skills.rest
danielstewart77
danielstewart77COMMUNITY
Explore all skills by this author →
GitHub

knowledge-graph-save

Write memory chunks to a knowledge graph with entity resolution and disambiguation.

1|Updated Mar 11, 2025
Search Tags:#knowledge graph#memory#data persistence#graph database#disambiguation#entity resolution
One-click install
npx skills add https://github.com/danielstewart77/hive_mind --skill knowledge-graph-save
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: knowledge-graph-save
Source: https://github.com/danielstewart77/hive_mind/tree/main/specs/skills/knowledge-graph-save
Command: npx skills add https://github.com/danielstewart77/hive_mind --skill knowledge-graph-save

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill provides a structured procedure for saving information chunks into a knowledge graph, ensuring data is stored accurately and relationships are maintained.

Core Features & Use Cases

  • Entity Resolution: Handles fuzzy matching for person entities and general graph queries for other types.
  • Disambiguation: Prompts the user when multiple potential matches are found for an entity.
  • Relationship Management: Ensures new nodes have at least one edge, flagging isolated nodes.
  • Use Case: When Ada needs to remember a new fact about a person, like "Manny is my friend's husband," this Skill ensures "Manny" is correctly identified and linked to the appropriate existing nodes for "friend" and "husband."

Quick Start

Use the knowledge-graph-save skill to save a new memory about a person.

Frequently Asked Questions about knowledge-graph-save

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

FAQPage Schema
How do I save memories to a knowledge graph while resolving entity conflicts?▼

Saving memories to a knowledge graph requires robust entity resolution to identify matching nodes before data persistence. This skill handles fuzzy matching for people and general graph queries for other entity types.

How does fuzzy entity search work when storing information about people in a semantic network?▼

Fuzzy entity search identifies potential matches for person entities before storing information in a semantic network. When ambiguous matches exist, it triggers disambiguation prompts so you can select the correct node.

What happens if I create isolated nodes without edges in my knowledge graph?▼

Isolated nodes without edges are flagged during the knowledge graph save process. Relationship management ensures every new node has at least one edge to maintain semantic network connectivity.

Can I store and organize information about systems and projects using this graph database approach?▼

Yes, this approach supports storing and organizing information about people, projects, systems, and concepts within a semantic network. It ensures data persistence with robust entity resolution and relationship mapping.

When do I need entity disambiguation before writing data to a graph database?▼

Entity disambiguation is needed when fuzzy search returns multiple potential matches for an entity before graph database persistence. This prevents duplicate nodes and ensures memories link to the correct existing records.

Related Skills

Explore More Software Engineering Skills→
sharpninjasharpninja

GraphRAG Knowledge Graph

Ingest raw text into a GraphRAG knowledge graph and run graph-aware queries.

Community
Advanced
ncz-osncz-os
29

mnemos-memory

Store and retrieve persistent memories across agent sessions via API.

Official
Intermediate
FrancisVargaFrancisVarga

Graph Algorithms

Execute PageRank, Louvain, BFS, DFS, and shortest path algorithms on in-memory property graphs.

Community
Advanced
like-a-freedomlike-a-freedom

memory-management

Store and retrieve user memories in a knowledge graph for context-aware conversations.

Community
Intermediate