tldr-router

To route questions for code analysis, intent detection identifies keywords in the query and maps them to specific tldr commands. This mechanism translates natural language into targeted actions for architecture understanding and data flow tracing.

The best way to explore code architecture is by querying with natural language questions, which leverages intent detection to automatically select the correct tldr layer. This approach simplifies code exploration by translating user intent directly into structural analysis commands.

You can trace data flow and assess complexity by asking plain questions, as the routing mechanism uses intent detection to automatically execute the correct tldr command. This eliminates the need to memorize specific syntax for data flow tracing or complexity assessment.

No, tldr-router does not require manual command selection for impact analysis because it uses automatic hook integration. Intent detection keywords automatically route the query to the appropriate tldr layer, seamlessly handling the impact analysis process.

To get a file overview of a specific directory extension, ask a natural language question like "What files are in the src directory?". The intent detection maps this query to automatically execute the tldr tree command with the appropriate extension filter.

Intent-based routing for code exploration relies on keyword matching to map questions to tldr commands, meaning it is limited by the specific intent detection keywords configured. Queries lacking these keywords may not route to the correct code analysis layer.