rag-query

To perform cross-domain search across code, docs, or papers, you query the project's RAG index using configured MCP tools like rag_query and corpus_list. It infers the appropriate corpus from your intent and accepts QUERY, CORPUS, and K inputs to return structured results.

Cross-domain retrieval reconciles implementations with literature by querying codebases and papers concurrently. It formats results to highlight paths, sections, or citekeys, allowing you to view where a function is implemented and where a paper describes the method together.

Yes, you can locate function implementations and related paper citations by querying the RAG index. The tool uses rag_query_multi and citekey_resolve to format results, highlighting relevant file paths and resolving citekeys across your documentation and paper corpora.

Before querying a project corpus, you need a configured RAG index and the associated MCP tools. You must have your code, docs, and papers indexed so the retrieval tools can infer the correct corpus and execute targeted queries across the available domains.

The best way to retrieve literature references and code conventions is to use a tool that applies rag_query_multi across configured corpora. It formats results to highlight relevant paths, sections, or citekeys, presenting reconciled findings from both codebases and papers in a single view.