llm-wiki

Automate building and maintaining an interlinked Markdown knowledge base.

11|Updated May 17, 2026
One-click install
npx skills add https://github.com/StarryCod/cogitum --skill llm-wiki-starrycod
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: llm-wiki
Source: https://github.com/StarryCod/cogitum/tree/main/cogitum/data/skills/research/llm-wiki
Command: npx skills add https://github.com/StarryCod/cogitum --skill llm-wiki-starrycod

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Build a persistent, interlinked Markdown knowledge base that keeps cross-references and provenance intact, reducing manual curation and drift.

Core Features & Use Cases

  • Create and maintain a compounding knowledge base that supports cross-referencing between entities, concepts, and sources.
  • Ingest diverse materials (articles, papers, transcripts) and organize them into a structured wiki accessible via Obsidian, VS Code, or any Markdown editor.
  • Use for long-term research workflows requiring synthesis, consistency, and traceability across multiple sources.

Quick Start

Ingest your first sources and start linking related pages to build a persistent, interconnected knowledge base.

Frequently Asked Questions about llm-wiki

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

FAQPage Schema
How do I build an interconnected Markdown wiki from multiple research sources?▼

To build an interconnected Markdown wiki, ingest diverse materials like articles and transcripts to automatically generate cross-linked pages, enforcing frontmatter metadata and provenance tagging for consistent knowledge growth.

What is the best way to maintain provenance and cross-references in a Markdown knowledge base?▼

Maintaining provenance in a Markdown knowledge base requires automated frontmatter metadata and provenance tagging, supplemented by periodic lint checks to ensure cross-references between entities and concepts remain intact and traceable.

Can I organize ingested research papers into schema-driven layers in Obsidian?▼

Yes, you can organize ingested research papers into schema-driven layers accessible via Obsidian, VS Code, or any Markdown editor, structuring content to support long-term research workflows and concept synthesis.

Does this knowledge base approach support ongoing synthesis and consistency across long-term research?▼

Supporting ongoing synthesis and consistency across long-term research is achieved by organizing content into schema-driven layers and running periodic lint checks to prevent manual curation drift and ensure traceability.

What are the limitations of manually curating an interlinked Markdown wiki versus automating it?▼

Manually curating an interlinked Markdown wiki introduces drift and broken cross-references, whereas automating ingestion, schema-driven organization, and lint checks enforces consistency and traceability across compounding sources.

How do I ingest diverse transcripts and articles into a structured Markdown knowledge base?▼

Ingest diverse transcripts and articles into a structured Markdown knowledge base by processing raw sources into interlinked pages with enforced frontmatter metadata, automatically cross-referencing entities and concepts for ongoing growth.