maproom-guide

Maproom semantic code search results include headers, ranked results, and preview snippets. Understanding this structure helps you trace why specific code chunks matched your query and how to navigate the output effectively.

Maproom uses full text search (FTS) for exact keyword matching and vector search for semantic similarity. Understanding how these algorithms combine helps explain why certain results appear for your queries.

Troubleshooting Maproom CLI errors involves diagnosing common issues related to search execution and result retrieval. The guide helps you quickly identify error sources and resolve problems with your code search commands.

Unexpected semantic code search results often stem from chunking strategies or vector matching nuances. Analyzing the search headers and preview snippets clarifies why the algorithm selected specific code blocks.

Code chunking in Maproom divides source files into segments for indexing. Understanding this process is essential for diagnosing why semantic search algorithms return specific code blocks instead of whole files.

You can use Maproom semantic search without deep architectural knowledge, but understanding concepts like FTS, vector search, and chunking significantly improves your ability to interpret results and diagnose errors.