llm-wiki

Build a persistent interlinked Markdown knowledge wiki from ingested sources.

Updated May 26, 2026
One-click install
npx skills add https://github.com/ruiyangruiyi/hermes-agent --skill llm-wiki-ruiyangruiyi
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: llm-wiki
Source: https://github.com/ruiyangruiyi/hermes-agent/tree/main/skills/research/llm-wiki
Command: npx skills add https://github.com/ruiyangruiyi/hermes-agent --skill llm-wiki-ruiyangruiyi

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes assets (resource) components.

What problem does it solve?

This Skill solves the problem of repeatedly answering questions by re-deriving knowledge from scratch by building a persistent, interlinked Markdown knowledge base that stays current over time.

Core Features & Use Cases

  • Compiling a persistent wiki from sources: Ingest URLs, PDFs, and pasted text into an Obsidian-compatible directory structured into raw sources, entity/concept pages, comparisons, and query results.
  • Cross-referencing and consistency management: Create and update pages using a schema that enforces conventions, backlinks, and an index catalog to prevent duplicate work and contradictions.
  • Querying and maintaining the wiki: Answer questions using the wiki’s compiled structure, and lint/audit for broken links, missing index entries, or flagged low-confidence/contested claims.

Quick Start

Tell the agent: create a new wiki in the folder you choose and ingest these sources: a few links or files, then ask it to propose the first set of entity and concept pages to organize the knowledge.

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 knowledge wiki from research papers and transcripts?

To build a persistent knowledge wiki, ingest articles, papers, and transcripts into an Obsidian-compatible directory. The system extracts entities and concepts, enforcing Markdown frontmatter and cross-linking to compile interlinked understanding instead of re-deriving it.

What is the best way to maintain a Markdown knowledge base without duplicate entries?

Maintaining a Markdown knowledge base without duplicates requires an index catalog that enforces backlinks and schema conventions. The system performs deduplication against existing index entries to prevent contradictions and redundant work.

Can I use an interlinked wiki as a RAG alternative for answering queries?

Yes, you can use an interlinked wiki as a RAG alternative by querying its compiled structure. The system answers questions using previously extracted entities and concepts, reusing compiled understanding rather than re-discovering knowledge from raw sources.

How do I audit a Markdown wiki for broken links and missing index entries?

You audit a Markdown wiki by running lint and drift checks. The system enforces auditability via logs and raw sha256 drift checks, flagging broken links, missing index entries, and low-confidence or contested claims.

Does this knowledge base tool work with Obsidian-compatible directory structures?

Yes, this knowledge base tool works with Obsidian-compatible directory structures. It organizes raw sources, entity pages, concept pages, comparisons, and query results using standard Markdown with enforced frontmatter and cross-linking.

How do I ingest URLs and PDFs into an interlinked Markdown wiki?

To ingest URLs and PDFs into an interlinked Markdown wiki, point the agent to your sources and configured WIKI_PATH. The system processes raw inputs, extracts entities, and proposes initial concept pages to organize the knowledge.