investigate

You can conduct codebase exploration using parallel sub-agents. This approach offloads research tasks like dependency analysis and error tracing, keeping the main AI context clean and focused while concurrently searching and analyzing code structure.

Tracing feature implementations across modules is done by deploying dedicated sub-agents for parallel research. These agents execute glob and grep operations concurrently to identify all relevant files and map dependencies without overwhelming the primary context window.

Dependency mapping and cross-project research are performed by parallel sub-agents. They apply pattern analysis to investigate code structure and trace dependencies across multiple projects simultaneously, yielding comprehensive exploration results.

Yes, parallel exploration allows you to investigate code structure and trace errors across projects concurrently. Sub-agents handle the glob and grep operations independently, enabling deep dives into multiple projects without serializing the research process.

Yes, this method is designed for deep code exploration and investigation. Sub-agents execute pattern analysis and dedicated search operations specifically to handle complex code structure scenarios and deep dependency mapping.

Parallel code exploration preserves context by offloading research tasks to sub-agents. These dedicated agents handle the heavy lifting of pattern analysis and file searching independently, preventing the main context from being cluttered with intermediate search data.