find-knowledge

To search a knowledge base, you run a query against your centralized repository to retrieve matching file paths and contextual excerpts. This knowledge base search returns structured rankings and metadata, helping you quickly locate relevant playbooks, skills, or templates without duplicating effort.

You can filter knowledge base search results by constraining queries to specific categories like sales or seo, and by content types such as playbook, skill, doc, or template. This filtering scopes your retrieval to ensure only the most contextually relevant documentation is returned for your specific use case.

The best way to check if a topic exists is to run a knowledge base query like "customer onboarding" and review the top matches. The search returns brief excerpts and file metadata, allowing you to verify existing content and avoid duplication before creating new playbooks or documentation.

Information retrieval works by querying a centralized knowledge base to extract frontmatter-driven metadata and return contextual excerpts. The system applies structured result ranking and clean output formatting, providing the necessary context to guide decision-making and enabling quick downstream consumption of the retrieved information.

When retrieving documents from a knowledge base, expect results limited to brief contextual excerpts and file metadata rather than full documents. The system relies on frontmatter-driven metadata extraction for ranking, so incomplete or missing metadata in source files may impact the accuracy of structured search outputs.