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ThanabordeeN
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siyuan-second-memory

Index SiYuan notes into a structured knowledge graph with bidirectional links.

Updated Mar 5, 2026
Search Tags:#backlinks#knowledge-graph#memory-management#concept-maps#personal-memory#siuyan
One-click install
npx skills add https://github.com/ThanabordeeN/gemini-productivity-skills --skill siyuan-second-memory
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: siyuan-second-memory
Source: https://github.com/ThanabordeeN/gemini-productivity-skills/tree/main/siyuan-skill
Command: npx skills add https://github.com/ThanabordeeN/gemini-productivity-skills --skill siyuan-second-memory

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

SiYuan Notes are a powerful personal knowledge base, but without a structured framework they can become scattered and hard to recall. This skill turns SiYuan Notes into a structured Knowledge Graph where every document is a node, every link is a bidirectional reference, and documents live under a well-defined taxonomy, enabling more efficient memory, reasoning, and organization of personal knowledge.

Core Features & Use Cases

  • Three hard connectivity rules enforce a connected graph: Mandatory Link Prompt, Backlink Enforcement, and an Orphan Queue for weekly reviews.
  • Taxonomy-driven KG structure organizes notes into categories like Concepts, Projects, People, Decisions, Insights, References, Logs, ensuring consistent placement and discoverability.
  • Automation workflows support saving insights, building concept maps, linking notes, logging decisions, and retrieving contextual history to form a cohesive second brain.
  • Use Case: Save a decision, link it to related concepts and a project, then review orphaned notes weekly to maintain a coherent knowledge graph.

Quick Start

Ask the AI to generate a concept map from my notes.

Frequently Asked Questions about siyuan-second-memory

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

FAQPage Schema
How do I turn SiYuan Notes into a structured knowledge graph?▼

Turn SiYuan Notes into a knowledge graph by indexing documents, links, and metadata into a structured taxonomy. This enforces bidirectional links and categorizes notes into Concepts, Projects, and Insights for efficient memory recall.

How do I find and manage orphan notes in my personal knowledge base?▼

Find and manage orphan notes using an automated orphan queue designed for weekly reviews. This surfaces disconnected documents, prompting you to create backlinks and integrate them into your knowledge graph.

Can I use vector embeddings to search my SiYuan knowledge graph?▼

You can use optional vector and embedding services to index and search your SiYuan knowledge graph. This enables contextual recall and retrieves related history from your structured notes.

What are the rules for enforcing bidirectional links in a notes graph?▼

Enforcing bidirectional links in a notes graph relies on three hard rules: mandatory link prompts, backlink enforcement, and an orphan queue. This connectivity framework ensures every document is a connected node within the taxonomy.

How do I generate a concept map from my existing notes?▼

Generate a concept map from your existing notes by asking the AI to map your indexed documents. The knowledge graph structure automatically organizes linked notes into categories like Decisions and References to visualize connections.

Do I need a configured SiYuan instance to build a personal memory graph?▼

You need a configured SiYuan instance to build a personal memory graph. The system relies on this local instance to index documents, enforce link connectivity rules, and manage your structured second brain.

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