What problem does it solve? Teams often make architectural or technical decisions without a thorough understanding of the landscape. This Skill automates deep, PhD-level research on a topic and produces a structured survey document so decisions are grounded in evidence rather than guesswork. ## Core Features & Use Cases - Parallel Research Subagents: Spawns web search, codebase exploration, and docs scanning subagents simultaneously to gather comprehensive findings. - Structured Survey Output: Synthesizes findings into a rigorous template with abstract, taxonomy, per-approach analysis, comparative synthesis, open problems, and full references. - Memory & Docs Integration: Searches existing knowledge via ca search and checks docs/research/ and ADRs to avoid duplicating prior work. - Use Case: Before choosing a state management approach, ask for a survey of options; the Skill produces docs/research/state-management.md with trade-off tables and practitioner resources for the ADR process. ## Quick Start Ask the agent to research a topic, for example: research approaches to distributed caching and produce a survey document in docs/research.
