llm-knowledge-base

Create and maintain a hierarchical wiki knowledge base from raw sources.

Updated Apr 25, 2026
One-click install
npx skills add https://github.com/Serg28/demosite --skill llm-knowledge-base
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: llm-knowledge-base
Source: https://github.com/Serg28/demosite/tree/main/.agents/skills/llm-knowledge-base
Command: npx skills add https://github.com/Serg28/demosite --skill llm-knowledge-base

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill addresses the challenge of maintaining and organizing a growing collection of personal knowledge by leveraging an LLM to create and update a structured, persistent wiki system from raw sources, enabling continuous knowledge accumulation.

Core Features & Use Cases

  • Knowledge Organization: Automatically structures raw notes, articles, and research into interconnected wiki pages for easy retrieval.
  • Dynamic Maintenance: Keeps the knowledge base current by updating the wiki as new sources are added.
  • Use Case: A researcher saves papers and notes over time and asks the AI to synthesize insights, draft summaries, or identify knowledge gaps within the organized wiki.

Quick Start

Ask the AI to process new source files by placing them into the raw folder and instruct it to ingest the content, then query based on organized knowledge.

Frequently Asked Questions about llm-knowledge-base

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

FAQPage Schema
How do I organize raw notes and articles into a queryable personal knowledge base?

To build a personal knowledge base, you place raw notes and articles into a designated folder for the AI to ingest, automatically structuring the content into an interconnected, queryable wiki system with minimal manual intervention.

How does an LLM synthesize and update information in a personal wiki?

An LLM synthesizes information by ingesting raw source files and automatically updating the hierarchical wiki pages, keeping the knowledge base current as new sources are added while creating interconnected entries for easy retrieval.

Can I use an automated wiki to identify knowledge gaps in my research notes?

Yes, researchers can query the organized wiki to ask the AI to synthesize insights, draft summaries, and identify knowledge gaps accumulated across raw notes and research papers over time.

What is the best way to maintain a persistent personal wiki without manual formatting?

The best way to maintain a persistent personal wiki is using an LLM to dynamically process new source files, automatically updating and structuring the information into interconnected pages as your collection grows.

Does building an AI-powered personal wiki require manual data structuring?

Building an AI-powered personal wiki requires minimal manual intervention, as the LLM automatically ingests raw documents, synthesizes the content, and structures it into a cohesive, hierarchical knowledge repository.

What are the limitations of using an LLM to maintain a hierarchical wiki system?

Using an LLM to maintain a hierarchical wiki system relies on continuous ingestion of raw source files to update pages, requiring users to consistently provide new documents for accurate synthesis and knowledge gap identification.