llm-wiki

You can build a persistent knowledge base by ingesting, organizing, and querying interlinked markdown files using Python scripts for file processing and organization. This creates a structured repository for research data and references.

Yes, you can ingest various sources such as articles, papers, and transcripts into your wiki. The skill processes these sources and organizes them as interlinked markdown files within your existing knowledge base directory.

Organize research data for compounding by maintaining a structured directory of interlinked markdown files. This approach ensures easy navigation and linking between pages, allowing your repository to grow consistently over time.

Yes, Python scripts are required for file processing and organization within the knowledge base. These scripts handle the ingestion, organization, and querying of your interlinked markdown files.

You can check your knowledge base for consistency and completeness by performing linting health checks. The skill enables users to query the repository and run these checks to ensure data integrity across interlinked files.

Yes, this knowledge management approach works for unstructured research transcripts. The skill ingests transcripts alongside articles and papers, organizing them into structured, interlinked markdown files for easy querying.