llm-wiki

Build a local markdown knowledge base by configuring a directory path for the AI agent to ingest, query, and audit interlinked information. This creates a structured repository with immutable sources and entity pages for persistent research.

Maintain an interlinked knowledge base by compiling information once and auditing it through an AI agent to keep sources current. This layered wiki structure prevents the need to rediscover knowledge with each new query.

Yes, you can use a local file system to organize a structured wiki by setting a specific directory path for storage and processing. The system utilizes this directory to manage schema configurations and entity pages for domain-specific research.

An AI agent queries and audits a markdown wiki by processing the local directory structure containing immutable sources and entity pages. This mechanism targets research applications requiring a structured repository of current information.

You need a local directory structure defined by a path variable to set up a persistent markdown knowledge repository. This structure organizes schema configurations, immutable sources, and entity pages for the AI agent to process.

Use a markdown wiki over standard notes when you need to assemble knowledge once and keep it current for continuous learning. It provides a structured repository with schema configurations and entity pages that reduce redundant information rediscovery.