retrieve

To retrieve connected research notes, this skill uses BM25 keyword search to find seed notes and expands the context by recursively traversing wikilinks across your structured directories. It gathers papers, notes, and concepts into a navigable set for research synthesis.

Yes, you can find related concepts through wikilink traversal. The skill maps connections between objective paper summaries and personal annotations by following recursive links, building a comprehensive context set from your knowledge base.

No, the knowledge retrieval process requires no external API dependencies. It operates entirely through local execution of Python-based retrieval scripts to index files and resolve file paths within your structured directories.

The best way to gather notes on a complex topic is to use BM25 indexing combined with recursive wikilink traversal. This identifies seed notes and expands across sources, papers, and concepts to build a single navigable reference set.

Yes, you need Python to index local research notes. The skill relies on local execution of Python-based retrieval scripts to perform BM25 indexing and resolve file paths without external dependencies.

Local knowledge base search combines BM25 with wikilink traversal to solve fragmented research. BM25 finds relevant seed notes by keyword, while recursive link expansion maps connections between papers and concepts for comprehensive context.