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llm-wiki

Build and maintain an interlinked markdown knowledge base from ingested sources.

Updated Jun 5, 2026
Search Tags:#markdown#research#knowledge base#obsidian#ingestion#wiki#rag-alternative
One-click install
npx skills add https://github.com/xu1713/openhorse --skill llm-wiki-xu1713
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: llm-wiki
Source: https://github.com/xu1713/openhorse/tree/main/openhorse/openhorse/skills/research/llm-wiki
Command: npx skills add https://github.com/xu1713/openhorse --skill llm-wiki-xu1713

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve? Traditional RAG rediscovers knowledge from scratch on every query, losing cross-references and synthesis. This Skill maintains a persistent, compounding markdown wiki where sources are ingested once, cross-linked, and kept current, so accumulated knowledge is immediately queryable. ## Core Features & Use Cases - Source Ingestion: Capture URLs, PDFs, and pasted text into an immutable raw/ layer with sha256 drift detection, then synthesize entity, concept, and comparison pages with wikilinks and provenance markers. - Query & Synthesis: Answer questions from the compiled wiki via index and full-text search, filing valuable answers back as query or comparison pages. - Wiki Linting: Audit for orphan pages, broken wikilinks, stale content, contradictions, tag taxonomy violations, and source drift. - Use Case: A researcher tracking AI/ML developments ingests arxiv papers and articles weekly; the agent updates entity pages, flags contradictions between sources, and the wiki opens directly in Obsidian for browsing. ## Quick Start Ask the agent to create a wiki for your research domain and ingest your first source URL into it.

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 markdown knowledge base with an AI agent?▼

Set the WIKI_PATH environment variable or use the default ~/wiki directory, then ask the agent to initialize a wiki for your domain. The agent creates SCHEMA.md, index.md, and log.md, then ingests sources into raw/ and synthesizes cross-linked entity and concept pages.

How is an LLM wiki different from RAG?▼

RAG retrieves and re-derives knowledge from scratch per query, while the wiki compiles knowledge once into persistent markdown pages. Cross-references, contradictions, and synthesis are already resolved, so queries read pre-digested pages instead of raw chunks.

Does the wiki work with Obsidian?▼

Yes, the wiki directory functions as an Obsidian vault out of the box. Wikilinks render as clickable links, YAML frontmatter powers Dataview queries, and the obsidian-headless CLI enables sync on servers without a display.

How do I check a markdown wiki for broken links and orphan pages?▼

Ask the agent to lint the wiki. The lint operation scans all pages for broken wikilinks, orphan pages with no inbound links, index completeness, frontmatter validity, stale content, contradictions, and source drift via sha256 comparison.

What are the limitations of an agent-maintained wiki?▼

The agent must orient by reading SCHEMA.md, index.md, and recent log entries each session, or it risks duplicate pages and missed cross-references. Pages require disciplined frontmatter and tag taxonomy adherence, and large ingests touching 10+ pages should be confirmed with the user first.

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