What problem does it solve? Turning open-ended research questions into trustworthy, decision-ready findings is slow and error-prone: claims go uncited, sources go stale, and raw reports are hard for downstream planning artifacts to consume. This Skill structures research around a specific decision, enforces citation and freshness discipline, and produces a canonical cited summary other workflows can use directly. ## Core Features & Use Cases - Three research modes: Draft a deep-research prompt for external tools (ChatGPT, Gemini, Perplexity), Process a finished report into a cited summary, or Run native research with parallel web-search subagents. - Typed research packs: Built-in packs for market, domain, technical, competitive, user-voice, and academic literature research, each with prioritized dimensions, freshness bars, and two-source claim classes; supports a select mode for choosing between candidates. - Verification and lifecycle: Claims ledger with verified/disputed/unverified statuses, optional red-team passes, staleness tracking, and Refresh/Deepen workflows for existing run folders. - Use Case: Before committing to a new market, ask for market research on the opportunity; the Skill runs a plan-gated multi-source investigation, verifies load-bearing claims, and delivers research.md with an executive summary, source appendix, and staleness map. ## Quick Start Ask the assistant to run market research on a topic tied to a decision you need to make, for example: research the competitive landscape for my product idea.
