llm-wiki

Ingest raw sources into a persistent interlinked markdown knowledge base.

Updated Jun 17, 2026

Search Tags:#markdown #research #notes #wiki #knowledge-base #rag-alternative

Ready to run

npx skills add https://github.com/cxnaive/hermes-agent-llbot --skill llm-wiki-cxnaive

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: llm-wiki
Source: https://github.com/cxnaive/hermes-agent-llbot/tree/main/skills/research/llm-wiki
Command: npx skills add https://github.com/cxnaive/hermes-agent-llbot --skill llm-wiki-cxnaive

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill solves the problem of fragmented, ephemeral knowledge by creating a persistent, interlinked markdown-based wiki that compounds over time, unlike traditional RAG systems that rediscover information from scratch.

Core Features & Use Cases

Compounding Knowledge: Automatically cross-references, summarizes, and maintains consistency across your notes.
Agent-Assisted Curation: The agent handles the heavy lifting of filing, linking, and linting your knowledge base while you focus on high-level research.
Use Case: Use this to build a personal research library for AI/ML topics where you ingest papers and articles, and the agent automatically links them to existing concepts and entities.

Quick Start

Ask the agent to initialize a new wiki in your home directory and guide you through the initial schema setup.

Frequently Asked Questions about llm-wiki

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

FAQPage Schema

How do I build a persistent markdown knowledge base that compounds over time?▼

A persistent knowledge base prevents fragmented, ephemeral research by automatically cross-referencing and maintaining consistency across markdown notes. Unlike traditional RAG systems, it compounds information over time rather than rediscovering it from scratch.

Can I use this agent to automatically link research notes in Obsidian?▼

Yes, this Skill integrates with local or remote editors like Obsidian by managing markdown files directly in your file system. The agent handles the heavy lifting of filing, linking, and linting notes while you focus on high-level research.

What is the best way to maintain cross-session recall for AI and ML research notes?▼

You can start by asking the agent to initialize a new wiki in your home directory, which guides you through the initial schema setup. Once initialized, feed it raw sources to automatically synthesize structured markdown entity and concept pages.

Does this approach require file system access to manage markdown files?▼

Yes, this Skill requires file system access to manage markdown files and integrate with local or remote editors. This allows the agent to directly handle markdown management, filing, and linting within your knowledge base.

How does a compounding knowledge base compare to a traditional RAG system?▼

A compounding knowledge base synthesizes raw sources into interlinked markdown pages to build persistent recall, whereas a traditional RAG system rediscovers information from scratch. This approach ensures information consistency and cross-references across sessions.

What are the limitations of using markdown for agent-assisted knowledge curation?▼

The primary limitation is the strict dependency on file system access and compatible markdown editors like Obsidian for integration. Without this environment, the agent cannot perform the automated filing, linking, and linting required to maintain the wiki.