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AskTinNguyen
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3-layer-memory

Create a three-layer memory system with knowledge graph, daily notes, and tacit memory.

1|Updated Jan 26, 2026
Search Tags:#automation#context#synthesis#notes#knowledge-graph#memory-system#entity-management
One-click install
npx skills add https://github.com/AskTinNguyen/vesper-team-skills --skill 3-layer-memory
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: 3-layer-memory
Source: https://github.com/AskTinNguyen/vesper-team-skills/tree/main/3-layer-memory
Command: npx skills add https://github.com/AskTinNguyen/vesper-team-skills --skill 3-layer-memory

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

The Three-Layer Memory System solves the challenge of retaining long-term, structured knowledge across AI conversations by organizing memory into a knowledge graph, daily notes, and a tacit memory layer that evolve with use.

Core Features & Use Cases

  • Three-layer architecture: Knowledge Graph (entities), Daily Notes, and Tacit Memory for persistent context.
  • Automatic synthesis and manual updates: weekly synthesis with options for automation while preserving history.
  • Extensibility: scripts, references, and assets to customize workflows and templates.

Quick Start

Run the initialization script to set up the three-layer memory structure and seed an example entity.

Frequently Asked Questions about 3-layer-memory

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

FAQPage Schema
How do I retain long-term context across AI conversations using a knowledge graph?▼

A three-layer memory system solves long-term context retention by organizing data into a knowledge graph, daily notes, and tacit memory. It automatically extracts facts and evolves across AI conversations.

What's the best way to set up a self-updating memory graph for entity management?▼

Set up a self-updating memory graph by running an initialization script that creates a three-layer structure. This seeds example entities and parses YAML frontmatter to maintain current and previous fact states.

How does fact state management work with [current] and [was] in a memory system?▼

Fact state management parses YAML frontmatter in entity files to maintain [current] and [was] states. This preserves historical fact accuracy within the knowledge graph over time.

Can I automate weekly synthesis and fact extraction across notes?▼

Weekly synthesis is supported with optional automation. The system automatically extracts facts and performs syntheses across daily notes and the knowledge graph while preserving history.

Do I need any dependencies to maintain a three-layer memory graph?▼

No dependencies are required. The three-layer memory graph operates independently using scripts, references, and assets to customize workflows and templates for entity management.

When should I not use a tacit memory layer for knowledge context?▼

A tacit memory layer is not suited for short-term or ephemeral context needs. It is designed for long-term, structured knowledge retention requiring automatic fact extraction and weekly syntheses.

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