What problem does it solve? Answering questions about a large codebase requires reading many files, tracing connections, and understanding architectural decisions, which is slow and error-prone when done manually. This Skill automates comprehensive codebase research by decomposing questions, spawning parallel sub-agents, and synthesizing findings into a documented artifact. ## Core Features & Use Cases - Parallel Sub-Agent Research: Spawns 2-4 concurrent Explore and general-purpose agents to investigate different aspects of a question simultaneously. - Scope Clarification: Uses structured questions to align on research depth, focus areas, and output format before investigating. - Structured Research Documents: Generates a research.md file with YAML frontmatter, code references with file:line citations, architecture insights, and historical context from prior changes. - Use Case: Ask how authentication works in your project, and receive a comprehensive document tracing the auth flow across components with specific code references and links to past architectural decisions. ## Quick Start Invoke the skill and ask a research question such as how the API endpoints connect to the Supabase authentication layer.
