrative text or attach a document; the skill will extract structured data for immediate Neo4j registration.

Frequently Asked Questions about narrative-extractor

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I extract structured data from unstructured narratives into a Neo4j JSON schema?▼

To extract structured data from unstructured narratives into a Neo4j JSON schema, provide your caregiver notes or interview documents. The skill applies strict non-guessing rules and canonicalization to normalize entities and dates safely.

Can I extract entities from attached PDF and DOCX files for Neo4j ingestion?▼

Yes, you can extract entities from attached PDF and DOCX files for Neo4j ingestion. The skill processes attached documents including docx, pdf, xlsx, and txt formats, converting unstructured text into structured JSON data.

What is the best way to normalize name variants and resolve entities from care planning narratives?▼

The best way to normalize name variants and resolve entities from care planning narratives is using strict extraction rules. The skill canonicalizes name variants and performs entity resolution against existing Neo4j data to ensure consistency.

How does the extraction process handle implicit insights and care preferences without fabricating information?▼

The extraction process handles implicit insights by prioritizing them while enforcing strict non-guessing rules. It avoids fabricating information by only capturing care preferences and support logs explicitly mentioned in the source narratives.

Are there limitations when converting unstructured interview notes into connected client records?▼

A limitation when converting unstructured interview notes is the strict non-guessing rule, meaning the extraction will not fabricate missing information. It relies entirely on the explicit and implicit insights present in the provided text or attached files.

Do I need existing Neo4j data to perform entity resolution on extracted caregiver narratives?▼

No, you do not need existing Neo4j data to extract structured data, but having it enables entity resolution. The skill can resolve canonicalized name variants against existing Neo4j records to maintain connected client relationships accurately.